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Duration 14 hours
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.
