I help industrial SMEs and deep-tech hardware startups build robust embedded systems.
Fifteen years of safety-critical embedded work, focused now on the verification loop that lets AI coding agents build, test, and iterate on real embedded C++ — without a human in the middle of every cycle.
What this practice is
Two things, and they reinforce each other: deep safety-critical embedded experience, and the infrastructure that lets AI coding agents work on that kind of code without breaking it. If your embedded codebase has outgrown ad hoc development — legacy debt, reliability problems, a team that wants to move faster — that's the work I take on.
Safety-critical embedded
Fifteen years of C++ in systems where a defect that reaches the field is expensive to fix and hard to live with.
Agent-ready verification
Building the build-and-test feedback loop that makes AI coding agents genuinely usable on embedded codebases.
Measured by what ships
Audit and development engagements with acceptance criteria per milestone — progress you can see, not hours logged.
Latest post
- Why Embedded Is a Better Place for AI Agents Than Web Development
Once the surrounding infrastructure is built the right way, embedded is a better fit for an AI coding agent than a typical web codebase. What "agent-ready" means, and how to get there.