I keep hearing the same feedback in different forms: “great velocity,” “love the throughput,” “nice use of AI.”
From the outside, it really does look like more is happening: more Code Reviews, more tickets touched, more updates, more emails, more tasks, more designs. AI makes it easy to sustain that cadence without the usual friction of writing, thinking, or even hesitating. But inside the work, there’s a dilemma that keeps getting bigger.
There’s the actual engineering: tracking down a race condition that only shows up under load, or realizing a “simple” bug is really a broken assumption in the design. Or deciding not to refactor a system just because it’s messy, because it still works and the risk isn’t worth it. That part doesn’t get faster with AI. Do you do the work that AI can do and have far lower metrics than the other engineers? Or do you just go ahead and prompt all day, make code and designs at all time? Do you find ways to have NO code solutions or do you use AI to create a shit ton of features, systems, designs? Yes... I don't know what to do either.
Then there’s everything around it. AI makes it trivial to generate a large “cleanup” refactor that renames files and reshuffles modules so the code looks better in a PR. Or to spin up a broad test suite that gives the impression of coverage without really targeting the failure modes that matter. Or to split a single coherent change into ten smaller PRs so the activity graph looks healthier. Even documentation gets pulled into this, polished, expansive docs that read well... but are never actually read anymore because too much noise is happening. We prompt AI to generate designs and then, our reviewers, prompt AI to summarize and review. And management seems to love it.
Engineering behavior adapts to the KPIs that count. More incremental commits, more PR fragments, more “AI helped me generate this” notes that signal participation in the expected workflow. Even when the real work is still the slow part, debugging, reasoning, saying no to unnecessary changes,it increasingly has to be wrapped in artifacts that look like momentum. We all want to keep our jobs.
The uncomfortable part is that AI didn’t just increase productivity. It lowered the cost of producing convincing evidence of productivity. And once that becomes easy, it starts to compete with the harder question of whether any of it actually mattered.