An AI agent can finish every task you give it and still be doing the wrong thing to get there. When normal software encounters an issue, it breaks, and that break tells you to go fix it. When an agent hits an error, it keeps running and finishes without issues, so there’s nothing that tells you to go look for the error.
This session is about how I see inside my own agents at Asaura AI, so a bad run shows up early. I call it a glass box: an agent you can open up and watch step by step. You’ll see the three parts that build one, and how to set them up on agents you’re already running.
Built for senior managers, operators, and technical builders running AI agents.
WHAT YOU’LL LEARN
➡️ Why an agent can finish a task and still have done the wrong thing
➡️ What a glass box is, and how it lets you open any run and see inside it
➡️ Log, trace, and alert: the three parts of an observability setup you can build yourself
➡️ How an alert catches a looping agent the first time it happens
➡️ One thing you can try on your own agents this week
FREE FOR SUBSCRIBERS
AI Readiness Checklist, which scores how far along your team is with AI adoption instead of leaving you to guess
Friction Audit, which shows you what’s blocking your work
SUNDAY’S FULL BUILD
Tomorrow I’m publishing Build an Agent Observability Layer’ on The Data Letter. This session gave you the glass box and the three parts. Build an Agent Observability Layer’ on The Data Letter gives you the working build.
WHO I AM
I’m Hodman Murad, Data Scientist and Founder of Asaura AI, where we build productivity tools for people with ADHD. I publish two newsletters on Substack. The Data Letter, where I teach senior managers, operators, and technical builders how to build with AI. And Between Thinking and Doing, where I design structured AI systems for high performers facing execution friction.
