This isn’t just retreading familiar ground (that AI still needs experienced engineers to impose that discipline). It’s something different. After all, faster implementation doesn’t automatically create extra human capacity. Yes, it can change the work people attempt, the decisions they must make, and the expectations attached to their jobs. But a team can deliver more and still find the work more demanding. Both can be true.
Companies should be careful about budgeting as though AI has already given them both a larger road map and a smaller need for engineering expertise. It’s by no means clear that faster coding is an unalloyed good.
Faster isn’t the same as easier
In the replies, one reader, Hillel, put it neatly: “It doesn’t get easier, you just get faster.” Geoffrey Huntley concurs, describing the work as “incredibly taxing” even for experienced operators. He reported roughly 16-hour days over the preceding 12 days, explicitly noting that this was his choice, not a requirement at work. That qualification matters because these comments aren’t representative measurements of developer productivity, nor are they evidence that agents inevitably exhaust everyone. They’re simply observations from people using the tools enthusiastically. The enthusiasm is part of the story. As more becomes possible, people attempt more.
