Runtime State, Progress, and Termination

Sat, 08 Aug 2026 16:56:00 +0100

A plan is a claim about the future. It says that reproducing the failure, then diagnosing it, then patching, then testing, is a route from here to a working system. Making that claim explicit was worth the machinery. But it is written before any of the work happens, and execution may invalidate one of its assumptions almost immediately.

Execution produces something else entirely: a trajectory. Actions went out, observations came back, and some of what came back may contradict the intended route. The patch step failed because a dependency is missing. The test step is not merely late; it is unreachable.

Agents From First Principles 05: AI Agent Gets Stuck in a Loop? Add State, Feedback and Stopping Conditions

Sat, 08 Aug 2026 16:56:00 +0100

An AI agent that keeps calling the same tool, revisiting the same page, rewriting the same file, or repeatedly saying “I’ll try again” is not displaying persistence.

It is displaying a control-flow bug.

This is one of the most common failure modes in agent software because the basic loop is deceptively simple:

observe
 ↓
decide
 ↓
act
 ↓
observe
 ↓
repeat

The problem is hidden inside the final word.

Tool Loops on AIBussin — AI applications, systems and books

Runtime State, Progress, and Termination

Agents From First Principles 05: AI Agent Gets Stuck in a Loop? Add State, Feedback and Stopping Conditions