I want to give a try to gsd + open code + Cerebras code. Any experience?

I started playing with skills yesterday. I'm not sure if it's just easier for the LLM to call APIs inside the skill — and then move the heavier code behind an endpoint that the agent can call instead.

I have a feeling that otherwise it becomes too messy for agents to reliably handle a lot of complex stuff.

For example, I have OpenClaw automatically looking for trending papers, turning them into fun stories, and then sending me the text via Telegram so I can listen to it in the ElevenLabs app.

I'm not sure whether it's better to have the story-generating system behind an API or to code it as a skill — especially since OpenClaw already does a lot of other stuff for me.

It seems cool! How to use it for free with acceptable quality? Also what are the alternative for a personal assistant that remember stuff automatically and message you about it?

Electronic devices are very effective distraction tools, especially phones. Companies and apps leverage our psychology and biology to get our attention, but we can take control of what we interact with—and if we remove the hooks, they won't be able to exploit them anymore.

What could help is taking control of how devices interact with us, rather than letting other people control that. This includes deciding which apps can be installed, how often they can notify or distract us, and so on.

A very basic step is using an app blocker. The ideal solution would be a phone with a local AI that is aligned with my personal preferences and instructions.

For example, it could deliver news just once a week from outlets across the entire political spectrum, eliminate social media entirely, and surface only important emails and messages at the most appropriate times.

I see LLMs as searchers with the ability to change the data a little and stay in a valid space. If you think of them like searchers, it becomes automatic to make the search easy (small context, small precise questions), and you won't keep trying again and again if the code isn't working(no data in the training). Also, you will realize that if a language is not well represented in the training data, they may not work well.

The more specific and concise you are, the easier it will be for the searcher. Also, the less modification, the better, because the more you try to move away from the data in the training set, the higher the probability of errors.

I would do it like this:

1. Open the project in Zed 2. Add the Gemini CLI, Qwen code, or Claude to the agent system (use Gemini or Qwen if you want to do it for free, or Claude if you want to pay for it) 3. Ask it to correct a file (if the files are huge, it might be better to split them first) 4. Test if it works 5. If not, try feeding the file and the request to Grok or Gemini 3 Chat 6. If nothing works, do it manually

If instead you want to start something new, one-shot prompting can work pretty well, even for large tasks, if the data is in the training set. Ultimately, I see LLMs as a way to legally copy the code of other coders more than anything else

Wow! Kudos for thinking it was possible and making it happen. I was wondering how long it would be before big local models were possible under 10k—pretty impressive. Qwen3-235B can do mundane chat, coding, and agentic tasks pretty well.

I am not sure I am doing it the right way or if there's a right way, but what I do is generate small files one at a time, with a functional system of stateless input/output. That way I can focus first on architecture, then on stateless input/output Lego blocks, and just ask the AI to generate the Lego blocks. Like this, everything is easy to keep in mind and update and change after experiencing the tech and having emotions telling me what to change. It has been working great for me. It strikes a good balance between simple and robust, fast to build, plus easy to update. The other thing is that since I haven't spent too much energy on writing the code, it is very easy to detach emotionally from it when reality gives me new info that requires throwing out part of the system.