Tag
prompt engineering
Prompt engineering is now part of the AI stack, not just wording. It covers shared prompt standards, structured outputs, agent loops, long-context handling, and governance concerns that affect error rates, token cost, and auditability in production.
25 articles
Prompt engineering is a writing skill, not a magic trick
Prompt engineering works best as disciplined writing, iteration, and verification, not as a shortcut to truth.
Deep Research Prompt Framework for Better AI Reports
FindSkill.ai breaks down a prompt framework for getting cited, multi-source research from ChatGPT, Claude, Gemini, and Perplexity.
6-part prompt scoring turns vague prompts into usable ones
I break down a six-part prompt checklist and turn it into a copy-paste template you can use before sending prompts.
How to Start Vibe Coding with AI
A practical guide to using AI coding tools for small, everyday apps.
Why Prompt Engineering Is Wrong About 2026
Prompt engineering is giving way to context engineering, and structured frameworks win because they reduce errors and improve repeatability.
Advanced Grok Prompt Guide 2026 for Grok 4.20
WiTechPedia’s 2026 guide covers Grok 4.20 prompting, multi-agent workflows, Grok Imagine edits, and 50+ templates.
How to Build a Harness for AI Agents
Harness engineering defines the control system that lets an AI agent perceive, act, and verify output.
How to Prompt Amazon Nova 2 for Moderation
Use Amazon Nova 2 Lite on Bedrock to moderate content with structured prompts.
How to Write Clear AI Prompts
A practical guide to writing clearer AI prompts for better, safer research results.
What large language models are, and how they work
Large language models turn huge text corpora into systems that generate, summarize, and reason with language.
Prompt engineering turns vague asks into usable outputs
I break down prompt engineering into practical patterns, with a copy-ready template for better LLM outputs.
IBM’s vibe coding guide turns prompts into code
I break down IBM’s vibe coding guide into a practical workflow, its limits, and a copy-ready template for AI-assisted coding.
Microsoft Copilot’s 2026 update targets real work
Microsoft’s 2026 Copilot update adds meeting intelligence, context-aware scheduling, and a five-part prompt method for harder work.
How to Engineer Prompts for AI Agents
This guide shows how to design a clear prompt and system prompt for an AI agent.
How to Switch AI Outputs from Markdown to HTML
Use HTML as the default output format for AI-generated content.
Prompt Engineering Jobs in 2026: Still Worth It?
Prompt engineering is still useful in 2026, but the best jobs now sit inside AI product, engineering, and operations roles.
How to Use OpenAI Sora in 2026
A step-by-step guide to generating and refining AI video with OpenAI Sora in 2026.
Prompt Engineering Is Becoming Infrastructure
Springer’s new chapter argues prompt engineering now needs ethics, governance, and domain expertise, not just clever wording.
Why Prompt Standards Matter for AI Work
A new Springer chapter argues prompt engineering needs shared standards to cut token waste, reduce errors, and improve AI accountability.
ChatGPT Ads Are Getting More Uniform
New data from 40,000 ad placements shows ChatGPT ads are becoming shorter, clearer, and more standardized as OpenAI optimizes for conversion.
Prompt Engineering for Agents and Structured Outputs
Prompt engineering gets harder in production: reasoning, long contexts, JSON contracts, and agent loops all need different prompt tactics.
Prompt Engineering, Explained Without the Hype
Prompt engineering turns vague requests into usable AI outputs. AWS breaks down the methods, use cases, and tradeoffs behind better prompts.
Why Prompt Engineering Isn’t Engineering
Prompt design is mostly heuristic, not formal engineering. The evidence shows weak standards, shaky testing, and a lot of guesswork.
Duplicate Prompts Can Lift Accuracy Fast
A Google study found repeating prompts once improved 47 of 70 model-benchmark pairs, with one task jumping from 21% to 97%.
Mastering AI Prompts: A 2026 Guide for Developers
38.5% of AI conversations need refinement in 2026. Discover strategies to streamline your AI interactions and reduce iterations for better outcomes.