Four ways to think better with AI

Each mode is a different structured reasoning workflow. Pick the one that matches how you want to challenge your thinking.

Crucible

Most popular

Stress-test any belief or decision

Submit a claim, thesis, or decision. Multiple AI models simultaneously build the strongest case FOR, the strongest case AGAINST, and audit every factual claim. Then a synthesizer delivers a verdict with a strength score.

Steelman
Red Team
Evidence Audit
Crux
Pre-mortem
Verdict
Example: "Our startup should raise a Series A now rather than bootstrapping for another year"

Perspectives

See through multiple expert lenses

Describe a problem or situation. Different AI expert personas (CEO, CTO, Researcher, Critic) each share their unique viewpoint. No debate, no consensus — the diversity of thought is the value.

CEO lens
CTO lens
Researcher lens
Critic lens
Example: "Should our 5-person startup invest in building an AI feature or focus on core product?"

Review

Find what you're missing

Paste an architecture doc, PRD, business plan, or code. Multiple AI reviewers independently critique it from different angles: technical correctness, completeness, and hidden assumptions.

Technical review
Completeness review
Assumptions review
Example: "Review this architecture: monolith FastAPI with in-memory state, JSONB snapshots to Supabase..."

Deep Analysis

AI models deliberate in depth

Ask a complex question. Multiple AI models independently research it with web search, then challenge each other's answers in iterative rounds with rebuttals and evidence. A consensus detector tracks agreement, and a synthesizer compiles the final answer.

Research
Challenge
Rebut
Consensus
Synthesize
Example: "What is the best database for a real-time analytics platform processing 10M events/day?"
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