> So far the biggest limiting factor is remembering to use it. Even people I consider power users (based on their Claude token usage) agree with the sentiment that sometimes you just forget to ask Claude to do a task for you, and end up doing it manually. Sometimes you only notice that Claude could have done it, once you are finished. This happens to me an embarrassing amount.
Yea, this happens to me too. Does it say something about the tool?
It's not like we are talking about luddites who refuse to adopt the technology, but rather a group who is very open to use it. And yet sometimes, we "forget".
I very rarely regret forgetting. I feel a combination of (a) it's good practice, I don't want my skills to wither and (b) I don't think the AI would've been that much faster, considering the cost of thinking the prompt and that I was probably in flow.
If you're forgetting to use the tool, is the tool really providing benefit in that case? I mean, if a tool truly made something easier or faster that was onerous to accomplish, you should be much less likely to forget there's a better way ...
Yep! Most tools are there to handle the painful aspects of your tasks. It's not like you are consciously thinking about them, but just the fact on doing them without the tool will get a groan out of you.
A lot of current AI tools are toys. Fun to play around, but as soon as you have some real world tasks, you just do it your usual way that get the job done.
There's a balance to be calculated each time you're presented with the option. It's difficult to predict how much iteration the agent is going to require, how frustrating it might end up being, all the while you lose grip on the code being your own and your head-model of it, vs just going in and doing it and knowing exactly what's going on and simply asking it questions if any unknowns arise. Sometimes it's easier to just not even make the decision, so you disregard firing up the agent in a blink.
You never forgot your reusable grocery bag, umbrella, or sun glasses? You've never reassembled something and found a few "extra" screws?
Many CLI tools that I love using now took some deliberate practice to establish a habit of using them.
I really really hate this idea that you should have AI do anything it can do, and that there's no value in doing it manually.
Some tasks are faster than cognitive load to create a prompt and then wait for execution.
Also if you like doing certain tasks, then it is like eating an ice cream vs telling someone to eat an ice cream.
And the waiting is somewhat frustrating, what am I supposed to do while I wait? I could just sit and watch, or context switch to another task then forget the details on what I was originally doing.
I think you’re supposed to spin up another to do a different task. Then you’ll be occupied checking up on all of them, checking their output and prodding them along. At least that’s what Anthropic said you should do with Claude Code.
If I wanted to be an EM, I'd apply for that job.
The thing is others will eat ice cream faster so very soon there'll be no ice cream for me.
I'm still having a hard time with coding agents. They are useful but also somehow immature hence dangerous. The other day I asked copilot with GPT4o to add docstrings to my functions in a long Python file. It did a good job on the first half. But when I looked carefully, I realized the second half of my file was gone. Just like that. Half of my file had been silently deleted, replaced by a single terrifying comment along the lines of "continue similarly with the rest of the file". I use Git of course so I could recover my deleted code. But I feel I still can't fully trust an AI assistant that will silently delete hundreds of lines of my codebase just because it is too lazy or something.
these models have hard time modifying LARGE files and then returning them back to you. That's inefficient too.
What you want is to ask for list of changes and then apply them. That's what aider, codex, etc. all do.
I made a tool to apply human-readable changes back to files, which you might find useful: https://github.com/asadm/vibemode
aider has this feature too.
Your first mistake was using Copilot. Your second mistake was using GPT 4o
> The most common thing that makes agentic code ugly is the overuse of comments.
I've seen this complaint a lot, and I honestly don't get it. I have a feeling it helps LLMs write better code. And removing comments can be done in the reading pass, somewhat forcing you to go through the code line by line and "accept" the code that way. In the grand scheme of things, if this were the only downside to using LLM-based coding agents, I think we've come a long way.
I've noticed Gemini 2.5 pro does this a lot in Cursor. I'm not sure if it's because it doesn't work well with the system prompt or tools, but it's very annoying. There are comments for nearly every line and it's like it's thinking out loud in comments with lots of TODOS and placeholders.
You can literally just ask it to not write too many comments, describe the kind of comments you want, and give a couple of examples. Save that in rules or whatever. And it's solved for the future :)
I tell them to write self-documenting code and to only leave comments when its essential for understanding, and that's worked out pretty well
Yeah that's what I do, remove the comments as I read through.
They tend to add really bad comments though. I was looking at an LLM generated codebase recently and the comments are along the lines of “use our newly created Foo model”, which is pretty useless.
> You can see this in practice when you use Claude Code, which is pay-per-token. Our heaviest users are using $50/month of tokens. That’s a lot of tokens.
How is your usage so low! Every time i do anything with claude code i spend couple of bucks, for a day of coding it's about $20. Is there a way to save on tokens on a mid-sized Python project or people are just using it less?
It's because by default it'll try to solve most problems agentically / by "thinking", even if your prompt is fairly prescriptive.
I use aider.chat with Claude 3.5 haiku / 3.7 sonnet, cram the context window, and my typical day is under $5.
One thing that can help for lengthy conversations is caching your prompts (which aider supports, but I'm sure Claude Code does, too?)
Obviously, Anthropic has an incentive to get people to use more tokens (i.e. by encouraging you to use tokens on "thinking"). It's one reason to prefer a vendor-neutral solution like aider.
> The product manager he sits next to has shipped 130 PRs in the last 12 months. When we look for easy wins and small tasks for new starters, it’s harder now, because he’s always got an agent chewing through those in the background.
I'd be curious to hear more about this, whether from the author or from someone who does something similar. When the author says "background", does that literally mean JIRA tickets are being assigned to the agent, and it's spitting back full PRs? Is this setup practical?
I have a confession. I don’t really get what Claude Code is… It’s not a model, it’s not an editor with AI integrated… So what is it? It bugs me on the website, I click on it, read, still don’t get it.
I have a Claude console account, if you can call it that? It always takes me 3 times to get the correct email address because it does not work with passkeys or anything that lets me store credentials. I just added the api key to OpenWebUI. It’s nice and cheaper than a subscription for me even though I use it all day.
But I’m still confused. I just now clicked on “build with Claude”, it takes me to that page where I put in the wrong email address 3 times. And then you can buy credits.
Have you installed the Claude cli tool?
Think of it as an LLM that automagically pulls in context from your working directory and can directly make changes to files.
So rather than pasting code and a prompt into ChatGPT and then copy and pasting the results back into your editor, you tell Claude what you want and it does it for you.
It’s a convenient, powerful, and expensive wrapper
"Making it easy to run tests with a single command. We used to do development & run tests via docker over ssh. It was a good idea at the time. But fixing a few things so that we could run tests locally meant we could ask the agent to run (and fix!) tests after writing code."
Good devops practices make AI coding easier!
> Good devops practices make AI coding easier!
Good devops practices make coding easier!
This is one of the most exciting things about coding agents: they make a lot of tooling that was so tedious to use it was impractical now ultra relevant. I wrote a short post about this a few weeks ago, the idea that things like "Semgrep" are now super valuable where they were kind of marginal before agents.
And also the payoff for “minor” improvements to be bigger.
We’ve started more aggressively linting our code because a) it makes the ai better and b) we made the ai do the tedious work of fixing our existing lint violations.
It can automate a lot of the tediousness for static typing, too
Having linting/prettifying and fast test runs in Cursor is absolutely necessary. On a new-ish React Typescript project, all the frontier models insist on using outdated React patterns which consistently need to be corrected after every generation.
Now I only wish for an Product Manager model that can render the code and provide feedback on the UI issues. Using Cursor and Gemini, we were able to get a impressively polished UI, but it needed a lot of guidance.
> I haven’t yet come across an agent that can write beautiful code.
Yes, the AI don't mind hundreds of lines of if statements, as long as it works it's happy. It's another thing that needs several rounds of feedback and adjustments to make it human-friendly. I guess you could argue that human-friendly code is soon a thing of the past, so maybe there's no point fixing that part.
I think improving the feedback loops and reducing the frequency of "obvious" issues would do a lot to increase the one-shot quality and raise the productivity gains even further.
Unless you are prototyping human-friendly code is a must. It is easy to write huge amounts of low quality code without AI. Hard part is long term maintenance. I have not seen any AI tool helping with that.
Good to see experiences from people rolling out AI code assistance at scale. For me the part that resonates the most is the ambition unlock. Using Brokk to build Brokk (a new kind of code assistant focused on supervising AI rather than autocompletes, https://brokk.ai/) I'm seriously considering writing my own type inference engine for dynamic languages which would have been unthinkable even a year ago. (But for now, Brokk is using Joern with a side helping of tree-sitter.)
> You can see this in practice when you use Claude Code, which is pay-per-token. Our heaviest users are using $50/month of tokens. That’s a lot of tokens. I asked our CFO and he said he’d be happy to spend $100/dev/month on agents. To get 20% more productive that’s a bargain.
fwiw we interviewd the Claude Code team (https://www.latent.space/p/claude-code) and they said that even within Anthropic (where Claude is free, we got into this a bit), the usage is $6/day so about $200/month. not bad! especially because it goes down when you under-use.
> I haven’t yet come across an agent that can write beautiful code.
o3 in codex is pretty close sometimes. I prefer to use it for planning/review but it far exceeds my expectations (and sometimes my own abilities) quite regularly.
As someone who really dislikes using Cursor, what does the HN hivemind think of alternatives? Is there a good CLI like Claude Code but for Gemini / other models? Is there a good Neovim plugin that gets the contextual agent mode right?
Have you tried Aider? They're making a CLI coding agent for quite some time and have gained quite a bit of traction.
Seconding aider, which was recommended to me months ago on HN. They don't integrate with vim directly per-se, but I'm a heavy vim user and I like the workflow of `aider --vim`, `ctrl-z`, `vim`.
They also have a mode (--watch-files) that allows you to talk to a running aider instance from inside vim, but I haven't used it much yet.
Sweet spot for me was cursor for autocomplete/editing and manually using Claude for more deep dive questions.
I cant go back to a regular IDE after being able to tab my way through most boilerplate changes, but anytime I have Cursor do something relatively complex it generates a bunch of stuff I don't want. If I use Claude chat the barrier of manually auditing anything that gets copied over stays in place.
I also have pretty low faith in a fully useful version of Cursor anytime soon.
Jetbrains tools have MCP plugin and can work with Claude.
> Is there a good CLI like Claude Code but for Gemini / other models
I built an open source CLI coding agent that is essentially this[1]. It combines Claude/Gemini/OpenAI models in a single agent, using the best/most cost effective model for different steps in the workflow and different context sizes. The models are configurable so you can try out different combinations.
It uses OpenRouter for the API layer to simplify use of APIs from multiple providers, though I'm also working on direct integration of model provider API keys.
It doesn't have a Neovim plugin, but I'd imagine it would be one of the easier IDEs to integrate with given that it's also terminal-based. I will look into it—also would be happy to accept a PR if someone wants to take a crack at it.
>Our head of product is a reformed lawyer who taught himself to code while working here. He’s shipped 150 PRs in the last 12 months.
>The product manager he sits next to has shipped 130 PRs in the last 12 months.
this is actually horrifying, lol. i haven't even considered product guys going ham on the codebase
Code review makes this a lot less scary. Honestly it seems like mostly a win. A while ago at my day job, a moderately technical manager on another team attempted to contribute a relatively simple feature to my team's codebase. It took many rounds of review feedback for his PR to converge on something close to our general design guidelines. I imagine it would have been way less frustrating and time consuming for him if he could have just told an AI agent what to do and then have it respond to review feedback for him.
Honestly, it's been pretty great at my tiny startup. The designer has a list of tweaks he wants that I could do pretty quickly... once I'm done with my current thing in a day or two. Or he can just throw claude at it. We've got CI, we've got visual diff testing, and I'll review his simple `margin-left: 12px;`->`margin-left: 16px;`.
But we're unlocking:
A) more dev capacity by having non-devs do simple tasks
B) a much tighter feedback loop between "designer wants a thing" and "thing exists in product"
C) more time for devs like me to focus on deeper, more involved work
Ostensibly the PRs are getting reviewed so it’s, maybe, not that bad but I had a similar reaction: I can slap together something with some wood, hammer, nails and call it a chair. Should I be manufacturing furniture?
that's actually great! win-win for everybody. Although not fun reviewing those early PRs.
Even if you don't think AI will replace the job of software developer completely, there's no way compensation is going to stay at the current level when anyone can ship code.