Ship it! Building Production Ready Agents — Mike Chambers, AWS

This talk explores the complexities of transitioning a SaaS company to an AI-first model, emphasizing that it's an evolutionary journey rather than a binary switch. It proposes a framework focusing on strategy, ways of working, and people to navigate this transformation. The core thesis is that becoming AI-first requires reimagining product development, embracing ambiguity, and fostering a cultural shift across the entire organization, not just within AI teams.

This talk discusses the challenges and solutions for implementing and scaling Message Communication Protocol (MCP) clients within a large organization. It highlights how the rapid evolution of AI models capable of tool calling led to integration chaos, with duplicated functionality and inconsistent interfaces across services. The solution proposed is to standardize on MCP for providing model context, treating it as a plumbing layer for integrations rather than a competitive differentiator.

This talk argues that the future of software development is agent-driven, moving beyond human-driven approaches. It posits that AI agents, when properly integrated and provided with sufficient context, can handle a majority of tasks across the software lifecycle, enabling production software to be built in minutes rather than months. The core thesis is that organizations must transition to an agent-native development paradigm to unlock the true power of AI.

This talk introduces an evaluation framework for AI product managers (PMs) focused on shipping reliable AI applications. It emphasizes the critical need for robust evaluation, analogous to software testing but adapted for the non-deterministic nature of AI models. The framework aims to provide PMs with tools and methodologies to build confidence in AI product performance, moving beyond subjective "vibe coding" to data-driven "thrive coding."

This talk details the process of developing and shipping Finn Voice, an AI-powered voice agent for customer support, within a 100-day timeframe. The core thesis is that voice AI represents a significant frontier in customer service, offering substantial benefits in cost savings, availability, and user experience compared to traditional phone support. The presentation emphasizes that successful deployment requires more than just advanced AI models; it necessitates a product-centric approach that considers use cases, conversation design, integration with existing workflows, and building user trust.