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Duration 14 hours
Course Outline
Enterprise AI Agents with Tencent ADP
- Understanding the definition of enterprise AI agents and their added value
- Overview of Tencent ADP’s features for agent development, knowledge integration, and workflow automation
- Distinguishing between agent-based solutions and standard chat applications
- Review of common enterprise use cases and implementation considerations
Designing Agents for Business Processes
- Establishing clear agent roles, boundaries, inputs, and outputs
- Evaluating the merits of single-agent versus multi-agent architectures
- Organizing prompts, tools, and business rules effectively
- Planning for escalation paths, human oversight, and system reliability
Constructing RAG and Knowledge Workflows
- Exploring RAG concepts for generating grounded answers and accessing enterprise knowledge
- Preparing documents, policies, and internal content for retrieval systems
- Architecting retrieval flows and patterns for response grounding
- Continuously testing and refining answer quality over time
Managing Workflows and Integrations
- Translating business processes into structured agent workflows
- Linking agents to APIs, internal services, and broader enterprise systems
- Managing decision points, approvals, retries, and fallback mechanisms
- Orchestrating transitions between workflow stages and specialized agents
Implementing Operational Safeguards
- Establishing safeguards for security, privacy, compliance, and policy adherence
- Mitigating risks associated with unsafe outputs, prompt injection, and data leakage
- Incorporating approval checkpoints, audit logs, and access restrictions
- Creating safe response protocols for high-stakes business scenarios
Monitoring, Evaluation, and Continuous Improvement
- Monitoring key metrics such as quality, latency, cost, and workflow success rates
- Validating agent behavior across realistic business contexts
- Diagnosing common issues in RAG, workflows, and orchestration
- Formulating implementation strategies for pilot testing and production rollout
Requirements
- A solid grasp of generative AI principles and typical enterprise AI applications
- Practical experience with APIs, web applications, or cloud-based platforms
- Fundamental knowledge in programming, system integration, or solution design
Target Audience
- Solution architects and technical leads
- AI engineers, application developers, and automation specialists
- Product managers and innovation teams driving enterprise AI strategies
