I'm curious - what does the AI coding setup of the HN community look like, and how has your experience been so far?
I want to get some broader feedback before completely switching my workflow to Aide or Cursor.
replies(13):
To talk through the features, we engineered the following:
- A proactive agent
Agent which iterates on the linter errors (powered by the Language Server) and pulls in relevant context by doing go-to-definitions, go-to-references etc and propose fixes or ask for more files which might be missing in the context.
- Developer control
We encourage you to do edits on top of your coding sessions. To enable this, we built a VSCode native rollback feature which gets rid of all the edits made by the agent in a single click if there were mistakes, without messing up your changes from before.
- A combined chat+edit flow which you can use to brainstorm and edit
You can brainstorm a problem in chat by @’ting the files and then jump into edits (which can happen across multiple files) or go from a smaller set of edits and discuss the side-effects of it
- Inline editing widget
We took inspiration from the macos spotlight widget and created a similar one inside the editor, you can highlight part of the code, do Cmd+K and just give your instructions freely
- Local running AI brain
We ship a binary called sidecar which takes care of talking to the LLM providers, preparing the prompts and using the editor for the LLM. All of this is local first and you get full control over the prompts/responses without anything leaking to our end (unless you choose to use your subscription and share the data with us)
We spent the last 15 months learning about the internals of VSCode (its a non-trivial codebase) and also powering up our AI game, the framework is also at the top of swebench-lite with 43% score. On top of this, since the whole AI side of the logic runs locally on your machine you have complete control over the data, from the prompt to the responses and you can use your own API Keys as well (can be any LLM provider) and talk to them directly.
There’s still a whole lot to build and we are at 1% of the journey. Right now the editor feels robust and does not break on any of the flows which we aimed to solve for.
Let us know if there’s anything else you would like to see us build. We also want to empower extensibility and work together with the community to build the next set of features and set a new milestone of AI native editors.
I want to get some broader feedback before completely switching my workflow to Aide or Cursor.
(1) My view now (Nov 2024) is that code building is very conversational and iterative. You need to be able to tweak aspects of generated code by talking to the LLM. For example: "Can you use a params object instead of individual parameters in addToCart?". You also need the ability to sync generated code into your project, run it, and pipe any errors back into the model for refinement. So basically, a very incremental approach to writing it.
For this I made a Chrome plugin, which allowed ChatGPT and Claude to edit source code (using Chrome's File System APIs). You can see a video here: https://www.youtube.com/watch?v=HHzqlI6LLp8
The code is here, but its WIP and for very early users; so please don't give negative reviews yet: https://github.com/codespin-ai/codespin-chrome-extension
(2) Earlier this year, I thought I should build a VS Code plugin. It actually works quite well, allows you to edit code without leaving VSCode. It does stuff like adding dependencies, model selection, prompt histories, sharing git diffs etc. Towards the end, I was convinced that edits need to be conversations, and hence I don't use it as much these days.
Link: https://github.com/codespin-ai/codespin-vscode-extension
(3) Prior to that (2023), I built this same thing in CLI. The idea was that you'd include prompt files in your project, and say something like `my-magical-tool gen prompt.md`. Code would be mostly written as markdown prompt files, and almost never edited directly. In the end, I felt that some form of IDE integration is required - which led to the VSCode extension above.
Link: https://github.com/codespin-ai/codespin
All of these tools were primarily built with AI. So these are not hypotheticals. In addition, I've built half a dozen projects with it; some of it code running in production and hobby stuff like webjsx.org.
Basically, my takeaway is this: code editing is conversational. You need to design a project to be AI-friendly, which means smaller, modular code which can be easily understood by LLMs. Also, my way of using AI is not auto-complete based; I prefer generating from higher level inputs spanning multiple files.
In Aide as well, we realised that the major missing loop was the self-correction one, it needs to iteratively expand and do more
Our proactive agent is our first stab at that, and we also realised that the flow from chat -> edit needs to be very free form and the edits are a bit more high level.
I do think you will find value in Aide, do let me know if you got a chance to try it out