Save and Reuse ChatGPT Prompts
ChatGPT doesn't have a real prompt library built in. Here is how people actually save, reuse, and repurpose prompts - plus a faster alternative.
Native options inside ChatGPT: pin a chat, use Custom Instructions, or build a Custom GPT. Each works for a handful of prompts but breaks down past 20 - chats get buried, Custom Instructions are global, and Custom GPTs need rebuilding for each variation.
External options: a Notion database, a markdown file in your editor, or a dedicated prompt library. The library wins as your collection grows past a few dozen entries because search, tags, and model-version notes are built in.
Repurposing is where most people lose the most time. A prompt written for a cold email rarely works for a follow-up without edits. The fix is to write prompts with explicit variables ({audience}, {goal}, {tone}) so you swap inputs instead of rewriting the whole prompt - every entry in our library follows this pattern.
If you do not want to maintain your own library, the Simple AI Prompt Library has 420+ tested prompts and 665+ Loops already organized by job, model, and domain. Free after a one-click sign-in.
Reusable prompt templates
Save these once. Swap the variables in curly braces, paste into ChatGPT or any other model, and reuse forever. Hit copy to drop the full template on your clipboard.
The Reusable Cold Email Prompt
Swap the variables in curly braces, paste into ChatGPT, get a tested cold email every time.
You are a senior B2B copywriter. Write a cold email to {audience} on behalf of {company}, which sells {product}.
Goal: {goal} (e.g. book a 15-min call, get a reply, drive a demo).
Tone: {tone} (e.g. direct, warm, playful).
Constraints:
- Under 90 words.
- One specific reason this email is relevant to them.
- One concrete CTA at the end.
- No emojis, no buzzwords, no "I hope this finds you well".
Return: subject line + body. Then list 2 alternative subject lines.The Reusable Blog-Post Prompt
A single template that adapts to any topic, audience, and word count. Built around named variables.
Write a {word_count}-word blog post titled "{title}" for {audience}.
Angle: {angle}
Primary keyword: {keyword}
Reader's job-to-be-done: {jtbd}
Structure:
1. Hook (2 sentences, no throat-clearing).
2. Why this matters now (1 short paragraph).
3. 3-5 H2 sections, each with a concrete example.
4. A "what to do next" close with one specific action.
Voice: {voice}. Avoid em dashes, "in today's world", and any phrase ChatGPT defaults to.The Reusable Code-Review Prompt
Drop in any diff or file. Returns ranked issues, not vague suggestions.
Act as a senior {language} engineer reviewing a pull request.
Code under review:
{code}
Context: {context} (what the change is meant to do).
Return:
1. Top 3 issues, ranked by severity (bug > security > perf > style). Cite line numbers.
2. For each issue: one-line fix + a code snippet showing the corrected version.
3. One thing the author did well.
4. A single sentence: ship / ship with changes / block.The Reusable Meeting-Notes Prompt
Paste any transcript. Get the same clean structured output every time.
Turn the transcript below into structured meeting notes.
Transcript:
{transcript}
Return exactly this structure:
- TL;DR (2 sentences)
- Decisions made (bullet list, with the owner in brackets)
- Action items (bullet list, format: "[owner] action - due {date}")
- Open questions
- Risks or concerns raised
Skip filler, side conversations, and pleasantries. Keep names exactly as spoken.The Reusable Customer-Reply Prompt
One template for support replies, refunds, escalations, and feature-request acknowledgements.
You are a {brand_voice} customer-support agent for {company}.
Customer message:
{message}
Situation: {situation} (e.g. refund request, bug report, angry user, feature ask).
Policy notes: {policy}
Write a reply that:
- Acknowledges the specific thing they said (not "thanks for reaching out").
- States what we will do, in plain language.
- Gives a realistic timeline.
- Ends with one clear next step.
Length: under 120 words. No corporate hedging.Featured loops
The Negative Persona Filter
Actively tries to disqualify a lead to save time on dead ends.
The Staff Burnout Buffer Loop
Identifies repetitive CRM clicks and proposes macro-automations to save staff time.
The Subscription Stickiness Loop
Refines the 'Subscribe & Save' value proposition to prevent immediate cancellations.
Frequently asked
Not as a library. You can pin chats, set Custom Instructions, or build a Custom GPT - none of which scale past ~20 prompts. Most people use an external library.
Yes, every prompt is stored in your chat history (unless temporary chat is on), but history is search-only - there is no prompt-library view.
Three options: pin the chat (sidebar > pin), paste into Custom Instructions for global use, or save in a Custom GPT for a focused workflow.
Write it with named variables once, store it externally, and swap inputs. Or skip the work and use a curated library.
Strip model-specific syntax (Claude XML tags, GPT system blocks) and re-test. Our library tags each prompt with the models it works on so you skip the trial-and-error.