Engineering at Meta

The 2026 Python Typing Survey received 1,794 responses. Type hint use changed little across three years, but checker selection changed sharply. Among respondents who reported which checkers they use, half selected more than one, and missing library type information was the most common difficulty. For the third consecutive year, we asked Python developers how they [...] Read More... The post Python Typing Survey 2026: AI Tools and the Shifting Checker Landscape appeared first on Engineering at Meta.

At the 2026 Open Compute Project (OCP) Global Summit, Meta shared the networking innovations that are directly supporting our latest AI models, including Muse Wonder and Muse Spark, and our gigawatt-scale Prometheus cluster. Highlights IcePack & IceCube: Meta’s first liquid-cooled network rack with 102.4T switch blades (128×800G, Broadcom Tomahawk 6C and NVIDIA Spectrum-6 variants), running [...] Read More... The post Meta Networking at the 2026 OCP Global Summit: Open Innovation for Scale-Up, Scale-Out, and Scale-Across AI Networks appeared first on Engineering at Meta.

Sometimes, giving an AI agent all of the knowledge it needs is the wrong approach. At Meta, we’ve seen notable improvements in efficiency and accuracy by keeping the orchestration layer of our data pipeline agents deliberately thin: It routes work and enforces reliability checks, while specialized agents do the domain reasoning. We’re sharing our own [...] Read More... The post The Thin Orchestrator: How We Made Our AI Agents More Reliable by Giving the Router Less to Do appeared first on Engineering at Meta.