validation
● Track 01 · Trustworthy Agent Output
Trust agent-authored PRs without slowing review to a crawl.
If your agents ship faster than your team can verify, the speed-up isn’t real yet — it’s just deferred risk sitting in the review queue. This track closes that gap: agents that already know your codebase, and a validation layer that makes “known-good” the default state of anything a human looks at.
the work
The pain
The agents produce volume, but the PRs ignore your house standards, re-derive context they should already know, and arrive in a shape that makes review the new bottleneck. You’re either rubber-stamping work you haven’t really verified, or you’ve become the human gate that erases the speed-up.
It compounds quietly. Each PR that slips through half-reviewed lowers the bar for the next one, and the architecture drifts away from the patterns your team actually agreed on — until a refactor nobody signed off on is suddenly load-bearing.
What you get
Two halves of the same problem, scoped together. First, your agents made codebase-aware — a local indexing service that scans your multi-repo codebase and exposes it so an agent queries your patterns instead of re-reading them, and a context rollout that makes agents enforce your standards by default.
Second, the validation layer — AI-focused automated testing, CI/CD, and validation agents on your commits, so what reaches a human is already known-good. Review stops being the gate and goes back to being a judgment call on work that’s already passed the machine.
Other tracks: AI Telemetry & Governance · Agent Orchestration
questions
Questions buyers ask first
Do you train on our code or reuse it for other clients?
No. Your code and context stay yours. The codebase-aware tooling runs against your repos for your engagement only — nothing is used to train models or carried over to other clients.
Do you work remotely, or only around Baltimore?
Remote-friendly and worldwide. I am based in Baltimore, MD, but engagements run remotely against your repos and your workflow.
Do we own what you build?
Yes. The context rollout and the validation layer are configured into your repositories and CI, and you own that work product. Engagements contract through Wood Fired Games and the ownership terms are set in the SoW.
How long is a typical engagement?
It ranges from a focused rollout to an ongoing retainer reviewing your agent-authored architecture, up to a custom build. The exact depth is scoped on a 30-minute call.
Which of my problems does this actually solve?
It solves agent PRs that ignore your house standards and turn review into the bottleneck. Agents become codebase-aware so they query your patterns instead of re-deriving them, and a validation layer makes "known-good" the default state of anything a human looks at.
next steps
Sounds like your week?
One 30-minute call. We pin down how deep this goes — a focused rollout, a review retainer, or a custom build — and if budget needs shaping before a SoW, I’ll help you build the case. Engagements contract through Wood Fired Games.