From Automation to Multi-Agent Architectures
In this series, you’ll learn how to design, build, and evaluate AI agents—from simple automation and ReAct-style agents to full multi-agent ecosystems. Each step introduces greater autonomy, coordination, and complexity, with a strong focus on evaluations to ensure reliability and real-world performance.
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Tue Feb 24·8:00 PM UTC
Part 1: Vertical Automated AI Agents That Deliver Results
Most AI agents today look great in demos but fail in real-world use. This course teaches you to build enterprise-grade AI agents that retrieve, analyze, and collaborate intelligently. You'll master multi-agent systems, optimized retrieval, and real-world deployment—focusing on practical, scalable AI over hype. Join us to build agents that actually work in production! 🚀
You'll learn from
Hamza Farooq
Founder & Adjunct Professor | 15+ years | Google | Stanford | UCLA
Gabriela de Queiroz
Ex-Microsoft & IBM AI leader | AI Advisor for Startups
Wed Feb 25·8:00 PM UTC
Part 2: Building ReAct to Multi-agent Architectures
Single-agent systems break down as tasks grow more complex. This matters because real-world AI systems require coordination, specialization, and reliability. Production AI systems must reason about context, constraints, and consequences before taking action. ReAct provides a foundation for building agents that are interpretable, flexible, and reliable, bridging the gap between static prompts
You'll learn from
Hamza Farooq
Founder & Adjunct Professor | 15+ years | Google | Stanford | UCLA
Gabriela de Queiroz
Ex-Microsoft & IBM AI leader | AI Advisor for Startups
Thu Feb 26·8:00 PM UTC
Part 3: Building Robust Evaluations for AI Agents
AI agents often seem to work, until real users, edge cases, and scale expose their failures. This matters because without proper evaluation, teams ship systems they can’t trust or improve. Robust evals turn agent systems from impressive demos into reliable, measurable, and production-ready products.
You'll learn from
Hamza Farooq
Founder & Adjunct Professor | 15+ years | Google | Stanford | UCLA
Gabriela de Queiroz
Ex-Microsoft & IBM AI leader | AI Advisor for Startups