Good Vibrations: somebody studied the joy↗ (external link)

A revised version of this landed at the end of June and it is the best thing I have read on why people actually like working this way. Pimenova, Fakhoury, Bird, Storey and Endres went through 190,000-odd words of interviews, Reddit threads and LinkedIn posts and built a grounded theory of vibe coding rather than another benchmark.

Their central claim is that trust is the regulator:

AI trust regulates movement along a continuum from delegation to co-creation and supports the developer experience by sustaining flow.

That continuum is the useful idea. Delegation at one end — you hand over a task and check the result. Co-creation at the other — you are in the loop, thinking alongside it. Where you sit is not a setting you choose or a property of the tool; it is a function of how much you currently trust the thing, and it moves constantly, sometimes several times inside one session. Everybody who does this seriously already knows the feeling. Nobody had named the axis.

It also explains why the productivity literature is such a mess. Two developers using identical tools on identical tasks can be at opposite ends of that continuum, which means they are doing genuinely different activities. Averaging them produces a number that describes neither.

The pain points they catalogue are refreshingly unromantic: specification, reliability, debugging, latency, code review burden, collaboration. Note that latency is on that list alongside correctness. Flow is fragile, and a model that is right but slow can be worse for the practice than one that is quicker and occasionally wrong. That is an uncomfortable finding and I believe it completely.

Qualitative work gets dismissed in this field as soft next to a benchmark score. This is a good argument for why that is backwards: the benchmarks can tell you what the model did, and only this kind of study can tell you what the person was doing while it happened.