Another programmer here. The bottleneck in most jobs isn't in getting boilerplate out, which is where AI excels, it's in that first and/or last 10-20%, alongside dictating what patterns are suitable for your problem, what proprietary tooling you'll need to use, what API's you're hitting and what has changed in recent weeks/months.

What AI is achieving is impressive, but as someone that works in AI, I think that we're seeing a two-fold problem: we're seeing a limit of what these models can accomplish with their training data, and we're seeing employers hedge their bets on weaker output with AI over specialist workers.

The former is a great problem, because this tooling could be adjusted to make workers lives far easier/faster, in the same way that many tools have done so already. The latter is a huge problem, as in many skilled worker industries we've seen waves of layoffs, and years of enshitification resulting in poorer products.

The latter is also where I think we'll see a huge change in culture. IMO, we'll see existing companies bet it all and die from supporting AI over people, and a new wave of companies focus on putting output of a certain standard to take on larger companies.