AI system design

Unlock AI's potential with Agent-to-Agent (A2A) communication. Design collaborative AI systems for scalability, specialization, and efficiency.

Saurav KumarJul 132,2411,000

Learn the differences between single-agent and multi-agent AI architectures and discover which approach works best for modern AI systems. In this session, Swarnim Srivastava explains orchestration models, scalability, collaboration patterns, performance trade-offs, and enterprise use cases for building intelligent AI agent systems.

CSharp TVMay 113,914250

Learn how LLMs and graphs are shaping the future of GenAI through GraphRAG. In this session, Jennifer Reif explains how GraphRAG combines knowledge graphs with retrieval-augmented generation to improve reasoning, contextual understanding, and AI accuracy in real-world applications.

CSharp TVMay 62,405250

A developer's guide to AI system design: Learn to build scalable, reliable, and intelligent applications. Master data pipelines, model deployment, and monitoring.

Niharika GuptaMay 55371,000

RAG vs Fine-Tuning — which one should you really use in real AI products?

CSharp TVFeb 3250

Building an AI model is easy. Running it reliably in production is hard.

CSharp TVJan 30250

Modern AI apps don’t use just one model. They use multiple AI models working together — through AI Orchestration.

CSharp TVJan 29250

ChatGPT is powerful. But modern AI apps need more than just LLMs.

CSharp TVJan 22250

Prompt Engineering teaches AI what to do; Context Engineering teaches AI what matters. Learn the difference between prompt and context engineering, their roles in generative AI, and how they shape the future of intelligent systems.

Mahesh ChandOct 12, 20254,7291,000