Skip to content
MAPMake AI Practical

About

About MAP

How a scattered group of people who wanted AI to actually help at work turned into a community that learns by building, and documents everything in the open.

How MAP started

It started with a simple frustration

MAP began with a group of people who kept hitting the same wall: endless talk about AI, but very little that helped with the actual work in front of them. What existed was scattered: an event in one place, a shared doc in another, a chat thread somewhere else, with no single home to learn, meet, or catch up.

So we started running small, practical sessions: build something real with AI, show each other how it went, and write down what worked. Word spread, more people came, and it grew into the community MAP is today.

Over 100 members now treat AI as a practical skill to build, not a spectator sport to read about.

How we learn

Learn by building, and document it in the open

We think the fastest way to actually learn AI is to build something small and real with it, then write down how it went, the wins and the dead ends, so the next person doesn't start from zero.

Nobody has to be an expert to take part. When one member figures something out, they share it, and the whole community moves forward. Everything we build and learn is documented publicly, so MAP gets a little smarter every week.

The curriculum

Three stages, from foundations to agents

Everyone moves at their own pace, but the path is the same: get comfortable with AI, wire it into your work, then hand off whole jobs to agents.

  1. Foundations

    Get comfortable with what today's AI can and can't do.

    Start here. We cover how modern AI actually behaves, how to ask for what you want, and how to tell when the answer is good enough to trust. No jargon and no maths, just the working mental model you need before AI can help with anything real.

  2. Workflows

    Wire AI into the real tasks you do every week.

    Once the basics click, we build AI into your actual work: drafting, summarising, research, the repetitive things that eat your week. You'll learn to chain a few steps together, connect the tools you already use, and turn a one-off prompt into something you reach for every day.

  3. Agents

    Hand off whole multi-step jobs to AI that can act on its own.

    The frontier stage. We build agents: AI that takes a goal, plans the steps, uses tools, and carries a multi-step job through with light supervision. You'll learn what agents can reliably do today, where they still need a human in the loop, and how to set one up for a task you care about.

Curious who runs all this? Meet the team →

Come build with us

MAP is free, friendly, and open to anyone who wants AI to work in their job. Start with your first session.

Join the community