A personal AI factory is built around a closed-loop workflow: planning, execution, and verification by specialized AI agents.
The guiding principle is to fix inputs—plans and prompts—instead of hand-patching generated outputs.
Multiple AI models (o3 for planning, sonnet 3.7/4 for execution, Goose for hosting) work together to generate, verify, and improve code.
Git worktrees enable running concurrent Claude Code instances for parallel feature development and manual merging.
Specialized agents enforce coding standards and workflows, such as style rules or library usage, by baking rules into plans.
Running many parallel iterations and feeding failures back into input templates drives self-improvement of the factory.
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