1–10 of 19 posts
Maybe other related or not so far areas like SRE. How is SRE these days? Can you still work the way you want to work? Are you being forced to switch as well?
Businesses often rely on these systems - and they rely on the processes to protect them so are reluctant to adopt AI
LLMs make for great tech demos, but when it comes to writing code for production that actually does something new and useful, it hasn’t impressed me at all.
* Accessibility. Accessibility isn’t a huge challenge unless you’re in a business with a pattern of largely ignoring it. Then it can be a huge challenge to fix. AI won’t be enough and it nightly likely require outside help.
* Speed. If you want faster executing software you need to measure things. AI will be learning from existing code that likely wasn’t well measured.
From what I’ve seen, LLMs are good at making stuff that has already been made and posted to GitHub a thousand times before. At my job we’re constantly asked to do things that really haven’t been done before, at least not by people sharing source code, so the LLMs suck at most of it. LLMs make for great tech demos, but when it comes to writing code for production that actually does something new and useful, it hasn’t…
From what I’ve seen, LLMs are good at making stuff that has already been made and posted to GitHub a thousand times before. At my job we’re constantly asked to do things that really haven’t been done before, at least not by people sharing source code, so the LLMs suck at most of it. LLMs make for great tech demos, but when it comes to writing code for production that actually does something new and useful, it hasn’t…
Ain't nothing new under the sun.
Maybe the thing has been done in general, but not in a way that’s useful for me. That’s why it looks good in tech demos. If I ask AI to write what I need, it will give me an answer, but it won’t actually work and integrate in the ways I need for production. The last time I tried it gave me 70 lines of code, the real end result was thousands. The AI version would look cool in a demo though.
To be fair the code they produce is dogshit, so it isn't a problem.
2. Low tolerance for LLM-induced errors: - Network protocols / telecom software - Medical software - Aerospace, automotive
3. Performance-critical code: - Game engine / graphics engine development (probably an area where we'll see them soon) - Kernels, drivers, microcontrollers.
etc. Not all is lost yet.
AI is predictive. Most people will fall to a comfort zone where AI tells them what to do. But you should become an expert and be one of the few who are telling it what to do.