486 community available in the Cursor directory
[https://gist.github.com/jasonkneen/4c065df2d7a95610e4fd30c3e3398b17](https://gist.github.com/jasonkneen/4c065df2d7a95610e4fd30c3e3398b17)
Anyone else here doing full-stack Next.js in Cursor and watching the Claude quota evaporate before lunch? I used to be in the same boat — massive context windows from all the components, pages, and DB logic would smoke the default limits fast. Not anymore. I’ve been on this setup for weeks and basically never hit a wall while still getting top-tier answers. Here’s exactly what I do: **1. .cursorrules is non-negotiable** I keep one in the root of every project. The key line I added: “Never explain the code to me. Just output the code blocks.” That single rule saves me thousands of output tokens a day. No more walls of “here’s what I changed and why” — just the goods. **2. Stopped using Cursor’s built-in Claude quota** I killed the default Cursor Pro subscription for the heavy stuff. Instead I use my own API keys and point Cursor’s “OpenAI Compatible” base URL at LLM Router Gateway. Inside [llmrouter](https://llmrouter.app/) routing settings I set up simple tags routing like this: * **UI & CSS tweaks**: gemini-3.1-flash → gpt-5.4-mini * **Deep backend / complex logic**: claude-opus-4.6 → deepseek-v3.2 * **General / quick questions**: llama-4-scout I sorted the fallback chains by speed vs intelligence. The router auto-detects the query type, so 90% of my UI polish and small fixes go to Gemini (basically free + huge context). I only actually hit Claude Opus 4.6 when I’m doing nasty database refactors or tricky architecture stuff. My Anthropic bill dropped \~70% overnight. **3. Cmd+K for everything small** Don’t open the full chat sidebar just to rename a variable or extract a component. Highlight the code, hit Cmd+K, let a fast model handle the inline edit. Saves a ton of tokens and feels way snappier. That’s it. Super simple but it completely changed how much I can actually use Cursor in a day. How are you all managing the limits? Using a Cursor Team? Or did you build your own router hacks too? Drop your setups — always looking to steal better ideas.
So I used to be a big cursor fan - striked the right balance between trusting the AI and being able to check the work. The new version however, sucks. Worktrees are now essentially AI initiated magic git commands that require manual approval, which is slow and annoying, and means I have to read through a bunch of git guff, and I have to wait like a minute before it does any real work for it to essentially do something that can be duplicated with a script, and it doesn't work well half the time - it had to retry twice to apply worktree changes! The new agent screen is pretty useless, because now you need to go and select a bunch of information that previously would be entirely obvious from context i.e. alt-tabbing into a specific repo's IDE. I don't like this direction and if they continue, I might start looking at competitors. Cursor is clearly aimed at and used by developers who can read code and want to read the code produced by AI. I use Claude Code if I want to just trust the AI.
We’re introducing Cursor 3. It is simpler, more powerful, and built for a world where all code is written by agents, while keeping the depth of a development environment. With the new Cursor, you can run as many agents as you want, everywhere you want: locally, in a worktree, on remote ssh, and in the cloud. And it has the best parts of the editor available when you need them. The new interface is available as a separate window that complements the IDE. Update Cursor to try it. We recently launched Composer 2, a frontier model with high limits. Then, with cloud, we gave agents their own computers so they can work truly autonomously. And now with Cursor 3, we’re releasing a new interface to collaborate with agents on software.
Cursor 3 out now
They kinda cute
Anyone got any workarounds to this? Got the meme from [ijustvibecodedthis.com](http://ijustvibecodedthis.com) (the AI coding newsletter thingy)
so i am using cursor for over 6 month now and the company that i work gave us Claude code. i always saw in in social media how people brag that Claude run for hours without stopping and for me the longest session with cursor was 20-30 minutes with no stops. so long story short now i understand why it just that Claude code is so fucking slow
Cursor can now search millions of files and find results in milliseconds. This dramatically speeds up how fast agents complete tasks. We're sharing how we built Instant Grep, including the algorithms and tradeoffs behind the design. [https://cursor.com/blog/fast-regex-search](https://cursor.com/blog/fast-regex-search)
all 100 are cooked... saw this meme on [ijustvibecodedthis.com](http://ijustvibecodedthis.com) (the ai coding newsletter) so credit to them!!
Nothing speaks louder than recognition from your peers
End. Bye. Done. Finished. Bye. Finished. End, Bye...
Thanks Kimi For the support!
Indeed, Composer 2 is kimi k2
Cursor just released Kimposer
context: cursor new model composer 2 is based on kimi k2.5 but does not indicate the source
composer 2 is just Kimi K2.5 with RL?????
All for 20 dollars? Thanks Cursor! XD
Composer 2 is now available in Cursor. It's frontier-level at coding, priced at $0.50/M input and $2.50/M output. There is also a faster variant with the same intelligence at $1.50/M input and $7.50/M output. These quality improvements come from our first continued pretraining run, providing a far stronger base to scale our reinforcement learning. Learn more: [https://cursor.com/blog/composer-2](https://cursor.com/blog/composer-2)
Since the latest update of Cursor AI, I have accidently pressed the "Undo All" button for several times as it appears right at the place the "Keep All" button was for last X times. Does anybody have a fix for that?
This mode is amazing at adding its own instrumentation then testing and confirming its hypothesis. I love it! Good job Cursor 👌
I don’t even know what to say about this it’s ridiculous. What do you even say in this PR
GPT 5.4 is now available in Cursor and leading benchmarks
I have been building with AI agents for \~18 months and realized I was doing what a lot of us do: leaving the model set to the most expensive option and never touching it again. I pulled a few weeks of my own prompts and found: * \~60–70% were standard feature work Sonnet could handle just fine * 15–20% were debugging/troubleshooting * a big chunk were pure git / rename / formatting tasks that Haiku handles identically at 90% less cost The problem is not knowledge; we all know we should switch models. The problem is friction. When you are in flow, you do not want to think about the dropdown. So I wrote a small local hook that runs before each prompt is sent in Cursor. It sits alongside Auto; Auto picks between a small set of server-side models, this just makes sure that when I do choose Opus/Sonnet/Haiku, I am not wildly overpaying for trivial tasks. **It:** * reads the prompt + current model * uses simple keyword rules to classify the task (git ops, feature work, architecture / deep analysis) * blocks if I am obviously overpaying (e.g. Opus for git commit) and suggests Haiku/Sonnet * blocks if I am underpowered (Sonnet/Haiku for architecture) and suggests Opus * lets everything else through * ! prefix bypasses it completely if I disagree **It is:** * 3 files (bash + python3 + JSON) * no proxy, no API calls, no external services * fail-open: if it hangs, Cursor just proceeds normally On a retroactive analysis of my prompts it would have cut \~50–70% of my AI spend with no drop in quality, and it got 12/12 real test prompts right after a bit of tuning. I open-sourced it here if anyone wants to use or improve it: [https://github.com/coyvalyss1/model-matchmaker](https://github.com/coyvalyss1/model-matchmaker) I am mostly curious what other people's breakdown looks like once you run it on your own usage. Do you see the same "Opus for git commit" pattern, or something different?