Research
How to build with AI agents — and trust the result.
We study what makes agent-assisted engineering reliable and secure, and turn the answers into open tools and standards anyone can use.
Research areas
Reliable agent engineering
Orchestration, decomposition and guardrails that keep AI agents on-task through long, multi-step work — without stopping early or drifting from the spec.
Security of AI-assisted delivery
How agent-written code fails, how to catch it, and how to make secure-by-design the default: IAM, AppSec and authorized red-teaming of what agents produce.
Standards & evaluation
What 'good' means for agent output, and how to measure it: normative playbooks, quality gates and tests that prove behavior instead of vibes.
Developer experience
Making the right way the easy way — tooling that installs standards, keeps them current, and gets out of the developer's way.
Our approach
In the open
Findings and tools are published, not hoarded. Reproducibility is the point.
Grounded in practice
We research by building and shipping — the lab and the products feed each other.
Security-first
If it isn't safe to run, it isn't done. Threat modeling and testing are part of the method.