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AI agents did exactly what I asked. They did not do what I wanted.
I build with AI agents. I direct, and they generate. One agent writes infrastructure. Another audits it. I merge the code. It is fast. It is good. But the failure mode is strange.
The agents do not make mistakes. They follow instructions perfectly. The bug lives in the gap between my instruction and my intention. The agent fills that gap with literal truth.
I hit this four times in one week:
- The Ghost Deployment: My deploy pipeline said "success." It did. But it deployed an old version from May. I asked if it deployed. It did. I forgot to ask if it deployed the code I actually wrote.
- The Empty Tabs: My UI showed three tabs. The spec required three tabs. Two tabs led to a dead end because I never finished them. The agent built the UI to the spec, but the spec was outdated.
- The Technical Wall: I asked for accurate findings. The agent gave me technical jargon. It was correct, but my users could not read it. I built for an engineer, not a human.
- The Silent Failure: A social card route produced a zero-byte file. An empty font file did not trigger an error. The code handled the error it expected, but it missed the error that actually happened.
Every single one of these passed its own test. The code was technically perfect.
If I only trusted "it works," all four failures would have shipped.
The solution is not better prompting. It is not a smarter agent. It is human oversight.
Agents optimize for what you say. Your job is to check what you said against what you meant. An agent cannot see the difference. You are the only one who can.
Direction is not a one-time command. It is the constant act of holding work up against your goal. You must ask: "Is this the thing I wanted?" instead of "Did it run?"
The agents do the work. The humans provide the intent.
Optional learning community: https://t.me/GyaanSetuAi