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.
Explore the shift from traditional, human-driven software development to an agent-native lifecycle. Learn how AI agents, powered by centralized context, can orchestrate the entire SDLC, from planning and coding to incident response, transforming developers into orchestrators of AI systems.
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.
Rakesh Kumar from Lyft details the evolution of their real-time feature generation platform, from cron jobs to a sophisticated streaming architecture using Apache Beam and Flink. Key discussions include solving the 'hot shard' problem with geohashes, building a custom geospatial feature store, and optimizing pipelines with YAML-based configurations.