Meta envisions its 200M business users scaling to billions as AI tools lower entrepreneurship barriers, creating a dynamic ecosystem where business agents interact with personal super-intel…

Meta reconstituted its AI lab with extreme talent density and a research-first operating model, shipping Muse Spark 1, image, and 1.1 in 11 months, with larger models imminent that aim to m…

Meta's strategy centers on making powerful models cheap and accessible to all developers, believing the best AI products haven't been built yet and that open ecosystems will drive combinato…

While the abstraction layer evolves from writing code to orchestrating agents to coordinating millions of agents, rigorous systematic thinking and a philosophical compass for directing civi…

Developing agentic AI systems that can coordinate and optimize feedback loops can generate massive alpha, as swarms of agents can accomplish the work of 100+ engineers. This creates investm…

By orchestrating agents in continuous feedback loops with clear metrics, companies can spend orders of magnitude more on tokens to drive outcomes, with internal Meta demos showing agent swa…