生产级AI Agent应用的真正瓶颈：Context、Skill与Agent Harness
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Merged summary
TL;DR - This engineering overview argues that production AI agents are constrained less by model capability than by context management, modular skills, and a secure Agent Harness. These layers make long-running agents more reliable, auditable, and recoverable.
- Manage context through editing, compression, external memory, and preservation of critical instructions.
- Load narrowly scoped Skills on demand to reduce token use, instruction conflicts, and routing errors.
- Use an Agent Harness to enforce permissions, validate tool calls, sandbox execution, and manage retries and resource limits.
- Track production metrics such as task completion, Skill activation accuracy, tool errors, recovery time, and audit coverage.
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生产级AI Agent应用的真正瓶颈：Context、Skill与Agent Harness
Public signals
N/A
TL;DR - This engineering overview argues that production AI agents are constrained less by model capability than by context management, modular skills, and a secure Agent Harness. These layers make long-running agents more reliable, auditable, and recoverable.
- Manage context through editing, compression, external memory, and preservation of critical instructions.
- Load narrowly scoped Skills on demand to reduce token use, instruction conflicts, and routing errors.
- Use an Agent Harness to enforce permissions, validate tool calls, sandbox execution, and manage retries and resource limits.
- Track production metrics such as task completion, Skill activation accuracy, tool errors, recovery time, and audit coverage.