We’ve raised $80 million in Series A funding, co-led by the Valor Atreides AI Fund and Hummingbird Ventures, with continued participation from Conviction, Abstract, A*, and Grant Gordon. This brings our total raised to over $100 million. We started Watney by asking a simple question -- what can a robot enable in industries where the work remains valuable on an infinite horizon? We found an answer in the fundamental inputs to civilization: energy, matter, and intelligence. A robot will never be as charming as a barista or as personable as a housekeeper, but it can be more exacting than a surgeon. And, a breakthrough in one quickly becomes the capability of millions. We don’t imitate human motions or processes. We care about the new, differentiated capabilities robots can unlock. We work on problems where our choice of embodiment gives us an order of magnitude advantage, whether through precision, reliability, or scale. Compute is just beginning to transform society, but it’s constrained by execution. Since 2025, Watney has been serving the largest hyperscalers in the world, helping accelerate their compute rollout through an end-to-end deployment model. Across hundreds of thousands of hours in customer facilities, our systems have achieved more than four nines of reliability. They’ve enabled our customers to build data centers faster, at larger scales, and with more ambitious architectures. Today, we operate the largest fleet of dexterous robots running 24/7/365 across the United States. This is all to say, it's an exciting time at Watney. We’re all here because we want to see more ambition in the physical world. We are hiring across all domains. Join us.

I didn’t think autonomy would get nationwide-scale this fast... but here we are 📷! Our work with @HUMAIN and @TareqAmin_ will bring thousands of trucks to KSA. But this is just the start – followed by robotaxis, ports, mining, construction, and more. The size, scale and scope is unprecedented! Letssss go! 🚀🚀🚀

Today we're announcing our $40M Series A at a $400M valuation, led by @a16z , with participation from existing investors @8vc, @pearvc, and @BloombergBeta and new investors @HRTVentures and @nextladder. Alongside the fundraise, three more announcements: - Vals Smith: is now generally available. Anyone can create a custom coding benchmark from any GitHub repo with 120 free credits to get started. - Frontier Risk Benchmarks: We are releasing the RSI Index in collaboration with @CoreWeave and just launched ReverseEngBench, a new cyber benchmark built with Columbia University, Tufts University, UC Berkeley, and UCLA. We are also sharing our initial work in mental health, with more to come across environmental impact, military, and biosecurity. - Website + Vals Index 2.0: We completely rebuilt the Vals website and have released Vals Index 2.0, with coverage of more of the economy. Our revenue has already grown 8x compared to all of 2025. Our customer base doubled and the team tripled in 6 months. Our results have been cited in model cards from OpenAI, Anthropic, Google, Meta, and xAI. The AI economy runs on self-reported grades. When a model ships, the scores come from the company that built it. No other trillion-dollar industry works this way. Finance has ratings agencies. Medicine has the FDA. AI has vibes and vendor benchmarks. We built Vals to be the independent evaluation layer the industry is missing. Check out our new website and try Vals Smith!

Announcing Hone Intelligence has become abundant. Yet the world looks remarkably similar to how it did five years ago. With every model release, the gap between what frontier AI can do and the economic value derived from it widens. Closing the gap requires re-organizing work around organizational outcomes, not individual tasks. Hone builds AI that creates, orchestrates, and improves agents and software continuously to own organizational outcomes over weeks and months. We are ex-founders and early core contributors to Cognition, Mercor, Ramp, and OpenAI. We obsess over real-world value, not theoretical benchmarks. Our core beliefs on closing the gap in the thread below.

1/ When expert clinicians see similar cases, they often reuse stable mental templates, known as diagnostic schemas. I built a way to test whether LLMs do the same. (Below: my study group thinking through a cardiogenic shock case during med school)