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Duration 14 hours
Course Outline
Overview of Enterprise AI Agents with Tencent ADP
- Defining enterprise AI agents and identifying where they deliver the most value.
- Exploring Tencent ADP capabilities for agent development, knowledge integration, and workflow automation.
- Distinguishing between sophisticated agent-based solutions and simple chat applications.
- Reviewing common enterprise use cases and key delivery considerations.
Designing Agents for Business Processes
- Establishing agent roles, boundaries, inputs, and expected outputs.
- Selecting between single-agent and multi-agent architectural designs.
- Structuring prompts, tools, and embedded business rules.
- Planning for escalation paths, human review processes, and system reliability.
Developing 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 patterns for response grounding.
- Testing and iteratively improving 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.
Implementing Operational Guardrails
- Establishing guardrails for security, privacy, compliance, and policy enforcement.
- Mitigating risks associated with unsafe outputs, prompt injection, and sensitive 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 metrics such as quality, latency, cost, and workflow success rates.
- Evaluating agent behavior across realistic business scenarios.
- Diagnosing and resolving common issues in RAG, workflow, and orchestration layers.
- Formulating a strategic implementation plan for pilot testing and production adoption.
Requirements
- A solid grasp of generative AI principles and standard enterprise AI applications.
- Professional experience interacting with APIs, web applications, or cloud-based platforms.
- Familiarity with basic programming, system integration, or solution architecture practices.
Target Audience
- Solution architects and technical leads.
- AI engineers, application developers, and automation specialists.
- Product managers and innovation teams driving enterprise AI initiatives.
