Build Reliable AI Agents.

“Fix agents that demo well and break on real work.”

In this order

The loop, the guardrails, and the verification layer that make an agent reliable outside a demo

Start here. You build the harness yourself, so you know why it holds.

A golden set, a calibrated judge, and a CI gate that blocks a bad prompt change before a user sees it

Then stop a prompt change from silently breaking what worked.

11 tools that kill context rot, a handoff packet a dead session passes on, and a token bill with a measured before and after

Fix the sixth hour being worse than the first.

A bounded, self-correcting Claude Code loop that ships trusted code overnight without burning $200

Bound the loop before an overnight run costs you $200.

A fleet of loops that runs overnight, verifies its own work before it reaches your branch, and prints the bill

The first loop that finishes without you watching it.

A threat model, scoped credentials, a sandbox, and a hardening runbook for every agent you ship

Lock it down before one of them gets owned.

A trace logger, an eval harness, and a router that proves a cheaper model keeps up on your own work

Last: prove a cheaper model keeps up, then route the work to it.