AI has a way of making work feel faster before it has made the work better.
That is the productivity trap hiding inside a lot of the current enthusiasm. The response arrives quickly. The draft appears. The code compiles. The meeting summary looks plausible enough to send. It feels like time has been saved because the empty page disappeared.
Then the review starts.
The prompt needed more context. The answer missed the constraint. The code handled the happy path and forgot the production path. The summary compressed away the thing that mattered. The time did not vanish. It moved into framing, inspection, correction, and judgment.
That does not make the tools useless. It makes them tools. High-quality prompting is work. Reviewing output is work. Teaching junior people how to reason when the machine can skip the beginner tasks is work. Ignoring environmental cost, data risk, and human development because the demo was fast is how the industry repeats old mistakes with a newer interface.
The useful question is not whether AI is impressive. It is where the speed holds after the full cost of use is counted.
Some of the time, it will. Some of the time, we are just typing less and thinking later.
Related episode: I, For One, Welcome Our Robot Overlords: Navigating AI Hype.
