People are subtracting a lot of hard parts from their thinking, and think it's simpler than it is. What happens when the test suite isn't testing the real thing? The ci/cd doesn't even start? There is a bug requiring a hot fix ASAP? The code is growing into a nasty meatball and spaghetti dish, and the llms just turn shift it around. What about when the agent starts thinking in circles and neefs guidance to start working?
I'm not a ludite: I use llms every day, but I try not to be a meat proxy. Some one off scripts are vibe coded, but applications need real maintainable code.
My prediction for winners and losers: some companies will lay off a ton of programmers and replace with AI, with short term success but long term big problems. Other companies will use llms to boost productivity, but keep their engineers responsible for the health of the products. Short term gains won't be as impressive, but productivity will be higher and the company will be competitive in the long term.
They already do that, hence the SaaSpocalypse. The hope for these AI companies is that the models get better than engineers such that the answer to all your questions is that the AI will handle it.
The market believes they will do that, hence the SaaSpocalypse. very important difference
> maybe you're just wrong and won't admit it, clutching to your preconceived notions.
I assume in your world this is only something other people do, but your judgement is perfect right?
A simple Google search found these, maybe you should look harder when looking to verify something instead of dismissal. My judgement is indeed perfect in this comment because, as I said, it is verifiable that it is happening, unless you think that no company at all is building internal tools with AI which would be the counter example to my claim that at least some are. Not even sure what your point is here, because your counter claim is nearly unfalsifiable unless you know every single company's operations in the world.