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    This project uses shared planning documents for collaboration with Claude Code. Please:

    1. First read and understand these files:

       - PLAN.md - current project roadmap and objectives

       - ARCHITECTURE.md - technical decisions and system design

       - TODO.md - current tasks and their status

       - DECISIONS.md - decision history with rationale

       - COLLABORATION.md - handoff notes from other tools

    2. Before making any significant changes, check these documents for:

       - Existing architectural decisions

       - Current sprint priorities

       - Tasks already in progress

       - Previous context from Claude Code

    3. After completing work, update the relevant planning documents with:

       - Task completion status

       - New decisions made

       - Any changes to architecture or approach

       - Notes for future collaboration

    Always treat these files as the single source of truth for project state.

e.g. maybe for CURSOR.md you just want to provide context and best practices without any tool-calling context (because you've found it doesn't do a great job of tool-calling), while for CLAUDE.md (for use with Claude Code) you might want to specify tools that are available to it (because it does a great job with tool calling).

Probably best if you have an AGENT.md that applies to all, and then the tools can also ingest their particular flavor in addition, which (if anything is in conflict) would trump the baseline AGENT file.

I guess having links to supplementary rules files is an option, but I'm not sure which agents (if any) would work well with that.

The whole agentic coding via CLI experience could be much improved by:

- Making it easy to see what command I last issued, without having to scroll up through reams of output hunting for context - Making it easy to spin up a proper sandbox to run sessions unattended - Etc.

Maybe for code generation, what we actually need is a code generator that is itself deterministic but uses AI, instead of AI that does code generation.

Side remark: CC is very expensive when using API billing (compared to e.g. GPT-5). Once a company adopts CC and all developers start to adapt to it at full scale, the bill will go out of the roof.

Yesterday, I was writing about a way I found to pass the same guideline documents into Claude, Gemini, and Aider CLI-coders: https://github.com/sutt/agro/blob/master/docs/case-studies/a...

Why are we purposely creating CLI dialects?

Claude Code likes to add "attribution" in commit messages, which is just pure spam.

If Cursor can build the better UX for all the use-cases, mobile/desktop chatbot, assistant, in IDE coding agent, CLI coding agent, web-based container coding agent, etc.

In theory, they can spend all their resourcing on this, so you could assume they could have those be more polished.

If they win the market-share here, than the models are just commodity, Cursor lets you pick which ever is best at any given time.

In a sense, "users" are going to get locked in on the tooling. They learn the commands, configuration, and so on of Cursor, it's a higher cost for them to re-learn a different UX. Uninstalling and re-installing another app, plugin, etc. is annoying.

I pay for Cursor and ChatGPT. I can imagine I’d pay for Gemini if I used an android. The chat bots (1) won’t keep the subscription competitive with APIs because the cost and usage models are different and (2) most chat bots today are more of a UX competition than model quality. And the only winners are ChatGPT and whatever integrated options the user has by default (Gemini, MSFT Copilot, etc).

[1]: https://github.com/google-gemini/gemini-cli/blob/main/docs/c...

The IDE/editor is for me, the agent doesn't need it. That also means I am not forced to used whatever imperfect forked IDE the agent is implemented against.

With the benefit that you can also pull in people who don't like using VSCode such as people who use Jetbrains or terminal based code editors.

cursor and 3rd party tools will, unless they make their own superior foundation model, will always have to fight the higher marginal cost battle. This is particularly bad insofar that they offer fixed pricing subscriptions. That means they’re going to have to employ more context saving tricks which are at odds with better performance.

If the cost economics result in Cursor holding, say, 20% fewer tokens in context versus model-provider coding agents, they will necessarily get worse performance, all things equal.

Unless Cursor offers something dramatically different outside of the basic agentic coding stack it’s hard to see why the market will converge to cursor.

You’re underestimating the dollars at play here. With cursor routing all your tokens, they will become a foundation model play sooner than you may think

Unless they pair up with OpenAI or Meta.

https://jules.google/

https://docs.anthropic.com/en/docs/claude-code/llm-gateway#l...

https://docs.litellm.ai/docs/tutorials/claude_responses_api

https://www.reddit.com/r/cursor/comments/1mk8ks5/discussion_...