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Course Outline

Enterprise AI Agents on Tencent ADP

  • Understanding the definition of enterprise AI agents and their value proposition.
  • Exploring Tencent ADP features for agent development, knowledge integration, and workflow automation.
  • Distinguishing agent-based solutions from standard chat applications.
  • Reviewing common enterprise use cases and deployment considerations.

Agent Design for Business Processes

  • Defining agent roles, operational boundaries, inputs, and expected outputs.
  • Evaluating single-agent versus multi-agent architectural choices.
  • Structuring prompts, tools, and embedded business rules.
  • Planning strategies for escalation, human oversight, and system reliability.

Developing RAG and Knowledge Workflows

  • Applying RAG concepts to ensure grounded answers and access enterprise knowledge.
  • Preparing documents, policies, and internal content for efficient retrieval.
  • Designing retrieval flows and patterns for response grounding.
  • Testing and iteratively improving answer quality over time.

Workflow Orchestration and System Integration

  • Translating business processes into structured agent workflows.
  • Connecting agents to APIs, internal services, and broader enterprise systems.
  • Managing decision points, approvals, retries, and fallback procedures.
  • Coordinating transitions between workflow stages and specialized agents.

Implementing Operational Guardrails

  • Establishing guardrails for security, privacy, compliance, and policy enforcement.
  • Mitigating risks associated with unsafe outputs, prompt injection, and sensitive data leakage.
  • Incorporating approval checkpoints, audit logs, and access control mechanisms.
  • Creating safe response protocols for high-impact business scenarios.

Monitoring, Evaluation, and Continuous Improvement

  • Tracking key metrics including quality, latency, cost, and workflow success rates.
  • Testing agent behavior against realistic business scenarios.
  • Diagnosing common issues related to RAG, workflows, and orchestration.
  • Formulating an implementation roadmap for pilot testing and production adoption.

Requirements

  • A foundational understanding of generative AI concepts and typical enterprise AI applications.
  • Practical experience interacting with APIs, web applications, or cloud-based platforms.
  • Background knowledge in basic programming, system integration, or solution design.

Target Audience

  • Solution architects and technical leaders.
  • AI engineers, application developers, and automation specialists.
  • Product managers and innovation teams driving enterprise AI initiatives.
 14 Hours

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