"I don't think the current wave of AI represents the end of software engineering as a profession. I do think it represents a serious contraction and a fundamental reshaping of what the work is. The fear of obsolescence is legitimate. The fear of skill rot is legitimate. And the fear that if you don't go fast enough you'll be left behind is — while often overstated — not entirely unfounded.But the bottleneck was never the code. It was always the human attention, the engineering judgment, the ability to hold a coherent vision for a system. We just didn't notice because writing code felt like the hard part. Now that it's being automated, those human capacities are revealed as the actual scarce resource. And scarce resources are valuable.So if you're feeling overwhelmed, destabilized, simultaneously more productive and less happy, know that you're not alone. The team building the tools you're probably using to navigate this moment is feeling it too. We're debugging our reward functions in real time, same as you.The code is changing. What we do with it is changing. How it feels is... a work in progress.But the humans are still in the loop. We're just tired. And that's worth talking about."pydantic.dev/articles/the-huma#AI #GenerativeAI #LLMs #Programming #SoftwareDevelopment #SoftwareEngineering #Automation #Productivity
@remixtures This nails it. The bottleneck was never typing code. It's the loop from work to feedback to a decision that changes the next work. AI shortens the typing, not the learning. If shipping faster doesn't change a decision, it's just faster actionism. The scarce resource is decision latency, not output. Wrote about that loop here: no-bullshit-agile.com/wfl/