aliyun/ai-agent-handbook

What it solves

This project addresses the challenges of moving AI agents from experimental prototypes to reliable, enterprise-grade production systems. It provides a systematic framework for navigating the complexities of agent architecture, engineering, governance, and optimization.

How it works

The handbook is structured as a comprehensive guide covering the full lifecycle of AI-native applications. It breaks down the process into six core pillars: architecture design, building with harness frameworks, runtime and sandbox management, governance (security and observability), continuous optimization (using evaluation datasets and feedback loops), and real-world case studies from various industries.

Who it’s for

It is designed for a wide range of professionals, including:

• Developers: To master engineering methods like task orchestration, state management, and tool integration.
• Architects & Platform Engineers: To design scalable agent infrastructure and define platform responsibilities.
• Technical Leaders & Managers: To support decision-making, project initiation, and organizational alignment.
• Product & Business Leads: To understand the boundaries between human and agent roles and identify suitable use cases.
• Security & Operations Teams: To establish mechanisms for observability, auditing, and safety.

Highlights

• Comprehensive Lifecycle Coverage: Detailed guidance on building, running, governing, and tuning agents.
• Enterprise-Focused: Insights into moving from isolated agent experiments to core business process integration.
• Practical Case Studies: Real-world examples from sectors like R&D, operations, retail, and finance.
• Continuous Knowledge Base: An open-source, evolving resource that incorporates weekly internal practices and community contributions.
• Actionable Frameworks: Clear definitions for agentic application architecture, task state machines, and evaluation data flywheels.