Compare small and large language models across cost, latency, privacy, and accuracy. Includes routing patterns, tuning options, and a decision checklist.
Build robust AI agent memory with episodic and semantic layers: schemas, retrieval, consolidation, evaluation, and governance—practical patterns included.
A 2026 field guide to modern LLM prompt engineering: patterns, multimodal tips, structured outputs, RAG, agents, security, and evaluation.
A practical guide to choosing RAG vs fine-tuning, with a clear decision framework, patterns, code sketches, and pitfalls.
How to build and use an AI text summarization API: models, request design, chunking, evaluation, security, and production best practices.
