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, whether legacy debt, reliability problems, or 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 posts
- Best Practices for Coding Agents Start With a Legible Codebase
How well a coding agent works usually isn't about the model, it's whether your codebase is legible to it: conventions, procedures, and discoverable automation.
- Sanitizers in Embedded C++ Belong in Your Host-Side Tests
AddressSanitizer, UBSan, and the rest are a host-side verification technique: they don't run on target hardware. Put them in your host unit-test and SIL builds to catch embedded C++ memory and undefined-behaviour bugs before they reach a device.
- Why Embedded Is a Better Place for AI Agents Than Web Development
Built the right way, embedded is a better fit for an AI coding agent than a typical web codebase. What an agent-ready feedback loop means, and how to get there.