The Data Letter

The Data Letter

Use Langfuse for AI Agent Observability and Catch Mistakes Early

Set up logging, tracing, and approval gates with Langfuse, so you can see every step your agent takes and stop it before it runs an action you didn’t approve.

Hodman | How To Build With AI's avatar
Hodman | How To Build With AI
Sep 20, 2026
∙ Paid

Last Sunday, I told you I’d show you how to see what your agents are doing while they run this week. Here it is.

By the end of this, you’ll be able to see every step your agent takes, with a rule that stops it before it does something you didn’t approve.

You want to follow an agent through every step, so you catch a mistake the first time it happens instead of after it has cost you. In yesterday’s live, I gave you the three parts that make it possible: log what the agent read and did, trace a single run from the request to the final action, and gate the actions you’d want to sign off on, so the agent pauses for you before it runs one.

Today we’ll build the agent and add all three parts.

We’re building it on a support agent that issues refunds through Stripe. This is the same observability layer I built for my own agents at Asaura AI. The setup works the same on any agent you run.

We’ll build the agent, add the three parts, and add a rule that pauses the agent before a step you’d want to check, so a person signs off before it goes through. On this agent, that step is a refund. On yours, it might be sending an email or changing a record.

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