> I simply know that I can solve any engineering problem (that I can come up with) with the help of artificial intelligence. I've tried it a few times — it works.

I think you just need to push yourself to do harder problems. For me, I pushed pretty aggressively into the hardware space, building things as a hobby that I originally felt would be far too time-consuming. This is an area where AI can certainly help accelerate but asking it to make small changes can be an expensive (token wise) proposition, so it forces you think through all the critical decisions and research up-front, and let AI do the boring scut-work.

Maybe you're not actually solving a problem, but revisiting a solved problem? Maybe you need to pursue bigger problems, or stop playing this version of the game? How can the title be "Challenge is Gone", then the post be about how what you used to do is (you believe) no longer relevant, and you're not sure what's next - isn't this the answer you're looking for?

Yes. Hardware is hard. If you even design… what, a simple led flasher, you will go through several iterations in production based on your purpose (every target audience has an almost endless list of constraints that only become clear after making and failing).

There's still tons of pure software engineering problems where iterations are time consuming, or there's no obvious solution, like physics simulations, DSP, computer graphics... I can trivially up the difficulty on any tasks that it can easily solve.

LLMs enable me to iterate quicker, accelerate and parallelise, research, scour the literature and integrate cross-disciplinary knowledge, easily implement more complicated algorithms, and are generally better at avoiding trivial mistakes.

Before LLMs, I can't believe how many hours I wasted debugging computer graphics or computer vision algorithms only to realise the problem was my handling of coordinates, flipping x and y, or one program needing the y axis flipped, or typos when copying the algorithm from equation to code. I have no nostalgia for that era.

Basically: run as fast as you can to escape AI. It's coming for the challenges you enjoy.

Yes but doing it like that helps the AI labs produce better AI. It's going fast now. Over the past few years AI has learned _faster_ to become a good software engineer than CS/SE college students do over a standard 4 year curriculum.