AI Engineer

Dream Machine: Scaling to 1m users in 4 days — Keegan McCallum, Luma AI

ComfyUI Full Workshop — first workshop from ComfyAnonymous himself!

Design like Karpathy is watching — Zeke Sikelianos, Replicate

On Curiosity — Sharif Shameem, Lexica

Real world MCPs in GitHub Copilot Agent Mode — Jon Peck, Microsoft

The rise of the agentic economy on the shoulders of MCP — Jan Curn, Apify

MCP is all you need — Samuel Colvin, Pydantic

Full Spec MCP: Hidden Capabilities of the MCP spec — Harald Kirschner, Microsoft/VSCode

Shipping an Enterprise Voice AI Agent in 100 Days - Peter Bar, Intercom Fin

The State of Generative Media - Gorkem Yurtseven, FAL

Teaching Gemini to Speak YouTube: Adapting LLMs for Video Recommendations to 2B+DAU - Devansh Tandon

Transforming search and discovery using LLMs — Tejaswi & Vinesh, Instacart

Netflix's Big Bet: One model to rule recommendations: Yesu Feng, Netflix

Netflix centralizes personalization efforts by transitioning from numerous specialized models to a unified foundation model based on transformer architecture. This shift addresses inefficiencies in label and feature engineering while enabling scalable, high-leverage innovation across diverse content types, including ga...

360Brew: LLM-based Personalized Ranking and Recommendation - Hamed and Maziar, LinkedIn AI

What We Learned from Using LLMs in Pinterest — Mukuntha Narayanan, Han Wang, Pinterest

Measuring AGI: Interactive Reasoning Benchmarks for ARC-AGI-3 — Greg Kamradt, ARC Prize Foundation

RL for Autonomous Coding — Aakanksha Chowdhery, Reflection.ai

Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon

Benchmarks Are Memes: How What We Measure Shapes AI—and Us - Alex Duffy, Every.to

Small AI Teams with Huge Impact — Vik Paruchuri, Datalab