Founder
Anthropic, the skeptical founder
Pressure-tests the idea, looks for the wedge, calls out weak demand, and asks what should be cut before anyone builds.
00
Rough ideas becomebuildable plans.
A structured council between OpenAI and Anthropic runs on your machine and writes a plan you can build from.
01
Two voices, one verdict.
One prompt gives an answer. The council gives each model a job, makes them read each other, and argues until the recommendation is clear.
CTO
OpenAI, the pragmatic CTO
Designs a buildable MVP, names the data model and services, and flags any strategy that becomes expensive in code.
Research first, then five council steps.
Each step writes to disk as it completes. The run is local-first, readable, and degrades gracefully when a source is unavailable.
- 00
Scout the market
Competitors, demand signals, and source notes ground the council before the models speak.
- 01
Shape the wedge
Anthropic turns the raw idea into a focused customer, offer, and risk map.
- 02
Design the MVP
OpenAI designs the smallest useful release and calls out technical traps.
- 03
Attack the architecture
The product lens asks what is too large, too slow, or not tied to proof.
- 04
Attack the strategy
The engineering lens asks which assumptions are costly or infeasible for an MVP.
- 05
Deliver the packet
The debate resolves into a recommendation, backlog, risks, and validation tests.
03
A founder packet in five parts.
Structured for the next week of work, not for a slide deck nobody opens again.
Summary
The recommended product, the customer, and the reason to build this version first.
MVP backlog
An ordered list of the smallest valuable release, ready for a coding agent.
Risks
The assumptions that can break the plan, paired with practical mitigations.
Validation tests
Concrete experiments, success metrics, and kill criteria for the first proof loop.
Next prompts
Prompt handoffs for product, design, engineering, and follow-up research.
Files on disk
Every run writes readable Markdown artifacts locally, including the founder brief.
04
The council starts with evidence.
Dossier
Sources become a competitor matrix, opportunity map, validation experiments, and a one-page founder brief.
Idea discovery
Name a market and a goal. IdeaClyst looks for complaints, fresh launches, and gaps, then ranks buildable candidates.
Promotion to council
Only ideas with evidence become council-worthy. The selected report carries its thesis into a full planning run.
Find, validate, build, and learn.
IdeaClyst keeps a local library of ideas, reports, decisions, validation outcomes, and build-ready specs.
Evidence ledger
Claims, experiments, and validation outcomes move the score. Stale evidence gets sent back to research.
Decision log
Open assumptions and council disagreements become inspectable memory for the next run.
Watchtower
Monitor competitor pricing and positioning changes, then score the ones that affect your assumptions.
Build queue
A council verdict compiles into requirements, tasks, GitHub issues, and visible status.
Local-first by design.
Runs are stored on your own disk as JSON and Markdown. IdeaClyst does not handle API keys: OpenAI and Anthropic authenticate through their own local sessions.