Lance Martin - LangChain

Lance Martin - LangChain

Chroma CEO Jeff Huber sits down with Lance Martin to discuss the current state of agents and more. Find Lance on X, https://x.com/RLanceMartin, and his website, https://rlancemartin.github.io/ 0:00 Introduction & Welcome 0:09 Context Engineering: What It Is and Why It Matters 2:05 Context Rot and Performance Degradation 3:31 Year in Review: 2025 AI Trends 4:28 Giving Agents a Computer (File System & Shell) 5:00 Model Context Protocol (MCP) and Tool Bloat 6:07 Multi-Tier Action Space Architecture 8:24 Tool Search and Progressive Disclosure 10:33 Agent Harness Structure & Deep Agents 12:17 Skills and Standard Operating Procedures (SOPs) 14:13 Context Offloading Techniques 15:49 Plan Offloading & The Ralph Wiggum Loop 18:00 Context Caching for Cost & Speed 18:27 Sub-agents and Context Isolation 21:16 Summary: Key Context Engineering Principles 22:00 Evolving Context & Continual Learning 25:02 Claude Diary: Reflecting on Sessions 26:06 Skill Learning from Agent Trajectories 27:00 Memory Management in Token Space vs Weights 28:35 RLMs: Reason Language Models & Learned Context Management 31:30 What Can Be Absorbed Into Models (The Classifier Test) 35:30 Memory: Writing vs Retrieval Challenges 40:00 File Systems as Agent Primitives 42:46 Limitations of File Systems for Large Codebases 45:02 Multi-Agent Collaboration & Concurrency Challenges 49:35 Layers of Context: Session, Agent, Organizational, Global 52:27 File Systems vs Databases: A Hot Take 55:51 Sandboxing and Agent Infrastructure 58:42 What's Most Exciting: Memory, Personal Agents & Bioscience 1:02:18 Wrap Up — Chroma is the open-source AI application database. Batteries included. Embeddings, vector search, document storage, full-text search, metadata filtering, and multi-modal. All in one place. Retrieval that just works. As it should be. Try it today:https://trychroma.com/cloud

Drew Breunig

Jeff Huber sits down with Drew Breunig to talk about the origins of Context Engineering and more. Drew has a wide range of his writing about AI on his website: https://www.dbreunig.com/ [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqblA4ZW9mMWF0d2pFMnYwU0JBdVV2UmpwN09rZ3xBQ3Jtc0tsR2xFNVROYi03NUZ2XzlPT1B1NHUxVFZmT3EtSVBCd2pzeWR1eTYta3JiY3lFeERFQVFlbmo1YzZqVTdVZF8wajdkc1FpT210OVdvcnRFRnpSZWlJbzdoWEhhYm04X1o4WEsxWnM3b201Wi1XSUg3TQ&q=https%3A%2F%2Fwww.dbreunig.com%2F&v=vI2hURmsCkQ] 00:36 Why write about AI? (Writing as a searchable index) 01:28 The two buckets of AI writing: Hype vs. Research 04:08 The Gemini 1.5 Paper & Pokemon: The birth of Context Engineering 06:50 The "Karpathy Effect" on Context Engineering 08:17 Benchmarks, Model Cards, and the "Agent Harness" 11:41 The Weightlifting Metaphor for AI Benchmarks 14:02 Testing Opus 4.5: Building internal tools in one shot 15:54 Models are untapped: The gains are in the harness 17:05 Why isn't there a standard Context Engineering harness? 19:20 The "Hello World" Experiment: Testing Agent Frameworks (LangChain, Crew, etc.) 21:42 Compact and Grep vs. File Systems 23:45 "Naked" tool calls vs. Frameworks 24:50 The GPT-8 Thought Experiment: Why Software Engineering still matters 27:12 Compound AI Systems: What agents can learn from Data Pipelines 31:00 Reliability is the bottleneck (The MAP Report) 36:00 Token Speed: When code generates faster than humans can read (Groq/Cerebras) 41:00 The UX of Multi-Agent Systems (The "Starcraft" problem) 43:57 ChatGPT Deep Research: The Shopping Use Case 46:25 Building Trust: Agent Design as Client Services 49:30 Continual Learning: Weights vs. Context/Memory 51:50 The problem with "Black Box" memory (The Chocolate Example) 56:30 The need for "Modes" (Work vs. Home context) -- Chroma is the open-source AI application database. Batteries included. Embeddings, vector search, document storage, full-text search, metadata filtering, and multi-modal. All in one place. Retrieval that just works. As it should be. Try it today: https://trychroma.com/cloud [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbDhSa3pBTWVtU01KU1RCSTdlUnlWeFRlM1AyZ3xBQ3Jtc0tsZWdyVHZQVWdGT1Bub19xN2RvOXBIeEdRNlZHTk5Zb0FOT0tZNEQyb2FLU2NPOWNwVGhycUVxaEJnVE5RZTRVTXlOQlpwbGRfeVc4THllWm5xNm03MmFDTW9DeTZ5OFhOcGtLREZhbTRvVHg5ck5xOA&q=https%3A%2F%2Ftrychroma.com%2Fcloud&v=vI2hURmsCkQ]

Dex Horthy

Chroma CEO Jeff Huber chats with Dex Horthy about agents and context engineering. Dex on X: https://x.com/dexhorthy 0:00 - Introduction 0:23 - Context Engineering Origins 0:33 - 12 Factor Agents 0:43 - New AI Models 1:43 - Model Switching Strategy 3:07 - Personal Productivity Systems 7:57 - AI UX Patterns 13:07 - Todo List Management 15:01 - Collaborative AI Workspaces 22:09 - In-Person vs Remote 24:05 - Tab Complete Patterns 25:00 - Shared Context Layer 27:00 - Markdown & Airtable 32:35 - Data Storage Systems 34:00 - AI-Native Organizations 36:00 - OAuth & Authentication 38:00 - Desktop App Development 43:42 - Context Engineering Evolution 45:00 - Evals & Observability 46:00 - LM-as-Judge Discussion 48:00 - Snapshot-Based Evals 54:47 - Agent Memory Systems 56:00 - Instruction Following Limits 57:57 - Closing Remarks -- Chroma is the open-source AI application database. Batteries included. Embeddings, vector search, document storage, full-text search, metadata filtering, and multi-modal. All in one place. Retrieval that just works. As it should be. Try it today: https://trychroma.com/cloud [https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa3Q3WFhGTUdlZ1lFX1ljb1VWRnZKdUN5OTU0d3xBQ3Jtc0tuNXRqNkF2dVNOejNibkpXTy1pWVliV1h2X1ByeU1QczhZdHlFWVpZU2w3ZWlab3BHOW9Pbm0yOG4wVHRJVmhWbTY4NXl0YW1Qa3A2c0JRenJ4SlVScTdPTmd6eWpPT1JEcUVkcUZVQjJIdDVjMnlSWQ&q=https%3A%2F%2Ftrychroma.com%2Fcloud&v=BNhRnx_O95c]