Whenever I talk about AI agents, people tend to imagine something quite futuristic and complicated. Visions of matrix-style screens appear before you and it’s easy to get so overwhelmed by it all that you end up doing nothing, leaving that niggling feeling that you can (and should) be using AI to create more leverage for yourself but you don’t actually end up doing it because it all feels too much.
The reality is that AI agents are much more simple to create and implement than you might think. In fact, you can have one up and running in less than an hour.
One of my highest leverage AI agents is my meeting notes and task follow up agent that runs inside Notion and it handles everything that happens after every meeting I have.
For a long time, every meeting ended in exactly the same way. I’d close Zoom and immediately have another half an hour of work waiting for me. I’d tidy the notes, pull out the important decisions, work out who had agreed to do what, add my actions to my task list and then draft the follow-up email while the conversation was still fresh in my head.
That is assuming I wasn’t hopping straight onto another call in which case, the follow-up work would inevitably get pushed late into the night or the next day, leaving me feeling like I was always chasing my tail.
None of work is especially difficult. It’s just repetitive, easy to delay and surprisingly good at eating into the rest of the day.
It is also exactly the sort of work I want AI to do. So when I built this agent last year, it completely changed my working day and I am now finally free from the shackles of call follow-ups!
Annnd I know what you’re thinking “but Helena there are tools like Granola and Wispr and Zoom that do this already”. And yes, they do some of this. But the key part about this agent is the task set-up and collating everything YOU need to do across every meeting, every project, every interaction AND across your business and personal life in one place. No more siloed to-do lists and actions. Instead you have a single point of truth for it all.
Before we start, here’s the finished workflow.
Every time I finish a meeting, I change the meeting status to Completed.
From there, the agent automatically:
reads the meeting transcript
identifies what was actually agreed
creates my follow-up tasks and adds them to my tasks database
links those tasks back to the meeting
drafts the follow-up email in my voice
Importantly, it doesn’t send the email.
I always review it first.
This isn’t about replacing relationships with AI. It’s about removing thirty minutes of repetitive admin after every meeting.
In this guide, I’m going to show you exactly how I set up this agent inside Notion, starting with the databases it relies on, then the workflow itself, and finally the instructions that tell it how to do the job properly. Because the most important part of this setup isn’t actually the prompt — it’s the system underneath it.
One of the biggest mistakes I see people make with AI agents is starting with the instructions.
They open a blank page, spend an hour writing something incredibly detailed and then wonder why the results are inconsistent.
Usually, the problem isn’t the prompt but the information (and the structure of that information) the agent is working with.
An AI agent can only work with the structure you give it. If your client information lives in one place, your projects somewhere else, your meeting notes are scattered across random pages and your tasks are sitting in a completely separate system, the agent has to work out how everything fits together.
That is when you start getting duplicate tasks, follow-up emails that miss important context and actions assigned to the wrong person.
Before you build the agent, you need to build the system it is going to work inside.
Watch the complete setup (10 mins)
In this walkthrough I’ll show you the finished workflow so you can see what this looks like in action. The step-by-step set-up instructions are then outlined for you below.
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