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Course Outline

Enterprise AI Agents with Tencent ADP

  • An overview of enterprise AI agents and their strategic value in government operations
  • Tencent ADP capabilities to support agent development, knowledge integration, and workflow automation for government agencies
  • Distinguishing agent-based solutions from standard chat applications
  • Key enterprise use cases and critical delivery considerations for federal implementations

Designing Agents for Business Processes

  • Defining agent roles, operational boundaries, inputs, and outputs within agency workflows
  • Selecting between single-agent and multi-agent architectures based on mission requirements
  • Structuring prompts, integrated tools, and adherence to business rules
  • Planning for escalation protocols, human oversight, and system reliability

Building RAG and Knowledge Workflows

  • RAG concepts for providing grounded answers and secure enterprise knowledge access
  • Preparing documents, policies, and internal content for effective retrieval in government contexts
  • Designing retrieval flows and response grounding patterns to ensure accuracy
  • Testing and continuously improving answer quality over time

Orchestrating Workflows and Integrations

  • Mapping existing business processes into automated agent workflows
  • Connecting agents to APIs, internal services, and legacy enterprise systems
  • Managing decisions, approvals, retries, and fallback paths for mission continuity
  • Coordinating handoffs between workflow steps and specialist agents to ensure seamless operation

Applying Operational Guardrails

  • Implementing guardrails for security, privacy, compliance, and policy control in government systems
  • Mitigating risks associated with unsafe output, prompt injection, and sensitive data exposure
  • Establishing approval checkpoints, audit trails, and strict access controls
  • Designing safe response patterns for high-impact business scenarios involving public services

Monitoring, Evaluation, and Continuous Improvement

  • Tracking key metrics including quality, latency, cost, and workflow success rates
  • Evaluating agent behavior across realistic government business scenarios
  • Troubleshooting common challenges related to RAG, workflows, and orchestration
  • Developing an implementation plan for pilot testing and subsequent production adoption for government use

Requirements

  • Demonstrated familiarity with generative artificial intelligence frameworks and prevalent organizational applications
  • Practical proficiency in utilizing application programming interfaces, web-based systems, or cloud infrastructure services designed for government environments
  • Fundamental expertise in software development, system integration, or architectural solution planning

Target Audience

  • Solution architects and senior technical leadership
  • Artificial intelligence engineers, application developers, and automation specialists
  • Product managers and innovation units tasked with advancing enterprise AI strategies
 14 Hours

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