Install the operating model for an AI-native engineering team.
A partner-led engagement that rewires how a team works with AI — tool stack, conventions, eval discipline, mentorship — and leaves the muscle behind.
AI-native is an operating model, not a tool purchase.
Every team has the same models now. License counts went up; throughput didn't. Adoption plateaus at ~30%the moment AI touches the parts of the workflow nobody rewired — review, ownership, what “done” means, how quality is measured.
“You can't buy your way to an AI-native team. You install the conventions, prove them with evals, and let the compounding do the rest.”
The bottleneck was never the model. It's the absence of conventions— a brief format, eval ownership, failure triage, cost attribution, and a clear picture of what a senior engineer's day looks like when 60% of first drafts come from agents.
Outcomes are pipeline-shaped.
The Advisory deliverable isn't a deck. It's a team that can stand up a ticket-to-PR or post-PR-heal pipeline themselves, in a quarter — and run it without us. The four pipelines Studio builds are also the outcomes Advisory aims at: we teach your engineers the shape; they come to own the mechanism.
Advisory teaches your team to stand these up. Studio builds them end-to-end — see the full mechanism on /studio →
Measurable, not vibes.
An operating model is only real if it answers questions with numbers. Before we touch a tool, we name the questions your team should be able to answer at any moment — then instrument them. If the scoreboard can't move, the engagement hasn't worked.
Four pillars of an AI-native team.
Every engagement moves the team along all four. Where you start depends on where the operating model is weakest.
Tool stack
The opinionated set of tools, the conventions for using them, and the guardrails that keep them from becoming shelfware.
Workflow conventions
How AI enters review, ownership, and "done." The unwritten rules made explicit, so the whole team works the same way.
Eval discipline
The measurement loop that tells you whether AI output is getting better or worse. Without it, you're shipping vibes.
Mentorship
The engineers who will own this after we're gone. We pair, we review, we hand over — the muscle stays in the building.
Audit
A read on the operating model: where adoption stalls, what's missing, what to fix first. Ends with a scoreboard baseline and a prioritized roadmap.
- Workflow & tooling review
- Eval maturity + scoreboard
- Prioritized roadmap
Sprint
One pillar installed end-to-end — tool stack, conventions, eval discipline, or mentorship — with your engineers, then handed over.
- One pillar, end-to-end
- Embedded, partner-led
- Handover to champions
Embedded Advisor
A standing partner at fractional-CTO register — quarterly evals, convention updates, and a direct line to the founder.
- Quarterly eval refresh
- Convention & tooling updates
- Direct founder access
The operating model is the product. Everything else is downstream.
“Adoption isn't a training problem. It's a conventions problem. Fix the conventions and the adoption follows.”
Tell us where adoption stalls.
The founder leads every Advisory engagement and replies within two business days.