aye-chat

l unnecessary as long as there is a strong safety net to allow easy rollback of the changes. Yes, the idea is not exactly groundbreaking: other tools already offer "set a dangerous flag and remember to recover later" settings, but what I am exploring is defaults, not capability. With Aye Chat, the default is the opposite: apply immediately and make undo trivial. There are no flags to remember, no mode switches, and you don't need to exit the tool to roll back. You can watch a 1-minute demo here: https://youtu.be/h5laV5y4IrM Basically, the typical workflow goes like this (instead of a chat window, you stay in your terminal): $ aye chat # starts the session > fix the bug in server.py Fixed undefined variable on line 42 > vim server.py [opens real Vim, returns to chat after] > refactor: make it async Updated server.py with async/await > pytest Tests fail > restore Reverted last changes I use Aye Chat both in my work projects and to build Aye Chat itself. Recently, I used it to implement a local vector search engine in just a few days. Lower-level technical details that went into the tool: The snapshot engine is a Python-based implementation that serves as a lightweight version control layer. For retrieval, we intentionally avoided PyTorch to keep installs lightweight. Instead, we use ChromaDB with ONNXMiniLM-L6_V2 running on onnxruntime. File indexing runs in the background using a fast coarse pass followed by AST-based refinement. What I learned: The key realization was that the bottleneck in AI coding is often the interface, not the model. By shifting to the AI writing code immediately with users still maintaining full control to undo those changes - we eliminate the cognitive load of the review-and-approve loop. I also learned that early users do not accept a custom snapshot engine, so to make it professional-grade we are now integrating it with git refs. What I’d love feedback on: - After using it for a while, did replacing approvals with undo actually change how you work, or did it feel no different from existing terminal-based AI tools (GitHub Copilot CLI, Claude Code)? - Was there a moment when this started to feel natural to use, or did it never quite click? There is a 1-line quick install: pip install ayechat Homebrew and Windows installer are also available. Repo: https://github.com/acrotron/aye-chat. If you find it interesting, a repo star would mean a lot! It's early days, but Aye Chat is working well for me. I would love to get your feedback. Feel free to hop into the Discord (https://discord.gg/ZexraQYH77) and let me know how it goes.

via OpenRouter, direct OpenAI API usage with your key, and also includes an offline local model (Qwen2.5 Coder 7B). You can watch a ~1-minute demo here: https://youtu.be/i-vGI6-kP4c Basically, the typical workflow goes like this (instead of a chat window, you stay in your terminal): $ aye chat # starts the session > fix the bug in server.py Fixed undefined variable on line 42 > vim server.py [opens real Vim, returns to chat after] > refactor: make it async Updated server.py with async/await > pytest Tests fail > restore Reverted last changes I use Aye Chat both in my work projects and to build Aye Chat itself. Recently, I used it to implement a local vector search engine in just a few days. Lower-level technical details that went into the tool: The snapshot engine is a Python-based implementation that serves as a lightweight version control layer. For retrieval, we intentionally avoided PyTorch to keep installs lightweight. Instead, we use ChromaDB with ONNXMiniLM-L6_V2 running on onnxruntime. File indexing runs in the background using a fast coarse pass followed by AST-based refinement. What I learned: The key realization was that the bottleneck in AI coding is often the interface, not the model. I also learned that early users do not accept a custom snapshot engine, so to make it professional-grade we are now integrating it with git refs. What I'd love feedback on: - Does the snapshot safety net give you enough confidence to let the AI write files directly, or does it still feel too risky? - Shell integration: does the ability to execute native commands and prompt the AI from a unified terminal interface solve the context-switching problem for you? There is a 1-line quick install: pip install ayechat Homebrew and Windows installer are also available. It's early days, but Aye Chat is working well and is legitimately the tool I reach for first when I want to iterate faster. I would love to get your feedback. Feel free to hop into the Discord (https://discord.gg/ZexraQYH77) and let me know how it goes. If you find it interesting, a repo star would mean a lot!

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at's possible or do you think it would be a wasted effort and that kind of improvement would not happen? The source is here - give it a star if you like what you see: https://github.com/acrotron/aye-chat

ared to that - I now realize that what I originally built (an AI helper for a terminal: https://github.com/acrotron/aye-chat) is on the "naive" side: prompt until you either get it right from AI or give up and try from the beginning - and with this context generation approach explained I think I will start moving to the agent-based implementation while keeping control plane still in the terminal: current implementation works on smaller code bases but with this approach should be able to cover larger ones as well. With these techs developing so fast - I think it's just a matter of keeping up with the news - and be aware of what's being done successfully, and unfortunately that's not always easy to do. This one specifically - to let go of code reviews and learning how to work with spec files only - will require mentality change, and it will be a psychological barrier to overcome.

aude Opus model in Aye Chat environment. Happy hacking! - and looking forward to your feedback