Why this is worth a day
Right now your AI coding rules live in scattered CLAUDE.md files, per-IDE settings, wikis, and personal prompts. They drift, nobody reviews them, and no one can tell you whether agents actually follow them. That shows up as inconsistent code review, wasted tokens, and governance risk nobody owns. Writing more rule files doesn't fix it - the missing piece is the operating model around them: versioning, validation, rollout, and measurement.
Not just opinion: models don't use long context uniformly - accuracy drops as input grows, well before the window is full, so much of a bloated context is paid-for noise (Context Rot, Chroma 2025). Managing that context has become a formally defined discipline - a 2025 survey maps1,400+ papers.
First design-partner pilot · 12 engineers · 5 repos · 2 weeks. Your own pilot fills in your numbers - the workshop shows you how to measure them.
What your team actually brings back
This is not a lecture with slides. It is a build day. Whoever you send leaves with four concrete things:
The full context supply chain, yours to keep
A working kit for governing agent standards: ownership, validation, rollout, recovery, and measurement. Works out of the box.
Trained owners who can run it
Whoever you send operates the kit hands-on - extends it, breaks it, fixes it, ships and rolls back a release - so they can set it up on your stack afterwards.
A two-week pilot path with real metrics
A baseline-first measurement plan: repo selection, adoption evidence, and a leadership report from your own data - not invented figures.
Architecture that outlives our code
Transferable patterns - domain scoping, skill routing, freshness without version bumps - that apply to any agent setup you own.
The shift, in plain terms
A build day, not slideware
across 8 modules
Who's teaching it
Who it's for - pick your path
Enterprise-grade mechanics, useful at every scale. Every layer of the context supply chain kit is an independent, dependency-free script - start where you are and add layers as you grow.
The owners of your standards
Start with the small group that owns your team's AI standards - your rules, packaged and kept current for the agents you use. Run the lightweight slice first, then add rollout, access policy, and measurement as you grow - without ever migrating to a different system.
The rollout team
Adoption sticks when the future co-owners train together: the people behind standards, tooling, and governance leave with one shared operating model - not three interpretations of it.
- Staff / principal engineer - owns the standards
- Platform / DevEx engineer - owns rollout and installs
- Engineering manager / security - owns governance and sign-off
Train everyone, not just the owners
A handful of people own the platform - but knowing how agents use context is fast becoming core engineering fluency, and every developer who gets it ships better with AI. A private workshop trains your owners and builders together and includes a 2-week implementation pilot to prove the rollout in your repos.
Recommended next step
Book the planning call and pick the scope that fits - the core owners, the team who'll run the rollout, or your whole engineering org. Whichever you choose, ask for the same deliverable: evidence from your own repos- not enthusiasm. If it holds up, you'll have the evidence - plus the kit and know-how - to roll it out for real.