LLMs give you a power tool after you spent your whole career using hand tools.

A chainsaw and chisel do different things and are made for different situations. It’s great to have chainsaws, no longer must we chop down a giant tree with a chisel.

On the other hand there’s plenty of room in the trade for handcraft. You still need to use that chisel to smooth off the fine edges of your chainsaw work, so your teammates don’t get splinters.

LLMs require fuzzy input and are thus good for fuzzy output, mostly things like recommendations and options. I just do not see a scenario where fuzzy input can lead to absolute, opinionated output unless extremely simple and mostly done before already. Programming, design, writing, etc. all require opinions and an absolute output from the author to be quality.

I find LLMs very efficient in a lot of things except writing big chunks of code that require some organization. They’re good at closing knowlwdge gaps, finding strategies to solve problems, writing code for defined scopes and even reviewing large PRs. However, as others said they can easily alienate you from your own project.

Using gemini cli, I really need to try out claude code 1 day, and you ask it to make a change and it gives you the diff on what it plans to change.

You can say no, then give it more specific instructions like "keep it more simple" or "you dont need that library to be imported"

You can read the code and ensure you understand what it's doing.

This is still an ad that tries to lure heretics in by agreeing with them. This is the new agile religion. Here are suit-optimized diagrams:

https://zed.dev/agentic-engineering

"Interwoven relationship between the predictable & unpredictable."

Just like garbage sources on search engines or trash stack overflow answers. There’s still plenty of junk to sift through with LLM.

LLM will even through irrelevant data points in the output which causes further churn.

I feel not much has changed.

Using AI definitely makes me more productive. However I spend 80% of my "AI time" fixing mistakes made by the AI or explaining why the solution doesn't work.

> Alberto initially embraced LLMs with genuine enthusiasm, hoping they would revolutionize his development workflow.

Is there any other way but down from such revolutionary ungrounded expectations?

Previous discussion on the linked blog post:

https://news.ycombinator.com/item?id=44003700

Unfortunately it seems that nobody 'dialed back' LLM usage for the summary on that page - a good example of how un-human such text can feel to read.