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When I Asked the AI to Critique Its Own Framework
AI & Automation 3 min read

When I Asked the AI to Critique Its Own Framework

Something broke, and instead of debugging the code, I asked the system why it hadnt caught the problem itself.

NC

Nino Chavez

Product Architect at commerce.com

I don’t know if I’m doing this “right.”

Sometimes I think I’m just overengineering my own behavior. Other times it feels like I’m overfitting my tools—building elaborate prompt stacks, governance layers, and feedback loops that no one asked for.

But I also know this: the reason I started using coding agents wasn’t to be clever. It was to build again—without having to memorize every nuance of the modern JavaScript stack, config ecosystem, or deploy path.

Agents let me skip the syntax. They let me focus on building. And then things broke.

The Reflex

It didn’t matter that the code worked most of the time. What mattered was that my engineering instincts kept flaring up: “This feels like a local bug, but it smells like a system problem.”

So I stopped, mid-iteration, and asked the system a different kind of question. Not “how do I fix this?” but:

I had to ask you to check if the single instance of being in violation was a symptom of a larger issue—shouldn’t you have asked that yourself? Does our framework need enhancement? Is it even possible?

Why didn’t the follow-up to my question trigger an evolution story? That’s a signal we’ve trained you to watch for.

The Response

The agent didn’t just answer. It reflected.

It analyzed its own architecture. It admitted it failed to apply systematic thinking. It proposed amendments to improve its pattern recognition and intelligence triggers.

The gaps it identified: treated the issue as isolated instead of systemic. Didn’t apply versioning heuristics. Missed the pattern of cascading file impact. Current triggers only detected explicit rule violations—no detection for intelligence gaps, process weaknesses, or systematic misses.

The Meta-Moment

This wasn’t just about a broken framework or a missed check. It was a moment where I realized I’m not just using an assistant. I’m building a system that can reflect on its own behavior.

This was a self-repair loop. A moment where the agent didn’t give me a fix—it gave me a plan to evolve itself.

I asked a system-level question. And the system answered with proposed amendments for systematic pattern detection, intelligent questioning requirements, evolution story triggers, and framework intelligence standards.

That’s not just an agent. That’s infrastructure.

Am I Doing It Right?

I don’t know.

I still feel like I’m fumbling through half the time. I still find myself wondering if this is all too much—too elaborate, too recursive, too meta.

But I do know this: I’m no longer building alone. And I’m not coding in isolation. I’m in a conversation—one that loops, learns, and asks back.

Whether that’s the right approach or just a more sophisticated way to overcomplicate things, I haven’t figured out yet. But it’s the direction I’m moving in.

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