AI Prompt Engineering Blog
Expert guides, tutorials, and insights to master the art of prompt engineering for ChatGPT, Claude, Gemini, and beyond.
Latest Articles
Page 12 of 22Needle in a Haystack Prompting Guide (2026)
What the needle-in-a-haystack benchmark tests, why passing it isn't enough, and how to prompt so buried facts are actually findable.
Plan-and-Execute Prompting: Decompose First, Then Act (2026)
The plan-and-execute agent pattern — decompose the goal into a plan, review the plan, then execute. Trade-offs vs ReAct and when to use each.
Prompt Caching Guide (2026): Cutting LLM Costs With Cache Hits
How prompt caching works at Anthropic and OpenAI in 2026 — cache markers, hit requirements, TTL, and how to structure prompts so the cache actually fires.
ReAct Prompting Guide: Reasoning Plus Acting for AI Agents (2026)
How the ReAct pattern works — interleaved reasoning, action, and observation. When ReAct beats chain-of-thought or pure tool use, and how to prompt for it.
Reflexion Prompting Guide: Verbal Self-Reflection After Failures (2026)
How reflexion prompting works — the agent writes a reflection after each failed attempt, accumulating episodic memory that guides later retries.
Replit Agent Prompting Guide (2026)
How to prompt Replit Agent — product-brief prompts for full-stack scaffolding, iteration patterns, and the run-observe-refine loop.
Retrieval-Augmented Prompting Patterns (2026)
Four prompt patterns that make RAG actually work — explicit citation, groundedness framing, chunk formatting, and negative handling.
Self-Refine Prompting: Critique and Revise in One Loop (2026)
How self-refine prompting works — the model produces, critiques, and revises. When this single-model loop helps, when it hurts, and how to prompt for it.
Semantic Caching vs Prompt Caching: Different Caches, Different Jobs (2026)
Semantic caching skips the model on similar queries; prompt caching skips compute on repeated prefixes. Both cut cost but solve different problems — and most production systems use both.
Spec-Driven AI Coding: Writing Specs Agents Execute Well (2026)
How to write specs agents execute well — user story, acceptance criteria, out-of-scope, constraints. The spec is the prompt when agents run autonomously.
System Prompt vs User Prompt: What Goes Where (2026)
The difference between system prompts and user prompts — stable persona vs dynamic task — and why the split matters for caching, attention, and consistency.
Token Economics Guide (2026): Making AI Cheap Enough to Ship
Token economics for production LLM apps — input vs output pricing, caching amortization, model tiering, and the trade-offs that decide what's affordable.
Tool Use Prompting Patterns: Getting Reliable Tool Calls (2026)
Prompt patterns that make tool use reliable — clear tool descriptions, tool-forcing vs tool-permitting, error recovery, and handling malformed arguments.
v0 Prompting Guide: How to Prompt Vercel v0 (2026)
How to prompt Vercel v0 for production-quality UI. Component-level prompts, screenshot-to-UI, iteration patterns, and what v0 is (and isn't) good at.
Windsurf AI Prompting Guide (2026)
How to prompt Windsurf — Codeium's AI-first IDE. Cascade agentic mode, flow-based context awareness, and when to trust vs. constrain auto-context.
AI Contract Analysis: How to Prompt AI to Review Contracts Like a Senior Associate
Step-by-step guide to using AI for contract analysis. Prompt templates for clause extraction, risk flagging, liability analysis, and comparison against standard terms.
Legal Research with AI: Prompts for Case Law, Statutes, and Regulatory Analysis
AI prompt templates for legal research — case law analysis, statutory interpretation, and regulatory compliance. Includes critical guidance on verifying AI output and avoiding hallucinated citations.
Which AI Model Should You Use? A Decision Framework for 2026
A practical decision framework for choosing between Claude, ChatGPT, Gemini, and other AI models based on your task, budget, and workflow.