having dinner with @garrytan wasn’t on my bingo card when I joined the bay 2 months ago amazing day at @ycombinator AI startup school thanks for the invite garry!

this is insane

Was great to get invited at Meta HQ to discuss our experience working with the new Llama API. A unified way to use all models from any provider is the way for developers. Performance and cost rule!

Let him in! We gotta have a bigger Zurich delegation

We're excited to announce the winners of the first LlamaCon Hackathon! These talented individuals and teams have demonstrated exceptional skill and creativity in their projects using Llama. 🥇 1st Prize: OrgLens An AI-powered expert matching system that connects you with the right professionals within your organization. By leveraging data from various sources, OrgLens creates a comprehensive knowledge graph and detailed profiles, streamlining expert matching. See their GitHub Repository: bit.ly/4k62WaO @KPJedrzejewski, @clemhus 🥈 2nd Prize: Compliance Wizards An AI-powered transaction analyzer designed to detect fraud and alert users. It uses Llama API’s multi-modality to assist fraud assessors in determining client involvement in criminal activities. See their GitHub Repository: bit.ly/3RRxiBS @SamDc73, @k_a__reem, @nicetomeetyu2, @sorhanft 🥉 3rd Prize: Llama CCTV Operator A Llama CCTV AI control room operator that identifies custom surveillance video events without model fine-tuning. It uses Llama 4’s multi-modal image understanding to assess and report predefined events. See their GitHub Repository: bit.ly/4d9UPrw @torayeff 🌟 Best Llama API Usage: Geo-ML This project uses Llama 4 Maverick and GemPy to generate 3D geological models, processing extensive geology reports into structured data for 3D representations. See their GitHub Repository: bit.ly/3GITT15 @WilliamJSDavis Please join us in congratulating these winners on their outstanding achievements! We're honored to have them as part of the Llama community. 🎉

We won Meta's Llamacon Hackathon! Imagine engineers, PMs, or managers being able to query their org’s knowledge base in natural language: 🧠 “Who’s responsible for the normalization layer of the Llama 4 models?” 🔐 “Who’s an expert in our multi-step auth flow?” Had a blast hacking this up. Btw, we didn't use Cursor/Windsurf. I actually believe that planning ahead and understanding the exact structure of your code is key to deliver a project you own.