Prompt engineering

Garden · not yet reviewed Fading: still around, used less Widely discussed since 2022

The early practice of finding special wording, templates and tricks to coax better answers from AI. Much of it matters less as models improve; its lasting core lives on in context engineering.

Also called: prompt hacks · magic prompts · prompt formulas · role prompting

Connections

Understand first

Ideas this one builds on.

• Prompting (garden)

Evolved into

Newer ideas that grew out of this one.

• Context engineering (garden)

Blueprints that practise it

• Let AI ask before it plans (garden)

Resources that teach it

• Claude Help Center: Introduction to prompt design (garden)
• Gemini API prompt design strategies (garden)
• Gemini for Workspace prompting guide (PDF) (garden)
• Prompt engineering best practices for ChatGPT (garden)
• Getting started with AI: Good enough prompting (garden)

Competency

• Describe the task

Find prompt engineering on the commons map ↗

You may know it from

• search history keyword tricks in early web search Quotation marks and special operators mattered a lot until search engines got good at understanding plain questions.
• advertising copywriting formulas

In plain words

In 2022 and 2023, getting good results from AI often depended on wording. People traded templates, told the model “you are a world-class marketer”, offered imaginary tips, or added “think step by step”. Job ads for prompt engineers appeared. Some of these tricks did help the models of the time.

Newer models understand plain requests far better, and reasoning models already work step by step. Many of the old tricks now make little difference, and some just add noise. The parts that lasted are the unglamorous ones: say what you want, give the background, show an example, describe the output format. Those moved under a wider idea, context engineering, which focuses on what the AI can see rather than how you phrase one line.

The status here is “fading”, which means the label is fading. The care it encouraged still matters.

Example

A marketing coordinator kept a page of “power prompts” from 2023. Testing them against a plain, well-briefed request on today’s tools, she found the plain version matched or beat most of them, and was easier for teammates to reuse.

How it connects

• It grew out of basic prompting.
• It evolved into context engineering, which keeps the lasting parts.
• Reasoning models made several of its tricks unnecessary.

Try it

Find an old “magic prompt” you or a colleague saved. Predict whether it still beats a plain, clear request. Run both on the same task and compare the results.

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Read this card as plain Markdown: /concepts/con-prompt-engineering.md. Know a parallel from your own field, or a product that implements this? Add it.