A practical, data-driven guide comparing prompting vs. fine-tuning for LLM apps, with decision checklists, trade-offs, and implementation tips.
Design a production-grade AI marketing copy generation API: architecture, prompts, guardrails, evaluation, and code examples.
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.
