AI Image Aspect Ratios Explained: Which to Use and When
A practical guide to AI image aspect ratios: 1:1, 16:9, 9:16, 4:3, 3:2, 21:9. Best ratios per platform and exact syntax for Midjourney, Flux, DALL-E.
Tag
prompt-engineering
10 articles tagged prompt-engineering. Browse the full blog.
AI Video Prompting Guide 2026: Sora, Veo, Runway, Kling, and More
How to write prompts for AI video generators. Covers Sora, Veo 2, Runway Gen-4, Kling 2, camera moves, durations, seed reuse, and style transfer.
AI Prompting Glossary: Every Term You Need to Know
A-Z reference for AI prompting terms: chain-of-thought, few-shot, system prompt, temperature, top_p, function calling, ReAct, prompt injection, and more.
AI Image Prompting Guide 2026: Get Better Results From Every Generator
Practical prompting techniques for Midjourney, DALL-E, Flux, and Stable Diffusion. Covers syntax, negative prompts, aspect ratios, and style control.
Prompt Engineering for Agents vs. Chatbots: What Changes and Why
How prompt engineering differs for AI agents vs chatbots. System prompts, tool definitions, ReAct, structured outputs, persistence, error handling.
How to Write Cursor Rules in 2026: Real Examples for Every Stack
Practical .cursorrules patterns for Python, TypeScript, and Rust projects. Project-level vs global rules, what works, what doesn't, and real examples.
AI Agent Prompt Injection Defenses: What Actually Works in 2026
Real prompt injection attacks against AI agents and the defenses that stop them. Output filtering, structured prompts, sandboxing, and case studies.
AI Coding Agent Prompt Engineering: Real Patterns That Work
Practical prompt engineering for Claude Code and Cursor. CLAUDE.md structure, system prompt patterns, context priming strategies used by working developers.
Prompt Engineering for AI Agents: What's Different in 2026
Agent prompting is not chatbot prompting. Learn how to design system prompts, tool descriptions, planning prompts, and reflection prompts that make agents.
Getting Reliable Structured Output from AI Agents in 2026
JSON mode, XML tags, Zod schemas, and real patterns for reliable structured output from LLMs. What works, what breaks, and why.