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Course Outline

Enterprise AI Agents with Tencent ADP

  • Defining the value proposition of enterprise AI agents and their strategic impact.
  • Leveraging Tencent ADP capabilities for agent development, knowledge integration, and workflow automation.
  • Distinguishing between agent-based solutions and standard chat applications.
  • Identifying common enterprise use cases and key delivery considerations.

Designing Agents for Business Processes

  • Establishing clear agent roles, boundaries, inputs, and outputs.
  • Evaluating single-agent versus multi-agent architectural approaches.
  • Structuring prompts, tools, and embedded business rules effectively.
  • Planning for escalation paths, human review, and system reliability.

Building RAG and Knowledge Workflows

  • Applying RAG concepts to ensure grounded answers and secure access to enterprise knowledge.
  • Preparing documents, policies, and internal content for effective retrieval.
  • Designing retrieval flows and response grounding patterns.
  • Iteratively testing and refining answer quality over time.

Orchestrating Workflows and Integrations

  • Translating business processes into structured agent workflows.
  • Connecting agents to APIs, internal services, and broader enterprise systems.
  • Managing decision logic, approvals, retries, and fallback mechanisms.
  • Coordinating handoffs between workflow steps and specialized agents.

Applying Operational Guardrails

  • Implementing guardrails for security, privacy, compliance, and policy enforcement.
  • Mitigating risks associated with unsafe output, prompt injection, and data exposure.
  • Incorporating approval checkpoints, audit trails, and strict access controls.
  • Designing safe response patterns for high-impact business scenarios.

Monitoring, Evaluation, and Continuous Improvement

  • Tracking key performance indicators such as quality, latency, cost, and workflow success rates.
  • Testing agent behavior across realistic business scenarios.
  • Troubleshooting common issues in RAG, workflows, and orchestration.
  • Developing a strategic implementation plan for pilot testing and production adoption.

Requirements

  • Fundamental understanding of generative AI concepts and typical enterprise AI applications.
  • Practical experience with APIs, web applications, or cloud-based platforms.
  • Basic proficiency in programming, integration, or solution design.

Target Audience

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

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