Battle-tested patterns, production insights, and practical guides for building AI systems that actually work. No hype, just engineering.
An in-depth analysis of a real-world RAG system failure in the legal industry, and the architectural lessons every AI engineer should learn from it.
Real infrastructure patterns for high-volume LLM applications: queue management, intelligent retries, request batching, and graceful degradation.
Real examples of prompt injection attempts against our enterprise AI products, from naive attacks to sophisticated multi-step exploits.
How we built a memory system that lets our AI agents remember context across months of interactions without blowing up costs or latency.
Why response_format isn't enough, and the validation pipeline that catches the 3% of malformed outputs that will break your production system.
Build your intuition for neural networks from the ground up. Understand exactly how neural networks learn, why they work, and what happens inside - with diagrams, examples, and no hand-waving.
A comprehensive guide to embeddings - the secret sauce behind modern AI's understanding of language, images, and more. Learn how words become numbers that capture meaning.
The definitive guide to writing prompts that get results. Learn the techniques that separate amateur prompts from expert-level prompts that unlock AI's full potential.
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