Writing on production AI.
We write about the work of putting AI into production and keeping it there: agents, retrieval, document automation, integration and MCP, evals, security, and cost control. Every piece is anchored in real implementation detail, and every load-bearing claim carries its source.
Why your AI pilot did not reach production
Your AI pilot did not reach production because it was built to prove a model works, not to survive an operation.
document automation
Does the human review gate eat the savings?
A review gate pays for itself when the time saved on the items that pass exceeds the time spent on the items that stop.
cost control
What we check before an AI agent touches a real system
Before an agent we build gets access to a real system, it passes a fixed preflight: bounded scope, a human approval gate, an eval set it must clear, a kill switch, an audit trail, a cost ceiling, and a tested rollback path.
agents