ls-consult-polymaths

name

ls-consult-polymaths

description

Spawn expert polymathic thinking agents for deep analysis. Use proactively when the user wants expert opinions, multi-perspective review, or mentions specific thinkers by name. Triggers on 'consult polymaths', 'ask the polymaths', 'polymath review', 'expert opinions on', 'what would the polymaths say', 'get Feynman to review', 'ask Carmack', 'what would Jobs think', 'multi-perspective review', 'diverse expert perspectives', 'run it by the polymaths', 'task the polymaths', 'debate this architecture', 'expert analysis'. Also trigger when the user names ANY polymathic agent (Feynman, Carmack, Jobs, Munger, Shannon, Linus, Tesla, etc.). Internal thinking agents — different from /consult which queries external LLM APIs.

Consult Polymaths

Spawn multiple polymathic thinking agents in parallel to analyze a task from different expert perspectives. Each polymath applies a historical figure's cognitive architecture as structural constraints on reasoning — they're read-only consultants that analyze and advise.

Available Polymaths

Code & Architecture

Agent	Lens
carmack	Performance, systems architecture, technical feasibility — finds the real constraint
linus	Code review, taste, BS detection, maintainability — demands elegance
tesla	Systems architecture, infrastructure, API design — complete mental model first
shannon	API design, simplification, hidden structure — strips to the invariant skeleton

Design Patterns (Gang of Four)

Agent	Lens
gamma	Code architecture, API design — refactor TO patterns, composition over inheritance, Rule of Three
helm	Architectural evaluation, enterprise design — behavioral contracts, explicit tradeoff analysis
johnson	Framework design, library architecture — three concrete examples before abstracting
vlissides	Complex domain architecture, multi-pattern design — pattern constellations, bridge knowing-applying gap

Product & UX

Agent	Lens
jobs	Product vision, UX simplification, feature pruning — taste-first
rams	Product design, UI simplification — less but better
vangogh	UI/UX, color systems, emotional design — feeling before function
disney	Experience design, creative strategy — Dreamer/Realist/Critic triad

Strategy & Decisions

Agent	Lens
bezos	Customer-obsessed design, decision speed — press release first
thiel	Contrarian analysis, monopoly strategy — zero-to-one thinking
gates	Platform strategy, ecosystem design — decompose into atoms
andreessen	Market timing, technology adoption — spot discontinuities
suntzu	Competitive strategy, positioning — win before fighting
musk	Moonshot feasibility, aggressive simplification — delete before optimize

Thinking & Analysis

Agent	Lens
feynman	Debugging, first principles, cargo cult detection — freshman test
holmes	Debugging, incident investigation, forensic evidence, negative signals — case file first
moriarty	Adversarial strategy, threat modeling, deception, hidden networks — move two
tao	Problem decomposition, cross-domain connections — toy models first
munger	Decision frameworks, bias detection — invert every problem
socrates	Assumption testing, exposing hidden ignorance — elenctic questioning
lovelace	Technology visioning, system abstraction — operational patterns
davinci	Cross-disciplinary synthesis, bio-inspired design — find the analog
aurelius	Decision-making under pressure, resilience — obstacle is the way

Marketing & Content

Agent	Lens
ogilvy	Copywriting, ad strategy — headline is 80% of the work
godin	Marketing strategy, audience building — smallest viable audience
graham	Startup strategy, product-market fit — do things that don't scale
mrbeast	Content strategy, attention engineering — retention curves

Workflow

Step 1: Gather the Task

If the user provided a clear task in their message, use it directly. Otherwise, use AskUserQuestion to ask:

• "What problem or task do you want the polymaths to analyze?"

Step 2: Select Polymaths

Based on the task domain, select the most relevant polymaths. Consider:

• Code problems → carmack, linus, feynman, shannon, tesla
• Product decisions → jobs, rams, bezos, feynman, thiel
• Architecture → carmack, tesla, shannon, linus, gamma, helm
• Design patterns → gamma, helm, johnson, vlissides
• Strategy/business → bezos, thiel, gates, munger, suntzu
• UX/design → jobs, rams, vangogh, disney
• Debugging → holmes, feynman, moriarty, carmack, linus, socrates
• Threat modeling / adversarial review → moriarty, holmes, munger, dijkstra, shannon
• Marketing → ogilvy, godin, graham, mrbeast
• Decision-making → munger, aurelius, bezos, socrates, feynman
• Innovation → davinci, lovelace, thiel, musk, tao

Cross-domain tasks benefit from mixing categories (e.g., a product architecture question might get carmack + jobs + shannon).

Step 3: Confirm with User

Use AskUserQuestion to present:

1. How many polymaths? — Offer 2, 3, 4, or 5 (suggest 3 as default for good coverage without overwhelming output). More than 5 gets noisy; fewer than 2 defeats the purpose.

2. Does this selection look good? — Show the selected polymaths with a one-line rationale for each. Let the user swap any out.

If the user wants to swap agents, adjust the selection and proceed. Don't re-confirm unless they explicitly ask.

Step 4: Spawn in Parallel

Spawn all selected polymaths simultaneously using the Agent tool with:

• subagent_type matching the agent name (e.g., polymathic-feynman)
• The same task prompt for each agent
• Each agent gets the full task context

The prompt to each agent should be the user's task, verbatim. Don't paraphrase or filter — let each polymath's cognitive architecture shape their unique response.

Step 5: Synthesize

After all agents return, provide a brief synthesis:

• Consensus — Where do the polymaths agree?
• Tensions — Where do they disagree, and why?
• Surprise insights — Anything unexpected that only one polymath surfaced?
• Recommended action — Based on the combined perspectives, what should the user do?

Keep the synthesis concise. The individual polymath responses carry the depth; the synthesis highlights patterns and conflicts.