📰 Dev.to · Luke Fryer

Learn how Answer Engine Optimization (AEO) differs from traditional SEO and how to implement JSON-LD, FAQ schema, and structured data for AI discovery.

A production-ready .cursorrules template that enforces Tailwind, TypeScript strict mode, and App Router conventions in Cursor AI. Copy-paste ready.

Stop chatting with AI. Learn how system prompts, structured JSON outputs, and deterministic constraints transform AI from a chatbot into an engineering tool.

How Claude handles XML-tagged documents vs GPT-4o system instructions. Optimisation tips for both LLM architectures.

Client-side rendering is invisible to AI bots. Learn how to use react-helmet-async, JSON-LD, and edge functions to serve pre-rendered schema to GPTBot and Claud

A step-by-step framework for writing deterministic, version-controlled system prompts that survive production traffic. Covers constraint layering, output schema

How to implement JSON-LD structured data in React and Vite SPAs for maximum SEO and AEO visibility. Covers Article, FAQPage, HowTo, Product, and Organization sc

Should you use pre-built prompt templates or write custom prompts from scratch? A practical decision framework for engineering teams, with real-world examples a

How to build, organise, and maintain a shared prompt library for your engineering team. Covers naming conventions, categorisation, version control, and governan

Should your startup fine-tune a model or invest in prompt engineering? A practical cost-benefit analysis covering compute costs, iteration speed, maintenance bu

A practical guide to testing AI prompts in production. Covers evaluation metrics, A/B testing methodology, automated regression suites, and building feedback lo

Master chain-of-thought (CoT) prompting techniques for GPT-4 and Claude. Learn zero-shot CoT, few-shot CoT, self-consistency, and tree-of-thought methods.

Learn how to build automated AI code review workflows using GPT-4 and Claude. Covers prompt engineering for security audits, performance reviews, and style chec

Comprehensive guide to defending against prompt injection attacks in production LLM applications. Covers input sanitisation, output validation, and architectura

Complete guide to multi-modal prompting with GPT-4 Vision and Claude. Learn to combine images, code, and text for powerful AI workflows across vision and langua

RAG or long context? A technical decision guide comparing Retrieval-Augmented Generation with long context windows for production LLM applications. Covers cost,

Deep dive into AI agent architectures including ReAct, Chain-of-Thought, tool use, and multi-agent systems. Learn to build production-grade AI agents with struc

A free, copy-paste Next.js Master Prompt template for Cursor, Claude, and Devin. Lock your AI into App Router, TypeScript strict mode, and Tailwind best practic

Frustrated by your AI coding assistant losing context or building the wrong architecture? Learn why vague prompts fail and how enterprise-grade Master Prompts k

<p>BYOK (Bring Your Own Key) is a model where you provide your own Google Gemini API...

Embedding raw LLM prompts in codebases is a massive architectural anti-pattern. We used to write...

You type a prompt into ChatGPT, hit enter, and get back a generic, surface-level response. Sound...