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Designing Multi-Tier AI Agent Systems for Enterprise Workflows

7 chapters · 33 lessons

1. 1. Agent Execution Loops and Control Flow

   4 lessons

   Build the core loop that enables an agent to plan, act, retrieve context, and evaluate results.

2. 2. Retrieval-Augmented Generation for Agent Context

   5 lessons

   Equip agents with relevant knowledge by integrating document retrieval and vector search.

3. 3. Tool Interfaces and Safe Integration

   5 lessons

   Connect agents to external systems with clear boundaries, permissions, and error handling.

4. 4. Enterprise Tier Architecture and Governance

   5 lessons

   Design managed agent infrastructure with identity, audit, data residency, and compliance controls.

5. 5. Local Tier Deployment for Latency and Privacy

   4 lessons

   Run agents on user devices or edge infrastructure for offline access and low-latency interaction.

6. 6. Hybrid Agent Systems and Task Routing

   5 lessons

   Architect systems that route tasks between local and enterprise tiers based on complexity and risk.

7. 7. Production Patterns and Operational Readiness

   5 lessons

   Deploy and maintain agent systems with reliability, observability, and continuous improvement.