Jan 12, 2026

9 Lessons Learned from Deploying GenAI at Scale • Garth Gilmour & Stuart Greenlees • GOTO 2025

Drawing from their experience at Liberty Mutual, a Fortune 100 company, Garth Gilmour and Stuart Greenlees share nine hard-won lessons from deploying Generative AI for 5,000 developers. This "from the trenches" talk moves beyond the hype to discuss the real-world challenges of scaling AI, including managing spiraling costs, the complexities of RAG, the difference between shipping and adoption, and the necessity of building a governed platform. They detail their mistakes, solutions, and the evolution of their strategy for architecture, developer education, and model management.

Jan 12, 2026

Multi-Agent Systems for the Misinformation Lifecycle

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.

Dec 29, 2025

Memory in LLMs: Weights and Activations - Jack Morris, Cornell

This talk explores the limitations of current methods for providing knowledge to LLMs, such as large context windows and Retrieval-Augmented Generation (RAG). The speaker argues that the future lies in training knowledge directly into the model's weights. This is achieved through a combination of generating large synthetic datasets from small amounts of source material and using parameter-efficient fine-tuning (PEFT) techniques like LoRA to avoid catastrophic forgetting. The goal is to create more capable, personalized, and efficient models by fundamentally altering how they store and access information.

Dec 29, 2025

Agentic Al in SW Development: Evolving Patterns & Protocols • Bhuvaneswari Subramani • GOTO 2025

Bhuvaneswari Subramani details the "Agentic Shift" in AI by presenting an evolutionary journey through seven foundational system design patterns. The talk progresses from simple conversational clients to sophisticated, multi-agent systems, covering key patterns like Retrieval-Augmented Generation (RAG), Self-Correcting RAG, and the Model Context Protocol (MCP), explaining how each pattern adds new layers of context, action, and autonomy.

Dec 16, 2025

Context Engineering 2.0

Simba Khadder explains the evolution of feature stores and MLOps, detailing why they remain crucial in the age of LLMs for high-scale use cases. He discusses the acquisition of his company, Featureform, by Redis and outlines their new vision: building a "Context Engine" for AI. This engine aims to unify structured data, unstructured data, and memory into a single pane of glass, moving beyond simple RAG to a more sophisticated "Context Engineering 2.0" that empowers agents with rich, queryable context.

Nov 22, 2025

Context Engineering & Agentic Search with the CEO of Chroma

Jeff Huber, CEO of Chroma, discusses "context rot," the degradation of AI performance in large context windows, and outlines a new vision for retrieval infrastructure. He covers the evolution of search, the importance of a two-stage recall-then-precision pipeline, and the challenges of agentic memory, advocating for a shift from AI "alchemy" to reliable engineering.