How to Build an AI Agent Harness from Scratch in TypeScript

By Gabor Koos • October 20, 2026 • #ai agents

Many AI agent tutorials start with a language model, give it a few tools, and run a loop until it produces an answer. That's enough to demonstrate tool calling, but it leaves the interesting engineering questions unanswered.

What happens when a tool fails? Who validates the arguments? What prevents an agent from running indefinitely, executing unsafe commands, or exhausting its context window? And how do you test any of this without relying on unpredictable model responses?

These are the responsibilities of the agent harness: the software layer between a language model and the environment it operates in.

In this tutorial, we'll build a small, provider-independent harness in TypeScript, using a coding agent as our example. We'll start with a basic execution loop and progressively add tool validation, workspace isolation, execution budgets, context management, observability, and deterministic failure testing.

2026 context: Agent harnesses have become a first-class concern as AI agents move from demos to production. Frameworks like the Model Context Protocol (MCP) and emerging agent standards now emphasize sandboxing, observability, and reproducible testing—the exact concerns this tutorial addresses.

What We'll Cover

• Prerequisites
• 1. Build the Basic Agent Loop
• Test Without a Real Model
• 2. Validate Tool Calls Before Executing Them
• A Registry with Explicit Contracts
• Not Every Error Means the Same Thing
• 3. Give the Agent Tools Without Giving It the Machine
• Confine File Operations to a Workspace

(Full article continues below with the remaining sections.)

via FreeCodeCamp