the single biggest thing people are missing about @crawlnetwork: we're not another crypto agent project, another autonomous agent swarm, or another llm wrapper dressed up as a serious agentic product we're the first small llm lab focused on building a small niche model trained on crypto data and we've already started: 3 versions of our llm are trained, and their open weights are public on hugging face but that's where our philosophy, and the fact that we're built on crypto, becomes important: you don't just watch the model get trained you take part in training it. you have crawlers: in essence, agents with an identity layer through nfts. agents that roam the internet freely, collect data from every corner of it, and train the first narrow crypto ai model on it and anyone can steer what the model learns: you place an order, and the crawlers go read the site you point them at, so the llm trains on that data. anyone can watch, live, exactly what data the model is training on. every crawler's screen streams in real time, and the whole build happens in public so what does it actually mean? why would anyone need a narrow crypto llm when gpt and claude exist? the answer is simple: narrow wins big general models know a little about everything, while a narrow model knows its domain perfectly. it's been proven again and again: a 27M-parameter model trained on just 1,000 sudoku puzzles solves the hardest ones, where frontier llms score 0%. a model trained only on the rubik's cube solves every scramble in the fewest moves possible outperforming large models so crawlnet is the first experiment of its kind: an llm trained for one narrow job - crypto. for the first time ever, live transactions, chain history, fundraising rounds, polymarket odds and charts go straight into a model's weights, into its long-term memory, so the model actually remembers the market and the 800 agents we just released on crawl.md are not nfts sitting next to the project - they're what gives the agents an identity. an agent is a worker that actually runs on the llm, does a useful job training it, and gets paid for it. every agent is credited on the model's hugging face card and written right into its weights: when the queen thinks, she knows which of the 1,000 agents a piece of knowledge came from. so the identity really becomes part of the next layer: the larger intelligence it is helping to build and you can own it a lab, building in public, owned by the people who train it crawlnet.network