Afleveringen
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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
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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
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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/
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 -
Zijn er afleveringen die ontbreken?
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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
