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Duration 14 hours
Course Outline
Enterprise AI Agents with Tencent ADP
- Understanding enterprise AI agents and the value they deliver
- Tencent ADP’s capabilities for agent development, knowledge integration, and workflow automation
- Distinguishing agent-based solutions from basic chat applications
- Common enterprise use cases and delivery considerations
Designing Agents for Business Processes
- Defining agent roles, boundaries, inputs, and outputs
- Selecting between single-agent and multi-agent architectures
- Structuring prompts, tools, and business rules effectively
- Planning for escalation, human review, and system reliability
Building RAG and Knowledge Workflows
- RAG concepts for grounded answers and access to enterprise knowledge
- Preparing documents, policies, and internal content for retrieval
- Designing retrieval flows and response grounding patterns
- Testing and refining answer quality over time
Orchestrating Workflows and Integrations
- Mapping business processes into agent-driven workflows
- Connecting agents to APIs, internal services, and enterprise systems
- Managing decisions, approvals, retries, and fallback mechanisms
- Coordinating handoffs between workflow steps and specialist agents
Applying Operational Guardrails
- Implementing guardrails for security, privacy, compliance, and policy control
- Mitigating risks associated with unsafe output, prompt injection, and data exposure
- Incorporating approval checkpoints, audit trails, and access controls
- Designing safe response patterns for high-impact business scenarios
Monitoring, Evaluation, and Continuous Improvement
- Tracking metrics such as quality, latency, cost, and workflow success rates
- Evaluating agent behaviour across realistic business scenarios
- Troubleshooting common issues in RAG, workflows, and orchestration
- Developing an implementation plan for pilot and production adoption
Requirements
- A general understanding of generative AI concepts and common enterprise AI use cases
- Experience working with APIs, web applications, or cloud-based platforms
- Basic programming, integration, or solution design experience
Audience
- Solution architects and technical leads
- AI engineers, application developers, and automation specialists
- Product managers and innovation teams supporting enterprise AI initiatives