The Problem With AI Agent Pipelines
Most agentic AI systems today are built the same way: chain a bunch of LLM calls together, pass mutable state between them, cross your fingers, and deploy. When something breaks — and it will — nobody can tell you which step failed or why.
This is the equivalent of writing a 2,000-line function with no tests and saying “it works on my machine.”
What Pure Functions Give You
A pure function has no side effects and returns the same output for the same input. When you build an AI agent pipeline as a chain of pure functions, something powerful happens:
- Each step is independently testable. You can unit test your email classifier without running the entire pipeline.
- Each step is independently replaceable. Swap Claude 3 for Claude 3.5 Sonnet and run your test suite — you’ll know immediately if anything regressed.
- Debugging becomes tractable. When a classification is wrong, you can isolate exactly which stage produced the bad output.
The Proof: 406 Tests on a Production AI System
Our bid automation system processes construction RFI emails through a pure function pipeline: raw email in, classified and extracted data out. When we upgraded from Claude 3 to Claude 3.5 Sonnet, the regression suite caught 3 classification edge cases that would have silently degraded accuracy in production.
That’s not theoretical. That’s 406 tests running in under 3 minutes, catching real regressions on a real production system.
The Discipline
Building AI agents with pure functions isn’t harder — it’s more disciplined. And discipline is the difference between a demo and a system that runs on Monday morning.
The pattern is simple:
- Define the interface. What goes in, what comes out.
- Write the test first. What does correct behavior look like?
- Implement the minimal function. Make the test pass.
- Chain the functions. Compose them into a pipeline.
- Regression test the chain. Catch drift before users do.
This is computer science, not prompt engineering. And it’s the future of building AI agents that survive production.