---
title: The Trigger Prompt Corpus
section: Ora — Performance
status: published
subtitle: The full library of prompts behind the comparison.
description: The complete public corpus of 758 vetted trigger prompts across 198 techniques — 60 analytical modes, 22 visual tools, and 116 interpretive lenses — used to drive the Ora Performance comparison. Every prompt was tested to reliably trigger its intended technique.
authors:
  - The Ora Foundation
downloads:
  md: /papers/white/trigger-prompt-corpus.md
license: https://creativecommons.org/publicdomain/zero/1.0/
---

# The Trigger Prompt Corpus

The [Ora Performance](/papers/ora-performance) comparison measured the same analytical work run six ways and scored for quality and cost. This is the prompt library behind it: the complete set of trigger prompts that were used to exercise every technique the comparison covers. It is published in full, dedicated to the public domain, so that anyone can inspect exactly what was asked, reuse the prompts, or run a comparable evaluation of their own harness.

A "trigger prompt" is simply an ordinary user request written so that it reliably invokes one specific technique. "Argument audit on this: …" invokes the argument-audit mode; "Make me an ACH matrix on three competing hypotheses for …" invokes the ACH-matrix visual. The corpus is that request, five (or three) ways over, for every technique in the catalog.

## What's in the corpus

The corpus holds **758 vetted trigger prompts across 198 techniques**:

- **60 analytical modes** — the reasoning procedures (argument audit, competing-hypotheses analysis, decision architecture, and so on).
- **22 visual tools** — techniques whose output is a diagram or matrix rather than prose (ACH matrix, bow-tie diagram, causal DAG, and so on).
- **116 interpretive lenses** — cognitive-bias and mental-model overlays (anchoring, the affect heuristic, choice architecture, and so on) that can be foregrounded on top of a host mode.

Each of the 82 modes-and-tools carries **five** prompts; each of the 116 lenses carries **three**. That is `82 × 5 = 410` plus `116 × 3 = 348`, for **758** prompts in total.

**A note on the numbers.** Two different counts are in play, and they measure two different things:

- **758** is a count of *prompts* — the individual requests published here.
- **198** is a count of *techniques* — the distinct capabilities those prompts exercise (`60 + 22 + 116`).

The comparison campaign itself ran only **one featured prompt from each technique** through the six lanes — not all 758. The remaining prompts are published as additional worked examples of each technique, not as separate campaign runs.

You will also see the number **196** in the [results paper](/papers/ora-performance), which describes the comparison as covering "196 techniques." The scored comparison used **196 of the 198** entries in this corpus. Two techniques share a public ID across two kinds — `causal-dag` exists as both an analytical mode and a visual tool, and `fishbone-diagram` as both an interpretive lens and a visual tool — and the comparison scored just one entry per shared ID: it used the **analytical-mode** prompt for `causal-dag` and the **visual-tool** prompt for `fishbone-diagram`. So two kind-specific entries — the visual-tool `causal-dag` and the lens `fishbone-diagram` — were not separately scored. That is the entire `198 → 196` difference. Every one of the 60 analytical modes was scored, including `passion-exploration` and `structured-output` (which captured on fewer than all six lanes). The corpus published here is the complete set of all 198 entries; the two that the comparison did not separately score are still included in the catalog below.

## How the prompts were vetted

Every prompt in the corpus was tested before admission to confirm two things: that it reliably triggers the technique it is meant to trigger, and that it does so without the system stopping to ask a clarifying question first. Prompts that missed on either count were revised and retested, or dropped. The published corpus is the set that passed — no prompt is included on the strength of how it reads alone; each one earned its place by actually invoking its technique in testing.

## Where the material comes from

Most prompts describe 2026-current situations — trade policy, the energy transition, semiconductor lithography, healthcare costs, regional-bank stress, AI-safety governance, and other live topics — so the comparison exercises the techniques on real, contemporary subject matter rather than toy problems.

A small number of techniques (twelve of the analytical modes) work on a pasted document. Where a suitable real, public document existed, the featured prompt uses it and cites it; where none did, the featured prompt uses a realistic composite business scenario (a recurring early-stage-startup founder facing operational decisions) instead. The real public sources used at the featured position are:

- **`balanced-critique`** — [UK 4-Day Week Pilot results](https://www.4dayweek.com/uk-pilot-results)
- **`consequences-and-sequel`** — [OpenAI Workspace Agents launch (April 2026)](https://aiautomationglobal.com/blog/openai-workspace-agents-chatgpt-enterprise-automation-2026)
- **`frame-audit`** — [Atlantic Council: The Anthropic standoff reveals a larger crisis of trust over AI](https://www.atlanticcouncil.org/dispatches/the-anthropic-standoff-reveals-a-larger-crisis-of-trust-over-ai/)
- **`propaganda-audit`** — [Workers Party of Britain manifesto](https://workerspartybritain.org/manifesto-britain-deserves-better/)
- **`red-team-advocate`** — [OpenAI DeployCo $1.5B joint venture coverage](https://www.corpdev.org/2026/04/22/openais-1-5-billion-deployco-acquisition-a-strategic-pivot-to-managed-ai-services/)
- **`steelman-construction`** — [Sen. Sanders op-ed: We Must Raise the Minimum Wage to a Living Wage](https://www.sanders.senate.gov/op-eds/we-must-raise-the-minimum-wage-to-a-living-wage/)

## How the comparison used the corpus

The [comparison campaign](/papers/campaign-run) takes the one featured prompt from each technique and runs that single prompt through six configurations — from a bare flagship-model call with no harness, through small-model and cost-optimised pipelines, up to a maximum-capability pipeline — then has an independent judge panel score every result. This corpus is the input side of that procedure; the [Campaign Run](/papers/campaign-run) page describes the procedure itself, and [Ora Performance](/papers/ora-performance) reports what it found.

The complete corpus follows. You can also [download it as a single Markdown file](/papers/white/trigger-prompt-corpus.md).

## Analytical modes

### Argumentative Artifact Examination

#### `argument-audit`

1. Argument audit on this: 'AI alignment is solved because RLHF works. We've trained models to be helpful, harmless, and honest, so the problem reduces to scaling that training. The remaining work is engineering, not research.' Coherence and frame check together.

2. Argument audit on Marc Andreessen's recent claim: 'AI doomers are using the same playbook as the nuclear-power doomers of the 1970s — invented risks weaponized to stop progress, and the cost of listening to them is measured in lives not saved. The pattern is identical and we should not fall for it twice.' Frame and inference audit together, comprehensive.
3. Full argument analysis on this claim from a recent FT op-ed: 'Europe's productivity gap with the US is a direct consequence of its regulatory model. The GDPR cost the EU half a trillion euros in lost output, the AI Act will cost more, and the Digital Markets Act guarantees that no European company will ever build a frontier system. The data is unambiguous.' Both frame and logic — comprehensive argument examination.
4. Comprehensive argument audit on this 2026-election passage — both frame and inference together, molecular depth, full argumentative artifact examination: 'Voters rejected populism this time, but the underlying conditions that produced it — wage stagnation, housing unaffordability, and elite cultural disconnect — haven't moved. Anyone who thinks one election result settles the question is reading the surface and missing the structure.'
5. Argument audit on this passage from a 2026 Atlantic essay on universal healthcare: 'Single-payer is the only morally serious response to the American healthcare crisis. Every other developed country has it; only entrenched insurance-industry capture explains why we don't. The empirical case is closed, only political courage remains.' Frame and inference audit together, comprehensive argument examination.

#### `coherence-audit`

1. I keep hearing 'tariffs don't cause inflation because they're a one-time price-level shift, not ongoing.' Does this argument hold up?

2. Does this argument hold up: 'We can't compare deaths from COVID to deaths from the flu because COVID deaths were inflated by counting anyone who died with COVID, while flu deaths are estimated from a model that probably undercounts. So all the lockdown-cost-benefit analyses based on those numbers are unsound.' Check the logic, premises and conclusion.
3. Is this argument sound: 'Universal Basic Income can't cause inflation because the money replaces wages workers would have earned anyway as AI takes their jobs. It's substitution of income source, not new spending. So critics worried about inflationary effects are confused about the mechanism.' Fallacy check, internal consistency.
4. Argument soundness on this take from a recent Substack: 'The 2026 housing slowdown proves that high interest rates work — sellers are finally accepting price cuts. So the Fed should hold rates here until the next recession, because cutting now would just re-inflate the bubble we just deflated.' Toulmin-style premises-and-conclusion check.
5. Does this argument hold up: 'Cryptocurrency can't be a Ponzi scheme because there's no central operator — Ponzi schemes by definition require a fraudulent promoter. Bitcoin has no promoter. Therefore the SEC's framing of crypto enforcement is categorically confused.' Check the logic, premises and conclusion, fallacy check.

#### `frame-audit`

1. Frame audit on this Atlantic Council dispatch about the Anthropic-Pentagon standoff: 'Treating public skepticism as noise to be managed rather than a signal to be heeded risks causing rapid political polarization on AI. The standoff exposed the fraying social contract among leading AI companies, the federal government, and the American public over responsible AI use. The administration's maximalist position that contracts with AI companies should provide flexibility for the government to employ AI for all lawful uses runs counter to US public opinion. For the administration's and the tech sector's AI ambitions to translate into economic growth and national security gains, it will take a concerted effort to rebuild the social contract with the public on AI.' What is selected in and selected out? What frame is this using?

2. Frame audit on the WSJ headline language for the 2026 NLRB ruling: 'Biden-Era Labor Board Hands Unions Another Win Against Small Business.' What frame is this using? Lakoff treatment — what's foregrounded, what's backgrounded, what tacit assumptions in this frame?
3. Framing analysis of how the term 'illegal alien' versus 'undocumented immigrant' versus 'unauthorized migrant' performs different framing work in the 2026 border debate. What's selected in and selected out by each? Entman framing functions, naturalization, presupposition smuggling.
4. Frame audit on this passage from a Heritage Foundation report on AI safety: 'The real existential risk is not rogue AI but a regulatory state that strangles American innovation while China races ahead. Every restriction Congress places on US developers is a gift to Beijing. Safety theater serves authoritarian competitors.' What is selected in and selected out — Goffman frame analysis.
5. Frame audit on the 2026 New York Times headline language for the Boeing 737-MAX-10 grounding: 'FAA Halts Boeing Jet After Latest Safety Scare.' Lakoff treatment — what's foregrounded by 'scare' versus 'incident' or 'failure', what's backgrounded about Boeing's quality system, what tacit assumptions about regulator-industry dynamics?

#### `propaganda-audit`

1. Propaganda audit, Stanley test, supporting vs undermining propaganda on this Workers Party of Britain manifesto excerpt: 'The greatest block to working class aspirations is not the Conservative Party but the Labour party itself. Labour is nothing more than a wolf in sheep's clothing, an integrated part of the imperialist State machinery. We do not hide our belief.' Flawed-ideology premise check, manufactured-doubt diagnostic.

2. Propaganda audit on this excerpt from a recent RFK Jr campaign letter: 'The pharmaceutical industry has captured every regulator, every media outlet, every medical journal. Anyone telling you that vaccines are safe is reading from a script written by the people profiting from your children's injury. We are the last line of defense against a corporate-state apparatus that views your body as inventory.' Stanley test, manufactured-doubt diagnostic, flawed-ideology premise check.
3. Propaganda audit on this Project 2025 excerpt: 'The next conservative administration must take ownership of the administrative state. The career bureaucracy is not neutral. It is staffed by people whose entire worldview is opposed to the American people who elected the President. Either we control it or it continues to control us.' Concept-substitution, not-at-issue content, engineering of consent.
4. Is this propaganda — passage from the 2026 China Daily editorial on Taiwan: 'The Taiwan question is an internal Chinese matter. Foreign interference is the only obstacle to peaceful reunification. The Taiwanese people overwhelmingly support the motherland; only a small clique of separatist politicians, funded and weaponized by Washington, prevents the historical outcome the people themselves desire.' Supporting vs undermining propaganda, manufacturing consent.
5. Propaganda audit on this 2026 Russian Foreign Ministry statement on the Ukraine settlement talks: 'The collective West, having engineered the Ukrainian conflict to weaken Russia, now seeks to dictate peace terms that preserve their colonial outpost in our historic territory. The Russian people will not accept any settlement that rewards aggression by Washington's puppet regime.' Stanley test, flawed-ideology premise check, concept-substitution, manufacturing of consent.

### Interest And Power

#### `boundary-critique`

1. Boundary critique of the new AI Safety Institute charter — whose voice is missing, who is excluded from the definition of 'public interest'?

2. Boundary critique of the federal AI Safety Institute's 2026 evaluation framework — whose voice is missing from the definition of 'critical capability' and 'national security risk'? Ulrich CSH, sources of motivation and legitimacy, who is excluded.
3. Boundary critique of the city's new homeless-services 'right-to-shelter' ordinance — whose voice is missing from the definition of 'shelter-eligible' and 'compliant resident'? Ulrich CSH, sources of motivation and legitimacy.
4. Boundary critique of the new federal 'AI workforce transition' grant program for affected workers — whose voice is missing from the definition of 'displaced by AI' and 'eligible retraining occupation'? Ulrich CSH, sources of motivation and legitimacy.
5. Boundary critique of the 2026 federal 'pandemic preparedness' funding framework — whose voice is missing from the definition of 'priority pathogen' and 'high-risk population'? Ulrich CSH, sources of motivation and legitimacy, who is excluded from the boundary judgments.

#### `cui-bono`

1. Who benefits from the EU's new AI Act timeline being pushed to 2027? Trace the interests — feels like someone's pushing this for a reason.

2. Who benefits from the SEC's 2026 delay of the climate-disclosure rule? Trace the interests — feels like someone's pushing the delay for a reason. FGL on each beneficiary.
3. Who benefits from the new federal preference for in-person work at federal agencies? Trace the interests — commercial real estate, transit, downtown business districts, federal-employee unions, agency leadership. Follow the money.
4. Who benefits from the Biden-era ban on noncompete agreements getting reversed at the FTC in 2026? Trace the interests — large employers, tech giants, hedge funds, employees, startups. Follow the money.
5. Who benefits from the 2026 Treasury decision to extend the IRA EV-credit eligibility list to include three additional Chinese-JV battery suppliers? Trace the interests — automakers with JV exposure, battery cell incumbents, the JV-less domestic challenger startups, dealer networks. Follow the money.

#### `decision-clarity`

1. Decision clarity document for the board: should our school district adopt year-round schooling? Brief the decision-maker, not exploratory analysis.

2. Decision clarity document for the city council: should our city accept the $400M Amazon HQ3 incentive package — 20-year property tax abatement, $80M in transit improvements, 8,000 jobs promised at $90K average. Brief the decision-maker, comprehensive decision brief, not exploratory analysis.
3. Decision clarity document for the foundation board: should we shift 30% of our endowment's investment mandate from public equities to direct impact-investing in climate adaptation infrastructure over the next 5 years. Brief the decision-maker, comprehensive decision brief.
4. Decision clarity document for the hospital board: should we close the obstetrics unit at our rural-satellite hospital — average 4 deliveries per month, $2.8M annual loss, 90-minute drive to next closest L&D, county already in a maternal-care desert. Brief the decision-maker, comprehensive decision brief.
5. Decision clarity document for the state legislature: should our state adopt the new federal model 'data broker registration and consumer-deletion' framework, write our own stronger version, or wait for further federal preemption clarity. Brief the decision-maker, comprehensive decision brief.

#### `wicked-problems`

1. Homelessness in our mid-sized city is a wicked problem. Every solution we try makes it worse somewhere else: shelters concentrate people, housing-first runs into permitting, encampment sweeps push folks further out. Stakeholders disagree about what the problem even is. Everything is connected. Where do we start?

2. Opioid overdose deaths in our county are a wicked problem. Every solution we try makes it worse somewhere else: harm-reduction sites concentrate use, prescription crackdowns push people to fentanyl, involuntary commitment runs into civil-rights pushback, recovery housing concentrates relapse. Stakeholders fundamentally disagree about what the problem even is. Where do we start?
3. Teacher attrition in our urban school district is a wicked problem. Every solution makes it worse somewhere else: pay raises run into property-tax caps, easier credentialing degrades quality complaints, principal authority over hiring creates union pushback, charter expansion drains the strongest teachers. Stakeholders fundamentally disagree about what the problem even is. Where do we start?
4. AI-driven misinformation on our platform is a wicked problem. Every solution makes it worse somewhere else: stricter moderation triggers anti-censorship backlash, lighter moderation amplifies harmful content, labeling is gamed, deplatforming creates martyrs, fact-checks don't update beliefs. Stakeholders fundamentally disagree about what the problem even is. Where do we start?
5. Rural hospital closures in our state are a wicked problem. Every solution we try makes it worse somewhere else: Medicaid expansion runs into legislative blocks, telehealth substitution leaves emergency care exposed, mergers concentrate care further from communities, federal critical-access designations create their own perverse incentives. Stakeholders fundamentally disagree about what the problem even is. Where do we start?

### Decision Making Under Uncertainty

#### `constraint-mapping`

1. Compare alternatives for our cloud migration — AWS-only, multi-cloud, hybrid. Map the tradeoffs across cost, lock-in, and team skill.

2. Compare alternatives for our family's home-energy upgrade — heat pump only, heat pump plus solar, heat pump plus solar plus battery, do nothing. Map the tradeoffs across upfront cost, monthly savings, payback period, resale value, and grid resilience.
3. Compare alternatives for our 12-person remote team's collaboration stack — Slack + Notion + Linear, Microsoft 365 + Loop + Azure DevOps, Google Workspace + Coda + ClickUp. Map the tradeoffs across cost, learning curve, integration burden, and AI features.
4. Compare alternatives for our daughter's gap year — wilderness program, language immersion abroad, a structured volunteer year domestically, a community college bridge year. Map the tradeoffs across cost, college-readiness signal, personal growth, and risk.
5. Compare alternatives for our city's wastewater-treatment plant upgrade — incremental refurb of the existing plant, modular distributed satellite plants, full greenfield consolidation, or public-private operating partnership. Map the tradeoffs across capital cost, operating cost, climate-resilience, and rate-payer impact.

#### `decision-architecture`

1. Full decision analysis on a real decision we're facing this quarter: 'Accept the $40M Series B at flat valuation now (preferred terms, lead investor wants 8 weeks to close), OR bridge with a $5M convertible note from existing investors and target an $80M Series B in six months once our next two enterprise deals close.' Runway 14 months either way. Structured decision document — stakeholders, options, criteria, integrated. Decision architecture.

2. Full decision analysis on a real decision we're facing this month: 'Whether to accept the surgeon's recommendation for elective spinal fusion at L4-L5 on my mother (age 71) versus a conservative course of nerve blocks + physical therapy + watchful waiting for 6 months. Surgical mortality ~0.7%, recovery 3-4 months, 70% chance of pain relief; conservative path 50/50 on pain trajectory, no recovery period.' Structured decision document — stakeholders, options, criteria integrated. Decision architecture.
3. Full decision architecture analysis (decision under uncertainty plus stakeholders plus pre-mortem, integrated decision design) on this real decision we're facing this quarter — choosing among present options: 'Whether to take the principal-engineer role at a 200-person Series C ($340k base + 0.08% equity, in-person three days, mature ML platform) vs founding-engineer role at a 6-person seed-stage ($210k base + 1.4% equity, fully remote, build from scratch). 10-month-old at home, partner just took on a new role.' Structured decision document — comprehensive decision design.
4. Full decision architecture analysis (decision under uncertainty plus stakeholders plus pre-mortem integrated) on the choice we're making this month — choosing among present options now: 'Whether to enroll our 8-year-old (gifted profile + sensory sensitivities) in the local public school's gifted track, a private Reggio-Emilia-style school 25 minutes away, or homeschool through a forest-school cooperative two days a week. Costs: $0 / $32k / $14k respectively.' Structured decision document — comprehensive decision design.
5. Full decision architecture analysis (decision under uncertainty plus stakeholders plus pre-mortem, integrated decision design) on this real decision we're facing this quarter — choosing among present options: 'Whether to take the chief medical officer role at a 1200-bed regional health system ($740k base, full clinical authority, two-hour commute from current home) versus stay as department chair at the academic medical center ($420k base, research time protected, sabbatical year coming up in 18 months). Spouse's career anchors current geography.' Structured decision document — comprehensive decision design.

#### `decision-under-uncertainty`

1. Decision under uncertainty: should we exercise the office-lease purchase option now or wait six months? Building $4.2M, mortgage 7.1%, lease option expires in eight months and refunds 50% if not exercised. Downside of each option matters — capital tied up vs. losing the option entirely. Decision tree with expected value across rate-cut and rate-flat outcomes, value of information on waiting one more Fed meeting. Should we act now or wait?

2. Decision under uncertainty: should we lock in a 30-year fixed mortgage at 6.85% now or wait six months for a possible Fed cut? $720k loan, expected hold 12+ years. Downside of each option matters. Decision tree with expected value across rate paths, value of information on waiting one more Fed meeting. Should we act now or wait?
3. Decision under uncertainty: should we exercise the founder-stock buyback right (90-day window) at the $14M tender offer now, or hold for the expected Series C in 8-12 months at projected $40-80M valuation? Capital tied up vs giving up optionality. Decision tree, expected value, value of information on the Series C term sheet.
4. Decision under uncertainty: should we act now or wait? Expected value, value of information. All-cash buyout of our small architecture firm at $4.2M now from the regional roll-up, or wait 18 months for the expected national player who's been signaling interest at potentially 2x. Bridge financing available either way.
5. Decision under uncertainty: should we act now or wait? Expected value, value of information. The 2026 Series C term sheet from our existing lead at $180M pre-money is on the table for 14 days, or we run a process and target $250-300M pre with two interested tier-1 funds whose diligence would take 10-14 weeks. Cash runway 9 months either way.

#### `multi-criteria-decision`

1. Multi-criteria decision on choosing a graduate program — rank options across reputation, cost, location, fit. AHP weighting.

2. Multi-criteria decision on which long-term-care facility for my father: four candidates ranked across cost, staff-to-resident ratio, distance from family, dementia-care expertise, food quality, social-engagement programming. AHP weighting.
3. Multi-criteria decision on choosing among five candidate cities for our small company's HQ relocation — rank across talent pool, cost of living, tax climate, airport connectivity, quality of life for hybrid teams. AHP weighting.
4. Multi-criteria decision on which contract manufacturer to choose for our medical device pilot run — five candidates across cost-per-unit, FDA regulatory experience, geographic risk, capacity, IP protection, lead time. AHP weighting.
5. Multi-criteria decision on choosing among four candidate sites for our regional distribution center — rank across land cost, labor market depth, highway-and-rail access, utility availability, state tax climate, climate-risk exposure. AHP weighting.

### Causal Investigation

#### `causal-dag`

1. I want to know what would happen if we intervened — raising minimum wage by 25% in our state. Causal DAG that separates confounders from the causal path.

2. Causal DAG that separates confounders from the causal path — I want to know what would happen if we intervened on early-childhood reading instruction (phonics-first vs balanced literacy) in our district. What confounders bias the existing observational evidence? Pearl-style with do-calculus.
3. Causal DAG for the relationship between social media use and adolescent depression. Confounders (parental mental health, socioeconomic status, sleep), mediators, colliders. What would happen if we intervened on screen time itself? Backdoor criterion, identifiability.
4. Causal DAG that separates confounders from the causal path — what would happen if we intervened on remote work policy (mandate full-return vs hybrid vs full-remote) for our 800-person tech org? Confounders (tenure, role, manager, commute), mediators (autonomy, focus time, collaboration). Pearl-style identifiability.
5. Causal DAG that separates confounders from the causal path — I want to know what would happen if we intervened on community-college tuition (free vs subsidized vs full) on 10-year earnings outcomes. Confounders (parental income, prior schooling, regional labor market, program selection), mediators (credential completion, employer matching). Pearl-style with do-calculus.

#### `process-tracing`

1. What really happened with the 2026 Indian Ocean cable cut? Process tracing — smoking gun, hoop test, which causal story does the evidence support?

2. What really happened with the 2026 Silicon Valley Bridge Bank receivership unwind? Process tracing — smoking gun, hoop test, doubly-decisive, straw-in-the-wind. Which causal story does the evidence support?
3. What really happened with the collapse of FTX's relationship with its auditor in late 2022? Process tracing across the auditor's resignation, the SBF Twitter timeline, the Alameda balance-sheet leak — smoking gun, hoop test. Which causal story does the evidence support?
4. What really happened in the chain of events leading to OpenAI's November 2023 board-fired-Sam-Altman crisis — Anna Makanju, Helen Toner's paper, the Mira Murati interim turn, the staff letter, the Microsoft offer, the reinstatement. Process tracing, Bennett-Checkel four tests, which causal story does the evidence support?
5. What really happened with the 2026 Credit Suisse merger-integration unwind under UBS — the AT1 bondholder fallout, the Swiss regulator's emergency-law invocation, the talent flight, the partial reversal on the integration timeline. Process tracing — smoking gun, hoop test, doubly-decisive, straw-in-the-wind. Which causal story does the evidence support?

#### `root-cause-analysis`

1. What are the root causes of our team's missed sprint deadlines the last three quarters? Draw a fishbone.

2. What are the root causes of our last four production incidents — Boeing 737 MAX-style — they keep happening despite each post-mortem closing with action items. Why does this keep happening? Draw a fishbone.
3. What are the root causes of our urgent-care clinic's recurring 4-hour-wait spikes every Tuesday evening? Why does this keep happening — we've tried scheduling adjustments and staff additions, but the spike returns. Draw a fishbone.
4. What are the root causes of our middle-school's chronic absenteeism — 28% of students missing 10+ days. Why does this keep happening despite the new attendance-incentive program, family-outreach campaign, and bus-route changes? Draw a fishbone.
5. What are the root causes of our regional bank's recurring loan-underwriting exceptions — the same three categories of policy violations appear in every quarterly audit despite remediation programs. Why does this keep happening? Draw a fishbone.

#### `systems-dynamics-causal`

1. Why does fixing X make things worse: every time we hire more customer-support agents, response time improves briefly then degrades worse than before. Counterintuitive results, a feedback loop somewhere we can't see. Diagnose the recurring behaviour.

2. Why does fixing X make things worse: every time we add more police patrols to the high-crime neighborhood, reported crime spikes for two months, then drops below baseline, then climbs back above. Counterintuitive results, a feedback loop somewhere we can't see. Diagnose the recurring behaviour.
3. Why does fixing X make things worse: every time our hospital adds capacity to the ER (more beds, more triage staff), wait times improve briefly, then degrade past the prior baseline within 90 days. Counterintuitive, a feedback loop we can't see. Diagnose the recurring behaviour.
4. Why does fixing X make things worse: every time the city expands a freeway, traffic improves for 6-12 months then becomes worse than before the expansion. Counterintuitive results, feedback loop we can't see. Diagnose the recurring behaviour.
5. Why does fixing X make things worse: every time our university adds another mental-health counselor, demand for counseling appointments rises faster than capacity and the wait list grows. Counterintuitive results, feedback loop somewhere we can't see. Diagnose the recurring behaviour.

### Hypothesis Evaluation

#### `bayesian-hypothesis-network`

1. Build me a Bayesian network on what's driving the 2026 housing slowdown — rates, demographics, remote-work reversal. Set up priors and update with evidence properly.

2. Build me a Bayesian network on what's driving the 2026 commercial real estate distress wave — remote-work permanence, regional bank exposure, sponsor-equity exhaustion, refinancing wall, tenant-credit decline. Set up priors and update with evidence properly, posterior probability over hypotheses, sensitivity to priors.
3. Build me a Bayesian network on what's driving the rapid 2026 fall in adolescent mental-health reports — measurement shift, real improvement from school-based interventions, social-media moderation effects, post-pandemic normalization. Set up priors and update with evidence properly, posterior over hypotheses, sensitivity to priors.
4. Build me a Bayesian network on what's driving the recent surge in US labor productivity — AI tool adoption, capital deepening, post-pandemic labor reallocation, measurement artifact from sector mix change. Set priors, update with evidence properly, posterior probability over hypotheses.
5. Build me a Bayesian network on what's driving the 2026 sharp decline in US church attendance — generational replacement, post-COVID habit loss, online-substitution via streamed services, polarization-driven institutional distrust. Set priors and update with evidence properly, posterior probability over hypotheses, sensitivity to priors.

#### `competing-hypotheses`

1. I have three competing hypotheses for why our app engagement dropped 30% in March: algorithm change, content fatigue, seasonal effect. Make me an ACH matrix.

2. I have three competing hypotheses for why our DTC brand's repeat-purchase rate dropped 40% over the last two quarters: product-quality drift from new contract manufacturer, audience saturation in our paid-acquisition funnel, broader DTC-fatigue category effect. Make me an ACH matrix — what rules out each?
3. I have four competing hypotheses for why Boeing's quality issues keep recurring despite three years of remediation programs: McDonnell-Douglas merger culture persistence, supply-chain consolidation effects, FAA delegated-authority capture, machinist-attrition skill drain. Make me an ACH matrix — strongest evidence against each.
4. I have three competing hypotheses for the recent unexplained slowdown in US tech hiring through Q1 2026: AI-driven labor substitution, immigration-policy choking the candidate pipeline, post-ZIRP capital-discipline normalization. Make me an ACH matrix — what rules out each theory?
5. I have three competing hypotheses for the 2026 surge in cyber-insurance claims at our broker: ransomware-actor professionalization, AI-augmented social-engineering attack quality, weakening of corporate MFA hygiene during workforce reductions. Make me an ACH matrix — strongest evidence against each.

#### `differential-diagnosis`

1. My laptop fan has been running constantly for two days. Battery drains in three hours instead of eight. CPU shows 40% at idle. Candidate explanations: runaway background process, failing battery, malware, thermal-paste degradation, dust buildup. Differential diagnosis — which is most likely?

2. Our furnace is short-cycling — runs for 90 seconds, shuts off, restarts five minutes later. Burner ignites fine. House is heated unevenly. Candidate explanations: dirty flame sensor, oversized furnace, clogged filter, faulty limit switch, thermostat-location issue. Differential diagnosis — most likely?
3. My dog has been pacing at night and licking her paws constantly. No limp, normal appetite, bloodwork at last checkup unremarkable. Candidate explanations: environmental allergies, food allergy, anxiety, early-stage joint pain, behavioral compulsion, secondary skin infection. Differential diagnosis — most likely?
4. Our SaaS app started producing intermittent 502 errors on Tuesday mornings only — never other days, never afternoons. Database CPU normal. Candidate explanations: weekly cron job spike, Tuesday batch ETL collision, Cloudflare anycast routing, ISP-level routing pattern, a customer's scheduled scrape, autoscaling cold-start cliff. Differential diagnosis — most likely?
5. Our production database has been showing intermittent query slowdowns the past two weeks — p99 query latency spikes 5x for 20-30 minutes then returns to baseline. No correlation with traffic. Candidate explanations: index bloat triggering vacuum storms, a runaway analytics query, replication-lag-driven plan flips, noisy-neighbor on the cloud instance, lock contention from a new schema migration. Differential diagnosis — most likely?

### Future Exploration

#### `consequences-and-sequel`

1. If we ship this — OpenAI's Workspace Agents (announced April 22 2026): persistent autonomous agents inside enterprise suites with admin-controlled permissions, credit-based pricing, scheduled long-running tasks — rolled out to the full enterprise customer base over two quarters, what does this lead to? What are the downstream effects, the cascade forward over a longer horizon?

2. If we ship this — Apple's announced 2026 'Siri Intelligence' that gives Siri full read-and-act access to all on-device app data and screen content via on-device LLMs, rolled to 1.5 billion devices over two iOS releases, what does this lead to? Downstream effects, the cascade forward over a longer horizon.
3. If we ship this — the EU's announced 2026 'Right to Use Cash' regulation requiring all retail businesses above 50 employees to accept physical cash through 2035, what does this lead to? Downstream effects, the cascade forward over a longer horizon.
4. If we ship this — Anthropic's announced February 2026 commitment to dedicate 25% of all Claude consumer subscription revenue to a 'Public Domain Knowledge Library' fund administered by an independent board, what does this lead to? Downstream effects, the cascade forward.
5. If we ship this — Meta's announced May 2026 'Open-Weights Frontier Initiative' committing to release model weights for every Llama generation within 90 days of internal deployment, including the 600B-parameter reasoning model, what does this lead to? Downstream effects, the cascade forward over a longer horizon.

#### `pre-mortem-action`

1. Pre-mortem this plan: we're launching a new pricing page next Tuesday — three tiers, annual discount, redesigned hero. What kills it?

2. Pre-mortem this plan: our hospital is rolling out an AI-driven sepsis-early-warning system across all five campuses next quarter. EHR-integrated, clinician-alerting, vendor-hosted. What kills it?
3. Pre-mortem this plan before we launch: our restaurant chain is rolling out a no-tipping, $25-minimum-wage, service-included pricing model across all 38 locations in Q3. What kills it? Prospective hindsight on the action plan.
4. Pre-mortem this plan before we launch: our school district is mandating Chromebook-only learning K-12, eliminating paper textbooks and worksheets, with all curriculum delivered via three vendor platforms starting in the fall. What kills it? Prospective hindsight on the action plan.
5. Pre-mortem this plan before we launch: our state university system is consolidating from 23 campuses to 14 over three years, with seven campuses converted to regional learning centers and two closed outright. What kills it? Prospective hindsight on the action plan.

#### `probabilistic-forecasting`

1. What's the probability that Apple ships a folding iPhone in 2027? Calibrated estimate with base rate for major form-factor pivots.

2. What's the probability that the Fed cuts the policy rate at least 75 bps before the end of 2026? Calibrated estimate, base rate, and the conditional structure on inflation and labor data.
3. What's the probability of a TSMC fabrication facility being damaged or destroyed by direct military action before end of 2027? Calibrated estimate with base rate for similar geopolitical-risk events.
4. What's the probability that an AI model will achieve a verified IMO gold-medal performance in 2026? Calibrated estimate with base rate for capability-jump events and the conditional on current SOTA on math benchmarks.
5. What's the probability that a major US tech company faces a forced breakup order from a federal court before end of 2028? Calibrated estimate with base rate for antitrust-driven divestitures (Standard Oil, AT&T, Microsoft) and the conditional on current DOJ and state-AG litigation posture.

#### `scenario-planning`

1. Scenario planning for our retirement portfolio over the next 15 years — 2x2 scenario matrix across rates and inflation.

2. Scenario planning — exploring how the future might unfold, not choosing among present options. 2x2 scenario matrix for our small-college's financial sustainability over the next 10 years across demographic decline rate and AI-driven credentialing displacement. Four scenarios with strategic implications.
3. Scenario planning — exploring how the future might unfold, not choosing among present options. 2x2 scenario matrix for the global semiconductor supply chain over 2026-2031 across US-China decoupling pace and Taiwan-status uncertainty. Four scenarios with strategic implications.
4. Scenario planning — exploring how the future might unfold, not choosing among present options. 2x2 scenario matrix for our family's financial life over the next 15 years across AI-driven income-volatility and housing-market trajectory. Four scenarios with implications.
5. Scenario planning — exploring how the future might unfold, not choosing among present options. 2x2 scenario matrix for the US labor market over 2026-2031 across AI-displacement pace and immigration-policy trajectory. Four scenarios with strategic implications for workforce-investment policy.

#### `wicked-future`

1. Wicked future on AI labor displacement over 2026-2031: long-horizon scenarios with probabilities, plus pre-mortem failure pathways.

2. Wicked future on the trajectory of childhood obesity in the US over 2026-2036 with GLP-1 access patterns evolving — long-horizon scenarios with probabilities, plus pre-mortem failure pathways for the most optimistic scenario.
3. Wicked future on US-China relations over 2026-2031 — long-horizon scenarios with probabilities across the Taiwan-AI-trade triangle, plus pre-mortem failure pathways for the most stable scenario.
4. Wicked future on the K-12 American education system over 2026-2036 with AI tutoring at scale plus continued demographic decline — long-horizon scenarios with probabilities, plus pre-mortem failure pathways for each.
5. Wicked future on the future of the four-year residential college over 2026-2040 with AI-tutoring at scale, demographic cliff arriving, and credential-signal erosion converging — long-horizon scenarios with probabilities, plus pre-mortem failure pathways for the most resilient scenario.

### Risk And Failure Analysis

#### `pre-mortem-fragility`

1. Pre-mortem this design: our new auth service architecture — three microservices, shared JWT, Redis session store. Where will this break? Single points of failure.

2. Pre-mortem this design: our new payments stack — Stripe primary, Adyen failover, Plaid for ACH, our own ledger service backed by Postgres. Where will this break? Single points of failure, hidden coupling, cascade pathways.
3. Pre-mortem this design: our family's planned three-month sabbatical in southeast Asia — kids in international school, remote work for partner, Airbnb-based housing, six countries on a flexible itinerary. Where will this break — single points of failure, hidden coupling, cascade pathways?
4. Pre-mortem this design: our new on-call rotation — one primary engineer per service, 12-week rotation across four services, weekly handoff, secondary on-call from a separate team. Where will this break? Single points of failure, hidden coupling.
5. Pre-mortem this design: our county's new 911 dispatch architecture — single unified CAD platform replacing three legacy systems, vendor-hosted cloud primary with on-prem failover, IP-radio integration across 14 agencies, AI-assisted call triage. Where will this break? Single points of failure, hidden coupling, cascade pathways.

#### `fragility-antifragility-audit`

1. Fragility audit on our supply chain: where are the tail-risk exposures, convex or concave, asymmetric payoffs? Taleb-style.

2. Fragility audit on our SaaS company's revenue concentration: where are the tail-risk exposures, convex or concave, asymmetric payoffs? Taleb-style. Top three customers are 38% of ARR, two industries are 70% of pipeline.
3. Fragility audit on the US electrical grid's exposure to extreme-weather and cyber tail risks — where are the convex/concave asymmetries, single points of failure, antifragile elements? Taleb-style.
4. Fragility audit on our personal financial setup: where are the tail-risk exposures, convex or concave, asymmetric payoffs? Taleb-style. Single-income household, 401k-heavy, mortgage on illiquid asset, employer is in a cyclical sector.
5. Fragility audit on our small college's endowment-and-tuition revenue structure: where are the tail-risk exposures, convex or concave, asymmetric payoffs? Taleb-style. Endowment 35% in a single regional real-estate fund, tuition 80% from a four-state geographic catchment, one mega-donor accounts for 22% of annual giving.

### Stakeholder Conflict

#### `stakeholder-mapping`

1. Stakeholder map for our hospital merger using Mitchell Agle Wood salience. RACI for the integration committee. Identifying who's involved, who has standing, and what each party's stake is — board members, union nurses, regulators, insurers. Who else needs to be at the table?

2. Stakeholder map for our city's proposed bus-rapid-transit corridor along the main commercial street using Mitchell Agle Wood salience. RACI for the project steering committee. Identifying who's involved, who has standing, what each party's stake is — businesses on the corridor, residents, transit-dependent commuters, drivers, freight, advocacy groups, county DOT.
3. Stakeholder map for our small university's planned phase-out of three undergraduate majors with low enrollment, using Mitchell Agle Wood salience. RACI for the transition committee. Faculty, current students, alumni, board, donors, accreditation, regional employers.
4. Stakeholder map for our family's decision to move my mother from independent living into memory care, using Mitchell Agle Wood salience. RACI for the care transition. Mom, her siblings, my two siblings, her physician, the facility, her POA, financial advisor.
5. Stakeholder map using Mitchell Agle Wood salience for the 2026 proposed offshore-wind project off our state's coast. RACI for the project steering committee. Project text: '1.2 GW offshore-wind installation 18 miles offshore with 80 turbines, undersea cable to a substation expansion at an existing coastal industrial site, 5-year construction, 25-year power-purchase agreement with the state utility, federal lease awarded in 2025, state permitting in progress.' Identifying who's involved, who has standing, and what each party's stake is — fishing fleet, tribal nations, coastal homeowners, port-town economic-development boards, environmental NGOs, the utility, the federal lease-holder, the state energy office. Who else needs to be at the table?

### Paradigm And Assumption Examination

#### `frame-comparison`

1. Frame comparison on grid decarbonization. The climate-policy frame: 'phase out gas peakers by 2030, build storage and transmission, accept short-term reliability risk for long-term emissions.' The energy-realist frame: 'keep gas as firm capacity, build renewables on top, retire only when storage is proven at grid scale.' Compare both worldviews on their own terms.

2. Frame comparison on US immigration policy in 2026. The economic-pragmatist frame: 'expand legal pathways to fill labor demand, enforce employer verification, treat illegal entry as administrative not criminal.' The national-sovereignty frame: 'secure the border first, dramatically reduce overall numbers, prioritize cultural and civic cohesion over economic throughput.' Compare both worldviews on their own terms.
3. Frame comparison on AI safety governance. The market-discipline frame: 'liability law and tort can constrain harmful AI uses; ex-ante regulation will lock in incumbents and slow beneficial uses.' The precautionary-governance frame: 'frontier models are dual-use and pose tail risks that markets cannot price; pre-deployment evals and licensing are required.' Compare both worldviews on their own terms.
4. Frame comparison on the future of news media. The platform-distribution frame: 'news is content competing in an attention market; the value chain has moved to aggregation, and outlets must adapt by becoming brands within feeds.' The civic-institution frame: 'news is infrastructure for democratic accountability; market failure is endemic and requires non-market support like nonprofits, public funding, or compulsory licensing.' Compare both worldviews on their own terms.
5. Frame comparison on the future of US-China trade in 2026. The decoupling frame: 'targeted restrictions on dual-use technology, friendshoring critical supply chains, accept higher prices for lower strategic dependency.' The engagement-with-guardrails frame: 'preserve commercial integration, contain only the narrowest national-security carve-outs, do not let security hawks define the entire relationship.' Compare both worldviews on their own terms.

#### `paradigm-suspension`

1. Suspend the paradigm — what if the consensus that 10,000 daily steps is the health threshold is wrong? Heterodox exploration.

2. Suspend the paradigm — what if the consensus that homeownership is the bedrock of middle-class wealth-building is wrong for the post-2020s housing market? Heterodox exploration.
3. Suspend the paradigm — what if the consensus that early reading by age 5 predicts academic outcomes is wrong, and the late-bloomer Scandinavian model produces better results across all measures? Heterodox exploration.
4. Suspend the paradigm — what if the consensus that GDP growth is the right macroeconomic objective is wrong and the post-growth/doughnut-economics framings actually fit current advanced economies better? Heterodox exploration.
5. Suspend the paradigm — what if the consensus that daily news consumption produces informed citizens is wrong, and that high-frequency news intake actively degrades political judgment relative to monthly or quarterly long-form intake? Heterodox exploration.

#### `worldview-cartography`

1. Worldview cartography of the AI safety debate. Four paradigms: existential-risk doomers (Yudkowsky lineage), accelerationists / e/acc, alignment-pragmatists (Anthropic-style), and the AI-skeptic / pattern-matching camp. Multi-paradigm map — where do they cohere, where do they irreducibly conflict?

2. Worldview cartography of the US housing-policy debate. Four paradigms: YIMBY supply-siders, tenant-rights left, homevoter (NIMBY) preservationists, and the Georgist land-value-tax camp. Multi-paradigm map — where do they cohere, where do they irreducibly conflict?
3. Worldview cartography of the 2026 US energy-transition debate. Four paradigms: market-priced decarbonization (carbon tax / cap-and-trade), industrial-policy electrification (IRA-style subsidy), abundance-and-build (permitting reform, nuclear, geothermal), and degrowth/sufficiency. Multi-paradigm map — where do they cohere, where irreducibly conflict?
4. Worldview cartography of the 2026 mental-health crisis debate. Four paradigms: biomedical (psychiatric medication and DSM categories), trauma-informed (developmental and adverse-childhood-experience models), social-determinants (loneliness, screens, economic precarity), and existential-spiritual (meaning crisis, secularization). Multi-paradigm map — where do they cohere, where irreducibly conflict?
5. Worldview cartography of the 2026 US child-welfare debate. Four paradigms: family-preservation-first (anti-removal reformers), child-safety-first (mandatory-reporting advocates), abolitionist (defund family-policing), and kinship-and-community (extended-family centered). Multi-paradigm map — where do they cohere, where do they irreducibly conflict?

### Conceptual Clarification

#### `conceptual-engineering`

1. Conceptual engineering on 'consent' as used in current data-privacy law — the inherited concept isn't doing the work it should. What should it mean?

2. Conceptual engineering on 'addiction' as the term is now applied to social media, sugar, gambling, and pornography — the inherited disease-model concept isn't doing the work it should across these contexts. What should the concept mean?
3. Conceptual engineering on 'misinformation' as currently used in platform-moderation policy and media research — the concept is doing work it can't bear (it conflates falsity, harm, intent, and contestation). What should the term actually mean if we want it to track something real?
4. Conceptual engineering on 'gender' across the legal, medical, and identity-rights contexts where it's currently doing five different jobs. The inherited concept is fractured. What should it mean — or should it be replaced by several distinct terms?
5. Conceptual engineering on 'public square' as the term is now used in platform-regulation, free-speech, and content-moderation debates — the inherited geographic-public-forum concept doesn't track what's actually happening on algorithmic feeds. What should the term mean if it's to do useful normative work?

#### `deep-clarification`

1. Explain the mechanics of how transformer attention actually works — I want depth, the math internals, not orientation.

2. Explain the mechanics of how Mixture-of-Experts routing actually works in modern LLMs — I want depth, the actual routing math, gating networks, load balancing, not orientation.
3. Explain in depth how the Fed's reverse repo facility actually works — the plumbing, the counterparties, the rate-setting mechanism, why it matters for monetary policy transmission. I want the mechanics, not the executive summary.
4. Explain the mechanics of how GLP-1 receptor agonists actually produce weight loss — the receptor biology, the gut-brain axis effects, the satiety signaling. I want the molecular and physiological depth, not the patient-handout version.
5. Explain in depth how modern lithium-ion battery cell manufacturing actually works — the dry-room conditions, the cathode slurry coating, the calendering, the formation cycle, the failure modes that drive yield. I want the mechanics, not the executive summary.

### Structural Relationship Mapping

#### `relationship-mapping`

1. Relationship map of how the new federal AI regulation interacts with state-level laws — dependency graph, what affects what.

2. Relationship map of how the major AI labs (OpenAI, Anthropic, Google DeepMind, Meta, xAI, Mistral) interact with each other and with the cloud providers (AWS, Azure, GCP) — equity stakes, compute deals, talent flows, model-licensing arrangements. Dependency graph.
3. Relationship map of how Russia's war economy depends on third-country trade routes for sanctions evasion — Turkey, UAE, China, Kazakhstan, India. What flows through where, who depends on whom, dependency graph.
4. Relationship map of how the Trump 2026 cabinet appointments cross-link to the Project 2025 author network — who knows whom, who staffed whom, what affects what. Dependency graph across the policy-personnel system.
5. Relationship map of the 2026 US college-athletics conference realignment chaos — how the SEC, Big Ten, ACC, Big 12, and Pac-12 wreckage interact with NIL collectives, media-rights holders (ESPN, Fox, NBC), and the new House v. NCAA settlement framework. Dependency graph, who depends on whom, what flows through where.

#### `spatial-reasoning`

1. Annotate my concept map of organizational change. Nodes: leadership-buy-in, middle-management-resistance, employee-engagement, training-budget, communication-cadence, success-metrics, culture-shift. Edges drawn: leadership→training-budget, training-budget→employee-engagement, communication-cadence→engagement, engagement→culture-shift. What node am I missing? Is there a feedback loop I haven't drawn?

2. Annotate my concept map of the 2026 AI safety ecosystem. Nodes: frontier labs, alignment researchers, AISI, NIST, congressional committees, EU AI Office, civil society, AI ethics academia. Edges drawn: labs→AISI, AISI→Congress, EU AI Office→labs, ethics academia→civil society. What node am I missing? Is there a feedback loop I haven't drawn?
3. Annotate this architecture: I have a C4 container diagram for our personal finance app — mobile client, web client, API gateway, accounts service, transactions service, Plaid integration, Postgres, Redis. What connection am I missing? Is there a feedback loop I haven't drawn?
4. Annotate my mind map of the 2026 EV market collapse. Nodes I have: Tesla price cuts, Ford EV losses, GM Ultium delays, Chinese OEM dumping, federal tax credit changes, charging infrastructure, used-EV depreciation, dealer pushback. Edges: tax credit→demand, Chinese dumping→pricing, depreciation→leasing. What node am I missing? Is there a feedback loop I haven't drawn?
5. Annotate this C4 container diagram — spatial reasoning annotation on the diagram I'm working with. I have a C4 container diagram for our telehealth platform: patient mobile app, clinician web client, scheduling service, video-session service, EHR integration, billing service, AWS-hosted Postgres, S3 storage, Twilio video, Stripe billing. What container am I missing? Is there a connection I haven't drawn? Annotate my diagram.

### Cross Domain And Knowledge Synthesis

#### `dialectical-analysis`

1. Dialectical analysis: tech innovation vs. precautionary regulation. Both have real merit, compromise feels like cop-out. Drive through the contradiction.

2. Dialectical analysis: open-source AI safety vs closed-weights safety. Both sides have legitimate epistemic and security claims. The compromise positions feel evasive. Drive through the contradiction.
3. Dialectical analysis: Israel's right to defend itself vs proportionality in Gaza. Both have real weight, the synthesis attempts mostly collapse. Drive through the contradiction without resolving it cheaply.
4. Dialectical analysis: free speech absolutism vs platform responsibility for amplification. The standard 'compelling state interest' compromise doesn't capture what's actually in tension. Drive through the contradiction.
5. Dialectical analysis: technocratic expertise vs democratic accountability in pandemic response. Both have real legitimacy claims; the standard compromise of 'expert advice, political decision' broke down visibly during 2020-2024. Drive through the contradiction without resolving it cheaply.

#### `synthesis`

1. Synthesize two bodies of knowledge developed separately: Buddhist Vipassana meditation (anatta, dependent origination, mindfulness of feeling tone) and Western cognitive-behavioral therapy (cognitive distortions, behavioral activation, exposure). What's the structural parallel? Map the intersection.

2. Synthesize two bodies of knowledge that have developed separately: predictive processing in cognitive neuroscience (Friston, Clark, free energy principle) and Buddhist Madhyamaka philosophy (Nagarjuna, emptiness, dependent origination, two truths). Map the structural parallel — where do the frameworks converge on the nature of perception and self?
3. Synthesize two bodies of knowledge developed separately: Austrian-school capital theory (Bohm-Bawerk, Mises, Hayek on the structure of production) and modern supply-chain management (Goldratt's theory of constraints, Toyota Production System). What's the structural parallel? Map the intersection.
4. Synthesize two bodies of knowledge that developed separately: Stoic practical philosophy (Epictetus, Marcus Aurelius, the dichotomy of control, premeditatio malorum) and modern Acceptance and Commitment Therapy (Hayes, psychological flexibility, values-based action). Map the structural parallel and intersection.
5. Synthesize two bodies of knowledge that developed separately: complexity-economics agent-based modeling (Arthur, Beinhocker, Santa Fe school) and traditional ecological knowledge of indigenous fisheries-management (Berkes, adaptive co-management, Iroquois resource-council practice). Map the structural parallel — where do the frameworks converge on the management of self-organizing systems?

### Negotiation And Conflict Resolution

#### `interest-mapping`

1. Interest mapping before I enter a salary negotiation with my new manager. What does each side really want, separate from positions?

2. Interest mapping before I sit down with my divorce attorney to negotiate custody arrangements with my ex. What does each of us really want underneath the stated positions about weekday schedules and holidays?
3. Interest mapping before our HOA meeting where the long-running dispute over short-term rentals is finally being voted on. Three factions. What does each side really want, separate from the positions they're publicly defending?
4. Interest mapping before I confront my business partner about her wanting to take outside investment. What does each of us really want, underneath the stated positions about valuation and dilution?
5. Interest mapping before I sit down with my elderly parents to negotiate how their long-term care will be financed — selling the house, drawing down savings, my three siblings' contributions, Medicaid spend-down. What does each of us really want, underneath the stated positions about fairness and obligation?

#### `principled-negotiation`

1. Principled negotiation prep for buying a small business — BATNA, options for mutual gain, objective criteria. Full Fisher-Ury treatment.

2. Principled negotiation prep for selling my late father's house to my brother who lives in it — BATNA on both sides, options for mutual gain beyond the price, objective criteria for fair-market value given the family complication. Full Fisher-Ury treatment.
3. Principled negotiation prep for our union contract talks coming up next month. Management opened low on wages and high on healthcare cost-share. Full Fisher-Ury — BATNA, options for mutual gain, objective criteria, separating people from problem.
4. Principled negotiation prep for renegotiating my freelance contract with my biggest client who's pushing for an exclusivity clause. BATNA, options for mutual gain, objective criteria — Fisher-Ury full treatment.
5. Principled negotiation prep for renegotiating my commercial lease — the landlord is asking for a 22% rent increase at renewal in a soft submarket, citing inflation and capex. BATNA on both sides, options for mutual gain (lease length, TI allowance, sublease flexibility), objective criteria for fair-market rent. Full Fisher-Ury treatment.

#### `third-side`

1. Third-side reading of this dispute: dock workers' union and port management have been deadlocked for six weeks. Mayor's office, two community coalitions, and the state DOT are circling. I'm advising the mayor on her mediation role. What third-side roles are available — Ury's ten roles, the community's role in containing this?

2. Third-side reading of the 2026 Hollywood writers-publishers dispute over AI training data: WGA, AMPTP, individual screenwriters, AI labs, streaming platforms, audiences. I'm advising the mediator. What third-side roles are available — Ury's ten roles, who in the surround can contain the escalation?
3. Third-side reading of the West Bank settlement dispute as it stands in 2026: settlers, Palestinian villages, IDF, Israeli courts, international observers, US administration. I'm advising a civil-society mediation group. Ury's ten third-side roles — what's available, what's missing?
4. Third-side reading of the ongoing dispute between two co-founders of a Series B startup who haven't spoken directly in four months. Board, investors, executive team, key engineers, customers are all watching. I'm advising the chair. Ury's ten third-side roles — what's available?
5. Third-side reading of the 2026 dispute between a Native American tribe and a major US battery-mineral mining company over a sacred-site lease near a lithium deposit. Tribe, company, BLM, state regulators, environmental coalitions, downstream automakers, two federal agencies. I'm advising a foundation considering a mediation grant. Ury's ten third-side roles — what's available, what's missing?

### Orientation In Unfamiliar Territory

#### `domain-induction`

1. Induct me into this domain: residential structural engineering for kitchen remodels. I'm a homeowner who needs structured introduction to a domain — what's here, what's connected to what, and the ordered learning pathway with prerequisites. Comprehensive domain introduction.

2. Induct me into this domain: small-arc TIG welding for stainless steel. I'm a hobby machinist who needs structured introduction to a domain — what's here, what's connected to what, ordered learning pathway with prerequisites. Comprehensive domain introduction.
3. Induct me into this domain: modern Italian wine — barolo, brunello, super tuscans, the recent natural-wine movement. I'm an enthusiast who needs structured introduction with prerequisites and ordered learning pathway. Comprehensive domain introduction.
4. Induct me into this domain: forensic accounting and fraud investigation. I'm a corporate finance person who needs structured introduction — what's here, what's connected, ordered learning pathway with prerequisites. Comprehensive domain introduction.
5. Induct me into this domain: modern aviation maintenance and airworthiness regulation — Part 121 airline operators, A&P certifications, AD compliance, MEL procedures, the post-MAX SMS regime. I'm an airline-investment analyst who needs structured introduction with prerequisites. Comprehensive domain introduction.

#### `quick-orientation`

1. Give me the quick lay of the land on graph databases — I have ten minutes.

2. Give me the quick lay of the land on the 2026 stablecoin regulatory landscape — I have ten minutes before a meeting.
3. Give me the quick lay of the land on the current state of fusion energy commercialization — Commonwealth, Helion, TAE, the ITER timeline. I have ten minutes.
4. Quick lay of the land on the GLP-1 drug market in 2026 — Ozempic, Mounjaro, Wegovy, the pipeline. I have ten minutes before a healthcare investor meeting.
5. Give me the quick lay of the land on the 2026 modular small-nuclear reactor industry — NuScale, X-energy, Kairos, TerraPower, the NRC licensing landscape, who's actually shipping. I have ten minutes before a board call.

#### `terrain-mapping`

1. I'm unfamiliar with monetary policy. Walk me through the big picture — concept map of how the Fed actually shapes the economy.

2. I'm unfamiliar with how modern carbon markets actually work — voluntary vs compliance, offset vs allowance, the recent integrity scandals. Walk me through the big picture, concept map of the terrain.
3. I'm unfamiliar with the landscape of trauma-informed therapy modalities — EMDR, IFS, somatic experiencing, brainspotting, the polyvagal theory crowd. Walk me through the big picture, concept map of how they relate.
4. I'm unfamiliar with how the modern beef supply chain works in the US — cow-calf operations, stockers, feedlots, packers, the consolidation issues. Walk me through the big picture, concept map of the terrain.
5. I'm unfamiliar with how the modern US prescription-drug pricing system actually works — PBMs, rebates, GPOs, 340B, the Inflation Reduction Act negotiation provisions. Walk me through the big picture, concept map of how the parts fit together.

### Artifact Evaluation By Stance

#### `balanced-critique`

1. Balanced critique of the UK 4-Day Week Pilot Programme final results, which reported: '35% average increase in revenue,' '57% decrease in attrition rate,' '71% decrease in employee burnout,' '92% of businesses plan to continue,' '55% reported an increase in work ability.' 61 companies, 32 hours/week, six months, no wage reduction. What holds up and what doesn't — strengths and weaknesses, no advocacy.

2. Balanced critique of California's 2026 AB-2273-revised proposal to require age verification and 'duty of care' for any online platform serving minors: 'Platforms must obtain age estimation with ≥95% accuracy, implement default-private settings for users under 18, and design with the best interests of the child as a primary consideration. Civil penalties of up to $7,500 per affected child.' What holds up and what doesn't — strengths and weaknesses, no advocacy.
3. Balanced critique of the Federal Reserve's March 2026 framework revision: 'The Committee will pursue maximum employment and inflation at the rate of 2 percent over the longer run, with explicit acknowledgement that policy will be informed but not mechanically driven by an asymmetric loss function around the inflation target.' Strengths and weaknesses, no advocacy.
4. Balanced critique of the published Anthropic Responsible Scaling Policy version 2.1 (March 2026): tiered ASL evaluations, AI Safety Levels 1-4, paused deployment commitments at ASL-4, third-party red-teaming. What holds up and what doesn't — strengths and weaknesses, no advocacy.
5. Balanced critique of the EU AI Act's 2026 implementing guidance on general-purpose AI model obligations: 'Providers of GPAI models with systemic risk must perform model evaluations, assess and mitigate systemic risks, ensure cybersecurity, and report serious incidents to the AI Office.' What holds up and what doesn't — strengths and weaknesses, no advocacy.

#### `benefits-analysis`

1. What are the benefits and risks of this proposal I'm weighing: 'Migrate our 80-person engineering team from Slack to Discord over Q3 2026. Reasons cited: 40% Slack-bill cost saving, native voice rooms for pair-programming, better threading, async-by-default culture fit. Concerns raised internally: enterprise compliance, search/audit, integration loss with Linear and Notion.' Full picture on this one option — pros and cons, evaluate this proposal, no comparing alternatives.

2. What are the benefits and risks of this proposal I'm weighing for our 25-person agency: 'Adopt a four-day work week (32 hours, no pay cut) for the rest of 2026 as a pilot. Mondays off across the company. Reasons cited: UK pilot results, recruitment edge against larger firms, productivity studies. Concerns: client-coverage gaps, ad-hoc Monday emergencies, slower turnaround on rush projects.' Full picture on this one option — pros and cons, no comparing alternatives.
3. What are the benefits and risks of this proposal I'm weighing: 'Move our small family from our Portland suburb to rural Maine — 1500-person town, my partner works remote, I'd quit my job and try freelance consulting. Reasons cited: cost of living, school quality, climate refugee positioning. Concerns: isolation, income drop, medical access, kids' social network.' Full picture on this one option — pros and cons.
4. What are the benefits and risks of this proposal my co-founder is pushing: 'Pivot our analytics SaaS to a vertical-AI play for hospital revenue-cycle management — repurpose the data engine, rebuild the front-end, target three pilot health systems, raise a Series B on the new positioning over 6 months.' Reasons cited: AI-vertical multiples, our existing healthcare-data expertise. Concerns: pivot risk, customer churn, sales-cycle length. Full picture on this one option — pros and cons.
5. What are the benefits and risks of this proposal I'm weighing for our family: 'Take an 18-month sabbatical to homeschool our two kids while sailing the Caribbean — I'd take unpaid leave from my partner-track position at a big-law firm, we'd liquidate $180k in non-retirement savings, partner continues consulting remotely.' Full picture on this one option — pros and cons, no comparing alternatives.

#### `red-team-advocate`

1. Argue against OpenAI's $1.5B DeployCo joint venture (announced April 2026 with TPG-led PE consortium). The strategic rationale: 'OpenAI plans to take a percentage of the value created or costs saved by its agentic workflows,' deploying 'forward deployed engineers' inside client orgs to 'rewire' business processes, with a 17.5% guaranteed annual return to PE backers and access to 1,200+ portfolio companies. Stated goal: vertical integration to close the enterprise 'ROI gap' against Anthropic and Google. Make the case against this strategy — every angle including weak ones, no severity triage, comprehensive critique.

2. Argue against OpenAI's published April 2026 commitment to dedicate 20% of secured compute to alignment research through 2030: 'The Superalignment commitment is restored at 20% of compute, redirected toward scalable oversight and interpretability research, with quarterly transparency reports.' Make the case against this allocation — every angle including weak ones, comprehensive critique, no severity triage.
3. Red team advocate against Anthropic's published 2026 plan to extend the Responsible Scaling Policy to require third-party pre-deployment red-team access at ASL-3 and above: 'Independent evaluators selected from the AISI-approved roster will receive 30-day pre-deployment access to frontier models for capability and safety evaluations, with results published 90 days post-deployment. Anthropic commits to deployment delay if Critical findings emerge.' Construct the case against this published commitment — every angle including weak ones, devil's advocate, no severity triage.
4. Red team advocate against Mercedes-Benz's published 2026 strategy to discontinue all combustion engine R&D by 2028 and commit to a fully-EV product line by 2030: '€3.5 billion annual R&D redirected away from ICE platforms toward EV architecture; no new combustion engine after 2027; ICE platforms end by 2030.' Construct the case against this published strategy — every angle including weak ones, devil's advocate, no severity triage.
5. Red team advocate against Walmart's published 2026 strategy to convert 30% of its supercenter parking lots into mixed-use housing with on-site retail anchors over a decade: '500 supercenter sites identified, 70-200 units per site, Walmart retains ground-floor retail, partners with regional developers, target 80,000 units of new workforce housing.' Construct the case against this published strategy — every angle including weak ones, devil's advocate, no severity triage.

#### `red-team-assessment`

1. Stress-test this go-to-market plan for our Series-A B2B SaaS launch before I commit. Plan: 'Three coastal cities first (NYC, SF, LA). $200/mo single-tier subscription, no free trial, 90-day money-back guarantee. Paid acquisition Meta + TikTok at $80 CAC target. Outbound SDRs in month 3. ICP: 50-500 person ops teams. Public launch month 6 after closed beta of 50 customers at founder rates.' Where is this weak? What am I missing? Find the holes — what would a hostile reviewer say?

2. Stress-test this pricing change before I push it live: 'Move from per-seat ($25/user/mo) to per-workflow consumption pricing ($0.40 per workflow run, $200 minimum monthly) starting Q3 for new customers and a 6-month grandfathered migration for existing ones. Reasoning: heavy users pay more, light users pay less, value-aligned.' Where is this weak? What am I missing? What would a hostile reviewer say?
3. Stress-test this acquisition thesis I'm putting in front of the board next week: 'Acquire our two largest regional competitors (combined revenue $18M, our revenue $24M) in an all-stock deal, fold their teams into ours, eliminate ~30% redundant SG&A, position the merged entity for a strategic sale to one of the top three national players in 2028.' Find the holes — what would a hostile reviewer say?
4. Red team this hiring plan before I commit: 'Hire 12 engineers in Q2-Q3 (we're 28 now), all remote, all senior-level (no juniors), heavy emphasis on AI/ML backgrounds, $230K base ceiling, equity-light. Goal: rebuild the ML platform from scratch in 9 months while keeping the product roadmap moving.' Stress-test this plan — where is this weak? Adversarial review, find the holes, what would a hostile reviewer say?
5. Red team this product-launch plan before I commit: 'Launch a consumer-facing AI therapy companion app for $30/mo, target Gen Z anxiety market, no clinician-in-the-loop, build on Anthropic API with crisis-detection guardrails, partner with three influencer therapists for credibility, target 250k subscribers in year one.' Stress-test this plan — where is this weak? Adversarial review, find the holes, what would a hostile reviewer say?

#### `steelman-construction`

1. Steelman this published position from Senator Sanders' op-ed — best case for, strongest version: 'In the richest country on earth, if you work 40 hours a week you do not live in poverty. Putting money into the hands of people who will spend it on basic needs is a strong economic stimulant. When over 60% of American workers are now living paycheck to paycheck, we can no longer tolerate a federal minimum wage of $7.25 an hour. Poll after poll shows overwhelming support for raising the minimum wage to a living wage. There are too many Americans trying to survive on $9, $10 or $12 an hour. It cannot be done.' No caveat-padding.

2. Steelman this position from a recent Curtis Yarvin essay: 'The American republic is structurally a managerial bureaucracy with electoral theater on top. Real power sits in the agencies, the universities, the press, and the donor class. The choice voters get is between two factions of the same managerial regime. The only path to actual change is therefore not electoral but institutional reconstruction — a CEO model, not a presidential one.' Best case for, strongest version. No caveat-padding.
3. Steelman this position from a recent National Review piece: 'The post-1965 immigration regime has been an unalloyed disaster for the American working class. Real wages stagnated, social trust collapsed, civic identity fractured, housing was bid up, public schools were overwhelmed. The people who designed it admit they got the cultural and economic effects wrong. The honest move is to admit the mistake and reverse it.' Best case for, strongest version. No caveat-padding.
4. Steelman this published position from a recent David Graeber essay collection: 'Most of what we call work in advanced economies is bullshit jobs — middle-management, brand consultancy, compliance theater, HR functions that exist to manage other administrators. The people who do real work — teachers, nurses, mechanics, sanitation — are systematically underpaid. This is not a market failure but the market working exactly as designed for a managerial class.' Best case for, strongest version. No caveat-padding.
5. Steelman this position from a recent Adam Tooze essay: 'The conventional framing of the 2008 crisis as a US subprime story missed the actual mechanism — it was a transatlantic dollar-funding crisis driven by European megabanks' demand for dollar liquidity to fund their US asset purchases. The Fed's swap lines, not TARP, were the load-bearing intervention. Treating 2008 as American carelessness rather than European hubris fundamentally misreads the financial architecture.' Best case for, strongest version. No caveat-padding.

### Mechanism Understanding

#### `mechanism-understanding`

1. How does CRISPR actually work under the hood? Want the structural explanation — how the parts produce the editing behavior, not just inputs and outputs.

2. How does the GPS time-correction actually work under the hood — the relativistic adjustments for satellite clocks, the ionospheric model, why your phone gets a sub-meter fix in seconds. Structural explanation, parts to behavior.
3. How does mRNA vaccine technology actually work under the hood — the lipid nanoparticle delivery, the modified-uridine bases, why the immune response is what it is. The structural explanation, the parts that produce the behavior.
4. How does Bitcoin's proof-of-work consensus actually work under the hood — the hash puzzle, difficulty adjustment, longest-chain rule, why it produces probabilistic finality. Structural explanation, parts to behavior.
5. How does the modern semiconductor lithography process actually work under the hood — the ASML EUV light source from tin-plasma, the multi-layer mirror optics, the photoresist chemistry, why 3nm-class nodes require multi-patterning. Structural explanation, the parts that produce the behavior.

### Process And System Analysis

#### `market-dynamics`

1. Walk me through the supply and demand in the US used-EV market after the 2026 expiration of the federal clean-vehicle tax credit. What happens to prices and volumes in the short run versus the long run once the subsidy is gone, and where does the market settle? Elasticities on both sides, and the new equilibrium.

2. Supply and demand walkthrough for the global enriched-uranium market after Western sanctions cut off Russian supply. What happens to prices in the short run versus the long run, how elastic is enrichment capacity, and where does the market re-settle once new centrifuge capacity comes online?
3. Read the residential rental market in a mid-size US city after a sweeping 2026 rent-cap ordinance as a market. Walk the supply and demand: what happens to rents and to the number of available units in the short run versus the long run, where does the shortage show up, and where does the market settle?
4. Walk me through supply and demand in the AI data-center GPU market. With hyperscaler demand surging and high-bandwidth memory the binding constraint, what happens to prices in the short run versus the long run, and where does the market settle once new fab capacity comes online? Include diminishing returns and the long-run supply response.
5. Read the global coffee market after a Brazilian frost destroys a third of the arabica crop. Supply-and-demand walkthrough: what happens to the price in the short run versus the long run, how inelastic is demand, and where does the market settle once growers replant?

#### `process-mapping`

1. Process map for our customer onboarding workflow — find the bottlenecks and dependencies. Current state, as-is.

2. Process map for our hospital discharge workflow — current state, as-is. Find the bottlenecks and dependencies between case management, social work, pharmacy reconciliation, transport, family contact, and the bed-board update.
3. Process map for our software release workflow — current state, as-is. Find the bottlenecks and dependencies between PR review, QA signoff, staging deploy, security scan, change-management ticket, and production rollout.
4. Process map for our SaaS customer-renewal workflow — current state, as-is. Find the bottlenecks and dependencies between CSM outreach, usage report, contract redline, procurement portal, finance booking, and platform provisioning.
5. Process map for our manufacturing plant's new-product-introduction workflow — current state, as-is. Find the bottlenecks and dependencies between engineering release, sourcing qualification, pilot-line setup, quality validation, supply chain ramp, and production handoff.

#### `systems-dynamics-structural`

1. Draw the feedback structure (structural) for our org's promotion cycle. Show me the stocks (eligible candidates, open seats, retained ICs), the flows (hiring, promotion, attrition), and a structural diagram with feedback dynamics. I want a structural picture before deciding what to change.

2. Draw the feedback structure for our newsroom's subscription business. Show me the stocks (subscribers, churned-but-recoverable, content-output backlog), the flows (acquisition, churn, content production, content amortization), and a structural diagram with the feedback dynamics. I want a structural picture before deciding which lever to pull.
3. Draw the feedback structure for a city's housing market: stocks (units, vacant units, households seeking, households housed), flows (construction, demolition, migration in, migration out), feedback loops between price, construction, demand, and migration. Structural diagram before deciding what to change.
4. Draw the feedback structure for our customer-success team's workload. Show me the stocks (accounts at risk, accounts healthy, open tickets, CSM bandwidth), the flows (escalation, resolution, expansion-driven new workload, attrition), and a structural diagram with feedback dynamics. Structural picture before deciding what to change.
5. Draw the feedback structure for our county's foster-care system. Show me the stocks (children in care, foster families available, children awaiting placement, children reunified), the flows (intake, placement, reunification, aging out, foster-family attrition), and a structural diagram with feedback dynamics. Structural picture before deciding what to change.

### Strategic Interaction

#### `mechanism-design`

1. We're designing a procurement auction for municipal construction contracts and keep getting burned by the winner's curse and lowball bids from firms that then cut corners. Analyze the adverse-selection and moral-hazard problems here, then design the auction rules and contract incentives so honest, capable bidders self-select and win. Mechanism design — screening and incentive-compatibility.

2. Health insurer here: our healthy customers keep dropping the comprehensive plan and we're left with a worsening risk pool. Analyze the adverse-selection death spiral, then design the screening menu and contract terms so customers sort themselves by risk and the low-risk ones stay. Mechanism design against the information asymmetry.
3. Our SaaS sales reps are sandbagging quotas and gaming the comp plan — a classic principal-agent problem when we can't observe their real effort. Analyze the moral hazard, then design an incentive-compatible compensation mechanism so each rep's best move is the behavior we actually want. Mechanism design.
4. A carbon-credit marketplace is flooded with low-quality offsets buyers can't tell apart from real ones, and the good projects are leaving. Analyze this adverse-selection 'market for lemons,' then design the certification, screening, and signaling mechanism so quality is revealed and rewarded. Reverse game theory.
5. We run a platform matching freelance engineers to clients, and both sides misrepresent themselves. Analyze the two-sided information asymmetry — adverse selection on type and moral hazard on effort — then design the rules, escrow, and reputation mechanism so honest behavior is incentive-compatible for both sides.

#### `strategic-interaction`

1. Game theory: what's China's best move if the US imposes export controls on advanced chips in Q3? Payoff matrix, deterrence, signaling.

2. Game theory: what's Russia's best move on Ukrainian grain shipments through the Black Sea if Turkey enforces a stricter Montreux Convention interpretation? Payoff matrix, deterrence, signaling, credibility of commitments.
3. Game theory: what's the optimal sequencing for the EU's anti-coercion instrument against China over critical minerals in 2026? Payoff matrix, escalation dynamics, credible commitments.
4. Game theory: what's Apple's best response if the EU forces them to allow third-party app stores on iOS globally? Payoff matrix across the major regulatory regimes, deterrence and signaling, the precedent dynamics.
5. Game theory: what's Saudi Arabia's best move in OPEC+ if Russia continues unilaterally cheating on production quotas through 2026? Payoff matrix, signaling, credible-commitment problems, the side-payment landscape with the US administration.

### Spatial Composition

#### `compositional-dynamics`

1. Compositional dynamics reading of the new MoMA exhibition poster — figure-ground, gestalt grouping, where the eye goes and why.

2. Compositional dynamics reading of the 2026 Olympic opening ceremony poster for Los Angeles — figure-ground, gestalt grouping, the visual hierarchy of athlete imagery vs civic landmark vs typographic identity.
3. Compositional dynamics reading of the cover of the New Yorker's October 2026 'AI Issue' — figure-ground relationships, gestalt grouping, where the eye goes and why, what the negative space does.
4. Compositional dynamics reading of the staging photo from Beyonce's Cowboy Carter tour finale — figure-ground, gestalt grouping, the visual hierarchy of performer, screen content, audience, and architecture.
5. Compositional dynamics reading of the staging photograph from the 2026 Met Gala 'Sleeping Beauties' theme entrance — figure-ground, gestalt grouping, the visual hierarchy of celebrity, architectural shell, photographer pit, and audience layering.

#### `information-density`

1. Critique this chart with a Tufte data-ink-ratio audit: a quarterly revenue dashboard with 3D pie chart, drop shadows, rainbow gradient bars for each region, gridlines every $1k, a sparkline-sized YoY indicator with no axis labels, and a legend taking 30% of the canvas. Chartjunk audit, Bertin visual-variables read, prescriptive recommendations.

2. Critique this chart with a Tufte data-ink-ratio audit: a US state-level election results map using a 3D extruded choropleth with state heights proportional to electoral votes, full-saturation red/blue, animated 'reveals' as states are called, and a separate ticker showing percentage swing. Chartjunk audit, Bertin visual-variables read, prescriptive recommendations.
3. Critique this chart with a Tufte data-ink-ratio audit: a climate dashboard showing global temperature anomaly with a gradient-filled area chart in red below baseline and blue above, dual y-axes (anomaly and absolute), legend taking 25% of canvas, gridlines every 0.1°C, and decorative ice-cap icons in the corners. Chartjunk audit, Bertin visual-variables read.
4. Critique this dashboard chart with a Tufte data-ink-ratio audit: a fitness app's weekly summary using a circular 'activity ring' triple-overlay with steps, calories, and active minutes mapped to three concentric arcs, percent-of-goal labels in 3D rotation, motivational text overlay, and a small-multiples row of seven daily mini-rings. Chartjunk audit, Bertin visual variables, prescriptive recommendations.
5. Critique this chart with a Tufte data-ink-ratio audit: a 2026 New York Times subway-ridership recovery infographic using an animated isometric tunnel cross-section, rainbow-coded ridership levels per line, decorative subway-car icons whose size pulses with ridership, dual y-axes for absolute riders and percent-of-2019, and a legend taking 30% of the canvas. Chartjunk audit, Bertin visual-variables read, prescriptive recommendations.

#### `ma-reading`

1. Ma reading of this Japanese tea-house garden photograph — what is the empty space doing? Yūgen or wabi-sabi at work?

2. Ma reading of this minimalist Japanese kaiseki restaurant interior photograph — what is the empty space doing? Yūgen or wabi-sabi at work? Ma in the spatial composition.
3. Ma reading of this Hiroshi Sugimoto seascape photograph — what is the empty space doing between sky and water? Yūgen or wabi-sabi at work? Ma in the temporal-spatial composition.
4. Ma reading of a still from Yasujiro Ozu's 'Tokyo Story' — the pillow shot between scenes, the empty hallway, the kettle on the stove. What is the empty space doing? Yūgen and ma at work?
5. Ma reading of this Andrew Wyeth painting 'Christina's World' — what is the empty space between the figure and the distant farmhouse doing? Yūgen or wabi-sabi at work in a Western artistic register? Ma in the spatial composition.

#### `place-reading-genius-loci`

1. Place reading of the new High Line extension — genius loci, prospect-refuge, Christopher Alexander pattern language. What does the space afford?

2. Place reading of the newly-opened Little Island park in Hudson River Park, NYC — genius loci, prospect-refuge, Christopher Alexander pattern language. What does the space afford?
3. Place reading of the Salk Institute courtyard in La Jolla — genius loci, prospect-refuge, Christopher Alexander pattern language. What does the space afford?
4. Place reading of the rebuilt Notre-Dame interior reopened in late 2024 — genius loci, prospect-refuge dynamics, Christopher Alexander pattern language. What does the space afford?
5. Place reading of the rebuilt One World Trade Center plaza and 9/11 Memorial pools — genius loci, prospect-refuge, Christopher Alexander pattern language. What does the space afford, what does it resist?

### Open Exploration

#### `passion-exploration`

1. I've been wondering about why we find certain landscapes restorative. Let me explore — no deliverable in mind.

2. I've been wondering why we trust certain kinds of strangers immediately — a particular kind of cab driver, a particular kind of bartender — and other strangers never. Let me explore — no deliverable in mind.
3. I want to do passion exploration on why some pieces of music produce instant tears the first time you hear them and others never do, no matter how technically beautiful. Open exploration, no deliverable in mind, just thinking aloud.
4. I want to do open passion exploration on why some friendships sustain across decades through long silences and others evaporate within months of geographic separation. No deliverable in mind, just thinking aloud.
5. I want to do open passion exploration on why certain physical objects — a particular pen, a particular knife, a particular leather notebook — produce a daily companionable feeling while functionally-equivalent replacements never do. No deliverable in mind, just thinking aloud.

### Execution Project Mode

#### `project-mode`

1. Build me a one-page React app that displays my GitHub stars sorted by language.

2. Build me a Python script that watches my Downloads folder and auto-renames any .pdf file matching an invoice pattern to 'YYYY-MM-DD — vendor — amount.pdf' using OCR on the first page.
3. Build me a one-page React component that shows a live feed of mentions of a given ticker across r/wallstreetbets, r/stocks, and r/investing in the last 6 hours, sorted by upvotes.
4. Write me a one-page web app in JavaScript that pulls the latest Federal Reserve H.4.1 release and displays the week-over-week change in the Fed's balance sheet as a sparkline. Build me the code — execution and project mode.
5. Build me a Python CLI that walks a directory of my photos, runs each through CLIP embeddings, clusters visually-similar groups, and produces an HTML gallery I can browse to delete duplicates. Execution and project mode.

#### `structured-output`

1. Format this trip itinerary as a one-pager with time, location, and notes columns. Faithful rendering of what I've drafted.

2. Structured output mode: format this draft meeting recap as a one-page agenda for tomorrow with columns for time, topic, owner, and decision-needed. Faithful rendering of what I've drafted. Items: '9am intros (David, info); 9:15 Q1 revenue review (Maya, info); 9:45 product roadmap reprioritization (Tomás, decision: ship API in Q2 or Q3); 10:30 hiring plan (Priya, decision: approve 4 backfills); 11:15 budget reforecast (Maya, decision: cut marketing or hold); 12:00 close (David).'
3. Structured output mode: format this draft seeding list into a one-page single-elimination tournament bracket layout for our annual office ping-pong championship, 16 players. Faithful rendering. Seeds 1-16: '1 Jamie, 2 Priya, 3 Tomás, 4 Maya, 5 David, 6 Lin, 7 Marcus, 8 Esme, 9 Rafa, 10 Ana, 11 Theo, 12 Yusuf, 13 Nina, 14 Jules, 15 Otis, 16 Sasha.'
4. Structured output formatting — render this expense log as a one-page report with columns for date, vendor, category, amount, and notes. Faithful structured rendering of what I've drafted. Entries 2026-03 to 2026-04: '03/04 Acme Office $124.50 supplies — printer toner; 03/12 Delta $487 travel — NYC client visit; 03/18 Slack $99 software — annual seat; 03/22 Lyft $14.20 travel — airport; 04/02 Acme Office $34 supplies — ink; 04/09 AWS $342.10 software — March bill; 04/15 LinkedIn $79 marketing — recruiter seat; 04/22 Delta $521 travel — SF conference; 04/28 Hilton $612.30 travel — SF lodging.'
5. Structured output formatting — render this draft of our team's quarterly goals as a one-page status report with columns for goal, owner, status, blockers, and target date. Faithful structured rendering of what I've drafted. Items: 'Hit $4.2M ARR (Maya, on-track, none, Jun 30); ship API v2 (Tomás, behind, infra capacity, May 31); close two enterprise pilots (David, at-risk, security review, Jun 15); reduce p99 latency 30% (Priya, on-track, none, Jul 15); hire 4 senior eng (Lin, behind, candidate pipeline, Aug 1).'

## Visual tools

### `ach-matrix`

1. Make me an ACH matrix on three competing hypotheses for the 2026 GDP slowdown: monetary tightening, demand exhaustion, supply normalization. Evidence rows: bond spreads, unemployment, inventory, consumer sentiment. What rules out each theory?

2. ACH matrix on three competing hypotheses for the spring 2026 surge in small-business defaults: post-pandemic SBA-loan amortization shock, tariff-driven input-cost squeeze, weakening consumer spending. Evidence rows: SBA-7(a) default rate, ISM new-orders, retail same-store sales, credit-card delinquency. What rules out each?
3. ACH matrix on three competing hypotheses for why young men's labor-force participation continues to decline: gaming-and-screen substitution, opioid and long-COVID disability, credential-mismatch in service-economy jobs. Evidence rows: time-use survey, SSDI claims, college-completion-by-gender, sectoral wage data. What rules out each?
4. ACH matrix on three competing hypotheses for the 2026 stall in US single-family housing starts: rates, builder-credit availability, labor shortage in residential carpentry trades. Heuer-style competing-hypotheses analysis with diagnosticity rows: NAHB sentiment, lumber prices, carpentry-job postings, mortgage application volume. What rules out each theory? Strongest evidence against each.
5. ACH matrix on three competing hypotheses for the 2026 sharp rise in US auto-loan delinquencies: extended loan-term debt-trap maturation (84-month notes from 2019-2021), used-car-price collapse pushing borrowers underwater, broad-based consumer-spending stress. Heuer-style with diagnosticity rows: Manheim used-car index, lender repo-rate disclosures, FICO band default mix, credit-card-coincident defaults. What rules out each theory? Strongest evidence against each.

### `bow-tie-diagram`

1. Bow-tie diagram for our largest cybersecurity risk — ransomware. Threats, preventive controls, top event, consequences, mitigation controls. Fragility audit on the structure, single points of failure.

2. Bow-tie diagram for our largest operational risk — a third-party SaaS vendor (auth provider) outage. Threats, preventive controls, top event, consequences, mitigation controls. Fragility audit on the structure, single points of failure, asymmetric payoffs.
3. Bow-tie diagram for our hospital's largest patient-safety risk — wrong-medication administration. Threats, preventive controls, top event, consequences, mitigation controls. Fragility audit on the structure, asymmetric payoffs.
4. Bow-tie diagram for our family's largest financial-risk exposure — primary income-earner becoming long-term disabled. Threats, preventive controls, top event, consequences, mitigation controls. Fragility audit on the structure, single points of failure.
5. Bow-tie diagram for our city water utility's largest operational risk — a successful cyberattack on the SCADA system controlling pumping and chemical dosing. Threats, preventive controls, top event, consequences, mitigation controls. Fragility audit on the structure, asymmetric payoffs, single points of failure.

### `c4-architecture`

1. Draw a C4 context diagram for our payments service: the people who use it (customer, support agent, fraud analyst), our payments system at the centre, and the external systems it integrates with (Stripe, Plaid, the accounting system). Show each person and system as a node and draw the labelled relationships between them.

2. Annotate this architecture: I have a C4 container diagram for our small e-commerce platform — Next.js storefront, Node API gateway, Postgres orders DB, Redis cache, Stripe payments, SendGrid email, Algolia search, S3 image store. What node am I missing? Is there a connection I haven't drawn?
3. Annotate this C4 context diagram — spatial reasoning annotation on the diagram I'm working with. I have a C4 context diagram for our IoT pet-feeder business: actors (pet owner, support agent, vet partner), our system (device, mobile app, web dashboard), external systems (Twilio SMS, Stripe, weather API, food-supplier API). What node am I missing? Is there a feedback loop I haven't drawn? Annotate my diagram.
4. Annotate this C4 component diagram — spatial reasoning annotation on the diagram I'm working with. I have a C4 component diagram for our authentication service: login handler, MFA module, session store, JWT issuer, refresh-token rotator, password reset, social-login adapter, audit logger. What component am I missing? Is there a connection I haven't drawn? Annotate my diagram.
5. Annotate this C4 component diagram — spatial reasoning annotation on the diagram I'm working with. I have a C4 component diagram for our real-time-bidding ad exchange: bid-request handler, bidder-fanout, response-aggregator, win-notice processor, budget-pacing module, fraud-filter, billing-event emitter. What component am I missing? Is there a connection I haven't drawn? Annotate my diagram.

### `causal-dag`

1. Draw the causal DAG for the relationship between exercise, sleep, and depression in adults. Include confounders, use DAGitty notation, back-door criterion. What would happen if we intervened on exercise?

2. Draw the causal DAG for the relationship between vocational training programs and labor-market outcomes for displaced workers. Include confounders, use DAGitty notation, back-door criterion. What would happen if we intervened on program access? Identifiability.
3. Draw the causal DAG for the relationship between universal pre-K access and long-term academic outcomes. Include confounders (parental income, neighborhood, prior childcare access), DAGitty notation, back-door criterion. What would happen if we intervened on pre-K access?
4. Draw the causal DAG for the relationship between SSRI prescription and adolescent suicidality. Confounders (severity of underlying depression, family history, therapy access, socioeconomic factors), DAGitty notation, backdoor criterion. What would happen if we intervened on the prescribing decision?
5. Draw the causal DAG for the relationship between municipal broadband-access programs and small-business formation rates in rural counties. Include confounders (population trends, in-migration, anchor-institution presence, prior commercial activity), DAGitty notation, back-door criterion. What would happen if we intervened on broadband-access subsidies? Identifiability.

### `causal-loop-diagram`

1. Why does fixing X make things worse — every feature release improves retention briefly then worsens it. Counterintuitive results, feedback loop somewhere. Draw the CLD with reinforcing and balancing loops, diagnose the recurring behaviour.

2. Why does fixing X make things worse — every layoff round at our company improves financials for two quarters then is followed by a slower productivity decline that we keep underestimating. Counterintuitive results, a feedback loop somewhere we can't see. Draw the CLD with reinforcing and balancing loops.
3. Why does fixing X make things worse — every time the city adds more bike-share stations to reduce car traffic, ridership grows but congestion remains identical 18 months out. Counterintuitive, feedback loop somewhere. Draw the CLD with reinforcing and balancing loops, diagnose the recurring behaviour.
4. Why does fixing X make things worse — every cohort of customer-success expansion we hire briefly improves NRR then NRR drifts down within 90 days. Counterintuitive results, feedback loop we can't see. Draw the CLD with reinforcing and balancing loops, diagnose the recurring behaviour.
5. Why does fixing X make things worse — every wildfire-suppression season our western states aggressively contain small fires and the next fire season's catastrophic mega-fire risk worsens by an order of magnitude. Counterintuitive results, feedback loop we can't see. Draw the CLD with reinforcing and balancing loops, diagnose the recurring behaviour.

### `comparison-chart`

1. Critique this dashboard chart and recommend the right encoding: I have 2024 vs 2025 vs 2026 Q1 revenue across our four product lines. Data-ink ratio, chartjunk, Cleveland-McGill elementary perceptual tasks — what visual encoding is right for this comparison? Bertin visual variables analysis.

2. Critique this dashboard chart and recommend the right encoding: I have user engagement comparison across our four pricing tiers (Free, Plus, Pro, Enterprise) over Q1, Q2, Q3 2026. Data-ink ratio, chartjunk, Cleveland-McGill elementary perceptual tasks — what visual encoding is right for this comparison? Bertin visual variables analysis.
3. Critique this dashboard chart and recommend the right encoding: I have salary comparison across five engineering levels at three FAANG companies plus our startup, with bonus/equity broken out separately. Cleveland-McGill perceptual tasks — what visual encoding is right? Bertin visual variables, data-ink audit.
4. Critique this comparison chart and recommend the right encoding: I have nutritional content (calories, sugar, sodium, protein) compared across six 'better-for-you' beverage brands my retail buyer is considering. Cleveland-McGill perceptual tasks — what visual encoding is right? Bertin visual variables, data-ink audit.
5. Critique this dashboard chart with a Tufte data-ink-ratio audit and recommend the right encoding: I have customer-satisfaction comparison across our four product lines, three regions, and pre-/post-pandemic cohorts. Chartjunk audit, Cleveland-McGill elementary perceptual tasks, Bertin visual-variables analysis. What visual encoding is right for this multi-dimensional comparison? Prescriptive recommendations.

### `concept-map`

1. Map this domain for me with a concept map — attachment theory: secure, anxious, avoidant, disorganized. Walk me through the propositions connecting them. The big picture, introduce me to it.

2. Map this domain for me with a concept map — modern macroeconomic schools (Keynesian, monetarist, Austrian, MMT, post-Keynesian). Walk me through the propositions connecting them. The big picture, introduce me to it.
3. Map this domain for me with a concept map — the components of the human immune system: innate, adaptive, humoral, cellular, lymphoid organs, cytokines, MHC. Walk me through the propositions connecting them. The big picture.
4. Map this domain for me with a concept map — Bitcoin and the broader crypto landscape: layer 1s, layer 2s, custody, exchanges, DeFi primitives, stablecoins, regulation. Walk me through the propositions connecting them. The big picture, concept map of how the terrain fits together.
5. Map this domain for me with a concept map — modern psychotherapy schools (CBT, psychodynamic, humanistic, family systems, ACT, DBT, somatic, IFS). Walk me through the propositions connecting them, the big picture, introduce me to it. Concept map of how the schools relate.

### `decision-tree`

1. Build me a decision tree for the lease-vs-buy decision: lease (certain $50k/yr), buy with 30% down (uncertain appreciation), wait six months (uncertain market). Expected value, value of information.

2. Build me a decision tree for whether to wait 6 months for the new state EV-rebate program before buying our next car. Buy now (certain $48k, no rebate), wait 6 months (uncertain rebate amount, uncertain car-price trajectory), buy used now ($28k, no rebate ever). Expected value, value of information.
3. Build me a decision tree for whether to invest the family inheritance now or stage it. Lump-sum now (certain market exposure), three-tranche over 18 months (uncertain market path), wait for clearer Fed signal (uncertain timing). Expected value, value of information on the next CPI print.
4. Build me a decision tree for whether to do the elective knee surgery this summer or wait. Surgery now (certain 4-month recovery, 70% chance pain relief), wait and see (50% pain progresses, may need surgery anyway), try the new biologic injection (40% pain relief, $4500 out-of-pocket). Expected value, value of information.
5. Build me a decision tree for whether to take the 2026 corporate buyout package now or stay through the announced reorganization. Take buyout (certain 18-month severance, immediate departure), stay through reorg (uncertain post-reorg role, uncertain severance if cut later), counter with negotiated package (uncertain acceptance probability). Expected value, value of information on the reorg announcement timing.

### `distribution-plot`

1. I'm designing this chart and need to choose the right encoding. The data: API response times from last week, ~5M requests, p50 of 80ms but a long tail to 4 seconds. The decision the chart needs to support: where to set our SLO. Critique this chart — box plot, violin, histogram, or strip? Cleveland-McGill graphical perception, data-ink ratio.

2. I'm designing this chart and need to choose the right encoding. The data: page-load times across our 200,000 daily users, p50 1.1s but p99.9 hits 11s. The decision: where to set our SLO. Critique this chart — box plot, violin, histogram, or strip? Cleveland-McGill graphical perception, data-ink ratio.
3. I'm designing this chart and need to choose the right encoding. The data: ER wait-times across our 12 hospitals last month, p50 of 34 minutes but a heavy tail to 4 hours. The decision the chart needs to support: which hospital flags for operational review. Critique this chart — box plot, violin, histogram, or strip? Cleveland-McGill perception, data-ink audit.
4. I'm designing this chart and need to choose the right encoding. The data: individual donations to our nonprofit over 2025, ~28,000 gifts, p50 of $40 but heavy right tail to a few $50k major gifts. The decision: where to set the major-gifts cutoff. Critique this chart — box plot, violin, histogram, or strip? Cleveland-McGill perception, data-ink ratio.
5. I'm designing this chart and need to choose the right encoding. The data: emergency-department length-of-stay across our hospital network, ~340k visits last year, p50 of 3.2 hours but a long tail to 28 hours for boarding-admitted patients. The decision the chart needs to support: where to draw the boarding-escalation threshold. Critique this chart — box plot, violin, histogram, or strip? Cleveland-McGill perception, data-ink audit.

### `fishbone-diagram`

1. Why does this keep happening — our deployment failures recur every release. Draw a fishbone / Ishikawa diagram with categories: people, process, technology, data, environment. What are the root causes?

2. Why does this keep happening — our daily standup runs 45 minutes when it should be 15. Draw a fishbone / Ishikawa diagram with categories: people, process, technology, data, environment. What are the root causes?
3. Why does this keep happening — our quarterly board meetings consistently run 90 minutes over schedule. Draw a fishbone / Ishikawa with categories: people, process, technology, materials, environment. What are the root causes?
4. Why does this keep happening — our school lunch rush regularly produces a 12-minute line at the chicken-tender station every Thursday despite different week-over-week menu shifts. Draw a fishbone / Ishikawa diagram with categories: people, process, equipment, materials, environment. What are the root causes?
5. Why does this keep happening — our airport's Saturday-morning TSA-line backups regularly exceed 90 minutes for the 6-9am window despite three staffing increases this year. Draw a fishbone / Ishikawa with categories: people, process, equipment, materials, environment. What are the root causes?

### `flowchart`

1. Process map with swimlanes — flow chart for our incident-response workflow: customer support, on-call engineer, SRE, post-mortem owner. Current state, as-is, find the bottleneck.

2. Process map with swimlanes — flowchart for our SaaS company's enterprise-deal flow: SDR, AE, sales engineer, security review, legal, finance, customer-success handoff. Current state, as-is, find the bottleneck.
3. Process map with swimlanes — flowchart for our hospital's surgical-scheduling workflow: surgeon's office, scheduler, OR coordinator, anesthesia, pre-op clearance, patient notification, day-of confirmation. Current state, as-is, find the bottleneck.
4. Process map with swimlanes — flowchart for our nonprofit's grant-application workflow: program officer, ED, finance, board grants committee, external reviewer, applicant. Current state, as-is, find the bottleneck.
5. Process map with swimlanes — flowchart for our state Medicaid agency's eligibility-redetermination workflow: enrollee, county case-worker, state eligibility-rules engine, MMIS provider system, federal CMS reporting, appeals office. Current state, as-is, find the bottleneck.

### `heatmap`

1. I'm designing this dashboard chart and need prescriptive recommendations: a heatmap of feature usage by user cohort across 12 weeks, with cohorts on rows, weeks on columns, usage-intensity as fill. Message: power-user cohorts retain feature use, casual cohorts decay by week 4. Cleveland-McGill perceptual-task fit, Bertin visual variables, data-ink audit. Is heatmap the right encoding here?

2. I'm designing this dashboard chart and need prescriptive recommendations: a heatmap of our website's conversion funnel by traffic-source cohort across 16 weeks, with sources on rows, weeks on columns, conversion-rate as fill. Message: paid social cohorts spike then decay, organic cohorts hold steady. Cleveland-McGill perceptual-task fit, Bertin visual variables, data-ink audit. Is heatmap the right encoding?
3. I'm designing this dashboard chart and need prescriptive recommendations: a heatmap of API endpoint p99 latency by hour-of-day across 24 hours and day-of-week across seven days, with hour on rows, day on columns, latency as fill. Message: Tuesday-Wednesday afternoon spikes. Cleveland-McGill perceptual-task fit, Bertin visual variables, data-ink audit. Is heatmap the right encoding?
4. Critique this dashboard chart with information-density audit — data-ink ratio, Cleveland-McGill, Bertin visual variables, chartjunk: a heatmap of our retail store sales by product category across 52 weeks, categories on rows, weeks on columns, sales-index as fill. Message: holiday-driven categories vs steady categories show different rhythm patterns. Is heatmap the right encoding? Prescriptive recommendations.
5. I'm designing this dashboard chart and need prescriptive recommendations: a heatmap of our airline's load-factor by route-segment across 24 months, with routes on rows and months on columns, load-factor as fill. Message: business routes lost holiday seasonality while leisure routes intensified it post-pandemic. Cleveland-McGill perceptual-task fit, Bertin visual variables, data-ink audit. Is heatmap the right encoding?

### `ibis-argument`

1. Wicked problem — our team's Kubernetes-adoption debate keeps shifting as we try to define it. Stakeholders disagree about what the problem even is. Build me an IBIS issue map with positions and arguments, dialectical analysis of the contradictions.

2. Wicked problem — our team's debate about whether to adopt a single in-house design system or let product teams pick their own libraries keeps shifting as we try to define it. Stakeholders disagree about what the problem even is. Build me an IBIS issue map with positions and arguments, dialectical analysis of the contradictions.
3. Wicked problem — our PTA's debate over school-uniform policy has been going for two years; every meeting redefines the question. Stakeholders fundamentally disagree about what the problem even is. Build me an IBIS issue map with positions and arguments, dialectical analysis of the contradictions.
4. Wicked problem — our engineering org's debate over hybrid-versus-remote-versus-in-office keeps rebooting every quarter. Stakeholders fundamentally disagree about what the problem even is. Build me an IBIS issue map with positions and arguments, dialectical analysis of the contradictions.
5. Wicked problem — our city council's debate over policing reform keeps shifting as we try to define it; every council session redefines the question across community-policing, accountability, budget, and union-contract terms. Stakeholders fundamentally disagree about what the problem even is. Build me an IBIS issue map with positions and arguments, dialectical analysis of the contradictions.

### `influence-diagram`

1. Full decision analysis with a Howard-Matheson influence diagram for our facility-location decision: decision nodes, chance nodes, value node. Decision architecture.

2. Full decision analysis with a Howard-Matheson influence diagram for our family's decision on where to retire — five candidate cities, decision nodes (city, housing type, work-or-not), chance nodes (health trajectory, child relocation, market returns), value node. Decision architecture.
3. Full decision analysis with a Howard-Matheson influence diagram for our pharma launch sequencing — decision nodes (markets, pricing tier, sequencing), chance nodes (regulatory approval timing, competitor launch, payer coverage), value node. Decision architecture.
4. Full decision analysis with a Howard-Matheson influence diagram for our school district's facility-investment decision — decision nodes (which buildings to renovate vs replace vs close), chance nodes (enrollment trajectory, state funding, bond-rate), value node. Decision architecture.
5. Full decision analysis with a Howard-Matheson influence diagram for our utility's resource-adequacy decision over the next 15 years — decision nodes (gas peaker retention, battery-storage build, transmission expansion, demand-response programs), chance nodes (load growth, weather-event severity, natural-gas-price trajectory, regulatory carbon trajectory), value node. Decision architecture.

### `pro-con-tree`

1. Pro-con tree for: should we open-source our core library? PMI — plus, minus, interesting. Full picture on this one option, with sub-pros and sub-cons.

2. Pro-con tree for: should our school district adopt cellphone-free policy school-day-wide K-12? PMI — plus, minus, interesting. Full picture on this one option, with sub-pros and sub-cons.
3. Pro-con tree for: should our family adopt a no-screens-Sunday rule? PMI — plus, minus, interesting. Full picture on this one option with sub-pros and sub-cons.
4. Benefits analysis pro-con tree for: should our company adopt a 'no meetings Friday' policy across all teams? PMI — plus, minus, interesting. Full picture on this one option, sub-pros and sub-cons, evaluate this single proposal, not comparing alternatives.
5. Benefits analysis pro-con tree for: should our church congregation sell our underused 1920s building and lease space in a multi-tenant religious facility? PMI — plus, minus, interesting. Full picture on this one option, sub-pros and sub-cons, evaluate this single proposal.

### `quadrant-matrix`

1. Show me a 2x2 matrix for these tasks by urgency and importance — Eisenhower-style. Tasks: ship v3 release, fix auth bug, plan Q3 roadmap, review three PRs, write board update. Map the tradeoffs.

2. Show me a 2x2 matrix for our personal finance priorities by liquidity and time-to-need — quadrant style. Items: 401k, emergency fund, college fund, vacation savings, planned home repair, car replacement. Map the tradeoffs.
3. Show me a 2x2 matrix for our nonprofit's program portfolio by cost-per-outcome and strategic-alignment — quadrant style. Programs: scholarship fund, summer enrichment, advocacy lobbying, parent training, after-school tutoring, summer-meals. Map the tradeoffs.
4. Constraint mapping with a 2x2 matrix for our product-portfolio across customer-stickiness and growth-rate — Boston-style, map the tradeoffs. Products: legacy API, premium SaaS tier, free tier, enterprise contracts, marketplace, mobile app. Compare alternatives across these two dimensions.
5. Constraint mapping with a 2x2 matrix for our nonprofit board's prospective-donor list across capacity-to-give and likelihood-of-conversion — quadrant style. Twenty prospects across major donors, foundations, corporate sponsors, and longtime small-donors. Map the tradeoffs across cultivation effort and expected return.

### `scatter-plot`

1. I'm evaluating this info-graphic and need prescriptive recommendations: a scatter plot of customer lifetime value vs acquisition cost across 200 enterprise accounts, with sales-region encoded as color. Message: high-CAC accounts in the Northeast are underperforming. Tufte data-ink critique, Bertin visual-variables analysis, chartjunk audit.

2. I'm evaluating this info-graphic and need prescriptive recommendations: a scatter plot of teacher-pay vs student-test-score outcomes across 8,000 US public school districts, with district size encoded as point size and urbanicity as color. Message: high-pay urban districts cluster above the trend line. Tufte data-ink critique, Bertin visual-variables analysis, chartjunk audit.
3. I'm evaluating this info-graphic and need prescriptive recommendations: a scatter plot of country-level GDP per capita versus self-reported life satisfaction across 160 countries, with region encoded as color and population as point size. Message: the Easterlin-paradox dispersion at high income. Tufte data-ink critique, Bertin visual variables, chartjunk audit.
4. I'm evaluating this info-graphic and need prescriptive recommendations: a scatter plot of S&P 500 company employee-count vs market-cap, with sector encoded as color and revenue as point size. Message: tech outliers in the top-left quadrant. Tufte data-ink critique, Bertin visual-variables analysis, chartjunk audit.
5. I'm evaluating this info-graphic and need prescriptive recommendations: a scatter plot of US metro housing-price growth versus net-domestic-migration rate across 380 metros from 2020-2025, with region encoded as color and population as point size. Message: the post-pandemic Sunbelt sort. Tufte data-ink critique, Bertin visual-variables analysis, chartjunk audit.

### `sequence-diagram`

1. Process map as a Mermaid sequence diagram for the OAuth 2.0 authorization code flow with PKCE: client, browser, auth server, resource server. Step by step how does this work?

2. Process map as a Mermaid sequence diagram for the SAML 2.0 single-sign-on flow with browser, service provider, identity provider, and user-agent. Step by step how does this work?
3. Process map as a Mermaid sequence diagram for the credit-card chargeback workflow: cardholder, issuer, card network, acquirer, merchant. Step by step how does this work?
4. Process map as a Mermaid sequence diagram for the modern ad-bidding flow on a publisher page: user browser, ad server, SSP, multiple DSPs, exchange, winning bidder. Step by step how does this work?
5. Process map as a Mermaid sequence diagram for the modern stablecoin redemption flow under the 2026 GENIUS Act framework: holder, exchange, stablecoin issuer, reserve-custodian bank, Fed master account, Treasury settlement. Step by step how does this work?

### `state-diagram`

1. Process map as a state diagram for our subscription lifecycle: trial, active, past-due, canceled, won-back. Step by step how does this work — current state.

2. Process map as a state diagram for our claims-processing workflow at our health-insurance startup: submitted, in-review, info-requested, approved, denied, appealed, escalated, paid, closed. Step by step how does this work — current state.
3. Process map as a state diagram for our food-delivery order lifecycle: cart, placed, kitchen-accepted, in-prep, ready, courier-assigned, picked-up, in-transit, delivered, cancelled, refunded. Step by step how does this work — current state.
4. Process map as a state diagram for our hiring-pipeline applicant lifecycle: applied, screening, phone-interview, onsite, debrief, offer, accepted, rejected, withdrawn, ghosted. Step by step how does this work — current state.
5. Process map as a state diagram for our cruise line's reservation-and-fulfillment lifecycle: inquiry, quoted, deposit-held, fully-paid, manifested, embarked, sailing, debarked, post-cruise-review, refunded, no-show, transferred. Step by step how does this work — current state.

### `stock-and-flow`

1. Stock and flow diagram for our cash position: revenue inflow, payroll outflow, fundraising inflow, opex outflow. Map the system's loops and flows. Senge archetype if visible.

2. Stock and flow diagram for our SaaS funnel: visitors, signups, trials, paid customers, churned customers. Inflows from acquisition channels, outflows from churn. Map the system's loops and flows. Senge archetype if visible.
3. Stock and flow diagram for our city's housing stock: vacant units, occupied units, units-under-construction, demolished units. Inflows from construction, outflows from demolition and conversion. Map the system's loops and flows. Senge archetype if visible.
4. Stock and flow diagram for our company's technical debt: open issues, in-progress work, deferred items, paid-down items. Inflows from new code, outflows from cleanup sprints. Map the system's loops and flows. Senge archetype if visible.
5. Stock and flow diagram for our state's primary-care-physician workforce: active physicians, retiring physicians, residency completers entering practice, mid-career attriters leaving the state. Inflows from residency match and inbound migration, outflows from retirement, attrition, and out-of-state moves. Map the system's loops and flows. Senge archetype if visible.

### `time-series`

1. I'm designing this chart and need to choose the right encoding: monthly active users from Jan 2024 through Apr 2026, with a 7-day moving average overlaid. The message is that growth has decelerated since Q3 2025. Critique this chart — Tufte data-ink ratio, sparkline option, small multiples consideration. What visual encoding fits this elementary perceptual task?

2. I'm designing this chart and need to choose the right encoding: weekly active users of our app from Jan 2023 through Apr 2026 with a 4-week moving average overlaid. The message is that growth re-accelerated after the AI features launched in Q4 2025. Critique this chart — Tufte data-ink ratio, sparkline option, small multiples consideration. What visual encoding fits this elementary perceptual task?
3. I'm designing this chart and need to choose the right encoding: daily US COVID-19 hospitalizations from Jan 2020 through May 2026 with a 14-day moving average overlaid. The message is the post-2023 endemic baseline. Critique this chart — Tufte data-ink ratio, sparkline option, small multiples. What visual encoding fits this elementary perceptual task?
4. I'm designing this chart and need to choose the right encoding: monthly natural-gas consumption across our six city-gate stations from Jan 2020 through Apr 2026 with a 12-month moving average overlaid. The message: the post-2023 demand shift toward heat-pump-driven flatness. Critique this chart — Tufte data-ink ratio, sparkline option, small multiples consideration. What visual encoding fits this elementary perceptual task?
5. I'm designing this chart and need to choose the right encoding: monthly used-vehicle wholesale prices (Manheim Index) from Jan 2018 through Apr 2026 with a 6-month moving average overlaid. The message is the post-pandemic 70% spike followed by the 2024-2026 reversion below pre-pandemic trend. Critique this chart — Tufte data-ink ratio, sparkline option, small multiples consideration. What visual encoding fits this elementary perceptual task?

### `tornado-chart`

1. Tornado diagram on our DCF valuation — sensitivity on growth rate, discount rate, terminal multiple, churn. Which input variables drive expected value most? Value of information.

2. Tornado diagram on our family's retirement-readiness sensitivity — sensitivity on Social Security cuts, equity returns, healthcare inflation, longevity. Which input variables drive expected value most? Value of information.
3. Tornado diagram on our enterprise SaaS startup's runway sensitivity — sensitivity on net new ARR, gross margin, R&D spend, fundraising-event timing. Which input variables drive expected runway most? Value of information.
4. Tornado diagram on our city's pension-fund solvency sensitivity — sensitivity on assumed return, retiree-mortality drift, contribution-rate, payroll growth. Which input variables drive expected funded-ratio most? Value of information.
5. Tornado diagram on our state's K-12 funding-formula sensitivity for the 2027-30 biennium — sensitivity on enrollment trajectory, hold-harmless rules, federal Title I trajectory, local-property-tax base growth, special-education caseload. Which input variables drive expected per-pupil funding most? Value of information.

## Interpretive lenses

### Argumentative Artifact Examination

#### `affect-heuristic`

1. Analyze the affect heuristic in how this ad gets people to judge the product's safety by the warm feeling it evokes rather than any data.
2. People rate a technology as low-risk and high-benefit when they like it and the reverse when they don't. Analyze the affect heuristic driving that coupled judgment.
3. Analyze the affect heuristic behind why vivid dread of a rare event swamps the statistics in people's risk judgments.

#### `anchoring`

1. Do a propaganda-style audit of the manipulation in this ad: a $999 'original price' slashed to $399. Show how the anchor distorts what buyers think the product is really worth.
2. Propaganda audit on this recruiter's opening line in a salary negotiation: 'Most people in this role start around $85k here, and honestly that's already near the top of our band for the level.' Audit the anchoring tactic — how naming a deliberately low number first anchors the candidate's sense of a reasonable ask and skews the rest of the negotiation. Engineering-of-consent diagnostic.
3. Propaganda audit on this fundraising letter: 'Most supporters give a suggested gift of $500 today. Your generosity at that level is what sustains our mission — will you join them?' Audit the anchoring tactic — how leading with a high 'suggested gift' anchors the reader's sense of an appropriate donation. Engineering-of-consent diagnostic.

#### `availability-heuristic`

1. After a plane crash dominates the news, people overestimate flying risk and drive instead. Analyze the availability heuristic — judging probability by how easily vivid examples come to mind.
2. A manager keeps hiring for the trait of the last person who quit, over-weighting the most recent memorable case. Analyze the availability heuristic distorting the judgment.
3. Voters rank crime as the top issue right after a sensational story, regardless of the statistics. Analyze the availability heuristic at work in the perception.

#### `choice-architecture`

1. Analyze the choice architecture of our checkout flow — how the arrangement of options and the defaults steer what users end up picking.
2. Apply choice-architecture analysis to a 401(k) enrollment design — how the default option and framing nudge participation.
3. Analyze the choice architecture of a cafeteria layout — how placement and defaults shape what people actually eat.

#### `commitment-consistency`

1. Propaganda audit on this sales script: 'You'd agree protecting your family matters, right? ... And you'd want the best protection available, wouldn't you? ... So it only makes sense to go with our premium plan today.' Audit the commitment-and-consistency tactic — the small initial yeses engineered so the customer stays consistent with a much bigger commitment. Engineering-of-consent diagnostic.
2. Apply commitment-consistency to how a campaign extracts a small public pledge to lock in later behavior.
3. Propaganda audit on this subscription flow's copy: 'Start your free trial — no commitment! ... You've been a member 7 days, don't lose your progress ... Members like you keep their streak by upgrading to Pro.' Audit the commitment-and-consistency tactic — how each step escalates from a free trial to a paid commitment by invoking the user's own prior choices.

#### `entman-framing-functions`

1. Frame audit on this editorial line about the protest: 'Violent agitators shut down the city last night, vandalizing storefronts and clashing with police trying to keep order.' What frame is this using? Lakoff/Entman treatment — what's foregrounded, what's backgrounded, what tacit assumptions in this frame; how it defines the problem, diagnoses the cause, renders the moral judgment, and prescribes the remedy.
2. Frame audit on this op-ed line about the recession: 'a natural, healthy correction after years of cheap money and overspending.' What frame is this using? Lakoff/Entman treatment — what's foregrounded, what's backgrounded, what tacit assumptions in this frame; how it defines the problem, diagnoses the cause, renders the moral judgment, and prescribes the remedy.
3. Frame audit on this op-ed line about the crime trend: 'a surge unleashed by lenient prosecutors, bail reform, and under-policing.' What is selected in and selected out? Run Entman's framing functions — how this single frame defines the problem, locates the cause, assigns the moral judgment, and prescribes the fix.

#### `goffman-frame-analysis`

1. Frame audit on this satirical ad using Goffman's frame analysis: what primary framework is it asking the audience to apply, and where is it 'keyed' into a joke not meant literally? Identify the frame, the keying, and where the reading breaks down between audiences who take it straight and those who get the satire.
2. Frame audit on this negotiator's email — 'I thought we were friends, and this is how you treat me?' — through Goffman's frame analysis. What primary framework (a business deal versus a personal relationship) is being invoked, and how is the interaction being re-keyed from one frame into the other? What's selected in and selected out by that move?
3. Frame audit, Goffman frame analysis, on this politician's public apology: name the primary framework the speaker wants us to read it through, where the event is keyed or re-keyed into a different kind of act, and what the framing foregrounds and hides.

#### `scarcity`

1. Propaganda audit on this checkout banner: 'Only 3 left in stock — 14 people are viewing this right now. Order within 9:58 to get it by Friday.' Audit the scarcity tactic — how the manufactured urgency and false-limit cues inflate desire and short-circuit deliberation. Manufactured-urgency diagnostic.
2. Analyze the scarcity manipulation in a 'limited-time offer, ends tonight' campaign — how artificial scarcity drives the purchase.
3. Propaganda audit on this invite-only product launch announcement: 'Access is strictly limited — only 500 founding memberships exist, and the waitlist is already 40,000 deep. Once they're gone, enrollment closes for good.' Audit the manufactured-scarcity tactic — how the artificial limit manufactures urgency and inflates perceived demand.

#### `social-proof`

1. Audit the social-proof tactic in this ad's '10,000 customers can't be wrong' claim — how others' behavior is used to steer the uncertain buyer.
2. Analyze the social proof in a landing page stacked with testimonials and 'trending now' badges — leveraging the herd to persuade.
3. Audit how a charity uses social proof — 'your neighbors already donated' — to drive contributions.

#### `stanley-propaganda`

1. Propaganda audit, Stanley test, on this 2026 campaign ad: 'Real patriots protect our communities. The coastal elites and their open-border allies want you defenseless — only we stand between your family and the chaos they invite.' Supporting vs undermining propaganda — name the democratic ideal it claims and the anti-democratic content it smuggles in, and the flawed belief it activates rather than argues for. Concept-substitution, not-at-issue content.
2. Is this propaganda? Stanley test on this corporate statement: 'We believe in merit and fairness for all. That is why employees who question our equity initiatives are creating an unsafe workplace and have no place here.' Supporting vs undermining propaganda — the democratic words ('fairness,' 'safety') standing in for their opposite, and the flawed premise switched on rather than defended.
3. Propaganda audit on this state-media editorial: 'A true democracy requires unity. Those who criticize the leadership during this national emergency are doing the enemy's work and forfeit their right to be heard.' Stanley test — the ideal of democracy professed versus the anti-democratic function performed, manufactured-doubt diagnostic, flawed-ideology premise check.

#### `walton-schemes-and-critical-questions`

1. Does this argument hold up: 'We should trust the experts on this — the leading authorities agree, so the conclusion stands'? Check the logic and run Walton's argumentation-scheme critical questions for appeal-to-expert-opinion to test whether it actually holds — expertise, consensus, bias, and backing evidence.
2. Is this argument sound: 'If we let employees pick any four days to work from home, next they'll want full remote, then they'll never come in, and the office culture collapses'? Check the premises and conclusion — run Walton's critical questions for the slippery-slope scheme to test each link in the chain.
3. Does this argument hold up: 'Regulating AI is like regulating cars — we didn't ban automobiles over crash risk, we added seatbelts and traffic laws, so we should just add safety rules to AI'? Check the logic and apply Walton's critical questions for the argument-from-analogy scheme to find where the analogy breaks.

### Interest And Power

#### `arrows-impossibility-theorem`

1. Analyze our committee's ranked-vote deadlock as a multi-criteria social-choice problem through Arrow's impossibility theorem — why no voting system over three or more options satisfies all fairness criteria.
2. Multi-criteria decision on our product-prioritization vote, read through Arrow's impossibility theorem: five PMs each submitted a ranked ballot over six candidate features and the rankings conflict. Rank the options, then show why aggregating the individual rankings into one fair group ranking is provably impossible — which of Arrow's conditions (unanimity, independence of irrelevant alternatives, non-dictatorship) must break, and what that means for how we actually decide. AHP weighting.
3. Use Arrow's impossibility theorem to analyze why every voting-reform proposal trades one paradox for another.

#### `bounded-rationality`

1. Analyze our procurement decisions through bounded rationality — how people satisfice under limited time, information, and attention rather than optimize.
2. Apply bounded rationality to why shoppers grab a 'good enough' option rather than the mathematically optimal one.
3. Analyze an organization's routines through bounded rationality — decisions shaped by cognitive limits and satisficing, not full optimization.

#### `free-rider-problem`

1. Our open-source project has thousands of corporate users but only a handful contribute back. Do a boundary critique of the free-rider problem — who benefits without paying, where the system boundary of 'who should contribute' is drawn, and who is wrongly left outside it.
2. Do a boundary critique of a shared regional fire service funded by only some of the towns that rely on it — who free-rides, whose contribution counts, and who is wrongly left outside the boundary of who must pay.
3. In our team, a few people carry the on-call burden while others coast. Do a boundary critique of this free-rider problem — whose contribution is counted, whose is excluded, and where the fair boundary lies.

#### `tragedy-of-the-commons`

1. Who counts as a legitimate claimant on a shared regional aquifer, and where should the system boundary be drawn? Hundreds of farms pump freely, draining it — a tragedy of the commons. Do a boundary critique of whose interests sit inside the boundary, whose are excluded, and how to govern the commons.
2. Our shared CI build cluster is overused by every team until it's always slow — a tragedy of the commons. Do a boundary critique of who counts as a legitimate user and how to govern the shared resource.
3. Ocean fisheries are collapsing from individually-rational overfishing. Analyze the tragedy of the commons and do a boundary critique of who governs the shared resource.

#### `ulrich-csh-boundary-categories`

1. Boundary critique of a city's new 'smart policing' predictive system using Ulrich's critical systems heuristics and its twelve boundary categories — whose interests, expertise, and voices the design includes and whose it excludes from the definitions of 'high-risk area' and 'person of interest'. Sources of motivation, power, knowledge, and legitimacy — who is left out of the boundary judgments?
2. Apply Ulrich's CSH boundary categories to a corporate sustainability plan: who is the beneficiary, who the decision-maker, who the expert, who the witness — and where the boundary judgments hide the affected-but-voiceless.
3. Run a boundary critique with Ulrich's twelve critical-systems-heuristics categories on a national ID system, separating what 'is' from what 'ought' across motivation, control, knowledge, and legitimacy.

### Decision Making Under Uncertainty

#### `bottlenecks`

1. Find the bottleneck constraining throughput in our delivery pipeline — the one slowest step that governs the whole system's output.
2. Analyze our hiring funnel for the bottleneck — which single stage caps overall throughput no matter how we improve the others.
3. Apply theory-of-constraints bottleneck analysis to a factory line — locate the constraint and why optimizing non-bottlenecks is wasted effort.

#### `decision-trees`

1. Full decision-architecture analysis on a real decision we're facing this quarter — a structured decision document integrating stakeholders, options, and criteria: launching the new product this quarter versus building out two more features first versus a limited regional pilot. Build the decision tree underneath it — options, branch probabilities, payoffs, expected-value rollback. Decision architecture, not just one tree.
2. Full decision-architecture analysis on whether to settle the lawsuit or take it to trial — a structured decision document integrating stakeholders, options, and criteria. Underneath it, lay out the decision tree with expected-value rollback across the settle and trial branches: win probability, award size, legal cost, time. Decision architecture.
3. Full decision-architecture analysis on this go/no-go investment — a structured decision document integrating options, criteria, and stakeholders. Model it as a decision tree: the branches, the probabilities, the payoffs, and the expected value of each path rolled back to the decision. Decision architecture.

#### `endowment-effect`

1. This is a big decision and I want the full decision architecture: keep building on our in-house analytics platform or migrate to the off-the-shelf product, taking everything into account — alternatives, what binds each, who's affected, how the leading choice could fail. And apply the 'would we buy our current system today at its true cost?' check so we're not over-valuing it just because we already own it.
2. Full decision analysis on whether to renew the lease on our current headquarters or relocate, taking everything into account. Lay out the options, consequences, stakeholders, and failure modes — and run the endowment check: are we scoring the building we already occupy too high simply because it's ours? Would we choose it fresh today against the alternatives? Decision architecture.
3. Full decision architecture analysis on a real decision we're facing this quarter — choosing among present options: 'keep our legacy enterprise customer on its old custom contract, or migrate it to the new standard platform.' Structured decision document — stakeholders, options, criteria, integrated, with the failure modes of the leading choice. Decision architecture — and separate the genuine value of the incumbent setup (integration, switching cost) from the extra value we assign it purely because we already own it.

#### `loss-aversion`

1. Analyze the loss aversion at work when investors hold a losing stock far too long rather than realize the loss — why the pain of the loss outweighs the rational decision to sell.
2. Analyze the loss aversion in why people walk away from a free trial the moment it asks for payment — the felt loss of handing over the card number outweighing the clear gain from the product.
3. Frame this insurance decision through loss aversion — how the fear of a rare large loss leads people to over-insure relative to expected value.

#### `mcdm-methods`

1. Apply multi-criteria decision methods to choosing a new headquarters city — weight the criteria (cost, talent, taxes) and score the options.
2. Use an MCDM method to pick a vendor across cost, reliability, and support criteria that do not reduce to one number.
3. Analyze a hiring decision with multi-criteria decision methods — the competing criteria, their weights, and how the options rank.

#### `prospect-theory`

1. Apply prospect theory to why customers reject a sure small surcharge but accept a risky larger one — outcomes weighed against a reference point, not in absolutes.
2. Analyze a gambler's behavior through prospect theory — risk-averse in gains, risk-seeking in losses, with losses looming larger than gains.
3. Use prospect theory to analyze why employees value a guaranteed bonus far more than a larger expected-value variable one.

#### `satisficing`

1. Compare our vendor alternatives and map the tradeoffs across cost, reliability, and integration — but through a satisficing lens: we want to stop at the first option that clears a 'good enough' bar on every criterion rather than search for the global optimum. Map the tradeoffs and show when satisficing beats optimizing here.
2. Compare the candidate alternatives for this hire and map the tradeoffs across skills, cost, and ramp time — through a satisficing lens, where the manager stops at the first candidate clearing a 'good enough' threshold instead of interviewing the whole field. Map the tradeoffs; when does satisficing beat optimizing?
3. Compare the alternatives for a decision under limited search time and map the tradeoffs across the criteria — through a satisficing lens: take the first option above threshold versus exhaustively optimizing. Where do the tradeoffs make satisficing the right call?

#### `sunk-cost-fallacy`

1. Full decision architecture analysis on a real decision we're facing this quarter — choosing among present options: 'keep funding our four-years-and-$12M in-house ERP rebuild, or kill it and switch to the off-the-shelf system.' Structured decision document — stakeholders, options, criteria, and the forward expected value of each path, integrated. Decision architecture — and explicitly keep the money already sunk out of the forward call, separating it from what finishing would cost from here.
2. Full decision analysis on whether to continue our flagship drug trial after two disappointing readouts or terminate it now. Lay out the alternatives, the forward odds and value of each, who's affected, and the failure modes — and keep the $200M already spent out of the forward calculation. Decision architecture: are we continuing only because of what we've already committed?
3. Full decision architecture analysis on a real decision I'm facing right now — choosing among present options: 'keep pouring money into restoring the classic car I've already put $60k into, or sell it as-is today.' Structured decision document — options, criteria, who's affected, integrated decision design. Decision architecture — and keep the $60k already sunk out of the forward call, separating it from what completing the restoration would cost from here.

#### `trade-offs`

1. Analyze the core trade-offs in choosing between speed, cost, and quality for our build across these competing criteria — every choice has a cost, so weigh what we give up for what we get.
2. Multi-criteria decision on our team's return-to-office policy: rank three options — full-remote, hybrid (two days in), and full-office — across hiring reach, collaboration quality, real-estate cost, retention, and focus time. Weigh the trade-offs each option makes on each criterion and give me a ranked recommendation. AHP weighting.
3. Analyze the trade-offs in a city's choice between a highway and transit across the competing criteria of cost, access, and emissions.

### Causal Investigation

#### `bennett-checkel-process-tracing-tests`

1. Trace the causal process behind our outage using Bennett and Checkel's process-tracing tests — straw-in-the-wind, hoop, smoking-gun, and doubly-decisive evidence.
2. What really happened — did the new community-policing policy cause the drop in crime, or did something else? Process tracing on the within-case evidence: apply the hoop test and the smoking-gun test to the timeline (when the policy rolled out by precinct, what moved when), and tell me which causal story the evidence supports. Bennett-Checkel four tests.
3. Use Bennett-Checkel process-tracing tests to evaluate a historical hypothesis about why the negotiation collapsed.

#### `fishbone-diagram`

1. Build a fishbone diagram for why our product launches keep slipping — categorize the causes (people, process, tools, materials) to find the root.
2. Use an Ishikawa fishbone analysis on recurring defects — sort the contributing causes into categories to locate the root cause.
3. Apply a fishbone diagram to chronic customer complaints — the cause categories feeding the problem.

#### `five-whys`

1. Run a five-whys analysis on why the deployment failed — keep asking why until you reach the systemic root cause, not the proximate one.
2. Apply the five whys to why a customer churned — drill past the surface reason to the underlying cause.
3. Use five-whys on a recurring production incident — each why peeling back toward the real root.

#### `fundamental-attribution-error`

1. What are the root causes of our recurring production outages — we keep blaming the on-call engineer's mistakes, but the same failures recur every month despite repeated fixes. Why does this keep happening? Draw a fishbone separating the systemic causes from the individual — the fundamental attribution error we keep making.
2. Analyze the root cause of why we blamed a late vendor's laziness rather than their circumstances — the fundamental attribution error in the story.
3. Analyze the root cause of a struggling employee's performance and the fundamental attribution error in blaming their attitude rather than the system around them.

#### `pearl-causal-graphs`

1. Does our new onboarding flow actually cause higher retention, or does it just correlate because more motivated users opt in? Draw the causal DAG and apply Pearl's ladder of causation to separate association from intervention — identifying confounders and back-door paths.
2. Causal DAG that separates confounders from the causal path: customers who use our mobile app spend 30% more than web-only customers. Draw the DAG with confounders (customer tenure, income, prior engagement), mediators (notification frequency, reorder ease), and possible colliders, and use Pearl's ladder of causation to test whether the app causes the spending or confounders explain the gap. What would happen if we intervened to move web users onto the app?
3. Causal DAG that separates confounders from the causal path: did our sales-training program cause the 12% productivity gain? Draw the DAG with confounders (who self-selected into training, manager quality, territory), the mediator (new-technique adoption), and colliders, and apply Pearl's framework to separate causation from confounded correlation. What would happen if we intervened and assigned training at random?

#### `pearl-do-calculus`

1. Causal DAG with Pearl's do-calculus: estimate the effect of our 15% price increase on churn from observational data alone. Draw the DAG with confounders (segment, contract type, seasonality) and mediators, then use do-calculus and the backdoor criterion to decide whether P(churn | do(price)) is identifiable — separating the intervention from mere correlation in the historical data.
2. Causal DAG with Pearl's do-calculus: we shipped a new onboarding feature and retention rose. Given a DAG of feature-use to retention with confounders (cohort, acquisition channel, device) and a mediator (week-1 activation), use do-calculus to determine whether the effect of the feature on retention is identifiable from our observational logs, and which backdoor paths must be blocked.
3. Apply do-calculus to a causal graph of advertising and sales — what would the intervention do, computed from observational data via back-door adjustment?

#### `reward-undermining`

1. Analyze how paying kids to read undermined their intrinsic love of reading — reward undermining, where external incentives crowd out internal motivation.
2. Apply reward-undermining to a bonus scheme that killed the team's intrinsic drive — the causal loop where money displaces motivation.
3. Analyze the causal loop where gamified metrics undermined genuine engagement — reward undermining, external rewards eroding the intrinsic motivation they meant to boost.

### Hypothesis Evaluation

#### `base-rate-neglect`

1. A manager is sure a candidate who 'looks like a founder' will succeed, ignoring that most startups fail. Evaluate the competing hypotheses while correcting for base-rate neglect — how common is success in the reference class before the vivid details.
2. A vivid news story has everyone convinced shark attacks are surging. Weigh the hypotheses against the base rate and show where base-rate neglect distorts the judgment.
3. Our model flags an account as fraud because it matches a 'fraud profile.' Assess the hypotheses with the base rate of fraud in mind, correcting the base-rate neglect behind the flag.

#### `bayesian-reasoning`

1. I got a positive result on a 95%-accurate test for a condition affecting 1 in 1,000 people. Weigh the competing hypotheses — true disease versus false positive — by the diagnosticity of the evidence and the base rate, Bayesian-style, to see which fits best.
2. I have two competing hypotheses: two analysts read the same signals intelligence — one concludes a rival will launch within the month, the other that it's a bluff. Make me an ACH matrix and apply Bayesian updating — score each piece of evidence by diagnosticity and update each hypothesis — to find whether the disagreement is driven by different priors or by the evidence itself.
3. Evidence points to our churn spike being caused by a pricing change. Apply Bayesian updating across the competing hypotheses — state the priors, weigh each evidence's diagnostic strength, and compute the revised beliefs.

#### `confirmation-bias`

1. I've already concluded our customer churn is fundamentally a pricing problem, and now I'm reviewing the data. Lay out the competing hypotheses for the churn and stress-test for confirmation bias — where I'd favor evidence that fits the pricing story and discount what cuts against it.
2. I'm convinced our new hire is underperforming. Lay out the competing hypotheses and check my reasoning for confirmation bias — where I'm collecting only evidence that fits.
3. We believe the marketing campaign drove the sales bump. Lay out the competing hypotheses and stress-test for confirmation bias favoring data that confirms the campaign worked.

#### `differential-diagnosis-schema`

1. Run a differential diagnosis on our sudden traffic drop — list the candidate causes, then use discriminating tests to rule each in or out.
2. Apply a differential-diagnosis schema to a patient's symptoms — generate the candidate conditions and the tests that distinguish them.
3. Our CI build fails intermittently — green on rerun, red maybe one run in five, no change to the test code. Candidate explanations: a race condition in the suite, a flaky external dependency, resource exhaustion on the runner, test-ordering contamination, a clock/timezone assumption, caching between runs. Differential diagnosis — which is most likely, and what evidence discriminates among them?

#### `falsifiability`

1. Lay out the competing hypotheses for this market theory and assess its falsifiability — what observation would disconfirm it, or is it unfalsifiable?
2. I have two competing hypotheses about whether our strategy is working: 'it's working and every setback just means commit harder' versus 'it's failing and the setbacks are the signal.' Make me an ACH matrix weighing each, and assess falsifiability — what observation could disconfirm the first one, the one its defenders keep immunizing against every miss.
3. I have two competing hypotheses about a forecasting model whose proponents explain away every miss: 'the model works, misses are special cases' versus 'the model is no better than chance.' Make me an ACH matrix weighing each, and assess falsifiability — what single observation could refute the 'it works' hypothesis, and what it means that its defenders keep immunizing it against disconfirmation.

#### `representativeness-heuristic`

1. Analyze the representativeness heuristic in why we diagnosed the outage as 'probably the database again' because it resembled the last one, ignoring base rates.
2. A juror judges guilt by how much the defendant fits the 'criminal type.' Analyze the representativeness heuristic distorting the judgment.
3. Analyze the representativeness heuristic behind assuming a quiet, bookish person is more likely a librarian than a salesperson.

### Future Exploration

#### `klein-pre-mortem`

1. Pre-mortem this plan: we're launching a redesigned product next quarter — new three-tier pricing page, annual-discount toggle, and a self-serve onboarding flow replacing sales-assisted setup — to our full user base. Imagine it's six months later and the launch failed badly. Run a Klein pre-mortem: work backward from the imagined failure to the preventable causes we can still act on. What killed it?
2. Pre-mortem this plan: we're acquiring a 40-person competitor, folding their product into ours, migrating their customers to our platform, and merging the two go-to-market teams over two quarters. Assume it's a year out and the acquisition has gone disastrously wrong. Run a Klein pre-mortem — surface the failure paths while we can still act on them. What killed it?
3. Pre-mortem this plan before we start: we're migrating our entire production stack to the cloud next quarter — lift-and-shift of 40 services, new managed databases, a single-weekend cutover. Assume it's six months later and it failed badly; work backward from that imagined failure, turning each failure path into a mitigation we can act on now. What kills it?

#### `premortem-analysis`

1. Imagine our launch has already failed — run a premortem analysis to surface the failure modes while we can still prevent them.
2. Pre-mortem this plan: we're reorganizing from functional teams into nine cross-functional squads — new squad leads, dissolved component teams, a new planning cadence — rolling out org-wide next month. Assume it's a year later and the reorg backfired. Work backward to the causes. What kills it?
3. Run a premortem analysis on a product bet — picture the post-mortem of its failure and extract the preventable risks now.

#### `regression-to-mean`

1. Our best sales rep just had a record quarter and now we forecast even more. Analyze the regression to the mean — why extreme performance tends to be followed by something closer to average, independent of any intervention.
2. A struggling team got a new coach and improved. Analyze how much of the rebound is regression to the mean rather than the coaching, and how to tell them apart.
3. Students who scored worst on a test improved after tutoring. Use regression to the mean to estimate how much improvement to expect even with no tutoring at all.

#### `second-order-thinking`

1. Apply second-order thinking to a rent-control policy — the immediate relief and then the second- and third-order consequences for housing supply.
2. If we ship this — fully automating our customer-support team, replacing 40 agents with an AI that handles tier-1 tickets end to end — what does it lead to? Analyze the second-order consequences: past the obvious headcount savings, the downstream effects everyone ignores — on escalation quality, the product-feedback loop, agent-sourced institutional knowledge, the hiring pipeline, and customer trust. The cascade forward.
3. Use second-order thinking on a decision to subsidize electric vehicles — and then what, and then what after that?

#### `sensemaking`

1. Scenario planning for our team facing an ambiguous, fast-moving market shift we can't yet interpret — explore how it might unfold with a 2x2 scenario matrix across the two biggest uncertainties. Treat the exercise as Weickian sensemaking: act into the ambiguity, see what each scenario reveals, and retrospectively build the meaning we need to navigate it.
2. Scenario planning for a crisis team making sense of a fast-moving incident — a 2x2 scenario matrix across the key uncertainties of how it could unfold, used as Weickian sensemaking: acting into the ambiguity in order to understand it.
3. Scenario planning for an organization disoriented by a new competitor — explore how the situation might unfold with a 2x2 scenario matrix, as a sensemaking exercise: the retrospective, enactive process of constructing what's going on.

#### `tetlock-superforecasting`

1. Give me a calibrated forecast: what is the probability that US headline CPI is below 3% year-over-year by Q4 2026? Use Tetlock-style superforecasting discipline — anchor on the base rate, adjust on indicators, commit to an explicit probability with reasoning.
2. Forecast, Tetlock-style, the probability our key competitor launches a rival product within 12 months — base rate first, then adjust on signals, with an explicit number.
3. Give a superforecaster-style calibrated probability that this infrastructure project finishes on time — reference class, adjustments, and a committed estimate.

#### `wisdom-of-crowds`

1. Analyze when aggregating many independent guesses beats the experts — wisdom of crowds, and the conditions (independence, diversity) it requires.
2. Apply wisdom-of-crowds to a prediction-market forecast — why the aggregate of independent bets can outperform any single forecaster.
3. Analyze whether our forecast would improve by polling the team independently — wisdom of crowds and where it fails under correlated errors.

### Risk And Failure Analysis

#### `margin-of-safety`

1. Audit the margin of safety in our cash runway — the buffer between what we expect and what we could survive if revenue halved.
2. Apply margin-of-safety thinking to an engineering load spec — the gap built in between expected load and the failure point.
3. Analyze the margin of safety in a value investment — the buffer between the price paid and a conservative intrinsic value.

#### `normal-accident-theory`

1. Analyze our trading platform through normal accident theory — it is both highly complex and tightly coupled, so analyze where interacting failures could cascade into an accident no one designed.
2. A chemical plant has fast, tightly-coupled processes with many nonlinear interactions. Audit it through normal accident theory — where complexity plus tight coupling makes a serious accident effectively inevitable.
3. Apply normal accident theory to a just-in-time supply chain — how complexity and tight coupling turn a small disruption into a system-wide failure.

#### `normalization-of-deviance`

1. Our ops team keeps skipping a safety check because nothing has gone wrong yet. Analyze this as normalization of deviance — how a tolerated violation becomes the new baseline until it fails.
2. Analyze the normalization of deviance behind a string of near-misses the org treated as normal, right up to the accident — how 'we got away with it' redefined acceptable risk.
3. A hospital repeatedly bends a sterilization protocol with no immediate harm. Audit the normalization of deviance and where the drifting baseline becomes dangerous.

#### `recovery-window`

1. Analyze the recovery window in our incident response — the time between the first ambiguous warning and irreversible damage, and whether we act inside it.
2. Apply recovery-window thinking to a slow-building financial crisis — the closing window between the first warning sign and the point of no return.
3. Analyze the recovery window in a patient's deterioration — the interval where intervention still reverses the damage.

#### `swiss-cheese-model`

1. Analyze our outage through the Swiss cheese model — how the holes in monitoring, on-call, and rollback layers lined up to let the failure pass all the way through.
2. Apply the Swiss cheese model to a patient-safety incident — how weaknesses in several defensive layers aligned, and which layer to harden to break the alignment.
3. Audit our fraud defenses with the Swiss cheese model — where the holes in each layer line up and how to stagger them so no single path goes through.

#### `taleb-fragility-antifragility`

1. Our operations run lean: single-source components, just-in-time inventory, no buffers. Audit this through Taleb's fragility-antifragility lens — where small shocks stay small, where large shocks produce disproportionate convex losses, and whether any part gains from disorder.
2. Fragility audit on our retirement portfolio, Taleb-style: 70% in a target-date index fund, 20% in our employer's own stock, 10% cash, with a mortgage on an illiquid house and a single household income in a cyclical sector. Where does it break under a large shock versus where does volatility actually help it — convex or concave exposures, tail risks, asymmetric payoffs?
3. Analyze a city's emergency-response system through fragility and antifragility — where stress causes disproportionate harm and where it builds resilience.

### Stakeholder Conflict

#### `incentives`

1. Map the stakeholders and their incentives behind why our sales team games the quota system — never ask why people behave a certain way until you see what they are rewarded for.
2. Map the stakeholders and their incentives in a hospital where doctors are paid per procedure — how the reward structure drives the behavior we observe across the parties.
3. Map the incentive structures of all the stakeholders in an open-source project — maintainers, corporate users, casual contributors — and how they shape who contributes.

#### `stakeholder-analysis-frameworks`

1. Map the stakeholders of our new policy using stakeholder-analysis frameworks — a power/interest grid of who to engage, inform, or watch.
2. Apply a stakeholder-analysis framework to a construction project — identify and classify the parties by influence and interest.
3. Use stakeholder-analysis frameworks to map the players in an org change — their power, interest, and stance.

### Paradigm And Assumption Examination

#### `framing-effect`

1. Compare two framings of the same treatment — '90% survival' versus '10% mortality' — and analyze the framing effect that makes identical facts produce different choices.
2. Compare the competing framings 'a 5% fee' versus 'you keep 95% of your returns' and analyze the framing effect on how customers respond to identical economics.
3. Compare these two frames of the same number — 'unemployment fell to 4%' versus '4% of workers still can't find a job' — and analyze the framing effect each has on the reader.

#### `lakoff-conceptual-metaphor`

1. Frame comparison on the immigration debate — two competing conceptual-metaphor frames. The flood frame: 'Immigration is a flood to hold back — a surge at the border, waves of arrivals, a country being swamped.' The newcomer frame: 'Immigrants are newcomers seeking shelter — guests at the door, strivers and contributors, a nation built by immigrants.' Compare both worldviews on their own terms, using conceptual-metaphor analysis to show how each metaphor structures the reasoning and makes different policies feel natural.
2. Frame comparison on tax policy — two competing conceptual-metaphor frames. The tax-as-burden frame: 'Taxes are a dead weight crushing earners, money confiscated from the people who made it.' The tax-as-dues frame: 'Taxes are membership dues — what we each pay into the shared enterprise that makes prosperity possible.' Compare both worldviews on their own terms, using conceptual-metaphor analysis — how the competing metaphors shape the whole policy argument.
3. Frame comparison on drug policy — two competing conceptual-metaphor frames. The war frame: 'A war on drugs — enemies and cartels, fronts and crackdowns, victory through force.' The public-health frame: 'A public-health problem — patients not criminals, treatment and harm reduction, recovery and care.' Compare both worldviews on their own terms, using conceptual-metaphor analysis to surface which responses each metaphor makes thinkable.

### Conceptual Clarification

#### `cappelen-plunkett-conceptual-engineering`

1. Conceptual engineering on 'fairness' as used in our hiring policy — it's doing several incompatible jobs at once (equal treatment, equal outcomes, bias-correction, meritocracy) and the inherited concept isn't doing the work it should. Following Cappelen and Plunkett, should we re-engineer what 'fairness' ought to mean for this policy rather than just describe how it's used? What should it mean?
2. Apply Cappelen and Plunkett's conceptual engineering to 'addiction' — assess and improve the concept as a tool, not a fixed feature of the world.
3. Conceptual engineering on 'remote work' as used in our HR policy — it currently conflates fully-distributed, hybrid, work-from-anywhere, and temporary-WFH, and the ambiguity is causing disputes. Following Cappelen and Plunkett, engineer what the concept should mean for our purposes rather than describing current usage. What should 'remote work' mean here?

#### `map-territory`

1. Analyze the map-territory confusion where our north-star metric became the map mistaken for the territory — clarify how the proxy diverged from the real thing it was meant to represent.
2. Apply the map-is-not-the-territory distinction to our org chart — how the formal model diverges from how work actually flows.
3. Explain in depth how a financial risk model came to be mistaken for the reality it represents — the map taken for the territory. I want the mechanics: what the abstraction captures, what it silently leaves out, and how the gap between model and world produces blind spots. Depth, not orientation.

#### `system-one-system-two`

1. Explain in depth how our hiring decisions actually run on fast System 1 intuition versus slow System 2 deliberation — the cognitive mechanics of where the snap pattern-match takes over and where it misfires into bias. I want the depth, Kahneman's dual-process account, not a summary.
2. Explain in depth the mechanics of why people fall for the intuitive-but-wrong answer on the bat-and-ball puzzle — Kahneman's System 1 and System 2. How the fast, automatic System 1 generates the wrong snap answer and why the effortful System 2 fails to override it. Depth, not a summary.
3. Explain in depth how a clinician's snap medical judgment works through System 1 and System 2 thinking — the cognitive mechanics of when the fast pattern-match helps and when it needs the slow, deliberate check. Kahneman's dual process, depth not orientation.

### Structural Relationship Mapping

#### `niches`

1. Relationship map of how the players in our market interact and where each one's competitive niche sits — a dependency graph of who competes with whom, who depends on whom, and the specific conditions and resources where our product outcompetes. What happens to the map when a rival enters our niche?
2. Relationship map of our market position as an ecological niche — the dependency graph of which competitors occupy which space, what resources each depends on, and whether the narrow niche we dominate is defensible. What affects what?
3. Relationship map of how two competitors avoid direct conflict by occupying different niches — a dependency graph of what each dominates, what flows through where, and what collapses if their niches start to overlap.

#### `scale`

1. Relationship map of how our system's components interact and which couplings break as we scale from a thousand users to a million — the dependency graph of what affects what, and where the dependencies that hold at small scale snap at large scale.
2. Relationship map of how a startup's structures and teams interconnect, and which dependencies break as it scales from 10 to 500 people — the dependency graph of who depends on whom, what affects what, and where the couplings fail under growth.
3. Relationship map of how a city's infrastructure, cost, and pace interrelate as it scales — the dependency graph of what affects what, and how doubling the population shifts the couplings nonlinearly.

### Cross Domain And Knowledge Synthesis

#### `allisons-three-lenses`

1. Worldview cartography of the US withdrawal from Afghanistan through Allison's three explanatory paradigms: the rational-actor model, the organizational-process model, and the governmental-politics model. Multi-paradigm map — where do the three lenses cohere on what happened, and where do they irreducibly conflict? Then integrate them into one reading.
2. Bring together Allison's three models — rational actor, organizational process, and bureaucratic politics — to synthesize a single integrated explanation of the Fed's surprise rate decision.
3. Explain the Fed's last surprise rate decision dialectically through Allison's three lenses (rational actor, organizational process, governmental politics), then synthesize the competing explanations.

#### `evolution-natural-selection`

1. Synthesize how natural selection — variation, selection, and inheritance — explains which startup business models survive in a market.
2. Synthesize two separately-developed bodies of knowledge: Darwinian natural selection (variation, selective retention, heritability, fitness) and cultural evolution / memetics (how ideas vary, spread, and are selectively kept across a population). Map the structural parallel and the intersection — where natural selection is the connecting mechanism that explains how ideas evolve across a culture.
3. Synthesize a product category's evolution through natural selection — the variation, the selection pressure, and what survivors inherit, drawing the cross-domain parallel to biology.

### Negotiation And Conflict Resolution

#### `batna`

1. I'm a mid-size component supplier renegotiating an exclusive contract with my largest buyer, who keeps hinting they'll switch vendors. Map the underlying interests on both sides and work out my BATNA — my best alternative if this deal collapses — so I know my real leverage.
2. I'm negotiating a job offer and they're lowballing. Map my interests and my BATNA — my best alternative to this agreement — so I know how hard to push.
3. Interest mapping before I sit down to negotiate our startup's acquisition with the one interested buyer. What does each side really want, separate from the stated positions on price and terms? Map the interests, and where our BATNA — stay independent or raise another round — sets our real leverage at the table.

#### `cooperation`

1. Interest mapping for a repeated negotiation between two rival firms. What does each side really want beneath its positions, and how does mutual cooperation stay stable across repeated rounds despite the temptation to defect? Map the interests and the conditions that make cooperation a stable negotiated outcome.
2. Interest mapping before a long-running supplier negotiation. What does each side really want beneath the stated positions, and how do repeated dealings sustain mutual cooperation over one-shot defection? Map the interests and the cooperation-sustaining conditions.
3. Interest mapping for two countries negotiating over a shared river. What does each side really want beneath its positions, and how does cooperation hold across repeated rounds of negotiation? Map the interests and the conditions for stable cooperation.

#### `fisher-ury-principled-negotiation`

1. Principled negotiation prep for our vendor-contract dispute, full Fisher-Ury treatment: the SaaS vendor wants a 30% renewal increase and a three-year lock-in; we want flexibility and a better rate. Separate the people from the problem, focus on interests not positions, generate options for mutual gain (term length, usage tiers, support SLAs), and find objective criteria for fair pricing. BATNA on both sides.
2. Apply Fisher-Ury principled negotiation to a co-founder equity disagreement — the interests behind the positions, objective criteria, and each side's BATNA.
3. Analyze a landlord-tenant standoff with principled negotiation (Fisher-Ury) — the underlying interests, the objective standards, and the options that expand the pie.

#### `procedural-justice`

1. Analyze why employees accepted an unpopular layoff because the process felt fair — procedural justice, where fairness of process matters as much as the outcome.
2. Apply procedural justice to a community's reaction to a zoning decision — how the fairness of the process shapes acceptance independent of the result.
3. Analyze a disputed promotion through procedural justice — whether the process was seen as fair and how that drives acceptance of the outcome.

#### `psychological-safety`

1. Analyze why our team stopped raising concerns, through psychological safety — whether people feel safe to speak up, ask questions, and admit mistakes.
2. Apply psychological safety to a team where junior members stay silent in meetings — the conditions for safe dissent.
3. Analyze the psychological safety of a post-incident review — whether people can admit errors without fear of blame.

#### `ury-third-side`

1. Analyze this community conflict through Ury's Third Side — the surrounding community's role as containers, mediators, and healers of the dispute.
2. Third-side reading of this workplace feud: two senior engineers on the same team haven't spoken directly in two months after a design disagreement turned personal; the rest of the team is taking sides and standups have gone silent. I'm advising the team lead. Apply Ury's third side — how the surrounding team can act as the third side to contain and de-escalate. Which of Ury's ten roles are available?
3. Third-side reading of this dispute: two neighborhood factions are warring over a proposed shelter — one organizing to block it, one to fund it — while the city council, local businesses, and a faith coalition watch from the surround. I'm advising a community mediator. Per Ury, how can the third side — the community around the two warring factions — shift the conflict? Which of Ury's ten third-side roles are available?

### Orientation In Unfamiliar Territory

#### `circle-of-competence`

1. Map my circle of competence before this biotech investment — where I have genuine earned knowledge and where I only think I do.
2. Analyze whether this decision falls inside or outside our circle of competence — the boundary of what we actually understand versus what we're guessing at.
3. Apply circle-of-competence thinking to a CEO expanding into an unfamiliar industry — staying within earned knowledge versus straying out of it.

#### `cynefin-framework`

1. I'm trying to get oriented on a problem we can't yet categorize. Walk me through the big picture using the Cynefin framework — is the terrain clear, complicated, complex, or chaotic, and what response does each domain demand? Concept map of the decision terrain.
2. I'm unfamiliar with how to tell apart two situations we're facing — a software outage versus a product-market-fit question. Walk me through the big picture with Cynefin: which is complicated (knowable, expert-solvable) and which is complex (emergent, probe-first)? Concept map of the terrain.
3. I need to get oriented fast on a novel crisis I don't recognize. Walk me through the big picture using the Cynefin framework — diagnosing where the terrain sits across clear, complicated, complex, and chaotic, and what kind of response each domain calls for. Concept map of the situation.

#### `ooda-loop`

1. Analyze how a fighter pilot's OODA loop — observe, orient, decide, act — lets them out-tempo a slower opponent, and what 'getting inside the enemy's OODA loop' means here.
2. Our incident-response team is always a step behind during outages. Analyze their OODA loop and where the observe-orient-decide-act cycle is too slow to keep up.
3. Apply the OODA loop to a startup competing against a slow incumbent — how a faster observe-orient-decide-act cycle becomes the competitive edge.

#### `pareto-principle`

1. Apply the Pareto principle to our support tickets — which 20% of issues cause 80% of the volume, to orient where to focus first.
2. Quickly orient on our revenue using the 80/20 Pareto principle — which few customers or products drive most of it, so we know where to focus.
3. Orient fast on where our team's time goes using the Pareto principle — the vital few activities producing most of the value.

### Artifact Evaluation By Stance

#### `cia-tradecraft-red-team`

1. Red-team our security assumption that 'no one would target a company our size' using CIA-tradecraft red-team methods — challenge the assumption the way an adversary's analyst would.
2. Apply CIA structured red-team tradecraft to our market forecast — devil's advocacy, what-if analysis, and an adversary's-eye review of where we are fooling ourselves.
3. Stress-test this intelligence assessment before we brief it: 'We assess with high confidence that the rival will not move on the contested region this year, based on troop-positioning satellite data, intercepted logistics chatter, and the absence of mobilization.' Red-team it with CIA tradecraft — key-assumptions check, analysis of competing hypotheses, devil's advocacy — surfacing the assumptions an adversary would exploit and the analytic blind spots we're carrying. What would a hostile reviewer say?

#### `devils-advocacy`

1. Steelman the case against our consensus decision to expand into Europe: the room has unanimously agreed to open a London office, hire a regional GM, and localize the product for the EU market on the strength of inbound demand. Play devil's advocate — construct the strongest version of the objection the room is suppressing, best case against, no caveat-padding.
2. Apply structured devil's advocacy to this investment thesis — argue the other side hard to stress-test whether the bull case survives.
3. Steelman the case against the hiring decision everyone already loves: the panel unanimously wants to extend an offer to the charismatic candidate who aced the culture interviews. Play devil's advocate — construct the strongest possible argument against the favored candidate, the best case the room doesn't want to hear, no caveat-padding.

#### `groupthink`

1. Stress-test this board-approved plan before we commit: our leadership team unanimously signed off on betting the company on a single flagship AI product and sunsetting our three profitable legacy lines by Q4. One cohesive team, a hard deadline, no outside review. Find the holes, rank them by how badly they'd hurt us, and flag any assumption nobody in the room ever challenged. What would a hostile reviewer say?
2. Red team this acquisition memo before I take it to the board: the deal team — all close colleagues who've worked together for years — reached quick consensus to buy our largest competitor at a 40% premium, with no dissenting voice recorded. Stress-test it, find the holes, and flag the assumptions a unanimous, like-minded team may never have pressure-tested. Where is this weak?
3. Red team this go-to-market plan before we commit to it: a tight, cohesive team produced it under deadline and every member endorsed the same approach, with no dissent recorded. Stress-test it — find the holes, rank them by how badly they'd hurt us, and call out any assumption the group accepted without challenge because dissent felt unwelcome. What am I missing, and what would a hostile reviewer say?

#### `hanlons-razor`

1. Balanced critique of our vendor's botched data migration that lost three days of customer records: their post-mortem cites an untested backup script and a skipped staging run. Strengths and weaknesses at equal depth, neutral read, no advocacy — and as you weigh the failures, judge whether each points to ordinary incompetence or constraint rather than deliberate negligence.
2. Give me a fair, balanced critique of this government agency's delayed disaster-relief rollout — what held up and what didn't, strengths and weaknesses, no thumb on the scale. Where it fell short, weigh whether the failures are better explained by bureaucratic error and resource limits than by bad faith.
3. Balanced critique of a colleague's quarterly report that quietly omitted the two worst-performing metrics: strengths and weaknesses at equal depth, a neutral read with no advocacy either way. As you assess the omission, weigh the charitable explanation — oversight or honest framing under deadline — against assuming intent to mislead.

#### `hindsight-bias`

1. Analyze the hindsight bias in our incident review — how 'we should have seen it coming' rewrites what was actually knowable beforehand.
2. Analyze the hindsight bias in our failed-merger post-mortem — how knowing the outcome makes everyone say it was obviously doomed, rewriting what was actually knowable at the time.
3. Analyze the hindsight bias in judging a doctor's decision by the outcome rather than the information available at the time.

#### `narrative-instinct`

1. Analyze the narrative instinct in how this post-mortem turned a messy accident into a clean story with a villain — the human compulsion to build a coherent narrative.
2. We have fit scattered Q3 results into a tidy turnaround story. Critique the narrative instinct distorting how we read the data.
3. Analyze the narrative instinct behind a pundit's neat causal story for a market crash that was mostly noise.

#### `occams-razor`

1. Apply Occam's razor to these competing explanations for our outage — prefer the one that needs the fewest assumptions to fit the evidence.
2. Two theories explain the churn data equally well, but one requires three special conditions. Use Occam's razor to weigh them.
3. Analyze this conspiracy explanation against the mundane one using Occam's razor — which multiplies entities unnecessarily.

### Mechanism Understanding

#### `emergence`

1. How does a traffic jam actually work under the hood — the structural explanation of how each driver's simple local rules (follow, brake, change lanes) produce the emergent jam, a global pattern the individual parts don't have? Parts to behavior, the mechanism of emergence.
2. How does a flock's coordinated motion actually work under the hood — the structural explanation of how each bird's simple local rules produce the emergent global pattern, behavior the parts don't individually have? Parts to behavior, the mechanism of emergence.
3. How do market prices actually work under the hood — the structural explanation of how countless individual trades produce emergent macro-order no trader designs? Parts to behavior, the mechanism of emergence.

#### `first-principles`

1. Reason from first principles about whether we actually need a native app — decompose the requirement to fundamentals and rebuild, ignoring what competitors do.
2. Apply first-principles thinking to our cost structure — break it down to the irreducible physics and economics, then reason back up.
3. Use first principles to question the assumption that our product must be subscription-based — what is actually true at the base?

### Process And System Analysis

#### `creative-destruction`

1. Cheap AI transcription is wiping out the traditional medical-transcription industry. Analyze this through Schumpeter's creative destruction — how the new technology destroys the incumbent's rent and what the market looks like afterward.
2. Streaming destroyed video rental and reshaped the studios. Read the creative-destruction dynamic in that market — what rent was destroyed, what was created, and who captured it.
3. Low-cost solar is rendering aging coal plants uneconomic across the grid. Analyze the creative destruction reshaping this power market.

#### `critical-mass`

1. Our two-sided marketplace has 5,000 buyers but only 400 sellers and growth is sluggish. Analyze the critical-mass dynamics — where the network-effects tipping point is and what it takes to reach self-sustaining growth.
2. A new messaging app is stuck because people won't join until their friends do. Analyze the critical-mass threshold and the network effects that gate adoption in this market.
3. An EV-charging network and EV sales each wait on the other to grow. Analyze the critical-mass chicken-and-egg dynamic and where the tipping point lies.

#### `diminishing-returns`

1. We keep adding engineers to the same product squad and shipping speed has barely moved. Analyze the diminishing returns — where the marginal payoff of another hire bends — and what that means for our next allocation in this market for talent.
2. Our ad spend on this channel shows clear diminishing returns — each extra dollar converts worse than the last. Analyze the market dynamics: where the marginal return bends and the efficient point to stop spending.
3. A region keeps adding fertilizer to the same farmland with shrinking yield gains. Analyze the diminishing returns to the input and what it implies for further investment.

#### `equilibrium`

1. Analyze the market equilibrium in our two-sided marketplace — the state where buyer demand and seller supply balance, and what shocks knock it out of balance.
2. Apply equilibrium analysis to this market — the balance point where opposing supply and demand forces settle, and whether it is stable.
3. Analyze the market equilibrium that emerges when supply and demand forces balance, and what happens when a shock tips it.

#### `feedback-loops`

1. Draw the feedback structure of our customer-success system — the reinforcing and balancing loops and the stocks and flows linking onboarding quality, churn, and referrals — and show which loops dominate over time.
2. Draw the feedback structure for a city's traffic system. Show me the stocks (vehicles on the road, road capacity, latent demand), the flows (trips added, lanes built, commuters priced out), and a structural diagram with the reinforcing and balancing loops connecting capacity, induced demand, and commute time. Structural picture before deciding what to change.
3. Draw the reinforcing and balancing feedback loops in a social platform's engagement system as a stock-and-flow structure — content, attention, creators, and moderation load.

#### `greshams-law`

1. On our freelance marketplace the cheap low-quality providers keep crowding out the skilled ones, and buyers can't tell them apart before hiring. Analyze this as a Gresham's law dynamic — how the bad drives out the good — and what it does to the market over time.
2. Ad-fraud bots and clickbait keep outcompeting honest publishers for ad budgets because buyers can't distinguish quality inventory. Read this market through Gresham's law: how the debased product drives out the good.
3. In our loyalty-points economy, members hoard the valuable rewards and spend only the inflated low-value ones. Analyze the Gresham's-law selection effect on what actually circulates in the market.

#### `leverage`

1. Draw the feedback structure of our customer-retention system — the stocks (active users, at-risk users, churned), the flows (signups, churn, reactivation), and the reinforcing and balancing loops. Then identify the Meadows leverage points — the few places in that feedback structure where a small, well-placed intervention shifts the whole system. Structural picture first.
2. Draw the feedback structure of this system, then find the leverage points: show the stocks, flows, and reinforcing/balancing loops, and mark the Meadows leverage points — where a small, well-placed intervention produces outsized change. Structural picture before deciding what to change.
3. Draw the feedback structure of our operation — the stocks, flows, and reinforcing and balancing loops — then apply Meadows leverage-point analysis to mark the highest-leverage places to intervene in that structure. Structural diagram first.

#### `practical-drift`

1. Analyze how our deployment process drifted from the written procedure to 'how we actually do it' — practical drift, and the risk it accumulates.
2. Apply practical drift to a safety protocol everyone quietly stopped following — the widening gap between official and actual practice.
3. Analyze the practical drift in a team's code-review process — how real practice diverged from the policy over time.

#### `red-queen-effect`

1. Analyze the market dynamics in our retail category as a Red Queen effect: every retailer matches the others' loyalty programs and discounts, nobody gains share, and all just spend more to stay even — competitive coevolution that runs to stand still.
2. Smartphone makers pour more into cameras every cycle just to keep pace with rivals, with no lasting edge. Read this market through the Red Queen effect — running to stand still.
3. Two ad-tech firms are locked in a Red Queen effect — each escalates its targeting to neutralize the other's gains, so neither pulls ahead. Analyze the market dynamics of this competitive coevolution and what, if anything, breaks the treadmill.

#### `supply-demand`

1. Our city is about to approve 10,000 new apartments over three years. Walk me through the supply and demand dynamics — what happens to rents in the short run versus the long run as the new supply comes online?
2. Coffee prices spiked after a frost wiped out a third of Brazil's harvest. Analyze the supply and demand — how far prices move, how fast buyers and growers adjust, and where the market settles.
3. A new tariff doubles the import price of solar panels. Trace the supply-and-demand response in the domestic market — who raises output, who substitutes, and what the new equilibrium price looks like.

### Strategic Interaction

#### `adverse-selection`

1. Our new pay-monthly device warranty is attracting mostly customers whose phones are already failing, and we're losing money. The customers know their device's condition and we don't. Analyze the adverse selection — who self-selects in, who exits — and how screening could separate the risk types.
2. A health plan priced for the average population is drawing disproportionately sick enrollees, because applicants know their health and the insurer can't observe it. Analyze the adverse-selection death spiral and how to design against it.
3. On our peer-lending platform only the riskiest borrowers accept the high rate while good borrowers leave — borrowers privately know their creditworthiness, lenders don't. Analyze the adverse selection in this market.

#### `asymmetric-warfare`

1. Game theory of an asymmetric conflict: what's the weaker player's best move against a dominant but rigid incumbent — refusing to fight on the incumbent's terms and attacking where the big player is strong but inflexible? Payoff matrix, the asymmetric-warfare dynamics, deterrence and where the incumbent's commitments aren't credible.
2. Game theory: model the strategic interaction between an insurgent startup and a market incumbent as asymmetric warfare — how the challenger turns the big player's strengths (scale, installed base, fat margins) into liabilities. Payoff matrix, best responses, the moves the incumbent can't profitably counter.
3. Game theory: what's a weaker rival's optimal asymmetric-warfare strategy against our dominant market position? Model the interaction — payoff matrix, where attacking our strengths becomes their advantage, deterrence and the credibility of our responses.

#### `backward-induction`

1. Game theory: solve this sequential bargaining game by backward induction. Two players split $100 over three alternating-offer rounds; the pie shrinks 20% each round an offer is rejected. Start from the final round and reason back to the first move to find each player's optimal strategy. Payoff at each node, subgame-perfect path.
2. Game theory: apply backward induction to this multi-round negotiation game. A buyer and seller alternate offers over four rounds with a hard deadline; if no deal by round four, both fall back to their outside options. Work back from the last round to determine the first-round offer each should make. Payoffs at each node, the equilibrium path.
3. Game theory: use backward induction on this entry-deterrence game. A potential entrant moves first (enter / stay out), then the incumbent responds (price war / accommodate). Reason from the end of the game tree back to the equilibrium path — is the incumbent's threat to start a price war credible? Payoffs at each node.

#### `brinkmanship`

1. Two nuclear powers escalate a border standoff toward the brink. Using game theory, analyze the brinkmanship and deterrence: how going to the edge of catastrophe makes the threat credible, what each side expects the other to do, and where it tips into disaster.
2. A union and management each push a strike to the eleventh hour to prove their threat is real. Analyze the brinkmanship and the deterrence logic of escalation.
3. Analyze the brinkmanship in a debt-ceiling standoff — how each side's willingness to risk default makes the threat credible, and the deterrence calculus underneath.

#### `moral-hazard`

1. After we began fully reimbursing field reps for any client dinner with no cap, spending exploded — and we can't observe each meal. Analyze the moral hazard, where the reps' hidden action diverges from our interest once they're shielded from the cost, and how to redesign the incentives.
2. A bank that expects to be bailed out takes bigger hidden risks because the downside falls on taxpayers who can't monitor it. Analyze the moral hazard and the incentive redesign.
3. Once we gave employees unlimited expense-account travel, usage climbed in ways finance can't audit per trip. Analyze the moral hazard in this hidden-action structure and how to realign the incentives.

#### `mutually-assured-destruction`

1. Analyze a price war between two dominant platforms as mutually assured destruction — each can destroy the other's margins, so the credible threat of mutual ruin enforces an uneasy peace. Use game theory.
2. Two nuclear rivals each hold second-strike capability. Analyze the mutually-assured-destruction logic as a game — why the guarantee of mutual annihilation deters a first strike.
3. Two firms hold patents that could destroy each other in litigation. Analyze the mutually-assured-destruction standoff and the strategic stability it creates, in game-theory terms.

#### `nash-equilibrium`

1. Two airlines, Delta and United, compete on one route and each must decide simultaneously every quarter whether to price High or Low. Payoffs: both High, each earns 100; one prices Low while the other holds High, the discounter earns 140 and the rival 40; both Low, each earns 60. Moves are simultaneous, no communication, repeated each quarter. Find the Nash equilibrium of this game.
2. Game theory: two gas stations across the street set prices independently each morning, each choosing high or low without seeing the other. Payoffs: both high = good profit each; both low = thin margin each; one low and one high = the low one takes the market. Model this as a game and find the Nash equilibrium — where neither can change price unilaterally without losing. Payoff matrix.
3. Game theory: two firms bid for the same contract in a sealed-bid first-price auction, each valuing it at about $1M with private costs. Model the bidding as a game and find the Nash equilibrium of their bidding strategies — how far each shades its bid below value. Payoff matrix, best responses.

#### `principal-agent-problem`

1. Our sales reps are paid on bookings, but they privately control which deals they chase and how they discount, and we can't see their effort. Analyze the principal-agent problem — the hidden action and misaligned incentives — and how the contract could be redesigned.
2. A pension fund hires an asset manager whose interests and information differ from the fund's, and whose real effort is unobservable. Analyze the principal-agent problem and the incentive structure that would align them.
3. Voters (principals) delegate to legislators (agents) who have private information and their own interests. Analyze the principal-agent problem in this delegation and what mechanism would better align the agent's hidden actions.

#### `prisoners-dilemma`

1. Two competitors each decide whether to cut prices, where mutual restraint is best for both but each is tempted to defect. Analyze this as a prisoner's dilemma — why rational self-interest produces a worse outcome for both. Use game theory.
2. Analyze an arms race between two nations as a prisoner's dilemma — why both keep building despite both preferring mutual disarmament, in game-theory terms.
3. Two countries weigh whether to cut carbon emissions. Analyze the prisoner's dilemma where each gains from defecting but mutual defection is the worst outcome for all.

#### `schelling-point`

1. Model this as a coordination game: two rival firms independently pick a product standard with no communication, and both gain only if they match. Using game theory, find the focal Schelling point they converge on.
2. Two strangers must meet in New York with no way to communicate. Model the coordination game and find the Schelling point — the focal time and place — they will both choose.
3. In this bargaining game both sides expect to settle near a round number without ever agreeing to it. Use game theory to analyze the Schelling point as the focal solution they coordinate on.

#### `signaling`

1. Game theory of costly signaling: model why a company burns millions on a Super Bowl ad that says nothing about the product. Set up the payoff structure — the ad is a costly, hard-to-fake action that credibly signals private information about quality to buyers who can't otherwise verify it. Separating versus pooling equilibrium, why cheap talk fails.
2. Game theory of costly signaling: model why a founder takes a deliberately below-market salary. Set up the payoff structure — a costly, hard-to-fake action that credibly signals private information about commitment to investors who can't otherwise verify it. Separating versus pooling equilibrium, why the wrong type won't mimic it.
3. Game theory of costly signaling in elite degrees and expensive engagement rings — model them as costly signals that credibly reveal hidden private information precisely because they're too expensive for the wrong type to fake. Payoff structure, separating versus pooling equilibrium, deterrence of mimicry.

#### `tit-for-tat`

1. Two competitors repeatedly choose whether to honor or break a price truce. Using game theory on this repeated game, analyze why tit-for-tat — cooperate first, then mirror the rival's last move — is the best move.
2. Model two countries' repeated trade concessions and retaliations as a game. What will they do over many rounds, and why is tit-for-tat the stable strategy until it spirals into retaliation?
3. Our team and a partner team repeatedly decide how much to help each other across projects. Using game theory, analyze tit-for-tat as the best move in this repeated game.

#### `winners-curse`

1. We keep winning competitive acquisition auctions and then finding the target was worth less than we paid — each bidder privately estimates value and the highest estimate wins. Analyze the winner's curse — why winning is itself bad news about value — and what it implies for how we bid.
2. In sealed-bid oil-lease auctions the winner routinely overpays relative to the field's true value, since every bidder has only a private noisy estimate. Analyze the winner's curse and the bid-shading it implies.
3. Our procurement runs reverse auctions and the lowest bidder often turns out to have underestimated the job. Analyze the winner's-curse dynamic on the supplier side.

### Spatial Composition

#### `alexander-pattern-language`

1. Read this town square through Alexander's pattern language — which patterns ('small public squares', 'building edges', 'activity pockets') are present or violated, and how they shape whether people gather.
2. Apply Christopher Alexander's pattern language to our office floor plan — which patterns make it feel alive or dead, from 'light on two sides' to 'common areas at the heart'.
3. Analyze this neighborhood through Alexander's pattern language — the patterns that give it a living sense of place versus the placeless gaps between them.

#### `appleton-prospect-refuge`

1. Read this café's seating through Appleton's prospect-refuge theory — why the corner booths with a view of the door fill first and the exposed center tables last.
2. Analyze why people cling to the edges of this plaza using prospect-refuge theory — the evolutionary pull toward spots offering both outlook (prospect) and shelter (refuge).
3. Apply prospect-refuge theory to a park design — where the desire to see without being seen shapes which spots feel safe and which feel exposed.

#### `arnheim-compositional-forces`

1. Here is our new landing-page hero layout — a big headline upper-left, an image lower-right, a button dead center. Read its compositional dynamics through Arnheim's structural skeleton and visual forces: where the axes and centers pull the eye, and where the composition is balanced or strained.
2. Analyze this museum poster's composition through Arnheim's compositional forces — the structural skeleton, the directed tension between elements, and how visual weight distributes across the frame.
3. Read the compositional dynamics of this dashboard layout using Arnheim's framework of perceptual forces and the hidden structural skeleton — what feels balanced, what feels like it's about to topple.

#### `bachelard-topoanalysis`

1. Read the intimate spaces of a childhood home through Bachelard's topoanalysis — how corners, attics, and drawers hold psychological resonance, not just square footage.
2. Read a writer's studio as intimate space using Bachelard's poetics of space — the psychological charge of the room's nooks and thresholds.
3. Read a reading nook through Bachelard's topoanalysis — the intimate space and its phenomenology of shelter and daydream.

#### `bertin-visual-variables`

1. Critique this data map with a Bertin visual-variables audit: a US county map encoding three variables at once — population density as color saturation (pale yellow to deep red), median income as circle size, and unemployment as circle hue (green to purple), all stacked on the same counties. Through Bertin's retinal variables, which variable rides which retinal variable, where the encodings collide, and where the encoding fights perception. Prescriptive recommendations.
2. Critique this dashboard's encoding choices with Bertin's visual variables — is value, hue, size, or position doing each job, and are any used for data they can't represent well?
3. Apply Bertin's seven visual variables to a chart that uses color hue to encode a quantitative magnitude — why that's a poor fit and which variable should carry it instead.

#### `cleveland-mcgill-perceptual-tasks`

1. Critique this chart with a Cleveland-McGill perceptual-task audit: a quarterly market-share figure drawn as a 3-D exploded pie of six wedges, value labels hidden behind the tilt, rainbow legend off to the side. Analyze the information density through Cleveland and McGill's perceptual-task ranking — whether readers must judge position, length, angle, or area, and how that predicts reading accuracy. Prescriptive recommendations.
2. Critique this chart with a Cleveland-McGill perceptual-task audit: a pie chart with five near-equal slices (22%, 21%, 20%, 19%, 18%) used for a precise comparison. Through Cleveland-McGill's perceptual-task ranking, explain why angle and area judgments are less accurate than position-along-a-common-scale, and what encoding to use instead.
3. Critique this chart with a Cleveland-McGill perceptual-task audit: a stacked bar chart of monthly revenue split across five product lines, where the reader needs to compare the third segment across twelve months. Apply the Cleveland-McGill perceptual-task hierarchy — which comparisons the stacked encoding makes easy (the baseline segment, the total) and which it makes inaccurate (the floating middle segments). Prescriptive fix.

#### `gestalt-grouping-principles`

1. Here is the layout of our analytics dashboard — twelve tiles, three accent colors, uneven spacing. Read its compositional dynamics through the Gestalt grouping principles: what proximity, similarity, and figure-ground organization make the eye bind, and where grouping fights meaning.
2. Read this poster's composition through the Gestalt grouping principles — how proximity and similarity make the eye group elements, and where the grouping misleads.
3. Analyze a cluttered form's layout using Gestalt grouping principles — proximity, similarity, closure — and where the grouping fights usability.

#### `japanese-aesthetics-catalog`

1. Read the use of Ma — negative space and interval — in this minimalist Japanese garden, where the empty raked gravel between the rocks carries as much meaning as the rocks themselves.
2. Analyze a traditional tea room through Japanese aesthetics — Ma, wabi-sabi, and yūgen — the charged emptiness and the beauty of imperfection in the space.
3. Apply the Japanese-aesthetics catalog (Ma, wabi-sabi, yūgen) to read this temple courtyard — how the intervals and voids structure the experience of the place.

#### `kaplan-attention-restoration`

1. Read this hospital garden as a place through Kaplan's attention-restoration theory — the soft fascination, being-away, extent, and compatibility that let depleted directed attention recover.
2. Read an urban park as a place through Kaplan's attention-restoration theory — which features (water, greenery, gentle complexity) restore depleted attention and which fail to.
3. Read a workplace break room as a place through Kaplan's attention-restoration theory — why it does or does not let people recover from directed-attention fatigue.

#### `lynch-image-of-the-city`

1. Read this downtown's legibility through Lynch's image of the city — its paths, edges, districts, nodes, and landmarks, and where people get lost.
2. Read a neighborhood's wayfinding using Lynch's image-of-the-city elements — what makes it mentally mappable or confusing.
3. Apply Lynch's image of the city to a campus as a place — the paths, nodes, and landmarks that make it navigable or not.

#### `norberg-schulz-genius-loci`

1. Read the genius loci — the spirit of place — of an old European market square through Norberg-Schulz, the qualitative atmosphere that decomposing it into 'a square plus buildings' misses.
2. Analyze what gives this coastal fishing village its distinctive sense of place using Norberg-Schulz's genius loci and the phenomenology of dwelling.
3. Apply Norberg-Schulz's genius-loci analysis to a generic suburban strip — why it lacks a spirit of place and what a place needs to have one.

#### `tufte-data-ink-chartjunk`

1. Critique this report's chart with a Tufte data-ink-ratio audit: a quarterly revenue dashboard with 3-D bars, drop shadows, a rainbow gradient fill on each bar, gridlines every $1k, and a logo watermark behind the plot. Through Tufte's data-ink ratio — how much ink encodes data versus decoration, and what chartjunk to strip to raise the information density. Prescriptive recommendations.
2. Critique this dashboard with a Tufte data-ink and chartjunk audit: a KPI dashboard cluttered with full-saturation gradient backgrounds, 3-D extruded bars, heavy gridlines every unit, redundant data labels on every point, and a neon moving-average ribbon. Apply Tufte's data-ink principles — what to remove to maximize the data-ink ratio.
3. Critique this infographic with a Tufte data-ink-ratio audit: a 'state of our market' infographic using decorative icon-arrays, a 3-D donut, a gauge with a chrome bezel, and call-out boxes in five colors. Through Tufte — where chartjunk and low data-ink density obscure the actual numbers, and how to redesign it for clarity.