I realized why 95% of AI agents fail after building a few

Past 6 months I’ve worked with 4 different teams rolling out Ai agents. And you know the deciding factor wasn’t the model, the framework, or even the prompts, it was grounding.

Ai agents sound brilliant when you demo them in isolation. but in the real world, even the smart-sounding ones fail miserably. that's because Customers don’t want creativity, they want consistency. And that’s where grounding makes or breaks an agent.

What I found was simple, feedback loops only worked when we stepped in manually, reflection slowed things down, code agents broke once tasks got messy, RLAIF collapsed outside demos, skill acquisition was hype, drift was unavoidable, and QA, unglamorous but relentless, was the only real driver of reliability.

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