Building Enterprise AI Agents with Tencent ADP: RAG, Workflows and Operational Guardrails Training Course
Building Enterprise AI Agents with Tencent ADP: RAG, Workflows and Operational Guardrails is a hands-on course focused on designing, constructing, and deploying enterprise AI agents using Tencent ADP.
This instructor-led, live training (available online or onsite) targets intermediate-level solution architects, AI engineers, developers, and technical product teams who want to leverage Tencent ADP to create production-ready enterprise AI agents featuring Retrieval-Augmented Generation (RAG), workflow automation, multi-agent coordination, and operational guardrails.
Upon completing this training, participants will be able to:
- Design AI agents within Tencent ADP tailored for practical enterprise use cases.
- Construct RAG pipelines and knowledge workflows to enhance response accuracy.
- Orchestrate workflows and coordinate multi-agent interactions for business processes.
- Implement guardrails, monitoring, and operational controls for production environments.
Course Format
- Interactive lectures and discussions.
- Guided exercises and practical activities.
- Hands-on implementation in a live lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Course Outline
Enterprise AI Agents with Tencent ADP
- What enterprise AI agents are and where they add value
- Tencent ADP capabilities for agent development, knowledge integration, and workflow automation
- Differences between agent-based solutions and basic chat applications
- Common enterprise use cases and delivery considerations
Designing Agents for Business Processes
- Defining agent roles, boundaries, inputs, and outputs
- Choosing between single-agent and multi-agent designs
- Structuring prompts, tools, and business rules
- Planning for escalation, human review, and reliability
Building RAG and Knowledge Workflows
- RAG concepts for grounded answers and enterprise knowledge access
- Preparing documents, policies, and internal content for retrieval
- Designing retrieval flows and response grounding patterns
- Testing and improving answer quality over time
Orchestrating Workflows and Integrations
- Mapping business processes into agent workflows
- Connecting agents to APIs, internal services, and enterprise systems
- Handling decisions, approvals, retries, and fallback paths
- Coordinating handoffs between workflow steps and specialist agents
Applying Operational Guardrails
- Guardrails for security, privacy, compliance, and policy control
- Reducing risk from unsafe output, prompt injection, and sensitive data exposure
- Adding approval checkpoints, audit trails, and access controls
- Designing safe response patterns for higher-impact business scenarios
Monitoring, Evaluation, and Continuous Improvement
- Tracking quality, latency, cost, and workflow success rates
- Testing agent behavior across realistic business scenarios
- Troubleshooting common RAG, workflow, and orchestration issues
- Building 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
Open Training Courses require 5+ participants.
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