LLM code-aware chats: continue.dev, with Claude 3.5
Autocompletions: GitHub Copilot, still it’s better that Mistral small code models in my opinion
Ask HN: How have you integrated LLMs in your development workflow?
31–40 of 78 posts
Re: Ask HN: How have you integrated LLMs in your development workflow?
#32I find LLMs via Aider great for: * code translation - e.g. convert a self-contained implementation of a numerical algorithm from one language to another and generate test cases and property tests which make sure the implementations are equivalent. The goal is to avoid having to proof read the generated code. * one-off scripts - any task where code design doesn't matter, the amount of code is limited to couple hundred…
Why aider?
Not OP but aider is pretty useful because it can write files in your repo, run commands commit changes etc. It's pretty flexible and easy to give it context by just providing a path.
Re: Ask HN: How have you integrated LLMs in your development workflow?
#33I built a simple desktop tool [1] to streamline my coding workflow with LLMs, like integrating with local code context, managing prompts and custom instructions, etc. It supports copy/paste into ChatGPT/Claude, and sending prompts via API.
Currently I estimate it writes about 70% to 80% code (including adding features to the tool itself), and saved me hours of work per week.
Lately I've been exclusively using API since it is cheaper than paying $20 monthly subscription.
Re: Ask HN: How have you integrated LLMs in your development workflow?
#34I've been using Zed with Claude 3.5 for a few weeks now, and I find it incredibly useful. Being able to be in full control what goes into the context, my workflow is usually
- add files, tabs, terminal output and IDE diagnostics into the context via slash commands - feed in documentation or other remote web content, also via simple slash commands - activate workflow mode, which will help you edit the files instead of having to copy things around - then ask questions, ask for refactoring, ask for new features
Often I like to ask for the high level approach, and if I agree with it let it guide the implementation. It makes mistakes, so I always have to validate and test what it creates, but as you add more information into the context and the LLM has a good amount of stuff to work with, the output quality really improves significantly.
It's a process though, and it takes time to get familiar with the workflow, build intuition when the LLM falls on its face, when you should try a different approach etc.
Generally I can echo what others have said, it works best if you already kind of know what you want to achieve and just use the LLM as an assistant that does the grunt work for you, documents the process, provides a rubber duck etc.
Generally, I would not want to work without an integrated LLM anymore, it provides that much value to my workflow. No panacea, no silver bullet, but when used right in the right circumstances it can be incredibly useful.
A secondary usecase for me is working on repositories where tasks and todos are structured in markdown files (even things like travel planning). Letting the LLM Guide you through todos and create a documentation trail through the process, identify important todos, carry along information as you go is wonderful, I would absolutely give that a try as well.
Re: Ask HN: How have you integrated LLMs in your development workflow?
#35The competition in AI editors is a bit silly at the moment. Everyone and their dog are "building" an AI assisted editor now by duct taping Ollama onto VS Code. I don't like my data being sent to untrusted parties, so I cannot evaluate most of these. On top of that, the things keep evolving as well, and editors that I dismissed a few months ago, are now all of a sudden turning into amazing productivity boosters, thanks to developments in both models as well as in editor tricks.
My money is on Cursor [1], which does not stop to amaze me, and seems to get a lot of traction. The integration is very clever, and it is scary how it figures out what I intend to do. Then again, I'm probably doing mundane tasks most of the time. For the few bright moments in my day I tend to use ChatGPT, because most of my real problems are in application domains, not in code.
I am not a firm believer in forking large open-source projects, though, as it will take a lot of effort to keep up with future diversions. This makes me a bit wary of projects such as Cursor and Void [2]. Somebody needs deep pockets to sustainably surpass the popularity of VS Code. To point out just one problem with forking: VS Code works fine in Ubuntu, but Cursor does not work out of the box there. Having to disable the sandbox is a show-stopper for most.
In that respect, the extensions might be a safer bet, and I think Sourcegraph's Cody and Continue are making the largest waves there. Hard to tell with so many waves.
Re: Ask HN: How have you integrated LLMs in your development workflow?
#36I write more than I code, but I use ChatGPT a lot throughout the day.
I am integrating AI translations into my custom static site generator. I will test the outcome heavily before putting my name (and a big warning) on my translated content, but the early results look good. Getting it right is a lot harder than piping the page through ChatGPT. Everything needs to be translated from the UI strings to the URL slugs.
My work will no longer just benefit English-speaking immigrants, but also locals and immigrants who Google things in other languages. I am very excited about it.
I also use ChatGPT heavily for “what’s the word/expression for” questions and other fuzzy language queries. As a non-native speaker, I want to know if a given expression is appropriate for the context, if it’s dated, if it’s too informal and if it’s dialect-appropriate.
I also use it for coding, but mostly because it’s faster than reading python’s docs. I ask it questions I know the answer to, hoping to find better approaches. So much happened since Python 2.7, and I don’t always know what to ask for.
On occasion I treat it like I treated my mom as a child. I ask it all sorts of questions about the world I observe around me. It’s amazing to get a short, clear answer to work from, instead of sifting through barely relevant, spammy search results. This is super helpful when getting to know new tech and figuring out what it actually is.
It’s just so damn cool to have a sort of real-life Hitchhiker’s Guide slash Pokédex in my pocket. These things appeared in the span of a year, and nobody seems impressed. Well, I am mad impressed.
Re: Ask HN: How have you integrated LLMs in your development workflow?
#37I've tried it, and I don't like it. There's too much confabulation to be useful as code completion, and any task more complicated than that results in logic errors most of the time.
Code completion was fine without LLMs, and solving problems myself usually ends up being quicker than trying to coerce an LLM into doing it correctly and then verifying that the output is actually correct.
The one time I used an LLM in my workflow to good success was using ChatGPT to automatically create an enum of every EU/EEA country and a switch statement over that enum. Those sort of "grunt work" tasks that don't require any thinking, but a lot of typing, seem to be where LLMs shine.
Re: Ask HN: How have you integrated LLMs in your development workflow?
#38I only use it to get a sense of a project. Instead of looking for a similar project (and ending up in medium hell), I now ask claude some first steps. I can continue from there. It's like helping out a friend get his project doing g
Re: Ask HN: How have you integrated LLMs in your development workflow?
#39I enjoy using the Projects feature of Claude. You have a workspace to add knowledge (file/image/text) that you are able to update and maintain throughout multiple discussions.
How is Claude performing when project grows and things get more complicated?
I had some issues with both gpt4 and sonnet getting slower and doing pointless refactors as project grows
Re: Ask HN: How have you integrated LLMs in your development workflow?
#40I wrote my own Notebook Assistent and I use it to quickly make data driven arguments. It is able to both code and read program outputs so it's very good at pulling remote sources, then peeking at the result, doing the data wrangling and then displaying the output. I think having the LLM being able to read program state is a big upgrade for what you can achieve, it can do test driven development for example because it can read the test report. However, being a side project limits the fluidity of the UX, it's open source and buildless though if you want to modify it.its very hackable by design.
https://observablehq.com/@tomlarkworthy/robocoop