AI Fluency & Building · AI Integration
Start here. Short, guided tasks that build the basics and give you your first piece of proof.
Task 1 of 3
Make and document real API requests in Postman.
What to do
Call a free public API useful to a business (weather, currency exchange, maps or a product catalogue API) from Postman. Document every request and response and publish the collection.
You’ll make
Done looks like
A published Postman collection with every request and response documented.
Task 2 of 3
Connect an AI to a tool and explain the permissions.
What to do
Install an existing MCP server (filesystem, fetch or a Google Drive server) in an MCP-capable AI app and record a demo of the AI using it for a business task, with a note on what permissions you granted and why.
You’ll make
Done looks like
A demo recording plus a note on the permissions you granted and why.
Task 3 of 3
How to store keys safely in a project.
What to do
Write a beginner's guide called 'API keys: how to store them safely', covering .env files, never committing secrets to GitHub, and what to do if a key leaks.
You’ll make
Done looks like
A beginner's guide covering .env files, secrets in git and key rotation.
Learn before you build
Free course
Free courses, including AI Fluency and Model Context Protocol, with certificates.
Free course
Learn to explore, test and document APIs.
Free tool
Open-source workflow automation you can self-host for free.
Code repo
Real MCP servers to read, run and learn from.
Article guide
The official MCP spec, quickstarts and SDKs.
Article guide
The fastest way to build a clean Python API.