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Moving from Claude Code to Codex to Cursor without rewriting your skills or MCP servers is roughly 90% solved by standards and a bit of generation. The one hard part, converting MCP to Codex TOML with secrets, rulesync does not cover. I read its source to be sure.

Your CLAUDE.md past 200 lines? Two independent Dev With AI talks (Allainmat, Gallet & Dahan) found the same pattern: more rules make Claude less precise, not more.

Your AI instruction system is an asset. Locking it to one runtime is a liability. Native primitives, cc-bridge routing, one command to prove portability.

Personal CLAUDE.md to team AI instruction system for six engineers. How Méthode Aristote separates sources, shares modules, and catches behavioral drift in CI.

Context engineer is hiring. Four adjacent roles that didn't exist three years ago: harness engineer, spec engineer, agent identity architect, AI eval engineer.

Confusing RTK, lean-ctx, and prompt caching? They're four layers, not competitors. The map, three deep dives, and where your real Claude spend hides.

A good CLAUDE.md on day one is easy. Keeping it accurate three months later is the hard part. Maturity model L0 to L5 with a drift-detection loop.

Same model, same stack, opposite outcomes: +67% vs -19%. The variable isn't the AI. It's context engineering, and Princeton research explains exactly why.

6 contributors in our git history. One is an AI. What the commit patterns actually look like after months of Claude Code, beyond the marketing claims.

The concepts I wish I'd known before week one. 8 tools, 200K tokens, hooks as the only deterministic layer, and why config eventually takes 30-50% of your time.

I've sent the same Slack message more than 20 times. Here's that message, with the context that makes it useful.

506 commits. 407 files. 8.6% of all repo activity. How AI config evolved from afterthought to infrastructure over 9 months on a real production codebase.

Everyone talks about shipping 10x faster with AI. Nobody talks about accumulating debt 10x faster. 7 months of production data from a real EdTech platform.

A non-developer modified 80 files in production in 10 days with Cursor AI. Exact timeline, AI config setup, and what it means for engineering teams in 2026.

Jeremy Twei coined it. Addy Osmani popularized it. Margaret-Anne Storey extended it to teams. Here's what I built to fight all three.

12 years scaling teams from 4 to 30+, then I quit the VP title. AI lets a solo builder match what small teams ship. Here's exactly what changed.