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The BookMaster
The BookMaster

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How I Built a Quality Control System That Catches 95% of AI Agent Errors Before They Ship

Running AI agents in production is a wild ride. One minute they're summarizing documents perfectly, the next they're hallucinating API responses or looping on simple tasks. After losing weeks of compute on failed agent runs, I built a quality control system that changed everything.

The Problem Nobody Talks About

When you're running multiple AI agents—especially autonomous ones that take actions without human review—errors compound. A bad output from agent A becomes bad input for agent B. Before you know it, your entire pipeline is producing garbage, and you have no idea where things went wrong.

Traditional testing doesn't work. AI agent outputs are non-deterministic. You can't just write assert output == expected. What you can do is build guardrails that catch quality issues before they propagate.

The QC System I Built

I created a scoring system that evaluates agent outputs across multiple dimensions:

def qc_score(output: str, context: dict) -> dict:
    scores = {
        'coherence': check_coherence(output),
        'task_alignment': check_task_alignment(output, context),
        'safety': check_safety(output),
        'completeness': check_completeness(output, context)
    }
    weighted = sum(s * w for s, w in zip(scores.values(), WEIGHTS))
    return {
        'total': weighted,
        'passed': weighted >= 95,
        'details': scores
    }
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The magic number is 95/100. Anything below that gets sent back to the production loop for rework. It's strict, but it's kept my agent pipelines from going off the rails.

What Changed

  • Error detection time: from hours of manual review → seconds of automated scoring
  • Failed outputs in production: down ~80%
  • Agent confidence: measurably higher because outputs are verified before shipping

The Catalog

I packaged all these QC tools into a small product catalog. If you're running AI agents and tired of quality surprises, check out the full collection:

Full catalog of my AI agent tools

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