Building Enterprise AI Agents with Tencent ADP: RAG, Workflows and Operational Guardrails Training Course

Enterprise AI Agents via Tencent ADP

• Defining the role of enterprise AI agents and identifying their value propositions.
• Exploring Tencent ADP’s features for agent development, knowledge integration, and workflow automation.
• Distinguishing between advanced agent-based solutions and standard chatbot applications.
• Reviewing common enterprise use cases and key delivery considerations.

Architecting Agents for Business Processes

• Defining specific agent roles, operational boundaries, input requirements, and output standards.
• Assessing when to employ single-agent versus multi-agent architectures.
• Structuring effective prompts, tool integrations, and business rule enforcement.
• Planning for escalation paths, human review mechanisms, and system reliability.

Developing RAG and Knowledge Workflows

• Understanding RAG principles for grounded responses and accessing enterprise knowledge bases.
• Preparing documents, policies, and internal content for optimal retrieval.
• Designing retrieval flows and response grounding strategies.
• Continuously testing and refining answer quality over time.

Orchestrating Workflows and System Integrations

• Translating business processes into structured agent workflows.
• Integrating agents with APIs, internal services, and broader enterprise systems.
• Managing decision logic, approval gates, retry mechanisms, and fallback procedures.
• Coordinating seamless handoffs between workflow stages and specialized agents.

Implementing Operational Guardrails

• Establishing guardrails for security, privacy, compliance, and policy adherence.
• Mitigating risks associated with unsafe outputs, prompt injection attacks, and sensitive data leakage.
• Incorporating approval checkpoints, audit trails, and granular access controls.
• Designing safe response patterns for high-impact business scenarios.

Monitoring, Evaluation, and Iterative Improvement

• Tracking key metrics such as quality, latency, cost efficiency, and workflow success rates.
• Validating agent performance across realistic business scenarios.
• Troubleshooting common issues related to RAG, workflows, and orchestration.
• Formulating a robust implementation plan for pilot testing and production rollout.