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How I program with agents

crawshaw.io

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Re: How I program with agents

#31

Post by osigurdson »

zOneLetter wrote: post #7

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…

I felt the same way until recently (like last Friday recently). While tools like Windsurf / Cursor have some utility, most of the time I am just waiting around for them while I get to read and correct the output. Essentially, I'm helping out with the training while paying to use the tool. However, now that Codex is available in ChatGPT plus, I appreciate that asynchronous flow very much. Especially for making small improvements , fixing minor bugs, etc. This has obvious value imo. What I like to do is queue up 5 - 10 tasks and the. focus on hard problems while it is working away. Then when I need a break I review / merge those PRs.

Re: How I program with agents

#32

Post by DebtDeflation »

closewith wrote: post #11
quantumHazer wrote: post #8

Earlier quoted context omitted.

I’m no better at naming things! Shall we propose LLM feedback loop systems? It’s more grounded in reality. Agent is like Retina Display to my ears, at least at this stage!

Agent is clear in that it acts on behalf of the user. "LLM feedback loop systems" could be to do with training, customer service, etc. > Agent is like Retina Display to my ears, at least at this stage! Retina is a great name. People know what it means - high quality screens.

>Agent is clear in that it acts on behalf of the user.

Yes, but you could say that AI orchestrated workflows are also acting on behalf of the user and the "Agentic AI" people seem to be going to great lengths to distinguish AI Agents from AI Workflows. Really, the only things that distinguish the AI Agent is the "running the LLM in a loop" + the LLM creating structured output.

Re: How I program with agents

#33

Post by BeetleB »

voidUpdate wrote: post #21
qsort wrote: post #14

Earlier quoted context omitted.

I have to flip the question, what is it that people like about it? I certainly don't enjoy writing code for problems that have already been solved a thousand times. We reach for a dictionary, we don't write a hash table from scratch every time, that's only fun the first time you do it. If I could go "give me a working compiler for this language" or "solve this problem using a depth-first search" I wouldn't enjoy prog…

Why do people enjoy going to the gym? Those weights have already been lifted a thousand times. I enjoy writing code because of the satisfaction that comes from solving a problem, from being able to create a working thing out of my own head, and to hopefully see myself getting better at programming. I could augment my programming abilities with an LLM in the same way you could augment your gym experience with a forkli…

OK. Be honest. If you had to write an argument parser once a week, would you enjoy it?

Or extracting input from a config file?

Or setting up a logger?

Re: How I program with agents

#34

Post by voidUpdate »

qsort wrote: post #29
voidUpdate wrote: post #21

Earlier quoted context omitted.

Why do people enjoy going to the gym? Those weights have already been lifted a thousand times. I enjoy writing code because of the satisfaction that comes from solving a problem, from being able to create a working thing out of my own head, and to hopefully see myself getting better at programming. I could augment my programming abilities with an LLM in the same way you could augment your gym experience with a forkli…

We are talking past each other here. Once I solved an Advent of Code problem, I felt like the problem wasn't general enough, so I solved the more general version as well. I like programming to the point of doing imaginary homework, then writing myself some extra credit and doing that as well. Way too much for my own good . The point is that solving a new problem is interesting. Solving a problem you already know exac…

If I'm having the same problem over and over, I'll usually copy the solution from somewhere I've already solved it, whether that be my own code, or a place online where I know the solution is

Re: How I program with agents

#35

Post by osigurdson »

throwawayscrapd wrote: post #27
divan wrote: post #15

Earlier quoted context omitted.

On one codebase I work with, there are often tasks that involve changing multiple files in a relatively predictable way. Like there is little creativity/challenge, but a lot of typing in multiple parts/files. Tasks like these used to take 3-4 hours complete before just because I had to physically open all these files, find right places to modify, type the code etc. With AI agent I just describe the task, and it does…

Did you ever consider refactoring the code so that you don't have to do shotgun surgery every time you make this kind of change?

You mean to future proof the code so requirements changes are easy to implement? Yeah, I've seen lots of code like that (some of it written by myself). Usually the envisioned future never materializes unfortunately.

Re: How I program with agents

#36

Post by bkolobara »

monkeydust wrote: post #18
bArray wrote: post #9

LLMs for code review, rather than code writing/design could be the killer feature. I think that code review has been broken for a while now, but this could be a way forward. Of particular interest would be security, undefined behaviour, basic misuse of features, double checking warnings out of the compiler against the source code to ensure it isn't something more serious, etc. My current use of LLMs is typically via…

Why isn't this spoken more about? Not a developer but work very closely with many - they are all on a spectrum from zero interest in this technology to actively using it to write code (correlates inversely seniority from my sample set) - very little talk on using it for reviews/checks - perhaps that needs to be done passively on commit.

The main issue with LLMs is that they can't "judge" contributions correctly. Their review is very nitpicky on things that don't matter and often misses big issues that a human familiar with the codebase would recognise. It's almost just noise at the end.

That's why everyone is moving to the agent thing. Even if the LLM makes a bunch of mistakes, you still have a human doing the decision making and get some determinism.

Re: How I program with agents

#37

Post by quantumHazer »

closewith wrote: post #11
quantumHazer wrote: post #8

Earlier quoted context omitted.

I’m no better at naming things! Shall we propose LLM feedback loop systems? It’s more grounded in reality. Agent is like Retina Display to my ears, at least at this stage!

Agent is clear in that it acts on behalf of the user. "LLM feedback loop systems" could be to do with training, customer service, etc. > Agent is like Retina Display to my ears, at least at this stage! Retina is a great name. People know what it means - high quality screens.

Retina Display means nothing. Just because Apple pushed hard to make it common to everyone it doesn’t mean it’s a good technical name.

Re: How I program with agents

#38

Post by gk1 »

> Overall, we are convinced that containers can be useful and warranted for programming.

Last week Solomon Hykes (creator of Docker) open-sourced[1] Container Use[2] exactly for this reason, to let agents run in parallel safely. Sharing it here because while Sketch seems to have isolated + local dev environments built in (cool!), no other coding agent does (afaik).

[1] https://www.youtube.com/live/U-fMsbY-kHY?si=AAswZKdyatM9QKCb... - fun to watch regardless

[2] https://github.com/dagger/container-use

Re: How I program with agents

#39

Post by asim »

The agentic loop. The brain in the machine. Effectively a replacement for the rules engine. Still with a lot of quirks but crawshaw and many others from the Google era have a great way of distilling it down to its essence. It provides clarity for me as I see it over and over. Connect the agent tools, prompt it via some user request and let it go, and then repeat this process, maybe the prompt evolves over time to be a response from elsewhere, who knows. But essentially putting aside attempts to mimic human interaction and problem solving, it's going to be a useful tool for replacing orchestration or multi-step tasks that are somewhat ambiguous. That ambiguity is what we had to code before, and maybe now it'll be gone. In a production environment maybe there's a bit of a worry of executing things without a dry run but our tools, services, etc will evolve.

I am personally really interested to see what happens when you connect this in an environment of 100+ services that all look the same, behave the same and provide a consistent path to interacting with the world e.g sms, mail, weather, social, etc. When you can give it all the generic abstractions for everything we use, it can become a better assistant than what we have now or possibly even more than that.

Re: How I program with agents

#40

Post by asabla »

bArray wrote: post #9

LLMs for code review, rather than code writing/design could be the killer feature. I think that code review has been broken for a while now, but this could be a way forward. Of particular interest would be security, undefined behaviour, basic misuse of features, double checking warnings out of the compiler against the source code to ensure it isn't something more serious, etc. My current use of LLMs is typically via…

> LLMs for code review, rather than code writing/design could be the killer feature

This is already available on GitHub using Copilot as a reviewer. It's not the best suggestions, but usable enough to continue having in the loop.

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