AI agent demos often look clean and linear. Input goes in, intelligence comes out. Anyone who has built a real agent knows that the reality is much messier.
There’s a whole layer of preprocessing that rarely gets documented.
Before an agent can reason, files need to be cleaned, converted, and sometimes reconstructed. Text extracted from PDFs may lose structure. Images may need resizing or re-encoding just to be usable. These steps aren’t intellectually exciting, so they tend to disappear from blog posts.
In my own projects, preprocessing usually takes longer than I expect. Not because it’s complex, but because edge cases pile up quickly. One unexpected format is enough to derail an automated flow.
I’ve stopped trying to be clever here. Instead, I focus on making preprocessing predictable, even if that means using small, boring utilities to get files into a known state before handing them off.
Conversations around autonomous systems are starting to acknowledge this hidden layer more openly. Sites like https://moltbook-ai.com/
collect perspectives that focus less on hype and more on how these systems actually operate.
Agents don’t fail because they can’t think. They fail because the input wasn’t ready.
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