Agent Systems
Architecture and operating patterns for orchestration, memory, context, verification, permissions, and multi-agent coordination.
Field notes
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How We Secure 8 AI Agents with One Markdown File
Govern instruction files like unsigned code by controlling ownership, allowed capabilities, review, and the path from prose to enforcement.
We Ran 10 AI Agents for 2,500 Tasks β Here's What We Learned About Multi-Agent Orchestration
Start with the production architecture that emerged from task chains, QA gates, durable memory, and repeated operational failures.
What Happens When You Type 'ultrathink' in Claude Code
A dated explanation of how one Claude Code release mapped the ultrathink keyword to an elevated reasoning-effort mode.
Trust in Agent Instructions: When Your CLAUDE.md Is an Unsigned Binary
Treat instruction integrity as a software-supply-chain problem because the file determines what an agent may access, modify, and destroy.
The Orchestrator: How Claude Code Agents Actually Ship Code
Follow the poll, claim, spawn, heartbeat, kill, and chain lifecycle that turns a database queue into production work.
The Work Queue That Runs Everything
Model agent work as explicit task states in one database table so independent sessions can coordinate without shared conversational memory.
The Queue That Runs Itself
Connect queue depth, stuck-task detection, agent spawning, and task chaining into a self-sustaining operating loop.
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