Last week my cofounder sent me a prompt.
"Hey, I use this in ChatGPT to summarize customer feedback. You should try it."
The prompt was good. Three paragraphs of instructions, specific formatting rules, examples of what good output looks like. He'd clearly spent time refining it.
I pasted it into a new chat. Got garbage output. The model ignored half the formatting rules. I asked him what I was doing wrong. He said "oh yeah, you need to paste the context document first, then the prompt, then the feedback." None of that was in the Slack message.
Twenty minutes later I got it working. Sort of. His outputs still looked better than mine, and I never figured out why.
This is how most teams share AI workflows today. And it's completely broken.
The three ways we share AI workflows
1. Prompts over Slack
Someone figures out a useful prompt. They paste it into Slack. You copy it into ChatGPT. It doesn't work the same way. You ask questions. They explain the context you were missing. You get it working, mostly. A week later they update the prompt and forget to tell you.
2. Scripts in a repo
Someone writes a Python script that calls the OpenAI API. They push it to a repo. You clone it. You set up a virtual environment. You realize you need API keys. You find the .env.example file and create your own .env. You run the script and get an error because you're on a different Python version. You spend an hour debugging dependency issues.
Eventually it works. A month later they make updates and you have to pull and hope nothing breaks.
3. Full repos with READMEs
The "professional" version. Someone maintains an internal tool with documentation. You clone it, follow the README, set up the environment, configure everything. If you're lucky, it works. If you're not, you're debugging someone else's code on your machine.
Every one of these methods has the same problem: the person receiving the workflow has to do significant work to make it run.
What sharing should look like
When I share a document with someone, I send them a link. They click it. They see the document. They don't have to install Word or set up Google Drive credentials or configure anything. They just see it.
Sharing a workflow should work the same way.
Send a link. They click it. They run the workflow. Same environment. Same configuration. Same results.
No prompts to paste. No repos to clone. No environments to set up. No API keys to refresh. Just a workflow that works.
Why the old way persists
The reason we share prompts and scripts is because there hasn't been a better option. AI tools are designed for individual use. You have your ChatGPT account, I have mine. There's no shared workspace where we both run the same workflow.
Scripts are the workaround. You package up your workflow as code and share the code. But code requires setup. It requires maintenance. It breaks when dependencies change or environments differ.
We've accepted this friction because we didn't have an alternative.
The shared environment changes everything
When workflows run in a shared environment, sharing becomes trivial.
You build a workflow. You click share. Your teammate gets a link. They click it and run the workflow. Same models. Same API connections. Same execution environment. Same results.
When you update the workflow, they get the update automatically. No re-sharing. No re-downloading. No "hey, I pushed a new version, make sure you pull."
When they have questions, they can see the workflow structure. They can see what each step does. They can see the context and the prompts and the outputs. They're not reverse-engineering a script or guessing what implicit context you had in your chat thread.
What this unlocks
When sharing is frictionless, people actually share.
The automation your cofounder built for sales emails? You can use it too. The workflow the ops team built for processing invoices? Anyone who needs it can run it. The prompt engineering someone on your team spent days perfecting? It's available to everyone, with all the context and structure intact.
You stop hoarding knowledge in individual chat threads. You stop maintaining parallel versions of the same script. You stop explaining the same setup steps to every new person who needs to run your workflow.
You just share a link, and it works.
That's what workflow sharing should be. Not prompts in Slack threads. Not scripts in repos. Not READMEs you hope someone reads.
Just workflows that work for everyone, instantly, in the same environment.
Because your team has better things to do than set up each other's environments.
Frequently Asked Questions
How do teams typically share AI workflows today?
Most teams share prompts via Slack or email, pass around Python scripts, or maintain internal repos that teammates have to clone and configure locally. Each method requires the recipient to do significant setup work.
What's wrong with sharing prompts?
Prompts lose context when copied. The person sharing them had specific context, formatting expectations, and follow-up steps in mind. The recipient just gets text to paste into a chat window, often with inconsistent results.
Can Miniloop replace internal automation scripts?
Yes. Workflows in Miniloop can do what most internal scripts do, but they run in a shared environment so there's no setup required. Anyone on your team can run them immediately.
