Building Enterprise AI Agents with Tencent ADP: RAG, Workflows and Operational Guardrails Training Course
This practical course, titled "Building Enterprise AI Agents with Tencent ADP: RAG, Workflows and Operational Guardrails," focuses on the design, development, and operational deployment of enterprise-grade AI agents using Tencent ADP.
Delivered as live, instructor-led training (available online or onsite), this program is tailored for intermediate-level solution architects, AI engineers, developers, and technical product teams. It equips participants to leverage Tencent ADP for creating robust AI agents featuring production-ready RAG, automated workflows, multi-agent coordination, and comprehensive operational guardrails.
Upon completion, participants will be able to:
- Design AI agents within Tencent ADP to address specific enterprise use cases.
- Construct RAG pipelines and knowledge workflows that enhance response accuracy and quality.
- Orchestrate complex workflows and multi-agent interactions to support business processes.
- Implement guardrails, monitoring, and operational controls to ensure stability in production environments.
Course Format
- Interactive lectures and group discussions.
- Guided exercises and practical hands-on activities.
- Live implementation exercises in a lab environment.
Customization Options
- For tailored training requirements, please contact us to discuss customization arrangements.
Course Outline
Enterprise AI Agents with Tencent ADP
- Understanding the role and value of enterprise AI agents
- Tencent ADP capabilities for agent development, knowledge integration, and workflow automation
- Distinguishing agent-based solutions from basic chat applications
- Identifying 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 architectural designs
- Structuring prompts, tools, and embedded business rules
- Planning for escalation, human review, and system reliability
Building RAG and Knowledge Workflows
- RAG concepts for grounded responses and accessing enterprise knowledge
- Preparing documents, policies, and internal content for effective retrieval
- Designing retrieval flows and response grounding patterns
- Testing and refining answer quality over time
Orchestrating Workflows and Integrations
- Translating 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 specialized agents
Applying Operational Guardrails
- Implementing guardrails for security, privacy, compliance, and policy enforcement
- Mitigating risks from unsafe outputs, prompt injection, and sensitive 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 quality metrics, latency, costs, and workflow success rates
- Evaluating agent behavior across realistic business scenarios
- Troubleshooting common issues in RAG, workflows, and orchestration
- Developing an implementation plan for pilot testing and production adoption
Requirements
- A foundational understanding of generative AI concepts and typical enterprise AI applications
- Practical experience with APIs, web applications, or cloud-based platforms
- Basic proficiency 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 initiatives
Open Training Courses require 5+ participants.
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