I'm building the trust layer for autonomous AI — so teams can let agents take real actions without giving up control or visibility.
AI is shifting from software that answers questions to software that acts: running code, sending email, moving money, calling APIs. As that happens, the limiting factor won't be capability — it will be trust. I work on that problem, in the open.
Aegize — infrastructure for autonomous AI agents
The runtime layer between an agent and the tools it uses. Every action gets an identity, is checked against policy, gated for approval when it matters, and recorded — before it reaches the outside world.
- ✅ Identity for every agent
- ✅ Declarative, default-deny policy
- ✅ Human-in-the-loop approvals
- ✅ Append-only audit
- ✅ Vendor-neutral and open source
Every meaningful AI action should pass through trusted runtime infrastructure before reaching the outside world.
Security is one outcome of getting this right; operability, reviewability, and confidence in deployment are the rest.
Autonomous AI systems · runtime governance · developer platforms · distributed systems · open source