Practical strategies to optimize LLM context windows—reduce cost and latency while preserving accuracy with RAG, chunking, compression, caching, and evaluation.
Use Stable Diffusion APIs in production: concepts, parameters, code examples, scaling, safety, and cost optimization.
A practical blueprint for preventing prompt injection in LLM apps: threat models, mitigations, code patterns, testing, and operations.
A practical guide to integrating an AI writing assistant via API—architecture, prompt design, code samples, safety, evaluation, and performance optimization.
A practical tutorial on reasoning models and chain-of-thought: safe prompting, self-consistency, tree-of-thought, tooling, and evaluation patterns.
A practical, end-to-end guide to reducing AI hallucinations with data, training, retrieval, decoding, and verification techniques.
