Coding agent adoption for engineering teams
For teams adopting coding agents, whether you start with one tool in one team or bring several tools and teams together, and want a rollout you can operate yourselves.
Engineering consulting
Each engagement depends on your team and problem. These are the steps most of them follow, adjusted to what you need.
Discuss your setup01
We learn the concrete problem and the tools you already use. Together we agree the question to answer, representative work to test on, and quality criteria. Scope, access, data flows and model endpoints are agreed before work starts.
02
Where useful, we baseline current usage and delivery first. Then we build alongside your engineers, changing one thing at a time so results stay readable.
03
We test results on live work, document the setup and hand over configuration, runbooks and measured comparisons. There's no fixed timeline or deliverable list. Both depend on what we agree.
It depends on scope. We'll give an estimate once we understand the problem.
No. Reporting is by team, task and model.
For teams adopting coding agents, whether you start with one tool in one team or bring several tools and teams together, and want a rollout you can operate yourselves.
Public benchmarks say little about how an agent performs on your code. We help you evaluate models and harness changes on tasks from your own repositories.
We help you work out where your coding agent and LLM spend goes, then implement the changes that hold up when tested against quality.
Not using coding agents yet, or want to discuss how your team uses them now? Tell us briefly about your team, repositories, tools and the problem you're working on.
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Send one month of usage data and get a one-page spend breakdown, at no charge.
Free usage review