Live from IBM Think 2026, experts discuss the maturation of enterprise AI, moving from siloed applications to integrated, end-to-end solutions. The panel explores the rising trust in AI for strategic decisions, the evolving role of the Chief AI Officer (CAIO), and the state of AI investment, arguing that the field is broadening to solve specific business problems.
Firsthand reflections from a visit to China’s most prominent AI labs, exploring the human side of the Chinese AI ecosystem, the technical constraints they face from chip supply, and how their research culture compares to the Bay Area.
Matt Pocock of AI Hero discusses the critical role of classic software engineering principles in the new era of AI development. He explores how concepts like Domain-Driven Design (DDD), deep modules, and intentional architecture are essential for building maintainable systems with AI, and shares his unique teaching philosophy for the rapidly evolving field of AI Engineering.
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.
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.
A practical guide on improving LLM coding agent performance by giving them direct access to a library's source code. The session demonstrates cloning the Effect repository to extract patterns and guide the agent in building a type-safe application from scratch.