An overview of the architectural shift from Shallow Agents (Agent 1.0) to Deep Agents (Agent 2.0) and how to build complex AI agents that can handle multi-step tasks over extended periods.
Notes on context engineering and agent harnesses for video libraries: designing the structured representations to make media legible to LLMs.
Since we started joining meetings from our computers, video has become the default way that organizations capture what happens at work. We’re at the point now where recording things
New blog: Building agents that reach production systems with MCP.
When should agents use direct APIs vs CLIs vs MCP? Plus patterns for building MCP servers, context-efficient clients and pairing MCP with skills.
https://t.co/JEogw5vWly
Structured Test-Time Scaling: From Multi-Agent Systems to General Inference Architectures
A unified theoretical framework for structured test-time scaling, showing how topology compression, scope isolation, and decoupled verification—a three-layer structural decoupling—bypass the linear collapse of long-horizon reasoning across multi-agent systems, recursive architectures, and coding agents.
What goes into the system prompt vs. what goes into an Agent Skill?
Agent’s system prompt is for identity, constraints, and persistent context.
• What the agent is and what it should always or never do
• How it should generally approach problems (reasoning style)
• Persistent
Dive into Claude Code: The Design Space of Today's and Future...
Claude Code is an agentic coding tool that can run shell commands, edit files, and call external services on behalf of the user. This study describes its comprehensive architecture by analyzing...
Harness, Memory, Context Fragments, & the Bitter Lesson
this is a work in progress mental dump on interesting intersections between how we use and design a harness, implications for memory being accumulated over long timescales, and the search bitter lesson we can’t escape
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