A deep dive into advanced engineering techniques for coding agents, focusing on effective context management in LLMs like Claude. The talk introduces a practical framework using a brain-inspired analogy, proposing a Markdown-based 'wiki' as a long-term memory system to augment the agent's limited context window. This approach is demonstrated through a real-world challenge of extracting structured data from technical drawings.
AI agents utilize four distinct types of memory, analogous to human cognition, to move beyond simple chatbot responses. This summary explores the CoALA framework, detailing working, semantic, procedural, and episodic memory and how they enable agents to learn, recall skills, and leverage past experiences.
A deep dive into Despegar's GenAI travel agent, Sofia. Explore its multi-agent architecture, the custom orchestration layer 'Chappi' built before MCP was a standard, and the strategy of decentralizing agent development across company squads to cover the entire five-phase travel arc.
Grant Miller challenges the "Hollywood view" of AI super agents, proposing a shift towards collaborative, specialized agentic systems. He introduces a framework for categorizing agents based on their risk and capability, detailing how to design safer, more effective AI applications by minimizing access, implementing dynamic controls, and incorporating a human-in-the-loop for high-risk tasks.
A detailed overview of a modular, five-agent system designed to combat the entire lifecycle of digital misinformation. Based on an ICWSM research paper, this practitioner's guide details the roles of the Classifier, Indexer, Extractor, Corrector, and Verifier agents. The system emphasizes scalability, explainability, and high precision, moving beyond the limitations of single-LLM solutions. The talk covers the complete blueprint, from agent coordination and MLOps to holistic evaluation and optimization strategies for production environments.
In this special year-end episode, experts from the Mixture of Experts podcast review the biggest AI moments of 2025 and predict what's next for 2026. The discussion covers the rise of "super agents" and the battle for the user interface, open source's breakout year and its remaining challenges, the AI hardware supply crisis and the push for efficiency, and the future of modular, multimodal AI systems.