For a Czech financial institution’s developer teams — measured before and after.
- Benchmark
- 15 golden tasks
- Quality
- 78.5% before, 95.2% after
Your developers learn agentic engineering on their own repositories: context files, skills, guard rails, memory and review discipline. A champion network keeps the practice alive after I leave.
Heads of engineering whose teams have AI seats but no shared practice, and organisations that need AI literacy under Article 4 of the EU AI Act.
Every developer productive with agents in your own stack, one shared kit of skills and guard rails installed per repository, named champions, and a before-and-after measurement.
1 day, up to 12 developers
We build a real change in your code with agents, end to end.
6 weeks
A few developers become the team's internal coaches.
Monthly
Reviews of how your team works with agents, and what to change.
What your team uses today and where it stalls.
I read your repositories and tooling before the first session.
Hands-on in your codebase, with a working result by the end of the day.
The same benchmark tasks before and after, so the gain is a number, not a feeling.
For a Czech financial institution’s developer teams — measured before and after.
A build kit for AI agents that survive a crash mid-task, stop at their budget and touch nothing without your approval.
One tunnel for your whole dev team: a tester circles a bug and writes one sentence, an agent fixes it and posts the after-shot.
Prices on request: tell me the scope and I will send a fixed quote.