AI
LLMs, prompt engineering, RAG, AI agents, MLOps and computer vision — always fresh.
LLMs, prompt engineering, RAG, AI agents, MLOps and computer vision — always fresh.
Using an LLM to generate meta descriptions, alt text, and schema.org data right in the CMS publish flow.
Comparing RAG with fine-tuning, and when to pick pgvector over a dedicated vector database.
Structuring system prompts, few-shot examples, and how to bound a chatbot's answer scope.
Evaluating accuracy, speed and cost of three popular models when generating NestJS/TypeScript code.
Designing an agent that reads content, checks SEO/i18n compliance, flags risk, and suggests edits before an editor approves it.
Packaging model serving into containers and managing GPU resources across multiple replicas.
Building an automated moderation pipeline for uploaded images before media gets published to a site.
A formula for input/output token cost, plus tips for reducing cost with prompt caching.