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Playground in Prod - Optimising Agents in Production Environments — Samuel Colvin, Pydantic

Playground in Prod - Optimising Agents in Production Environments — Samuel Colvin, Pydantic

Samuel Colvin, creator of Pydantic, demonstrates a hands-on workflow for continuously optimizing AI agents in production. The session covers using Logfire for running evaluations, GEPA (Genetic Pareto) for autonomously evolving better prompts, and managed variables to deploy these improvements to live services without redeployment.

Language-Agnostic Detection of Bugs in Zero-Knowledge Proof Programs

Language-Agnostic Detection of Bugs in Zero-Knowledge Proof Programs

A summary of a talk on a new language-agnostic approach using abstract interpretation to find critical vulnerabilities in Zero-Knowledge Proof (ZKP) programs by modeling and detecting mismatches between prover computations and verifier constraints.

Everything You Need To Know About Agent Observability — Danny Gollapalli and Ben Hylak, Raindrop

Everything You Need To Know About Agent Observability — Danny Gollapalli and Ben Hylak, Raindrop

Agent failures are unlike traditional software failures. This workshop provides a practical framework for monitoring production agents, moving beyond evals to real-world observability by using explicit signals (errors, latency) and implicit signals (user frustration, refusals, self-diagnostics) to catch regressions and understand agent behavior.

Beyond the Basics: Production Serverless Patterns for Extreme Scale • Janak Agarwal • GOTO 2025

Beyond the Basics: Production Serverless Patterns for Extreme Scale • Janak Agarwal • GOTO 2025

This presentation by Janak Agarwal from AWS provides a deep dive into scaling serverless applications for mission-critical, high-traffic workloads. It explores AWS Lambda's rapid scaling capabilities for handling extreme traffic bursts and introduces advanced patterns like Provisioned Concurrency for cost optimization during steady-state operations.

AI That Designs Its Own Chips: Ricursive's Anna Goldie and Azalia Mirhoseini

AI That Designs Its Own Chips: Ricursive's Anna Goldie and Azalia Mirhoseini

Co-founders of Ricursive Intelligence, Anna Goldie and Azalia Mirhoseini, outline their thesis that AI should design the chips that train AI. They detail their three-phase plan to first accelerate chip design with AI tools 100,000x faster than current software, then become a 'design-less' platform for custom silicon, and finally achieve vertical integration by building their own chips and models.

Skills at Scale — Nick Nisi and Zack Proser, WorkOS

Skills at Scale — Nick Nisi and Zack Proser, WorkOS

Nick Nisi and Zach Proser from WorkOS explain how to build, manage, and scale AI 'skills'—reusable, portable instructions that make AI agents like Claude more powerful and consistent. They cover the core anatomy of a skill, best practices for writing them, advanced techniques like progressive disclosure, and their application beyond coding, from video generation to automating business workflows.