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Paul Graham, Founder of Y Combinator, Live from Stockholm

Paul Graham, Founder of Y Combinator, Live from Stockholm

Paul Graham discusses the strategic importance for startup founders to immerse themselves in Silicon Valley's unique ecosystem and how this temporary migration is the key to fostering a thriving startup hub in Stockholm, potentially making it the "Silicon Valley of Europe".

Building AI Agents in Kotlin • Anton Arhipov • YOW! 2025

Building AI Agents in Kotlin • Anton Arhipov • YOW! 2025

Anton Arhipov from JetBrains introduces Koog, a lightweight, Kotlin-native framework for building tool-using LLM agents. This session covers the rationale for using Kotlin in AI, the architecture of Koog agents, and how its graph-based DSL enables the creation of structured, type-safe, and reproducible agent workflows, moving beyond simple prompt-chaining to sophisticated orchestration.

LLMjacking: How hackers steal your AI API keys and stick you with the bill

LLMjacking: How hackers steal your AI API keys and stick you with the bill

Experts discuss the rise of LLMjacking, where stolen AI API keys lead to massive financial losses. They explore how AI is reshaping adversary simulations, the enduring need for human expertise in the loop, and the debate over accelerating security patch timelines in the face of AI-powered threats.

Computer use in Codex

Computer use in Codex

Ari Weinstein discusses how Codex's 'computer use' feature allows the AI agent to operate local Mac applications in the background by combining multimodal vision with accessibility data, enabling non-intrusive, parallel task execution.

Give Your Agent a Computer — Nico Albanese, Vercel

Give Your Agent a Computer — Nico Albanese, Vercel

Nico Albanese from Vercel demonstrates how to build a stateful, learning AI agent from scratch using AI SDK v6. The workshop covers the core components: a tool loop, provider-executed tools like web search, end-to-end type safety, and Vercel's new persistent named sandboxes, which give the agent a file system to persist state, memory, and even self-generated tools across sessions.

Lessons from Trillion Token Deployments at Fortune 500s — Alessandro Cappelli, Adaptive ML

Lessons from Trillion Token Deployments at Fortune 500s — Alessandro Cappelli, Adaptive ML

95% of GenAI pilots fail due to feedback integration issues, not deployment challenges. Alessandro Cappelli argues that Reinforcement Learning (RL) provides the only systematic way to incorporate business metrics and production signals to continuously improve models, especially for complex agent-based systems.