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Browse all writing tagged with AI Coding Agents.
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A practical Claw Code usage guide for turning agent architecture into safe daily workflows with bounded tasks, permission gates, tests, checkpoints, and rollback.
Claw Code's public docs and parity repo reveal how an AI coding agent is assembled: runtime loop, tools, permissions, MCP connections, sessions, and plugins.
Hooks, plugin registries, and persistent sessions are what turn an AI coding assistant into an extensible platform instead of a one-shot demo.
Claw Code's parity repo shows why modern coding agents often split responsibilities between Rust for runtime-critical paths and Python for orchestration and migration.
A coding model becomes a real agent only when tool execution, permission policy, and MCP integration are designed as one coherent system.