A detailed summary of a workshop on building and deploying production-minded AI coding agents using Dagger. The session covers creating controlled, observable, and test-driven agent workflows and integrating them into CI/CD systems like GitHub Actions for automated, reliable software development.
A deep dive into using Google's A2A (Agent-to-Agent) framework and MCP (Model Context Protocol) to build intelligent, automated workflows. This summary covers the core concepts, strategic implementation, a practical multi-agent architecture, and critical insights on lean context management to control costs and latency.
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.
Babak Hodjat, CTO of AI at Cognizant and a co-inventor of the technology behind Siri, discusses the strategic shift from generative AI to autonomous, multi-agent systems. He explores how these agentic systems will redefine enterprise operations, the intense "arms race" for AI talent, and the critical need for a decentralized, secure framework for agent collaboration.