Prevents premature AI coding by transforming vague product ideas into structured specifications, architecture decisions, and acceptance criteria through a series of interrogation and compilation tools.
Assists AI developers with intelligent requirement analysis and architecture design through guided clarification questions, branch-aware management, and automated architecture generation with persistent storage.
Turns product ideas into implementation-ready planning packages including PRD, requirements, user flow, wireframes, data schema, API contracts, and SDK boundaries, with an MCP handoff for coding agents.
The decision system for agentic engineering: keeps your project's decisions, rationale, and rejected paths in plain files and surfaces them to AI coding agents before they plan or change code.
Enables capturing and storing AI coding decisions as markdown, and provides MCP tools for assistants to query and record those decisions so they respect past architectural choices.
Enables users to clarify vague goals through Socratic questioning and generate structured technical specifications, using a curated knowledge base and session state without external LLM APIs.