GitHub - APareek89/power-coding: Mindful-coding OS for any LLM coding agent (Claude Code, Codex, Gemini CLI) — the Five Forces: session handoff, eval loops, vibe-debugging diagrams, FMEA failure scans + a pre-commit secret gate. Plain markdown, no daemons. · GitHub
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Power Coding — The Five Forces of Mindful Coding
A structured framework for building scalable apps with AI coding agents, by Anand Pareek.
Five forces quietly kill every AI-assisted project. Each one has a proven counter-discipline — borrowed from aerospace, the Toyota Production System, and modern eval-driven ML practice, and translated for LLM agents. Power Coding installs all five as one system, in plain markdown files your agent re-reads every session. Works with any agent (Claude Code, Codex, Gemini CLI…) — no daemons, no hooks, no lock-in.
The Five Forces
Force (what kills projects)<br>Counter-force<br>What gets installed
Ambiguity — the agent confidently builds the wrong thing<br>Alignment<br>A one-page brief (PRD.md) every eval and scan reads · plain-language architecture sign-off before code is built against it (and before every shape-changing enhancement) · a decision log that's never silently reversed · a scope brake (smallest version that proves it works, first)
Amnesia — every session starts from zero<br>Memory<br>Handoff.MD — one magic phrase chains sessions ("Refer to Handoff.MD in and begin"), auto-updated before context runs out · Learning.MD — every bug gets a 5-whys root-cause entry so no mistake is made twice · git checkpoints at every working state and before every risky change — rollback beats a debugging spiral
Drift — "done" is declared without proof<br>The Loop<br>Loop.MD free evals drafted from your brief, run for real after every change with per-eval ✅/❌ · a golden set for agentic apps (curated inputs + reference outputs + check method, drafted from the brief) that runs only with your approval — paid API calls are never spent automatically · a status machine that offers to turn the loop on the moment the first draft works · evals that pass 3 runs in a row graduate into real automated tests
Opacity — you can't see what was built, or where the effort went<br>Sight<br>Mermaid flow diagrams to a strict debuggable convention (one step per box, AGENT vs FUNCTION, gates with real thresholds) + a standalone HTML viewer + optional local-only in-app debug tab — debug by pointing at a box instead of reading code · Session Pulse : a 2-line effort split (🎯 feature · 🔧 support · 🔁 rework) after major milestones
Entropy — silent failures accumulate until production finds them<br>Foresight<br>FMEA scans cross-referencing your diff against the PRD and architecture (Severity×Occurrence×Detection → RPN → P0/P1/P2, mandatory 12-category walkthrough) · Sentinel Scan : a silent four-lens sweep after every major completion (misuse traps, stop signals, silent failures, waste) — one-line flags only when something fires · a day-one security baseline (no committed secrets, server-side enforcement, validated inputs)
The lineage
None of this is invented from scratch — each counter-force is a reliability discipline with decades of production behind it, applied to LLM coding:
FMEA — aerospace/automotive failure-mode analysis
5-whys, Poka-Yoke, Andon, Jidoka, Muda — the Toyota Production System (they power Learning.MD and Sentinel's four lenses)
OEE from Total Productive Maintenance — the insight behind Session Pulse: your bottleneck is almost never what you think it is
The Loop — Andrew Ng's agentic-workflow argument: output quality comes from the build→check→revise loop more than from the model
The consent model
Every behavior fits one of three tiers — so the...