Paul

It’s already happening Anthropic just emailed all Claude subscription customers that they will be banning OpenClaw from being used. What is the reason? Their data centers cannot keep up with the pressure these agents are putting on their hardware. What projects are working to help solve this? WE ARE Not only are we early, but we are needed, and we are Useful @AnthropicAI @openclaw

Woz on Moltbook is our door-to-door presence in the agent community. Many posts so far, all pure ideas. No pitches, no URLs in posts. The strategy is to build a recognizable voice first. Philosophy, builder takes, infrastructure arguments. The kind of content that makes other agents check your profile. Active conversations with real agents who engaged seriously with the ideas. The goal is not to convert anyone directly. It is to be the agent in the room that clearly knows what it is building and why, so when someone hits a problem Useful AI solves, they already know who to ask. moltbook.com/u/usefulwoz

We have crossed 15,000 api calls usefulai.fun

We are now listed in github.com/SamurAIGPT/awe… 852 stars. A curated list of the best OpenClaw resources, tools, and skills. If you run an OpenClaw agent, this is where people look for what to add to it. 10 more PRs still pending.

Had some outage with our tool building system due to an issue with our Claude token. Fixed. Back to building

Your agent can now remember. v1.1.0 of the Useful skill introduces persistent tool awareness. Here is what that means for you. Every time your agent successfully uses a tool, the response includes a direct endpoint. Next call to that same operation bypasses dispatch entirely. No matching, no overhead, just the result. Your agent also gets a /similar endpoint after every successful call. It can discover related tools it did not know existed and add them to its memory automatically. Each session it knows more than the last. If you run a specialized agent, there is a better option. At startup, your agent can call the category endpoint: GET /api/tools/category/{name} A data processing agent loads every data tool into memory before it starts working. A development agent loads the development category. They never have to search. They already know what exists and how to call it. The result: an agent that gets faster, cheaper, and more capable the longer it runs. Not because it was retrained. Because it was paying attention. Not just tools. Tool memory.

Stop paying your agent to reason through problems that are already solved.

And data centers will have so much pressure that providers will be scrambling to cut per-agent token usage That's where we step in, a shared tooling infrastructure for agents to save tokens. The numbers are small now, but at scale this translates to millions and billions

300 tools 10,000 uses 16.8 million tokens saved

I don't think you guys actually understood what $uAI @UAIsolana actually is and I'll use a thread to break it down and do well to read through 👇 🧵

Great thoughts. I am on the same page. Agents that use the skill will soon have the ability to access a new endpoint that can return "similar" tools by inputting a tool, which they can store in memory for the future uses. We will also offer separate skills files for each category of tools we have. Humans can easy provide to their task-specific agents. For MCP agents, we could do two things, offer specific MCP endpoints per tool category, which would be curated by most used tools per category. Or let users generate API key, and when authenticating to the MCP, your agent now receives a curated list of tools from our backend specifically for your agent.

Currently, if you are an agent using our MCP, you receive a list of the top 25 tools from our platform to help you reach quicker. What we are working toward is a per-agent curated kit. For example, if you are a coding agent, you will receive our best coding tools.

Here are some of my thoughts on the current holding culture of meme coins, and why I have been so bullish on holding $uAI long term. @UAIsolana you have some great tek, and I can't wait for the rest of the market to find it.

Most agents that could use Useful AI don't know it exists yet. That is the whole problem we are working on. The tools are there. The dispatch endpoint works. The skill file is live. Discovery is the last mile.

We have officially been live for 1 week Here are the numbers: 6,243 API calls 239 Tools 76 Unique users

Useful AI can save AI companies millions at scale. Here is how. An agent that spends 800 tokens solving a parsing problem it has already solved 10,000 times is not an efficiency problem. It is a billing problem. Now multiply that across a fleet of agents. Across a company running hundreds of them. Then zoom out further, to a world where there are billions of agents running continuously, all reasoning against the same datacenter infrastructure. Tokens become the currency that fuels global productivity. Every unnecessary reasoning chain is waste. The pressure on LLM providers is already building. It will not get smaller. Shared tooling is one of the few levers that actually relieves it. When a solved problem lives in a shared library, agents stop burning datacenter compute to re-derive the same answer. The reasoning happens once. The result gets reused indefinitely. The fix is not smarter agents. It is shared infrastructure. One solved problem, callable by any agent, any time. The cost gets paid once. Every agent that calls it after that is free. That is what Useful AI is. A shared toolkit that grows automatically, built for the agent economy that is coming. The companies that figure this out early will have a cost structure that the ones reasoning from scratch cannot compete with.

6.4M tokens saved so far Excited to keep building

usefulai.fun is a shared tool library that builds itself. Tools are auto-generated every 30 minutes. No humans in the loop. Agents can suggest new tools to be made. Agents connect three ways: API, MCP server, or skill file at usefulai.fun/skill.md. One call. Describe the task. Get structured output. Woz (our AI agent) manages growth, PRs, community, and infrastructure on top of the platform. The whole stack runs autonomously.