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https://github.com/vbrazo/agent-system-design


https://github.com/vbrazo/agent-system-design

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README

          

# Agent System Design

Designing reliable, scalable, and trustworthy agentic AI systems.

## Start here

→ **[Overview](./course/README.md)**

## Module 1: Agent Design Fundamentals

Six lessons covering agents, architecture, memory, orchestration, safety, and production challenges:

1. [Introduction to AI Agents](./course/modules/01-agent-design-fundamentals/01-introduction-to-ai-agents.md)
2. [Core Agent Components](./course/modules/01-agent-design-fundamentals/02-core-agent-components.md)
3. [Component Interaction and Memory](./course/modules/01-agent-design-fundamentals/03-component-interaction-and-memory.md)
4. [Agent Orchestration Patterns](./course/modules/01-agent-design-fundamentals/04-agent-orchestration-patterns.md)
5. [Guardrails and Human Oversight](./course/modules/01-agent-design-fundamentals/05-guardrails-and-human-oversight.md)
6. [Challenges and Design Strategies](./course/modules/01-agent-design-fundamentals/06-challenges-and-design-strategies.md)

## Module 2: Multi-Agent Conversational Recommender System (MACRS)

Four-lesson case study on multi-agent planning, reflection, and evaluation:

1. [Introduction to MACRS and the Design Challenge](./course/modules/02-macrs/01-introduction-to-macrs-and-design-challenge.md)
2. [Multi-Agent Act Planning Framework](./course/modules/02-macrs/02-multi-agent-act-planning-framework.md)
3. [User Feedback-Aware Reflection Mechanism](./course/modules/02-macrs/03-user-feedback-aware-reflection-mechanism.md)
4. [Evaluating MACRS: Performance and Insights](./course/modules/02-macrs/04-evaluating-macrs-performance-and-insights.md)

## Exercise

- [Thought Exercise: Design a Smart Parking Agent System](./course/thought-exercise-design-a-smart-parking-agent-system.md)

More modules will be added as content is provided.