Today, we’re announcing Zeroset’s $5.2M pre-seed round to deploy world models into enterprises, co-led by @GradientVC and @2048vc, with participation from Leblon Capital and others. Frontier intelligence is capable of enormously complex tasks. And yet with an abundance of general capability and mandate, automation still requires enormous handwork. The models and systems that exist today lack an understanding of the world they act in. Robotics faced a similar problem. Building capable robots required more than compute-scaling on policies; they needed representations of their environments, encoding state and how it changed under actions. Over time, those representations shifted from hand-specified states toward learned models of the world. What is missing in the enterprise is a general system that represents work and learns from it. At Zeroset, we believe the same paradigm that enabled progress in robotics can be applied to represent enterprise “worlds.” We open with Nebula, a system that captures the state and traces created as people and agents work across systems, using them to model how an enterprise works and changes over time. These models contain the decisions, dependencies, and unwritten processes bespoke to a company. They are derived from the enterprise, and they should belong to the enterprise. Companies should be able to use the best models for their work and train them on their own operating knowledge freely. The underlying system does not need to change. Nebula is currently in closed research preview. If your team is automating complex work or exploring how to learn from the work your organization already does, please contact us. We are building the system through which that intelligence becomes increasingly specialized to the enterprise, allowing agents to act through it, and models to learn from it. If you’d like to join us in building this future, we’re hiring researchers and systems engineers. Read more here: businessinsider.com/zeroset-…

Happy ship it Sunday! This week I show off how I code in my browser with Radius, and brag about supporting 1Passsword (upvotes the the left). Check it out, link in bio!

SITUATION DETECTED: McDonald’s is using an AI “pricing engine” to analyze millions of daily transactions across 14,000 U.S. restaurants, estimate each area’s willingness to pay, and then generate what it calls “the optimal price” for every menu item at each store, per Reuters.

We are terminating Chris Degnan for unethical conduct involving Cognition. The last few months have seen incredible progress in AI capabilities. San Francisco has flourished as new companies that solve new, more ambitious problems are finding great success. Generally, it is a wonderful time to be building. We at @FactoryAI have seen overwhelming interest in our model-agnostic coding agents and our software factory product. Our team has 10x’d in size, while our revenue has 100x’d year over year. This momentum has been unprecedented. A much larger competitor, Cognition (makers of Devin) has fallen behind us on the capabilities that matter most to customers: cost, quality, and security. Instead of competing in the market, Cognition engineers feigned interviews with us to pry information about our product. Not finding what they were looking for, Cognition has decided to throw their weight and money at people with direct knowledge of our most confidential plans. It feels as though ethics is being thrown out of the window in the AI era. People are willing to do anything, including exploiting privileged information and violating ethical boundaries. I think this is unique to our time, and I don’t think it’s right. Integrity still matters. Yesterday, I made the decision to immediately terminate Christopher Degnan’s roles as a Board Observer and Advisor to Factory, after over a year of service. Prior to this decision, Chris told me he had a casual conversation with an executive at Cognition AI. When I questioned his intentions, he reassured me that ethics aside, he had “made too much money” and was “too lazy to go work for Cognition,” which I trusted and believed. On Monday, Chris spent time advising the Factory team on a handful of confidential board-level matters. That evening, he called me to say that the conversation that was initially described as casual and one-off was actually formal and recurring. For weeks, while he sat in our board meetings and advised our leadership team, he was also confiding with executives of our largest competitor. Chris was subject to confidentiality obligations in connection with his work with Factory. We do not know the extent of the information he shared, but it puts his timely questions about our product roadmap and what the parity gap involves into a new light. It is sad to sever a relationship with someone who has been a trusted advisor - and even a close friend - for over a year. But Chris’s conduct is unacceptable to me. Trust in Board Membership is one of the sacred bonds in the Silicon Valley, one that helps the startup ecosystem thrive. With it comes an enormous responsibility. That trust was violated. Competition is good. I respect and in many cases admire our competitors. San Francisco is a beautiful, singular place where the bold and ambitious go to defy the norms and precedents of the past. But certain principles that must remain. Violating ethics to seek advantage turns what should be positive-sum into zero-sum. We all love technology. And we all love to compete. But we must hold ourselves to a higher standard. The future of software engineering comes with abundance that will impact every person on Earth. Building that future comes with immense responsibility. We must build and compete with integrity.

The GUI is the final obstacle. Instinct is really close to getting it right, but ideally I can just talk to Siri and it'll do everything for me.

Peter Thiel: "I probably still play way too much chess on the internet all the time." "It's this very beautiful, somewhat dangerously addictive game." "At various points of delusion in my teenage years, I liked to say that everything in the world, if you didn't play chess, you didn't understand reality." "It's probably too extreme a thing to say." Via Mathias Döpfner

When your agent plans to make edits, it suggests multiple (ordered) files to read as context. Adding a cheap Jev gate on every request to read a file that your agents makes can save you about 24% time and 15% money in a method that is both more accurate and significantly more efficient (time and cost wise) than if you had used a small model (Luna) instead. It also does significantly better than if you had chosen to just choose the top 6-7 files every time. Think this could be a real unlock to quicker, cleaner, cheaper code