If you can code, and you understand the problem (or are well on your way to understanding it), but you're not familiar with the exact syntax of Go or whatever, then working with AI will save you hundreds of hours.
If you can't code, or do not (yet) understand the problem, AI won't save you. It will probably hurt.
I used Claude recently to refresh my knowledge on the browser history API and it said that it gets cleared when the user navigates to a new page because the “JavaScript context has changed”
I have the experience and know how to verify this stuff, but a new engineer may not, and that would be awful.
Things like these made me cancel all my AI subscriptions and just wait for whatever comes after transformers.
Good knowledge of facts, willing to give anything a try, but not much wisdom.
I haven’t seen this demonstrated in gpt-4 or Claude sonnet when asking anything beyond the most extreme basics.
I consistently get subtly wrong answers and whenever I ask “oh okay, so it works like this” I always get “Yes! Exactly. You show a deep understanding of…” even though I was wrong based on the wrong info from the LLM.
Useless for knowledge work beyond RAG, it seems.
Search engines that I need to double check are worse than documentation. It’s why so many of us moved beyond stack overflow. Documentation has gotten so good.
"Of course not," replied Bohr, "but I understand it brings you luck whether you believe it or not."
s/luck/lower negative log likelihood. Besides, a participant can still think about and glean truths from their reflections about a conversation they had which contained only false statements.
That it’s better to be superstitious than not, because maybe it matters?
That was GP's point. Steve Yegge has also talked about this.
Someone who does not have that experience would be much more harmed by the false information LLMs can and do spit out.
…which sometimes feels like it is more work than just fucking doing it yourself. So yeah. I dunno!
I used GitHub Copilot in a project I started mostly to learn Go. It was amazing. I spent not so much time fiddling around with syntax, and much more time thinking about design.
Could code assistants be used to help actually learn a programming language?
- Absolutely.
Will the majority of people that use an LLM to write a Swift app actually do this?
- Probably not, they'll hammer the LLM until it produces code that hobbles along and call it a day.
Also, LEARNING is aided by being more active, but relying on an LLM inherently encourages you to adopt a significantly more passive behavior (reading rather than writing).
Terraform? Hah. 4o and even o1 both absolutely sucked at it. You could copy & paste the documentation for a resource provider, examples and all, and it would still produce almost unusable code. Which was not at all helpful given I didn’t know the language or its design patterns and best practices at all. Sonnet 3.5 did significantly better but still required a little hand holding. And while I got my cloud architecture up and running now I question if I followed “best practices” at all. (Note: I don’t really care if I did though… I have other more important parts of my project to work on, like the actual product itself).
To me one of the big issues with these LLM’s is they have zero ability to do reflection and explain their “thought process”. And even if they could you cannot trust what it says because it could be spouting off whatever random training data it hovered up or it could be “aligned” to agree with whatever you tell it.
And that is the thing about LLM’s. They are remarkably good bullshitters. They’ll say exactly what you want them to and be right just enough that they fool you into thinking they are something more than an incredibly sophisticated next token generator.
They are both incredibly overrated and underrated at the same time. And it will take us humans a little while to fully map out what they are actually good at and what they only pretend to be good at.
Of course everything needs double-checking but just asking the LLM: "how do I do X" will usually at least output all the names of terrraform resources and most configuration attributes I need to look up.
They are great for any kind of work that requires "magical incantations" as I like to call them.