We ended up open sourcing that runtime if anyone is interested:

https://github.com/Vanclief/agent-composer

My personal hypothesis is that when using LLMs, you are only faster if you would be doing things like boilerplate code. For the rest, LLMs don't really make you faster but can make your code quality higher, which means better implementation and caching bugs earlier. I am a big fan of giving the diff of a commit to an LLM that has a file MCP so he can search for files in the repo and having it point any mistakes I have made.

However I feel what we really need is to have an open source version of it where you can pass any model and also you can compare different models answers.

(Aider and other alternatives really doesn't feel as good to use as Claude Code)

I know this is not what anthropic would want to do as it removes their moat, but as a consumer I just want the best model and not be tied to an ecosystem. (Which I imagine is the largest fear of LLM model providers)

I would expect that there have been multiple nuclear power plants that provide a net positive return, specially on countries like France where 70% of their energy is nuclear.

Douyin (The Chinese Tiktok version) limits users under 14 to 40 minutes per day and primarily serves educational content, while TikTok's algorithm outside China optimizes for maximum engagement regardless of content quality or user wellbeing.

US tech companies pursuing profit at the expense of user wellbeing is concerning and deserves its own topic. However, there is a fundamental difference between a profit driven company operating under US legal constraints and oversight, versus a platform forced to serve the strategic interests of a foreign government that keeps acting in bad faith.

If I need to do something more high level or that requires multiple files I still copy and paste to Claude / ChatGPT.

https://github.com/yetone/avante.nvim

We are a small SaaS that has very happy paying customers and a huge market. We solve a boring problem, with boring technologies and we are not the next OpenAI or Stripe. Yet we have easily a 10,000 X potential.

I feel like YC now prioritizes funding things that can be hyped more instead of actually funding things that can be solid software businesses.

From all my friends that are using LLMs, we software engineers are the ones that are taking the most advantage of it.

I am in no way fearful I am becoming irrelevant, on the opposite, I am actually very excited about these developments.

I also felt that Go errors where too bare-bones, so I developed a small package (https://github.com/Vanclief/ez) based on an awesome post that I saw here once. I use this package in all Golang code I touch.

I second this 100%

This for me is a major red flag. It could maybe be mitigated if OP would require customers to run their own instance of cc.dev.

I personally find myself choosing go because I feel I am way more productive with the language. By keeping me constrained, I have less choices to make on how I solve the problem, and focus more on solving the problem.