Lance: https://www.linkedin.com/in/lance-martin-64a33b5/

How Context Fails: https://www.dbreunig.com/2025/06/22/how-contexts-fail-and-how-to-fix-them.htmlHow New Buzzwords Get Created: https://www.dbreunig.com/2025/07/24/why-the-term-context-engineering-matters.htmlContent Engineering:

https://rlancemartin.github.io/2025/06/23/context_engineering/ https://docs.google.com/presentation/d/16aaXLu40GugY-kOpqDU4e-S0hD1FmHcNyF0rRRnb1OU/edit?usp=sharingManus Post: https://manus.im/blog/Context-Engineering-for-AI-Agents-Lessons-from-Building-ManusCognition Post: https://cognition.ai/blog/dont-build-multi-agentsMulti-Agent Researcher: https://www.anthropic.com/engineering/multi-agent-research-systemHuman-in-the-loop + Memory: https://github.com/langchain-ai/agents-from-scratch- Bitter Lesson in AI Engineering -Hyung Won Chung on the Bitter Lesson in AI Research:

Bitter Lesson w/ Claude Code:

Learning the Bitter Lesson in AI Engineering: https://rlancemartin.github.io/2025/07/30/bitter_lesson/Open Deep Research: https://github.com/langchain-ai/open_deep_research https://academy.langchain.com/courses/deep-research-with-langgraphScaling and building things that “don’t yet work”:

- Frameworks -Roast framework at Shopify / standardization of orchestration tools:

MCP adoption within Anthropic / standardization of protocols:

How to think about frameworks: https://blog.langchain.com/how-to-think-about-agent-frameworks/RAG benchmarking: https://rlancemartin.github.io/2025/04/03/vibe-code/Simon’s talk with memory-gone-wrong: https://simonwillison.net/2025/Jun/6/six-months-in-llms/

Full Video Episode

Timestamps

00:00 Introduction and Background

00:53 The Rise of Context Engineering

01:57 Context Engineering vs Prompt Engineering

05:56 The Five Categories of Context Engineering

10:02 Multi-Agent Systems and Context Isolation

14:48 Classical Retrieval vs Agentic Search

17:12 LLMs.txt and MCP Servers

24:51 Context Pruning and Memory Management

37:25 Memory Systems and Human-in-the-Loop

42:55 The Bitter Lesson Applied to AI Engineering

51:21 Frameworks, Abstractions, and Building for the Future

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