Automation is easy to start and hard to trust. The hard part isn't getting an agent to act — it's getting it to act accountably: to know its limits, keep a record, and escalate to a human instead of guessing.
The design principles
Our agent infrastructure is built on a few non-negotiables:
- Tiered inference — the cheapest model that meets the task runs it; heavier reasoning is reserved for when it's actually needed
- Supervision — a watchdog tracks health and catches silent failures
- Persistent memory — agents remember, so they don't re-derive the same answer every time
- Explicit escalation — when an agent is unsure, it pauses and pings a human. It never fakes a result.
Why escalation is the whole game
The difference between automation you can leave running and automation you have to babysit is what it does when it's unsure. Systems that guess quietly are the ones that burn you. Systems that stop and ask are the ones you can build a business on.
This is the machinery under the rest of the stack — the part that lets the other systems run without someone watching every tick.