Thriving 
PY Spend tokens on judgment, not typing. An MCP-native autonomous SDLC pipeline: frontier models plan and review, local models implement — engineering discipline on a $20/month budget.
https://github.com/motock/fagan/blob/master/docs/DEMO.md ↗// readme
Spend tokens on judgment, not typing.
A real story (STE-1, PR #986) crossing the board: implemented by an open-weight model, sent back once by review, merged. 14 minutes, time-lapsed.
Try it (macOS; Linux via Ollama or LM Studio), then see the Quickstart:
curl -fsSL https://raw.githubusercontent.com/motock/fagan/master/scripts/remote-install.sh | bash
Frontier models cost money per token and are excellent at judgment. Local models run free and are adequate at typing. This pipeline splits software engineering along exactly that line: a frontier model decomposes the work, plans it, reviews the diff, and adjudicates anything risky — while a local model writes the implementation at no marginal cost.
What makes the cheap half trustworthy is inspection. In Michael Fagan’s 1976 IBM study, formal inspection found 82% of the defects in the released product — 38 per KLOC, against 8 per KLOC for unit testing. Quality lives in the gate, not in the author. So this…