Llm

The humble tokenizer decides what a model can ever learn. Why BPE, WordPiece and Unigram differ, and how to build, test and monitor one properly.

Eight retrieval architectures, from Simple RAG to agentic swarms. The trick is not choosing the cleverest one, but the one that fixes your actual failure.

Tweaking a chatbot prompt is easy; knowing whether you improved it is not. How to A/B test LLM prompts in production—the mechanics, the metrics, the tooling.

Autonomous AI agents no longer just answer; they plan, act and fail in inventive ways. How to build them on AWS, from supervisors to event-driven swarms.

A demo agent that crashes loses everything; a production one must not. How LangGraph keeps state, survives failures and resumes where it left off.