u/SimulationHost

I'm on pro, 90% left, but dev harness saying rate limited. There's definitely an issue.

I'm really happy for you or sorry that happened to you bro I'm not reading all of that

You do realize that 95%+ of US frontier teams are staffed by Chinese researchers, right?

Re-read what I typed.

It runs on hardware at scale. Electricity costs something. Cooling cost something. Lower is not free. At a billion users, it's not cheap.

There is a single consciousness. You are an avatar of that consciousness expressing yourself temporarily as an individual for the purpose of learning. So you, you are in charge. As am I. We/Us/I am.

Yup

The costs to serve a billion users a day on deepseek are no cheaper

Not for the infrastructure providers they don't. The cost to upgrade from a 3G network to 4G to 5G is way cheaper than to start a 6G network from scratch. It's because the next generation of any of this has an upgrade path meant to keep companies glued to the sunk costs. There's a real reason no one has knocked NVIDIA off the throne, and that reason is CUDA and all the prior work that treats it as bedrock.

What will happen though is a very huge aftermarket of preciously loved Grace Hopper etc getting repurposed for local inference loads and private cloud compute.

It absolutely does. The entry costs are astronomical and the barriers to entry (compute, talent, resources, data) will only get higher. They can afford the billions to keep up: can anyone afford the trillions to come in late and play catch up? The richest man in the world is an also run 4th after stepping away for 2 or three years.

Reality is so much weirder than this. (actual reality, not the tax paying zombie shuffle most people accept as reality)

This is a favor to Elon Musk, the American oligarchy is alive and well

I always want to use the cheapest lane to accomplish a task. Not all local models are tool capable. Not all llm's produce efficient code. Sometimes a local model gets evaluated and routes the task to a codex, but codex is rate limited. The fallback lane reroutes to ollama deepseek pro.

Why not always pro? I don't want to burn any tokens to do cheap tasks, I'd rather save them to do expensive tasks. And rather than burn a plan, routing + fallback means I can accomplish everything I need without touching my 5 hour limits.

plus

It's a long post. Happy to answer questions, and like I said I will be sharing on github. I didn't start off trying to build this. I have a developer background and normally used VS code and dev in python and cpp. When agentic computing started to take off, I started tinkering eventually moving into agentic harnesses. I was an early adopter of codex, openclaw, but mostly as a learning exercise. I only had two rules, don't use anyone else's skills or plugins and build my own skills and extensions from scratch. Quickly I learned where the razor edges between LLM and agent harness were, and most of the issues issues I hear other people describing at some point I had. But rather than wait for a patch or a skill, I just rolled my own.

Since it was purely a learning exercise I focused on fixing the little annoyances always trying not to fork the main openclaw code. Memory management was a shit show. Context is a shit show. And everytime anyone updates a frontier model there was pain

I should say I know a lot of this will be fixed or rolled into future releases but again I was only doing it as a learning exercise

Anyway, this is what resulted. I replaced native memory with a custom SQLlite vector graph to improve speed and relevance in recall. I built a recursive learning method and something called guarenteed execution to patch over LLM bugs where agents either forget mid context what they're doing, get stuck in a loop, or drop tool handling, then I built a heuristic preselector that uses pytools to create a routing score that hands a prompt + memory based context off to a model that can answer or use tools and reasoning. This means I don't have a single model that I try to force every answer through, but it evaluates my ask and selects an appropriate model, preserves the prompt but adds context and routes it dynamically. Lastly I built a personality kernel (what I call it) that keeps my agents personality no matter what model lane answers or what happens in the frontier model upgrades.

Still doing polishing tweaks but it works good enough that anytime a frontier drops I can just ask my setup to add it, and it automatically weights it, slots it into a lane, and uses it when appropriate

In the background I have one evaluator cron that looks at different signals and evaluates performance and makes recommendations monthly for upgrades or fine tune.

It's survived every openclaw open AI upgrade for 6 months now

https://preview.redd.it/qz1vskcr4h2h1.png?width=1491&format=png&auto=webp&s=14b12b4a1b6bebd599076bc1a3ab11dd4a978663

It's a goddam shame what DEI did to those planes.

Your conscious is the only tether to this world and can move freely between the systems. Think the wifi connected to the console Mario "lives" on. Your consciousness is using that wifi right now.

I'll share something with you guys, it works for me with every code base (for context I am a developer, I use this for new code bases. This is an exact prompt I used to learn the Java based visual language Processing, as I don't have a Java background (more python, ruby, cpp)

" If I were going to learn Processing at a 200 level to achieve proficiency at using it, what are the topics I need to focus on to get started, wire it into my projects, build my hello world and then move towards mastery. What libraries would I need for Web dev or Android UI dev? What frameworks are required and what frameworks are compatible? What prerequisites must I have? What are the best use cases and practical lessons learned"

Take output from this prompt and reprompt:

"Next I'd like you to think through your syllabus and design learning modules for each, that include step by step tutorials and lessons created to reinforce the syllabus learnings. The first must be a getting set up lesson, and include step by step instructions to get your environment configured and deployed. At the end of each lesson should be a lessons learned recap. And each example should have a summary that covers a description what the lesson, example or tutorial, a summary of the main learning objectives, and an estimated time to complete."

This works with any language, stack or code base. I've found it particularly helpful wrapping my head around new git repos.

This is a curiosity question, not a you should do this question - I'm wondering if you went into settings and tweaked the personality or added custom instructions

Having tried personality tweaks, I find they drift a bit on any update, but a detailed custom instructions (which I have done but blanked out here), doesn't really

If you have done this and still see it is argumentative, maybe it's drifted a bit and you can also add a custom instruction.

https://preview.redd.it/z237hk9wg0jg1.jpeg?width=1856&format=pjpg&auto=webp&s=959bcf352dd8ab0ff047f94193086a6c378ff2ca

What is it going to take to teach Americans you do not fight in a Pizza shop, they may not all be Little Ceasars but clearly their hands are always Hot N' Ready?

Stepping in front of a turning car doesn't mean the driver was aiming at you it just means you're a dumbass and a sociopath

Choom!

Mine happened anytime, any place. I never lost consciousness, and it wasn't accompanied by headache or dizziness... Literally it was as if my vision switch flipped completely off then on again. It persisted through my 30 maybe once or twice a year (as opposed to weekly or monthly as a kid) , I've spoken to multiple doctors, had MRIs - they've never found anything.

Happened to me all the time as a kid. I would tell my mom. Went to our family GP several times, they could never establish a cause.