“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof. today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data. open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise. with castform, model training is as simple as prompt engineering. @castformai bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns. see what you can build with castform👇

i am at the frontier

Hebbian Robotics has joined @ycombinator's S26 batch! @bdono_ and I started @hbr_pbc because we believe the next generation of infrastructure will be built and maintained in places that are increasingly difficult for people to access safely and consistently: remote sites, subsea environments, orbit, and other demanding field conditions. Our goal is to build human-like robots that can work alongside expert field teams to help construct, inspect, maintain, and repair the systems that communities and industries rely on. YC will help us accelerate as we continue building toward that mission. Thanks @sdianahu for taking a chance on us! We are grateful to the early believers who supported us when there was not much to show beyond conviction, early prototypes, and a lot of work ahead. Your trust, feedback, and encouragement have meant a lot. There is still plenty to build, learn, and prove, but we are excited for what is ahead. We are grateful to be working with partners who share our mission in developing robotics to extend what humanity can do for the benefit of the communities they serve.

Samir Menon @blintzbase and I are thrilled to announce Sail @sailresearchco ! We build infrastructure for long-horizon agents: inference served at unbeatable prices-per-token for open models, plus sandboxes designed to run for days, weeks, or longer. We've raised $80M, w/ our seed led by @Sequoia and series A led by @KleinerPerkins. We're using this capital to build the most efficient infrastructure for long-horizon agents. What makes agents so different? Unlike a human waiting at a keyboard (top priority: speed), agents need scale, reliability, and sustainable cost. Sail finds this efficiency everywhere in the stack: we carefully choose our chips, write custom inference engines, and run a global controller that fully utilizes every computer in our fleet. Tight integration from silicon to API lets Sail open up the cost / latency frontier to our customers - the most patient agents can now access 10x more intelligence per dollar. We're excited to be working with great companies like @parallelweb, @detaildotdev,@Jackandjillai, and @quadrillion_ai to deploy long-horizon agents with trillions of tokens. Our team is thoughtful in our engineering craft and relentlessly ambitious in our pursuit of peak performance. We previously trained at companies like NVIDIA, OpenAI, Google, and so many trading firms. Now we're ready to do the work that will define our careers, in the most compute intensive market of all time. Welcome to the era of abundant intelligence. We can't wait to build with you!

very well-written piece. "Private reinforcement learning environments should let models grow stronger on real traces from inside the organization. Its knowledge base makes institutional memory queryable and use of tokens more efficient. This loop becomes the new IP of the firm. I think of it as a hill climbing machine. And unlike most assets, it compounds."

with the events around fable, it’s clear that companies & developers need to own their models. the ability to post-train & rl models must become a more broadly accessible skill. rl fine tuning sounds like rocket science, but it really isn’t. so @Thariq_q (not the claude code guy :D) made a video that explains it with as little jargon as possible👇

💯 agree. we are building @castformai to empower any developer in the world to be able to do this

one of the most exciting surprises from the launch has been seeing just how diverse the developer use cases are for custom models. human creativity is really unmatched :) we really want to help bring more of these ideas to life. so, we’re giving away $1,000 in free credits to folks with compelling ideas they want to train. just reply to the post with your idea, or email us at castie[at]castform[dot]com

This looks like a good way to get started with training your own model.