GitHub's Christopher Harrison explains how to leverage GitHub Copilot's agent capabilities. This summary covers using Copilot as an AI pair programmer, the importance of providing context, its different workloads, and how to use the new Copilot Coding Agent with the Model Context Protocol (MCP) to accelerate development responsibly.
Josh Albrecht, CTO of Imbue, discusses the engineering challenges in building reliable AI coding agents. He introduces Sculptor, an experimental environment designed to build trust in AI-generated code by focusing on preventing and detecting problems through structured workflows, automated testing, and AI-driven analysis, moving beyond simple code generation to create maintainable software.
Explore the shift from manual coding to AI-driven development. This session covers the mechanics of AI coding agents like OpenHands, best practices for using them effectively without accumulating tech debt, and practical use cases, emphasizing the continued importance of human oversight and critical thinking in software engineering.
Scott Wu, CEO of Cognition AI, discusses the exponential growth of AI capabilities in software engineering, likening it to a "Moore's Law for AI agents" with a doubling time of every 70 days. He chronicles the evolution of their AI agent, Devin, from handling repetitive code migrations to autonomously managing entire backlogs, highlighting the key technical challenges and paradigm shifts at each stage.
Misha Laskin, co-founder of Reflection AI and former researcher at Google DeepMind, discusses the company's mission to build superhuman autonomous systems. He introduces Asimov, a code comprehension agent designed to solve the 80% of an engineer's time spent on understanding complex systems, rather than just code generation. Laskin delves into the intricacies of co-designing product and research, the critical role of customer-driven evaluations, the bottlenecks in scaling reinforcement learning (RL) — particularly the "reward problem" — and why he believes the future is one of "jagged superintelligence" emerging in specific, high-value domains like coding.
Push Kohli and Máté Balog from Google DeepMind discuss AlphaDev, an AI agent that uses large language models and evolutionary search to discover novel, more efficient algorithms for fundamental computer science problems, marking a significant step in AI's ability to generate creative and practical solutions.