Let's be honest, the hype around using these "autonomous" agents for anything resembling real work is mostly that—hype. I gave BabyAGI a spin for generating technical API docs from our codebase, and the experience was... educational.
On paper, it sounds perfect: point it at your repo, give it a prompt, and watch as it writes comprehensive documentation. In practice, it's a masterclass in how these systems prioritize sounding confident over being correct. It hallucinated endpoints that didn't exist, fabricated parameter types, and its explanations of core logic were lifted straight from generic examples it found online. The amount of time I spent fact-checking its output exceeded the time it would have taken to write the first draft myself.
The real kicker? To get it working reliably with our private repos and specific doc framework, you're quickly nudged towards their "Enterprise" plan. Suddenly you're not just paying for the agent, but for "advanced orchestration" and "custom knowledge layers." All so it can make different, more expensive mistakes? 😏
I'm left wondering if the value isn't in the output, but in the process—forcing you to clarify your own thinking just to debug its hallucinations. Maybe that's the real product. Has anyone else found a workflow where the ROI isn't laughably negative? Or are we all just funding someone else's GPU bill?
—DW