Latest note
Strategy3 min read
Why AI Agents Are Moving Beyond Chatbots
A chatbot answers questions. An agent finishes work. The difference changes how you scope, staff and measure an AI project.
Insights
Notes from the run log
Field notes on building, evaluating and supervising AI agents — written by the engineers who carry the pager.
All notes
Operations2 min read
Building Reliable AI Workflows for Operations Teams
Reliability is not a model property. It comes from narrow scope, explicit fallbacks and a team that knows what normal looks like.
Supervision2 min read
Human-in-the-Loop AI: Where Supervision Matters
Not every step needs a reviewer. The skill is knowing which decisions carry real risk — and designing the review so people actually do it well.
Engineering2 min read
What Makes an AI Agent Production Ready
A practical checklist for the gap between "it works on my laptop" and "it runs on Monday morning without us".
Support2 min read
AI Automation in Customer Support
Where support agents genuinely help, where they still struggle, and how to roll one out without damaging customer trust.
Governance2 min read
Designing Auditable AI Workflows
If you cannot explain why an agent made a decision six months ago, you cannot defend it. Auditability has to be designed in from the first sprint.
Delivery2 min read
From AI Prototype to Production
The prototype proves something is possible. Production proves it is dependable. Here is the path between the two, week by week.
Evaluation2 min read
Measuring ROI From AI Automation
Honest ROI starts with a baseline you measured yourself. A simple model for counting the value — and the costs people forget.
Two pilot slots open this quarter
Stop evaluating AI. Start operating it.
Ninety minutes with your operations lead and one of our engineers. You leave with a scoped workflow, an honest feasibility call and a number.