241–250 of 308 posts
AI cannot know what we want it to write - unless we tell it exactly what we want by writing some unit-tests and tell it we want code that passes them.
But is any LLM able to do that?
Reading code has always been as important as writing it. Now it's becoming more important. This is my nightmare. Writing code can be joy at times; reading it is always work.
Reading code has always been as important as writing it. Now it's becoming more important. This is my nightmare. Writing code can be joy at times; reading it is always work.
I completely agree with the author's comment that code review is half-hearted and mostly broken. With agents, the bottleneck is really in reading code, not writing it. If everyone is just half-heartedly reviewing code, or using it as a soapbox for their individual preferences, using agents will completely fall apart as they can easily introduce serious security issues or performance hits. Let's be honest, many of tho…
Or even to make sure that the humans left in the project actually read the code instead of just swiping next.
I wonder if not exercising code writing will atrophy this ability. Similarly to how the ability to read a book does not necessarily imply the ability to write a book. I find that I understand and am more opinionated about code when I personally write it; conversely, I am more lenient/less careful when reviewing someone else's work.
That said, I can’t deny that my coding speed has multiplied. Since I started using GPT, I’ve completely stopped relying on junior assistants. Some tasks are now easier to solve directly with GPT, skipping specs and manual reviews entirely.
Earlier quoted context omitted.
Nobody is saying that you don't have to read and check the code. Especially for things like numerical constants. Those are very frequently hallucinated (unless it's something super common like pi).
I’ve now retired from professional programming and I’m now in hobby mode. I learn nothing from reading AI generated code. I might as well read the stack overflow questions myself and learn.
For loop, if else are replaced by LLM api calls Now LLM api calls needs
1. needs GPU to compute the context
2. Spawn a new process
3. Search internet to build more context
4. reconcile result and return api calls
Oh man! if my use case is simple like Oauth, I would solved using 10 lines of non LLM code!
But today people have the power to do the same via LLM without giving second thought about efficiency
Sensible use of LLMs still only deep engineers can do!!
But today, "Are we using resources efficiently?", wonder at what stage of tech startup building, people will turn and ask this question to real engineers in coming days.
Till then deep engineers has to wait
Finally some serious writing about LLMs that doesn’t follow the hype and it faces reality of what can and can’t be useful with these tools. Really interesting read, although I can’t stand the word “agent” for a for-loop that call recursively an LLM, but this industry is not famous for being sharp with naming things, so here we are. edit: grammar
With guardrails you can let agents run wild in a PR and only merge when things are up to scratch.
To enforce good guardrails, configure your repos so merging triggers a deploy. “Merging is deploying” discourages rushed merges while decreasing the time from writing code to seeing it deployed. Win win!
Maybe it's because I only code for my own tools, but I still don't understand the benefit of relying on someone/something else to write your code and then reading it, understand it, fixing it, etc. Although asking an LLM to extract and find the thing I'm looking for in an API Doc is super useful and time saving. To me, it's not even about how good these LLMs get in the future. I just don't like reading other people's…
You’re clinging to an old model of work. Today an LLM converted my docker compose infrastructure to Kubernetes, using operators and helm charts as needed. It did in 10 minutes what would take me several days to learn and cobble together a bad solution. I review every small update and correct it when needed. It is so much more productive. I’m driving a tractor while you are pulling an ox cart.
You just hope you are on a tractor.