1) Start with the Reality: Why Observability Matters Building AI agents is exciting—but running them in production is where most challenges appear. Common problems include: This is why observability is essential. Observability allows you to understand exactly what your AI agent is doing at every step—from input to final output. Platforms like LangSmith, developed by…
Introduction Computers do not understand words. They understand numbers. This simple fact is the foundation of all modern AI. Before a machine can process language, it must convert text into a form it can work with. That conversion happens through embeddings. Embeddings are the unsung heroes of modern AI. They power semantic search, recommendation engines, retrieval-augmented…
1) Start with the Problem: Why Do AI Agents Need Memory? Most AI agents fail not because of poor models—but because they forget. Imagine a customer support agent that helps you troubleshoot a problem, then completely forgets the conversation when you return an hour later. Or a personal assistant that asks for your preferences repeatedly because…