Alibaba Cloud has released the AI Agent Handbook, a book-style repository licensed under Apache 2.0. It examines how teams can move AI agents from demonstrations into core business processes while controlling reliability, security, latency, and cost.

AI agents combine language models with tools, memory, data, and workflow logic. Those components create failure modes that rarely surface in a demo: models produce variable outputs, tool calls can trigger harmful actions, long-running tasks lose context, and costs rise as agents invoke more models and services. The handbook organizes those operational problems into a production lifecycle.

The production gap in six numbers

The handbook follows Alibaba Cloud’s earlier white paper on AI-native applications, shifting attention toward the engineering demands that emerge at scale. Its survey report presents several indicators of the gap between agent development and dependable deployment:

• About 46% of teams have built an agent or are actively developing one, up from roughly 36% a year earlier. Around 18% have reached production.