blog · field notes
Blog
Field notes from building audit infrastructure for AI agents.
Perspective
Observability is not accountability
You already have traces, dashboards, and token counts. Would you hand them to a regulator? Observability answers your questions about your system; accountability answers other people's — and they don't trust you.
·4 min read
Perspective
Why we built on Microsoft AGT instead of our own chain
We had our own signing and hash-chain code in production. When Microsoft open-sourced the Agent Governance Toolkit, we retired ours and rebuilt on the standard. Easiest decision we've made — here's why.
·4 min read
Perspective
You hold the keys
What happens to your data the day your vendor gets breached? Our answer: an attacker would find tokens they cannot reverse and signatures they cannot forge — because the keys that matter were never ours to lose.
·5 min read
Quickstart
Instrumenting a LangChain agent in 5 minutes
Wire the wrapper in once, add one callback, and every tool call your LangChain agent makes lands on the tape — signed, sealed, verifiable. The current five minutes, replacing the retired v1 guide.
·4 min read
Deep dive
How Wytness works
A walk through the full path of one event: from the moment your agent emits it, through signing and buffered ingest, into the verification, hash-chain, and dual-store archive that an auditor pulls back out years later.
·7 min read
Perspective
The blackbox recorder for AI agents
Planes don't carry a flight recorder because crashes are common. They carry one because when something goes wrong, “trust us” is not an acceptable answer. AI agents have reached the same moment.
·3 min read
Perspective
Why AI agents need an audit trail
If a customer support agent issues a refund at 3am, who authorised it? AI agents are taking real actions on real systems, and they need the same audit story human operators have always had.
·3 min read