AI Deliberator
Guides
How to use AI DeliberatorView all 58 guides

Getting started

Evaluate and export a Council runHow to ask a better decision questionHow to choose models for an AI councilRun your first AI councilUse the Consideration MapContinue a decision with follow-up questionsEstimate and control LLM costs

Everyday decisions

Use an AI council for a career changeEvaluate a leadership role or promotionThink through a relationship decisionDecide whether to move to a new cityCompare degrees, certificates, and education optionsAnalyze a major purchaseUse live evidence mode

Work and teams

Use deliberation for a business strategy decisionSupport a hiring decision responsiblyPrioritize a product roadmapRun a decision pre-mortemMap a stakeholder disagreementAnalyze a policy proposal

Research design

Duplicate and pilot an experimentDesign an LLM deliberation experimentDefine outcomes and dependent variablesConfigure experimental conditions and independent variablesCompare deliberation with homogeneous reconsiderationBuild an independent model ensembleUse randomization, replications, and compute matching

Participant studies

Build a participant interaction studyDesign pre- and post-interaction questionnairesChoose Likert, slider, and questionnaire formatsAdd attention, manipulation, and exposure checksAnalyze and export participant-study resultsBuild a composable experiment timelineMeasure human–AI advice relianceAdd process tracing and cognitive tasksRun a human deliberation conditionBuild a human–AI hybrid deliberation chainRun a text, image, or video stimulus experimentRun a learning and tutoring experimentPlan a powered participant studyMonitor recruitment, cost, and attrition

Behavioral games

Design a behavioral economics gameRun a Dictator GameRun an Ultimatum GameRun a Trust or Investment GameRun a Prisoner’s DilemmaRun a Public Goods GameRun a Stag Hunt GameConfigure game payoffs, incentives, and feedbackManage private game links, consent, and completion

Benchmarks and results

Select benchmark questions and subsetsRun MMLU-Pro in AI DeliberatorRun PolicyBench for public-policy reasoningRun CogToM for social cognitionCreate and read 95% confidence-interval plotsCollaborate and preserve a reproducible experiment recordAnalyze sentiment and quantitative text metricsCompare two Council runs
Workspace

Work and teams

Use deliberation for a business strategy decision

Compare strategic options using objectives, evidence, capabilities, competitors, implementation constraints, and explicit uncertainty.

The basic idea

Strategy benefits from adversarial examination because teams often agree on goals while hiding disagreements about mechanisms. A structured council makes assumptions and competing causal stories visible.

Example

Compare entering a new market, focusing on an existing segment, partnering, or delaying until a capability gap is closed.

How to do it

  1. 1

    Define the objective and the metric that would indicate success.

  2. 2

    Describe the options, resources, constraints, and evidence behind the forecast.

  3. 3

    Assign advocate, critic, fact-checker, and chair roles across distinct model slots.

  4. 4

    Ask for a recommendation, leading indicators, stop conditions, and a learning plan.

What to watch for

  • Models may invent market facts; verify external claims.
  • A polished synthesis can conceal weak input data.
  • Do not upload confidential strategy or customer information without authorization.

What a useful result looks like

A useful result connects the recommendation to explicit assumptions and tells the team what evidence should change course.