Building Enterprise AI Agents with Tencent ADP: RAG, Workflows and Operational Guardrails Training Course
This practical course focuses on the design, development, and operationalization of enterprise AI agents utilizing Tencent ADP.
Delivered as a live, instructor-led session (either online or onsite), this training targets intermediate-level solution architects, AI engineers, developers, and technical product teams looking to leverage Tencent ADP to create enterprise AI agents featuring production-ready RAG, workflow automation, multi-agent coordination, and operational safeguards.
Upon completion, participants will be equipped to:
- Architect AI agents within Tencent ADP tailored for specific enterprise applications.
- Construct RAG pipelines and knowledge workflows that enhance response accuracy.
- Coordinate workflows and multi-agent interactions to support business processes.
- Implement guardrails, monitoring, and operational controls for production environments.
Course Structure
- Interactive lectures and open discussions.
- Guided exercises and practical tasks.
- Hands-on implementation within a live lab environment.
Customization Availability
- To arrange a customized version of this training, please reach out to us for scheduling.
Course Outline
Enterprise AI Agents via Tencent ADP
- Understanding the definition of enterprise AI agents and their value proposition
- Tencent ADP features for agent development, knowledge integration, and workflow automation
- Distinguishing between agent-based solutions and standard chat applications
- Typical enterprise use cases and deployment considerations
Designing Agents for Business Processes
- Defining agent roles, boundaries, inputs, and expected outputs
- Selecting between single-agent and multi-agent architectures
- Structuring prompts, tools, and business rules
- Planning for escalation, human oversight, and system reliability
Developing RAG and Knowledge Workflows
- RAG principles for accurate answers and accessing enterprise knowledge
- Preparing documents, policies, and internal content for retrieval
- Designing retrieval flows and response grounding strategies
- Testing and refining answer quality over time
Orchestrating Workflows and Integrations
- Translating business processes into agent workflows
- Integrating agents with APIs, internal services, and enterprise systems
- Managing decisions, approvals, retries, and fallback mechanisms
- Coordinating handoffs between workflow stages and specialized agents
Implementing Operational Safeguards
- Safeguards for security, privacy, compliance, and policy enforcement
- Mitigating risks from unsafe output, prompt injection, and data leakage
- Incorporating approval checkpoints, audit logs, and access controls
- Designing secure response patterns for high-impact business scenarios
Monitoring, Evaluation, and Continuous Enhancement
- Tracking quality, latency, costs, and workflow success metrics
- Evaluating agent behavior in realistic business scenarios
- Resolving common issues in RAG, workflows, and orchestration
- Creating an implementation plan for pilot and production rollout
Requirements
- A foundational grasp of generative AI principles and typical enterprise AI applications
- Practical experience with APIs, web applications, or cloud-based platforms
- Basic proficiency in programming, 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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