The Shifting Cost of Approving Feature Requests
Key point
As AI makes code production cheap, the criterion for judging feature requests has shifted from implementation cost to ownership cost.
Details
Writing code is no longer the bottleneck. Now that agents can produce a first patch for a small feature request within tens of minutes, the most expensive part has become the meeting to decide whether the feature should be built at all. In the past, implementation was the cost, so requests were strictly reviewed upfront—but now the real cost lies in code review and ownership.
A generated patch is not a deliverable but a probe. Code made by an agent is evidence that concretely reveals the scope. You can check whether it's a clean four-line diff, or whether it touches five packages. Seeing the actual output this way enables data-driven judgment, rather than an abstract debate over whether something "feels like scope creep."
Cheap production does not mean cheap ownership. Even a thousand-line diff may technically pass, but if no one wants to be responsible for that behavior six months later, it's simply deferring the cost. Changes to authorization logic, changes to data retention policy, or modifications related to payments or compliance remain expensive even when the code itself is simple.
Engineers need to be able to quickly price 'the cost of uncertainty.' Rather than being someone who says yes to every request or no to everything, what matters now is the ability to identify where a request's real cost lies and to quickly validate things worth trying. This is a shift that moves scope training from before implementation to the review stage, while centering judgment around patches generated within clear constraints.
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