In any REAL, workload, with good processes, code review makes speed of code generated a moot point. You still move as fast as you can review the code, and no, I won't debate that you can rely on LLMs, a deterministic language predictor, to determine the correctness of code; in the context of the business, and technical implications.

Kind of.... I don't know. To get placed such requirements from the top down and not fight back, just take it head on, not even maliciously, don't even oppose it on a technical basis, just be like "yeah, you've now gotta ship faster or you're left behind, so therefore LLMs must be the future!", no critical thought attached. Is this shit coming from experienced engineers?

Preposterous we're relying on "it's better because I feel like", "dudes who don't use it are falling behind at work", "they ask for it in job interviews".

Code review is specifically for code quality, more lower level stuff.

It circles back to the question, is this unimportant enough for me to delegate it to a LLM that might get it wrong? If the answer is yes, why even do it to begin with. If the answer is no, you have to do it manually.

I personally though, see value in this type of automation. Stuff like tag categorization, indexing, that otherwise would've been lost seems like a good fit for LLMs. Whether or not they're an ideal solution and something else like a search engine would've been a better fit, is a different question.

My entire team, very competent hot dog experts, was laid off after a hot dog cooking machine could do what took us 3 months, in just one day. I've been out of a job for 12 months. The reason? All hot dog making has been offloaded to Claudog Hotdog. "Sorry. Hot dog manual cooking is a thing of the past", one recruiter told me.

I'm working as a software engineer as we speak. I keep applying to hot dog related positions but I get no interviews. Even positions significantly below my pay grade and skillset. No one is hiring. Hot dog cooking is over. We are entering a new era.

Also LLMs will be used to attack only, no one will be smart to integrate it into CI flows, because everyone is that dumb. No security tools will pop up.

Did it ever occur to you that the ever changing goalposts might have more to do with the expensive marketing campaigns of the big LLM providers?

We could talk about what's a measurable metric and what's not. Certainly, we have not much more other than "benchmarks" of which, honestly, I don't know the veracity of, or if big LLM cheats somehow, or if the performance is even stable. The core idea is that LLMs remain able to do exactly what they were able to do back at release; text prediction. They got better in some regards, sure.

Your example is worrisome to me. It should be to you too. You didn't write a literature review, you generated a scaffold of a literature review, with the same vices of LLM-based-writing as anything it does and still needing review and revising. I would hope rewriting to avoid your work be associated with LLM-generation. For better or worse, you still need to, normally, revise your work. For, once again, because this point seems to be difficult to grasp, a text predictor is not a reliable source of information. We make tradeoffs, sacrificing reliability for ease of use, but any real work needs human reviewing: which goes back to my first point. In this example it's doing nothing other than it being a fancy search and scaffolding tool.

The ball is likely to be in the same place because, once again, they're text predictors. Not sentient beings, or intelligent. Still generating text, still hallucinating, probably even more so thanks to the ever increasing amount of LLM-written content on the internet and initiatives like poison fountain doing a number on the generated content.

It's wild to me to make such claims about the rate of change of those tools. You're claiming we'll see exponential gains for those tools, I take, while completely ignoring the base set of constraints those models will, never, be able to get rid of. They only know how to produce text. They don't know, and will never really, know if it's right.