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Course Outline

Enterprise AI Agents with Tencent ADP

  • Defining enterprise AI agents and identifying areas of added value.
  • Exploring Tencent ADP capabilities for agent development, knowledge integration, and workflow automation.
  • Distinguishing between agent-based solutions and standard chat applications.
  • Reviewing common enterprise use cases and key delivery considerations.

Designing Agents for Business Processes

  • Defining agent roles, boundaries, inputs, and outputs.
  • Selecting between single-agent and multi-agent architectural designs.
  • Structuring prompts, tools, and business rules effectively.
  • Planning for escalation paths, human review, and system reliability.

Building RAG and Knowledge Workflows

  • Understanding RAG concepts for grounded answers and accessing enterprise knowledge.
  • Preparing documents, policies, and internal content for retrieval systems.
  • Designing retrieval flows and response grounding patterns.
  • Testing and iteratively improving answer quality over time.

Orchestrating Workflows and Integrations

  • Mapping business processes into agent-driven workflows.
  • Connecting agents to APIs, internal services, and broader enterprise systems.
  • Managing decisions, approvals, retries, and fallback mechanisms.
  • Coordinating handoffs between workflow steps and specialized agents.

Applying Operational Guardrails

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

Monitoring, Evaluation, and Continuous Improvement

  • Tracking metrics for quality, latency, cost, and workflow success rates.
  • Testing agent behavior across realistic business scenarios.
  • Troubleshooting common issues in RAG, workflows, and orchestration.
  • Developing an implementation plan for pilot programs and production adoption.

Requirements

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

Audience

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

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