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.
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.
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.
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.
Naveen Rao, CEO of Unconventional AI, argues that the 80-year-old digital computing paradigm is hitting a fundamental energy wall. He proposes a new approach to AI hardware, inspired by neuroscience, that replaces matrix math with nonlinear dynamics, leveraging the time domain for computation to approach the thermodynamic limits of efficiency.