71–80 of 321 posts
Why is this even a legit question? I need to keep writing code to stay relevant, not to forget my craft, be able to review code... So many reasons. AI doesn't change a thing.
One way to "stay relevant" would be to admit that.
Why is this even a legit question? I need to keep writing code to stay relevant, not to forget my craft, be able to review code... So many reasons. AI doesn't change a thing.
Before my time ppl mostly did things in asm, I bet the vast majority of people reading this have never touched assembly and will never have any reason to. This is quickly becoming true of most "code". AI has changed that. One way to "stay relevant" would be to admit that.
And that is a far stronger abstraction than LLMs :)
I always hated writing code but loved debugging. LLM super charges systems thinkers & auditors, it’s just a different process and no different than copy and paste from stack overflow. It all comes down to the architecture design and LLM just exposes how bad people are at designing dynamic architectures.
Speak for yourself. A lot of people have great abilities at designing "dynamic architectures" and anything else an LLM is used for. It sounds like you don't realize that an LLM is only capable of what it does because it was trained on human-written code.
> For example, have you ever seen an agent follow the boy scout rule? Where they leave code better than they found it? And would you WANT them to try to do this? Yes, it's in the rules; run profiles, check code coverage, do a critical review, post the report and follow up tasks. 90% of people I've worked with did not follow these boy scout rules nearly as well as today's frontier LLMs. Is the author implying this is…
That quote is the lead in to an example I talk about after this quote illustrates what I often see. > Agents bias to making the current change as safely as possible. I had a situation in a previous codebase where one morning, pre-caffeinated, my meat brain mentioned using browser local storage. So some random state was managed in local storage. Everything else through a backend database. When I looked at the code, th…
I'm sure plenty of meat humans out there would make the same mistake (sorry, you said to use local storage boss!). You might give them a scolding. And maybe document that policy. Maybe in a markdown file for the next person. IME the latest models are significantly better than the median engineer at following this feedback.
I don't think it's fruitful to blame the LLM any more than it is to blame someone working under you.
In fact I would say this is an excellent example of how engineering does NOT fundamentally change in the era of AI.
Earlier quoted context omitted.
That quote is the lead in to an example I talk about after this quote illustrates what I often see. > Agents bias to making the current change as safely as possible. I had a situation in a previous codebase where one morning, pre-caffeinated, my meat brain mentioned using browser local storage. So some random state was managed in local storage. Everything else through a backend database. When I looked at the code, th…
Right, but this just seems like underspecification. In my experience as both a team leader and an "agentic engineer" (ugh), I try to blame myself for the lack of clarity of my asks, rather than the person/agent for making the "wrong" choice. I'm sure plenty of meat humans out there would make the same mistake (sorry, you said to use local storage boss!). You might give them a scolding. And maybe document that policy.…
In this case things mostly sorta worked and the simplest way to see the problem was look at the code. And try to take it apart a bit to see where the problem was.
I felt I arrived at a better pattern I could trust that the agent could use much more efficiently this way than asking the agent to do it. I could then test that the pattern was being adhered to and therefore better trust the agent not to go off the rails.
I personally internalized the details a lot better by doing this writing. I wouldn’t have internalized it - or more likely played whack-a-mole - by guiding an agent.
How do I arrive at the patterns to check for without exploring the code? And capturing a real failure case?
Earlier quoted context omitted.
I don't write code anymore, because AI writes better code than me. I could write code, but the next AI would find 10 ways to make it better and more consistent with the rest of the AI-generated codebase. So I just let it write all of it. However, I inspect it all carefully and I constantly asks it to reflect on the code quality, to refactor, to reorganize, to make the code as good as possible. The end result is code…
If AI is generating better code than you can, that does say a lot. I've tried various AI's available and outside of being a better Google or a fast reference for Stack Overflow; LLM's do not generate better code nor better running code.
Apparently it's not obvious to everyone, but if you can't write code, you can't review it. I do know people, and companies, that says: "So what, we ask Claude to write the code, Codex will then do the review". The thing that then strikes me as odd is that they still ask for the code in Python, Java, or some other high level language.... Why? Just ask Claude to dump out assembly, or a compiled binary, but no, they don…
I'm as hateful of LLMs hollowing out the job market as the next guy, but the reality is the frontier LLMs are really good at writing anything that's been done and documented on the Internet a million times and unfortunately most of what software devs have been doing the last couple decades is shitting out cookie cutter CRUD apps.
I have my doubts about whether the state of the industry is going to advance as long as we're having LLMs do all the creation, but that's another diatribe.
Earlier quoted context omitted.
I don't write code anymore, because AI writes better code than me. I could write code, but the next AI would find 10 ways to make it better and more consistent with the rest of the AI-generated codebase. So I just let it write all of it. However, I inspect it all carefully and I constantly asks it to reflect on the code quality, to refactor, to reorganize, to make the code as good as possible. The end result is code…
If AI is generating better code than you can, that does say a lot. I've tried various AI's available and outside of being a better Google or a fast reference for Stack Overflow; LLM's do not generate better code nor better running code.
Earlier quoted context omitted.
Right, but this just seems like underspecification. In my experience as both a team leader and an "agentic engineer" (ugh), I try to blame myself for the lack of clarity of my asks, rather than the person/agent for making the "wrong" choice. I'm sure plenty of meat humans out there would make the same mistake (sorry, you said to use local storage boss!). You might give them a scolding. And maybe document that policy.…
Yes but I always have to be on the lookout for this meta pattern that leads to code bloat. In this case things mostly sorta worked and the simplest way to see the problem was look at the code. And try to take it apart a bit to see where the problem was. I felt I arrived at a better pattern I could trust that the agent could use much more efficiently this way than asking the agent to do it. I could then test that the…
You don't!
Have you tried adding rules/automations that make it explicit to review and fix the code for bloat (per your taste, with examples if needed)?
With this setup + a good frontier model you will never have to be on the lookout for code bloat. You can even get the agent to send you text message with the LOC-- if it makes you feel better.
I think I understand where you're coming from, that it's hard to "let go" (I've been coding for 30 years and it was hard for me). That's why I'm recommending to have agents write verifiable quantified reports of the things you care about, so you can build up some trust in the agent's work and you don't have to do things by faith.