Comment by TheCapeGreek
3 days ago
I always hear this "writing code isn't the bottleneck" used when talking about AI, as if there are chosen few engineers who only work on completely new and abstract domains that require a PhD and 20 years of experience that an LLM can not fathom.
Yes, you're right, AI cannot be a senior engineer with you. It can take a lot of the grunt work away though, which is still part of the job for many devs at all skill levels. Or it's useful for technologies you're not as well versed in. Or simply an inertia breaker if you're not feeling very motivated for getting to work.
Find what it's good for in your workflows and try it for that.
I feel like everyone praising AI is a webdev with extremely predictable problems that are almost entirely boilerplate.
I've tried throwing LLMs at every part of the work I do and it's been entirely useless at everything beyond explaining new libraries or being a search engine. Any time it tries to write any code at all it's been entirely useless.
But then I see so many praising all it can do and how much work they get done with their agents and I'm just left confused.
Can I ask what kind of work area you're in?
Yeah, the more boilerplate your code needs, the better AI works, and the more it saves you time by wasting less on boilerplate.
AI tooling my experience:
- React/similar webdev where I "need" 1000 lines of boilerplate to do what jquery did in half a line 10 years ago: Perfect
- AbstractEnterpriseJavaFactorySingletonFactoryClassBuilder: Very helpful
- Powershell monstrosities where I "need" 1000 lines of Verb-Nouning to do what bash does in three lines: If you feed it a template that makes it stop hallucinating nonexisting Verb-Nouners, perfect
- Abstract algorithmic problems in any language: Eh, okay
- All the `foo,err=…;if err…` boilerplate in Golang: Decent
- Actually writing well-optimized business logic in any of those contexts: Forget about it
Since I spend 95% of my time writing tight business logic, it's mostly useless.