I have ADHD and for whatever reason telling the LLM what to do instead of doing it myself bypasses the task avoidance patterns and/or focus problems I tend to suffer from. I do not find it fun, but I am thankful for it.
Rarely do I use what the tool actually spits out. I just use it as a sounding board, like I’m chatting with a (very noob) writer. It doesn’t make me much faster but it helps me break through when I just can’t get words down.
I have gained a paranoid suspicion that our capacity to decrease immediate distress with technology has become so great that we are creating a world where people with certain temperaments can have their personalities become more and more extreme through the assistance of technologies which, for example, decrease the amount of interpersonal interaction required or prevent the need for deep focus.
But the difference with LLMs currently - I guess? - is that non-engineers are pushing the idea that it’s universally indispensable at scale. I think it leads to a lot of emotion bleeding into the debate.
It is significantly easier to micro-manage an AI than a suite of junior developers. The AI doesn't replace a principal engineer, it's replacing junior and weaker senior developers who need stories broken down extremely concisely to be able to get anything done. The time it takes to break down a story such that a junior through weak senior developers can pick it up and execute it well would have the AI already done with testing built around it.
Micromanaging LLMs is like having Dory from Finding Nemo as your colleague. You find ways to communicate, but there is no learning going on.
Of course if you don't provide that feedback loop, no learning happens. I guess the same could be said of a junior, though.
For me personally, it's a tradeoff of generating the first pass code 10x more quickly, but then deeply knowing and validating the code is then 10-20x more work than it would have been if I'd written it myself (and if time is of the essence, then there's the option of shallow validation/understanding in exchange for speed - which is a compromise in rigor and path towards tech debt). In the end, none of this seems like a net win (unless you don't care about quality), and it is much less enjoyable.
TL;DR; While LLMs are faster to spit out first pass code, by the time I've validated and fixed the LLM's first-pass work, I could've had my "by-hand" implementation done correctly, and had much deeper understanding out of the box. Net loss.
it depends on language and infra, but some/many require lots of boilerplate and memorizing thousands of APIs, automating this is easy LLM 10x gain.
I for example write SQL myself, because boilerplate is super-minimal, and core SQL is very minimal itself, there are like 20 constructs to memorize.
I can also switch between codebase with different frameworks and languages and make changes without spending all day reading docs.
It's also pretty good at tracing code and that's fairly straight forward to verify the results manually. It can build a flow diagram in 10-30 minutes (depending on what tool calls need allowed and how many prompts it needs) versus me taking a couple hours to do the same.
Every project should have a custom linter for their tech stack. It would check for not just syntax errors, but architectural choices as well as taste guidelines.
Whenever the LLM writes bad code, I add it to my linter to check against in the future.
