Genesis: Multi-File AI Code Orchestrator
A local-first orchestration pipeline that coordinates AI-authored code generation across modular codebases with deterministic validation and operator-gated.
AI Orchestrator
DIAGNOSTICS
Generating a large multi-file codebase with an AI assistant means babysitting it one file at a time — copying output, fixing broken imports, catching silent corruption. A single ERP-scale project is hundreds of files. Doing that by hand isn't a workflow; it's a bottleneck. The real problem wasn't writing code, it was orchestrating its generation reliably enough to trust.
A local-first orchestration pipeline: a Node.js bridge server paired with a Chrome extension that coordinates AI-authored code generation across an entire project. It runs a genesis-manifest → sequential file-author pipeline with strict output contracts, AST-level validation before staging, deterministic auto-fixes for known corruption patterns, and a build-verification gate (install, schema generate, typecheck, lint) after every module. The AI writes; the factory verifies.
Manual friction, automated away.
Each row contrasts the manual bottleneck against the optimized pipeline — the real efficiency gain, not a generic claim.
Errors shipped to disk, surfaced later as failed builds
3 caught pre-commit on the first module via automated verification
Core capabilities.
The specific features that make the difference — built in, not bolted on.
Manifest-Driven Generation
Decomposes a project into a sequential file-author pipeline, each file generated against an explicit output contract.
Deterministic Validation
AST-level parsing catches syntax corruption and invalid schemas before any file is written to disk.
Build-Verification Gate
Every module must pass install, schema-generate, typecheck, and lint before it counts as done.
Self-Healing Auto-Fix
Known corruption patterns are detected and repaired locally by the server — no round-trip to the model.
Modules shipped
Languages
Architecture