Most 'AI Agents' Are Just If-Statements in a Trench Coat

Description and use

Autonomous agents with reasoning loops often become slow, expensive, and nondeterministic. Converting them into a linear pipeline with fixed control flow improves speed, reduces cost, and simplifies debugging.

Problem

AI agents built with autonomous reasoning loops often become slow, expensive, and nondeterministic, making them hard to debug and test in production.

Outcome

A deterministic pipeline outperformed the autonomous agent on all key metrics: faster execution, lower cost, easier debugging, and reliable regression testing.

Workflow

• 1. Extract context
• 2. Call relevant tool
• 3. Format response
• 4. Return output

Evidence

If you can draw the flowchart of what your system does before it runs, you don't have an agent. You have a pipeline.

Source

A reasoning loop makes many more model calls than a fixed sequence — it thinks, it re-thinks, it reflects, it decides to loop again.

Source