Build an Enterprise Agent Harness from Scratch (10 Chapters)

It does not take much code to build an agent that can call tools. Give it a task, connect a few APIs, and let the model choose the next step in a loop. The demo can be running in an afternoon.

The real lesson begins when the demo ends. The agent says a refund is complete, but the payment system has no refund ID. An email request times out, and one retry may send two copies. By turn fifteen, the most important contract rule is buried in the history. The user authorized one order, but the test account can open the entire back office.

A longer prompt cannot solve all of these problems at once. I start with the smallest loop—choose the next step, call a tool, read the result. Each time we encounter a new failure, we add exactly the capability that failure requires. The system around the model that saves progress, controls actions, and verifies outcomes is the Agent Harness.

These ten chapters are a build-from-scratch course. By the end, you will be able to build an agent that remembers its progress, knows when to stop and ask a person, resumes after failure, and produces evidence when the work is complete. When you look at an existing framework, you will also be able to tell what it handles for you—and who still owns permissions, business rules, and the final result.

The material is current through November 8, 2026. Each chapter begins with a concrete task, moves from the smallest fix to an approach that can run inside an enterprise, and then shows which 2026 frameworks and products can take over part of the work. By the end of the series, these parts form one enterprise architecture. You will also be able to place existing tools into the same task and decide which combination fits your team.

1. What Breaks When You Hand-Build an Agent?
2. Why Does an Agent Declare Victory Too Soon?
3. Why Does an Agent Forget Mid-Task?
4. Why Do Tools Make an Agent More Dangerous?
5. Why Can’t You Simply Retry a Failed Agent?
6. What Permissions Should an Agent Actually Have?
7. Why Does an Agent Demo Well but Fail in Production?
8. Should You Add More Agents When One Is Not Enough?
9. What Does a Complete Enterprise Agent Look Like?
10. Which 2026 Frameworks and APIs Can Implement This Architecture?