7 ms·

Notes on rolling out Cursor and Claude Code

189 points by jermaustin1 1y ago

DGAP 1y ago
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.
jbellis 1y ago
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/ 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.)
datadrivenangel 1y ago
"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!
- tptacek 1y ago
  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.
  - kasey_junk 1y ago
    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.
    - jaredsohn 1y ago
      It can automate a lot of the tediousness for static typing, too
  - viraptor 1y ago
    The fact that you have to describe things in text suddenly made a few companies also publish API documentation as llm.txt and the content is what I wish they published for people instead.
- skydhash 1y ago
  > Good devops practices make AI coding easier! Good devops practices make coding easier!
NitpickLawyer 1y ago
> 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.
- manojlds 1y ago
  Yeah that's what I do, remove the comments as I read through.
- ellieh 1y ago
  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 :)
  - dockercompost 1y ago
    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
- meander_water 1y ago
  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.
  - felipeerias 1y ago
    That is because it is thinking out loud. Producing tokens is how it thinks.
    - 1y ago
aerhardt 1y ago
> 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.
- Trasmatta 1y ago
  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.
  - ErikBjare 1y ago
    The value is in doing the thing, how it's done is just a matter of preference and efficiency.
    - Trasmatta 1y ago
      This is a myopic and dehumanizing way to look at it.
      - avemuri 1y ago
        It really isn't. Not any more than growing your own herbs vs buying them at the market is.
        Trasmatta 1y ago
        Are you implying that there's no value to be found in someone growing their own herbs?
hallh 1y ago
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.
- kubav027 1y ago
  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.
- conradkay 1y ago
  I find that there's an very high correlation between code I'd expect to confuse humans and code which confuses/breaks LLMs When you let them pump out code without any intervention, there becomes a point where they start introducing bugs faster than they get fixed and things don't get better
christophilus 1y ago
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?
- deleted 1y ago
  [deleted]
- M4v3R 1y ago
  Have you tried Aider? They're making a CLI coding agent for quite some time and have gained quite a bit of traction. [0] https://aider.chat/ https://aider.chat/
  - gen220 1y ago
    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.
    - tcoff91 1y ago
      The file watch mode is great. Also nvim-aider is a great plugin which makes it really easy to manage context from within nvim and add diagnostics to chat
- polskibus 1y ago
  Jetbrains tools have MCP plugin and can work with Claude.
- ericmcer 1y ago
  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.
scudsworth 1y ago
>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
- fishtoaster 1y ago
  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
- snoman 1y ago
  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?
  - 11217mackem 1y ago
    Sure, if it's good, it works, it's reliable and people like it.
- asadm 1y ago
  that's actually great! win-win for everybody. Although not fun reviewing those early PRs.
- dgunay 1y ago
  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.
ollien 1y ago
> 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?
- ghiculescu 1y ago
  No, not so literally. I just meant that whenever a small throwaway task comes across his desk, he does it instead of making a ticket. Lots of "small tweak" PRs. (Also, your life will get better when you delete Jira!)
swyx 1y ago
> 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 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.
- ghiculescu 1y ago
  Thanks for sharing, looks like a great interview. Tell them I'm a big fan!
chw9e 1y ago
> 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.
teekert 1y ago
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.
- bognition 1y ago
  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
  - srvmshr 1y ago
    Not the OP but in a similar boat. Curious to understand how do you make sure that Claude code cli tool does not break existing code functionality? My hesitation to adopt stems from the events where Claude.ai WebUI ignorantly breaks the code, but since I can visibly verify it - I iterate it until it seems reasonable syntactically & logically, and then paste it back. With the autonomous changing of the code lines, I'm slightly nervous it would/could break too many parts concurrently -- hence my hesitation to use it. Any best practices would be insightful
    - theonething 1y ago
      By default, it shows you a diff of what it plans to do and ask you for permission before making the change.
    - ekidd 1y ago
rossant 1y ago
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.
- asadm 1y ago
  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 https://github.com/asadm/vibemode aider has this feature too.
- weird-eye-issue 1y ago
  Your first mistake was using Copilot. Your second mistake was using GPT 4o
- duxup 1y ago
  I’ve also seen catastrophic failures where the code returned completely fails for numerous “obvious” problems, including but not limited to missing code. I tend to have to limit the code I share and ask more pointed / targeted questions in order to lead the AI to a non catastrophic result.
mdrachuk 1y ago
> 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?
- gen220 1y ago
  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.
- ghiculescu 1y ago
  That seems really high to me. Maybe you write a lot more code than anyone else around. How big is the codebase? I have a feeling that (+ the stack) has a big impact.
- arresin 1y ago
  How though? Are you putting a massive code base into context each time?
  - itoprocess 1y ago
    Yeah, I think you need to do task in more discrete chunks, so you aren't' sending so many tokens each request by the end.
  - joshuanapoli 1y ago
    With Aider, you typically select only that part of the codebase that you want to work on. You can do this manually, or let the agent find files itself. It tends to break down if you need more than 20 files or so in the context.
ghiculescu 1y ago
Author here. Ask me anything! Since writing this a tangentially related thing we've added, is a github action that runs on any PR that includes a (Rails) database migration, and reviews it, comparing it to our docs for how to write good migrations. Claude helped write the action so it was super easy to set up.
- nu11ptr 1y ago
  Have you noticed people more productive, in general, using Claude Code or Cursor? Obviously it varies, but curious if one or the other is the clear productivity champion at this point.
  - ghiculescu 1y ago
    I wouldn't say there's an obvious winner yet. I do think it depends on the person and how they like to work / how they reason about problems. For Claude specifically, people who take more time to write long detailed prompts tend to get much better outcomes. Including me, since I made the effort to get better at prompt writing.
- vianarafael 1y ago
  You mentioned using Claude to help set up a GitHub Action for reviewing Rails migrations. How do you see agentic tools like Claude evolving in their ability to reason about big-picture concerns—not just boilerplate generation, but things like validating database changes, architectural decisions, or spotting long-term risks that aren’t immediately visible?
  - ghiculescu 1y ago
    They are really good if you give them guidance and tight scope. For example for the database migrations review bot, we give it our Cursor rules file on database migrations (which is about 200 lines) and tell it to review the PR based on that. It works particularly well for migrations because all the context is in the PR. We haven't had as much luck with reviewing general PRs where the reason for a change being good or bad could be outside the diff, and where there aren't as clearly defined rules for what should be avoided.
AtlasBarfed 1y ago
I'm wondering how much better llms are at "untyped"/loosely typed scripters like Ruby for large scale coding and error avoidance. Presumably an llm can actually maintain better contextual awareness of code and variables than, say cold loaded syntax highlights.
- viraptor 1y ago
  They likely aren't. I'm getting occasional issues caught by type checks in the LLM output. They would be weird crashes instead in other languages.
- 11217mackem 1y ago
  ultimately, it comes down to training data and character count llms can be better than most humans at applescript just need a fuck ton in context
- sensanaty 1y ago
  As a hobby rubyist, pretty terrible compared to Typescript. I suspect it's also that there's less Ruby in the training sata, but Ruby being so dynamic and ducktypable means it produces some truly nightmarish shit from time to time
SafeDusk 1y ago
Changing my old coding behavior aside, biggest limiting factor for me is understanding how and why the coding agent is doing this a certain way, so that I have the confidence to continually sharpen my tools. I want something simple that I have full control on, if not just to understand how they work. So I made a minimal coding agent (with edit capability) that is fully functional using only seven tools: read, write, diff, browse, command, ask, and think. As an example, I can just disable `ask` tool to have it easily go full autonomous on certain tasks. Or, ask it to `think` for refactoring. Have a look at https://github.com/aperoc/toolkami https://github.com/aperoc/toolkami to see if it might be useful for you.
- eschaton 1y ago
  It’s producing statically likely next tokens based on its training corpus and prompts. That’s what it’s doing. It’s not analyzing your code, it’s not considering approaches, it’s not theorizing about behavior, it’s just producing statistically likely tokens. This is why I don’t touch the shit—it’s fucking snake oil.
  - ekidd 1y ago
    If you "don't touch the stuff", you are probably relying on your initial impressions from 2022 to evaluate models in 2025. Also, predicting the next token with high accuracy may demand very high degrees of knowledge and reasoning. As an extreme example, please predict the next 1,000 tokens in this sequence: "ABSTRACT. In this paper, we show a mathematically elegant unification of quantum mechanics and gravity, which makes testable predictions. Testing these predictions shows that the quantum gravity model provides previously unexpected results accurate to 1 part in..." To predict the rest of that paper, it helps to actually come up with a workable model of quantum gravity. Which no current LLM can do, happily. But lots of current models are good enough at "predicting the next token" to solve high school honors math problems that they've never seen before. They can apply the chain rule, factor polynomials, double-check their work, backtrack, etc. Similarly, current-generation coding models are perfectly capable of reading compiler error messages, and generating diffs that fix the underlying problem. Current-generation summarization models are capable of reading several scientific papers, extracting the key concepts, and turning them into a fairly serviceable podcast. All of this happens because a (1) in order to predict the next token better, LLMs actually build thousands of specialized models that do things like "keep track of the state of a chess board" or "recognize lions in photos", and (2) transformer models are sufficiently powerful to model many problems well. So a big current-generation LLM is basically an ensemble of thousands of domain models glued together with a language model and a bunch of feed-forward layers. Now, none of the outputs from LLMs are of super high quality, compared to experienced humans. And there are deep reasons for that. But if you happen to have problem where medium-competence AI "slop" is actually beneficial, then yes, LLMs can actually be of real-world use.
asdev 1y ago
>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. In a serious organization, non technical people should not be shipping any sort of code. They should be doing the highest leverage things possible to help the business, and if that seems to be coding, there are grave issues in the company.
- ghiculescu 1y ago
  How do credibly define "non technical people" when everyone's code is written by an LLM? Serious organisations sound awful.
  - asdev 1y ago
    non technical people are people who are not hired for an engineering role
- wheelerwj 1y ago
  This sounds like a disaster waiting to happen
- n_ary 1y ago
  I see a fraudulent benefit in this case. When these non-tech people go into public talks or anything, they can suddenly claim “oh, I use AI to write 80% of my code” and voila! No one will ask whether their responsibility is to write code or do any engineering, simply being able to give some surface level claims makes them credible enough and feed the hype while appearing cool. It also gives investors more confidence to shower them with money when needed, as non-tech people are also doing AI coding and they are super agile! When Msft CEO claims that 80% code written by AI, there is a 50% doubt, but when someone adds that, yeah so I have done 150 PRs, now it feels more concrete and real.
  - ghiculescu 1y ago
    Author here. We don't have (or want) any investors. I encourage PMs to code because it's good for the business. Otherwise I wouldn't do it. I wrote about this years before we started doing AI-backed-coding: https://ghiculescu.substack.com/p/opening-the-codebase-up-to-everyone https://ghiculescu.substack.com/p/opening-the-codebase-up-to..., so some of the details are no longer correct, but the philosophy is the same.
deleted 1y ago
[deleted]

189 points by jermaustin1 1y ago

DGAP 1y ago

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.

jbellis 1y ago

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/ 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.)

datadrivenangel 1y ago

"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!

tptacek 1y ago
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.
- kasey_junk 1y ago
  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.
  - jaredsohn 1y ago
    It can automate a lot of the tediousness for static typing, too
- viraptor 1y ago
  The fact that you have to describe things in text suddenly made a few companies also publish API documentation as llm.txt and the content is what I wish they published for people instead.
skydhash 1y ago
> Good devops practices make AI coding easier! Good devops practices make coding easier!

NitpickLawyer 1y ago

> 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.

manojlds 1y ago
Yeah that's what I do, remove the comments as I read through.
ellieh 1y ago
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 :)
- dockercompost 1y ago
  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
meander_water 1y ago
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.
- felipeerias 1y ago
  That is because it is thinking out loud. Producing tokens is how it thinks.
  - 1y ago

aerhardt 1y ago

> 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.

Trasmatta 1y ago
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.
- ErikBjare 1y ago
  The value is in doing the thing, how it's done is just a matter of preference and efficiency.
  - Trasmatta 1y ago
    This is a myopic and dehumanizing way to look at it.
    - avemuri 1y ago
      It really isn't. Not any more than growing your own herbs vs buying them at the market is.
      - Trasmatta 1y ago
        Are you implying that there's no value to be found in someone growing their own herbs?

hallh 1y ago

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.

kubav027 1y ago
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.
conradkay 1y ago
I find that there's an very high correlation between code I'd expect to confuse humans and code which confuses/breaks LLMs When you let them pump out code without any intervention, there becomes a point where they start introducing bugs faster than they get fixed and things don't get better

christophilus 1y ago

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?

deleted 1y ago
[deleted]
M4v3R 1y ago
Have you tried Aider? They're making a CLI coding agent for quite some time and have gained quite a bit of traction. [0] https://aider.chat/ https://aider.chat/
- gen220 1y ago
  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.
  - tcoff91 1y ago
    The file watch mode is great. Also nvim-aider is a great plugin which makes it really easy to manage context from within nvim and add diagnostics to chat
polskibus 1y ago
Jetbrains tools have MCP plugin and can work with Claude.
ericmcer 1y ago
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.

scudsworth 1y ago

fishtoaster 1y ago
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
snoman 1y ago
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?
- 11217mackem 1y ago
  Sure, if it's good, it works, it's reliable and people like it.
asadm 1y ago
that's actually great! win-win for everybody. Although not fun reviewing those early PRs.
dgunay 1y ago
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.

ollien 1y ago

> 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?

ghiculescu 1y ago
No, not so literally. I just meant that whenever a small throwaway task comes across his desk, he does it instead of making a ticket. Lots of "small tweak" PRs. (Also, your life will get better when you delete Jira!)

swyx 1y ago

> 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 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.

ghiculescu 1y ago
Thanks for sharing, looks like a great interview. Tell them I'm a big fan!

chw9e 1y ago

> 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.

teekert 1y ago

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.

bognition 1y ago
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
- srvmshr 1y ago
  Not the OP but in a similar boat. Curious to understand how do you make sure that Claude code cli tool does not break existing code functionality? My hesitation to adopt stems from the events where Claude.ai WebUI ignorantly breaks the code, but since I can visibly verify it - I iterate it until it seems reasonable syntactically & logically, and then paste it back. With the autonomous changing of the code lines, I'm slightly nervous it would/could break too many parts concurrently -- hence my hesitation to use it. Any best practices would be insightful
  - theonething 1y ago
    By default, it shows you a diff of what it plans to do and ask you for permission before making the change.
  - ekidd 1y ago

rossant 1y ago

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.

asadm 1y ago
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 https://github.com/asadm/vibemode aider has this feature too.
weird-eye-issue 1y ago
Your first mistake was using Copilot. Your second mistake was using GPT 4o
duxup 1y ago
I’ve also seen catastrophic failures where the code returned completely fails for numerous “obvious” problems, including but not limited to missing code. I tend to have to limit the code I share and ask more pointed / targeted questions in order to lead the AI to a non catastrophic result.

mdrachuk 1y ago

> 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?

gen220 1y ago
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.
ghiculescu 1y ago
That seems really high to me. Maybe you write a lot more code than anyone else around. How big is the codebase? I have a feeling that (+ the stack) has a big impact.
arresin 1y ago
How though? Are you putting a massive code base into context each time?
- itoprocess 1y ago
  Yeah, I think you need to do task in more discrete chunks, so you aren't' sending so many tokens each request by the end.
- joshuanapoli 1y ago
  With Aider, you typically select only that part of the codebase that you want to work on. You can do this manually, or let the agent find files itself. It tends to break down if you need more than 20 files or so in the context.

ghiculescu 1y ago

Author here. Ask me anything! Since writing this a tangentially related thing we've added, is a github action that runs on any PR that includes a (Rails) database migration, and reviews it, comparing it to our docs for how to write good migrations. Claude helped write the action so it was super easy to set up.

nu11ptr 1y ago
Have you noticed people more productive, in general, using Claude Code or Cursor? Obviously it varies, but curious if one or the other is the clear productivity champion at this point.
- ghiculescu 1y ago
  I wouldn't say there's an obvious winner yet. I do think it depends on the person and how they like to work / how they reason about problems. For Claude specifically, people who take more time to write long detailed prompts tend to get much better outcomes. Including me, since I made the effort to get better at prompt writing.
vianarafael 1y ago
You mentioned using Claude to help set up a GitHub Action for reviewing Rails migrations. How do you see agentic tools like Claude evolving in their ability to reason about big-picture concerns—not just boilerplate generation, but things like validating database changes, architectural decisions, or spotting long-term risks that aren’t immediately visible?
- ghiculescu 1y ago
  They are really good if you give them guidance and tight scope. For example for the database migrations review bot, we give it our Cursor rules file on database migrations (which is about 200 lines) and tell it to review the PR based on that. It works particularly well for migrations because all the context is in the PR. We haven't had as much luck with reviewing general PRs where the reason for a change being good or bad could be outside the diff, and where there aren't as clearly defined rules for what should be avoided.

AtlasBarfed 1y ago

I'm wondering how much better llms are at "untyped"/loosely typed scripters like Ruby for large scale coding and error avoidance. Presumably an llm can actually maintain better contextual awareness of code and variables than, say cold loaded syntax highlights.

viraptor 1y ago
They likely aren't. I'm getting occasional issues caught by type checks in the LLM output. They would be weird crashes instead in other languages.
11217mackem 1y ago
ultimately, it comes down to training data and character count llms can be better than most humans at applescript just need a fuck ton in context
sensanaty 1y ago
As a hobby rubyist, pretty terrible compared to Typescript. I suspect it's also that there's less Ruby in the training sata, but Ruby being so dynamic and ducktypable means it produces some truly nightmarish shit from time to time

SafeDusk 1y ago

Changing my old coding behavior aside, biggest limiting factor for me is understanding how and why the coding agent is doing this a certain way, so that I have the confidence to continually sharpen my tools. I want something simple that I have full control on, if not just to understand how they work. So I made a minimal coding agent (with edit capability) that is fully functional using only seven tools: read, write, diff, browse, command, ask, and think. As an example, I can just disable `ask` tool to have it easily go full autonomous on certain tasks. Or, ask it to `think` for refactoring. Have a look at https://github.com/aperoc/toolkami https://github.com/aperoc/toolkami to see if it might be useful for you.

eschaton 1y ago
It’s producing statically likely next tokens based on its training corpus and prompts. That’s what it’s doing. It’s not analyzing your code, it’s not considering approaches, it’s not theorizing about behavior, it’s just producing statistically likely tokens. This is why I don’t touch the shit—it’s fucking snake oil.
- ekidd 1y ago
  If you "don't touch the stuff", you are probably relying on your initial impressions from 2022 to evaluate models in 2025. Also, predicting the next token with high accuracy may demand very high degrees of knowledge and reasoning. As an extreme example, please predict the next 1,000 tokens in this sequence: "ABSTRACT. In this paper, we show a mathematically elegant unification of quantum mechanics and gravity, which makes testable predictions. Testing these predictions shows that the quantum gravity model provides previously unexpected results accurate to 1 part in..." To predict the rest of that paper, it helps to actually come up with a workable model of quantum gravity. Which no current LLM can do, happily. But lots of current models are good enough at "predicting the next token" to solve high school honors math problems that they've never seen before. They can apply the chain rule, factor polynomials, double-check their work, backtrack, etc. Similarly, current-generation coding models are perfectly capable of reading compiler error messages, and generating diffs that fix the underlying problem. Current-generation summarization models are capable of reading several scientific papers, extracting the key concepts, and turning them into a fairly serviceable podcast. All of this happens because a (1) in order to predict the next token better, LLMs actually build thousands of specialized models that do things like "keep track of the state of a chess board" or "recognize lions in photos", and (2) transformer models are sufficiently powerful to model many problems well. So a big current-generation LLM is basically an ensemble of thousands of domain models glued together with a language model and a bunch of feed-forward layers. Now, none of the outputs from LLMs are of super high quality, compared to experienced humans. And there are deep reasons for that. But if you happen to have problem where medium-competence AI "slop" is actually beneficial, then yes, LLMs can actually be of real-world use.

asdev 1y ago

>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. In a serious organization, non technical people should not be shipping any sort of code. They should be doing the highest leverage things possible to help the business, and if that seems to be coding, there are grave issues in the company.

ghiculescu 1y ago
How do credibly define "non technical people" when everyone's code is written by an LLM? Serious organisations sound awful.
- asdev 1y ago
  non technical people are people who are not hired for an engineering role
wheelerwj 1y ago
This sounds like a disaster waiting to happen
n_ary 1y ago
I see a fraudulent benefit in this case. When these non-tech people go into public talks or anything, they can suddenly claim “oh, I use AI to write 80% of my code” and voila! No one will ask whether their responsibility is to write code or do any engineering, simply being able to give some surface level claims makes them credible enough and feed the hype while appearing cool. It also gives investors more confidence to shower them with money when needed, as non-tech people are also doing AI coding and they are super agile! When Msft CEO claims that 80% code written by AI, there is a 50% doubt, but when someone adds that, yeah so I have done 150 PRs, now it feels more concrete and real.
- ghiculescu 1y ago
  Author here. We don't have (or want) any investors. I encourage PMs to code because it's good for the business. Otherwise I wouldn't do it. I wrote about this years before we started doing AI-backed-coding: https://ghiculescu.substack.com/p/opening-the-codebase-up-to-everyone https://ghiculescu.substack.com/p/opening-the-codebase-up-to..., so some of the details are no longer correct, but the philosophy is the same.

deleted 1y ago

[deleted]