AI Engineer

Rethinking Team Building: how a 30-person Startup serves 50 Million Users — Grant Lee, Gamma

Building a 10 person unicorn - Max Brodeur-Urbas, Gumloop

Using OSS models to build AI apps with millions of users — Hassan El Mghari

Bolt.new: How we scaled $0-20m ARR in 60 days, with 15 people — Eric Simons, Bolt

Eric Simons discusses the unexpected growth of Bolt.new and the strategies his team used to handle the rapid scaling. He emphasizes the importance of a small, aligned team with shared core values, grit, and resilience, drawing parallels to the movie "300." Simons advocates for a "fire truck squad" approach to prioritiz...

Building Effective Voice Agents — Toki Sherbakov + Anoop Kotha, OpenAI

Monetizing AI — Alvaro Morales, Orb

Government Agents: AI Agents vs Tough Regulations — Mark Myshatyn, Los Alamos National Laboratory

Prompt Engineering and AI Red Teaming — Sander Schulhoff, HackAPrompt/LearnPrompting

Survive the AI Knife Fight: Building Products That Win — Brian Balfour, Reforge

Automating Escrow with USDC and AI - Corey Cooper, Circle

How LLMs work for Web Devs: GPT in 600 lines of Vanilla JS - Ishan Anand

[Workshop] AI Pipelines and Agents in Pure TypeScript with Mastra.ai — Nick Nisi, Zack Proser

AI Engineering with the Google Gemini 2.5 Model Family - Philipp Schmid, Google DeepMind

The New Code — Sean Grove, OpenAI

In this talk, Sean Grove discusses the evolving role of code and communication in programming, arguing that structured communication is becoming increasingly critical, especially with the advancement of AI models. He introduces the concept of specifications as a superior approach to traditional coding, emphasizing thei...

Agentic GraphRAG: AI’s Logical Edge — Stephen Chin, Neo4j

UX Design Principles for Semi Autonomous Multi Agent Systems — Victor Dibia, Microsoft

Production software keeps breaking and it will only get worse — Anish Agarwal, Traversal.ai

Thinking Deeper in Gemini — Jack Rae, Google DeepMind

A year of Gemini progress + what comes next — Logan Kilpatrick, Google DeepMind

2025 in LLMs so far, illustrated by Pelicans on Bicycles — Simon Willison