Ronak Malde
@rronak_ • 10,099 subscribers
Co-Founder of Trajectory @TrajectoryLabs prev @GoogleDeepmind, SWE-1 @windsurf | @stanford
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Today, Michael Elabd, Arjun Karanam, and I are excited to announce Trajectory. We are a research lab and product company building the platform for Continual Learning. Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. Trajectory We’ve raised $15M from Conviction, Bessemer, Radical Ventures, Jeff Dean, Fei-Fei Li and more. We’re partnering with some of the best AI-native companies: Clay AI Harvey, Decagon, Mercor, Rogo to power their agentic systems, some of which we are already in production with. We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma. AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.
Ronak Malde1,807,803 просмотров • 1 месяц назад
Ever since we launched windsurf, one of my internal evals for coding agents has been recreating the game SUPERHOT, a puzzle/action game where time only moves when you move. It's the perfect test of tricky game mechanics, simple but beautiful art style, and balancing level design. I have a robust prompt instructing the agent to make SUPERCOLD, and attach a reference image, and also allow 3 follow-up prompts that points out any mechnical issues. When Sonnet 3.5 came out, it could barely generate the world at all. Sonnet 3.7 and you could move around in the world, but it was still hilariously unplayable. Now, Opus 4.7 and it's playable, but still doesn't look great. What's needed to get all the way there? 1. Visual taste: Given a reference image, models should be able to discern whether their final output matches the reference image style. Shading, character design, etc, models should be unsatisfied with their current output 2. Stronger computer use: Frontier models somewhat attempt this, but agent should be able to play the entire level themselves, and iterate from there 3. Systems design: Complex projects are not yet written with scalable systems design as an experienced engineer would write it. This hinders the ability to create complex projects with a lot of moving parts. We're rapidly accelerating AI progress, let's see where we land in 3 months!
Ronak Malde151,857 просмотров • 1 месяц назад
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