AI enablement for product and engineering teams
Your team has AI coding tools. We help them actually use them: shared setup in your repos, real work done together, and a handover so it keeps going without us.
Sound familiar?
A few engineers use agents every day. Most tried once, got something that looked right and wasn’t, and went back to how they worked before. Leadership sees the invoice but not the change. The tools work; the team just hasn’t been set up to use them.
What we set up
| What | Why it matters |
|---|---|
| Shared rules for your agents | Every session starts from your conventions, not a guess |
| Skills for repeat work | Common tasks done the same way every time |
| Checks on every pull request | Agent-written code is tested before it merges |
| Work on your real backlog | People learn on work that ships |
| A handover | Your team keeps it going without us |
How it runs
| Step | What happens |
|---|---|
| Look | How your team works today, and where agents help or get in the way |
| Set up | Rules, skills and checks land in your repos as pull requests you review |
| Pair | We work real tickets alongside your team |
| Hand over | Written conventions, and a team that adds its own |
We work this way ourselves
We build with AI coding agents every day. When we hand a product area to a client’s engineers, it comes with a skill file their agents load first, and a decision log so settled questions stay settled. Here’s how we write that handoff, and a skill we publish for anyone to use.
Questions
What is AI enablement for a product team?
It's getting designers, product managers and engineers to use AI agents in their everyday work, with the setup and checks that make the output something you can trust. That means shared rules the agents follow, repeatable skills for common tasks, tests that catch a bad change before it merges, and time spent working alongside your team on real tickets. It happens in your repos, on your real work, not in a slide deck or a one-off training day.
Which tools do you work with?
Whatever your team already has, and plenty it doesn’t yet. Claude Code is our daily driver, but we work across the frontier model providers, including Anthropic, OpenAI and Google, and the agents built on them, like Codex and Cursor. Around the models we set up workflow automation, sandboxes where agents can run safely, design tools like Figma, and test tooling like Playwright. We’ve done this in a lot of different setups, so an unusual stack or a mix of tools across teams isn’t a blocker. We pick what fits your environment instead of asking you to switch.
Why isn't my team using the AI tools we already pay for?
Usually for ordinary reasons. The agent doesn't know how your team works, so its first attempts miss your conventions. One bad result in front of the team costs it everyone's trust. And learning a new way of working loses to the sprint every time. Each of those has a fix: give the agents your context, put checks in place so mistakes get caught early, and make room to learn on real work. None of them is buying more seats.
Is it only for engineers?
No. Engineers usually see the biggest change first, but designers use agents to turn ideas into working prototypes, and product managers use them to write specs, sort feedback and answer questions about the codebase without waiting on an engineer. We set things up so the whole product team works from the same context, which is where a lot of the time savings come from.
How do we know it's working?
We agree on what to look at before we start, using measures your team already cares about, such as how long work takes from ticket to release, how much of it is done with agents, and how often agent-written changes need rework. Then we review them together as we go. Just as important is whether people keep using the setup when nobody's watching, so we check that too before we hand over.
What happens when the engagement ends?
Your team keeps everything. The rules, skills and checks live in your repos as files you reviewed and merged, so nothing depends on us or on a tool we control. We write down the conventions, make sure a few people on your team know how to change them, and stay reachable if you want a check-in later.
Half an hour, no proposal. Tell us where your team is with AI today and we’ll tell you honestly whether we can help.