Madison Faulkner and Hugo Santos explain why traditional CI/CD, built for human developers, is failing under the load of AI agents. They propose a new paradigm of 'Continuous Compute' centered on intent-driven agent loops, fast inline validation, and a pre-merge layer where humans review outcomes, not diffs, paving the way for a 'multiverse' of parallel development.
Eric Zakariasson from Cursor explains the shift from single-agent pair programming to managing a multi-agent "software factory". He outlines the practical steps required, from establishing a well-structured codebase with guardrails to adopting a managerial mindset that focuses on automation, asynchronous work, and scaling agent fleets to increase software development throughput and consistency.
Y Combinator Partner Diana Hu explains how to build an AI-native company where AI is the core operating system, not just a tool. She covers how to make a company queryable, the impact on team structures, and why startups have a massive edge in this new paradigm.
This hands-on workshop details the construction of a sophisticated, dual-part AI system for producing high-quality technical content. It begins with an MCP-powered deep research agent that autonomously plans, searches the web, and analyzes sources like YouTube to synthesize a grounded research artifact. The second part is a constrained, deterministic writing workflow that transforms this research into polished, non-sloppy content using an innovative "Evaluator-Optimizer" pattern for iterative refinement. The session emphasizes crucial AI engineering principles, such as choosing between agentic and workflow-based architectures, and concludes with a deep dive into implementing practical observability and evaluation pipelines to ensure the system is both measurable and improvable.
Dotta, the creator of Paperclip, introduces it as an open-source orchestrator for building "zero-human companies." This talk demonstrates how to set up an organization of AI agents, leverage skills and custom instructions for reliable work, and automate business processes. Through a live demo, Dotta showcases creating a company from scratch, managing agent workflows with QA and routines, and outlines the exciting future roadmap for the platform.
Explores the challenges of single AI agents, such as context dilution and tool overload, and introduces hierarchical AI agents as a solution. This summary details the structure, benefits, and limitations of multi-agent systems for more scalable and efficient AI workflows.