A few months ago, I was trying to book a venue in Austin for an upcoming workshop. I emailed the contact and said something like:
“I’d love to use your space. I’m cc’ing my assistant Linda to help coordinate schedules.”
The contact replied. Linda replied back. They went back and forth over a couple of days.
I woke up to a confirmed meeting on my calendar.
Never touched it. Never saw the emails until after the fact.
And when I checked the bill on my Lindy account? Total cost for the entire coordination: 15 cents.
That was the moment this stuff stopped being a cool party trick and started being infrastructure.
Linda Isn’t a Person
When I said I was cc’ing my “assistant Linda,” I wasn’t lying exactly… I just wasn’t being fully transparent. Linda is my Lindy AI agent. She has access to my calendar, can read incoming emails, and knows my scheduling rules.
She saw the original email, checked my calendar, and responded with available times. When the venue contact replied with a different time, Linda checked again and counter-offered. They went back and forth a few times.
Done. Meeting on calendar.
The contact had no idea she wasn’t talking to a human assistant.
Now, if you want to give AI agents actual people’s names, that’s a judgment call. I’ve moved toward being more upfront since then — Hudson Penn (a client of mine who runs four businesses) actually prefers that I mention it’s an agent. He finds it more impressive, not less. But the point is the agent can do this level of coordination without you ever getting involved.
The Numbers Behind My Agent Stack
That 15-cent meeting isn’t a one-off.
Right now I’m running about 45-50 AI agents across my work. On my Lindy dashboard, I can see a weekly report: how many tasks they ran, and how much time they saved.
Last week: 1,074 tasks. 73 hours saved.
The week before: 867 tasks. 54 hours saved.
That’s somewhere between 2 and 3 extra work weeks per week… freed up. Not because I’m working less. Because a bunch of repetitive coordination work that would normally fall to me (or to a human assistant) is just… handled.
The 80-20 Agent Building framework I teach in my workshops is built around this idea: automate the tasks that happen daily and weekly, not the impressive-but-rare ones. Meeting scheduling happens constantly. That’s why it was the first agent I built, and why I still recommend it as the first one for anyone getting started.
The Three Levels of AI Work
Most people I meet are stuck at what I call Level 1.
There are actually three levels of AI work:
Level 1 — AI Assisted. You go back and forth with the AI to produce something. ChatGPT conversations, Claude responses. You’re still doing the driving.
Level 2 — AI Workflows. You’ve built a predictable process. Same input, same output, every time. More reliable, but you still kick it off manually.
Level 3 — AI Agents. The agent runs on its own. It monitors for triggers, executes a workflow, delivers the result. You’re not in the loop at all unless something goes wrong.
Most people I teach are comfortably at Level 1. Some are experimenting with Level 2. Very few have gotten to Level 3 — but that’s where the real hours come back.
The scheduling agent I built for Linda is pure Level 3. It monitors my inbox, finds the emails that need scheduling, handles the coordination, and puts the meeting on my calendar. I don’t initiate it. It just runs.
Your First Agent Should Be This
If you’ve been thinking about building an AI agent but haven’t started yet, start with scheduling.
Here’s why: it’s a contained problem. The inputs are clear (calendar availability, email threads). The output is clear (confirmed meeting). The failure mode is low-stakes (worst case, you step in and sort it out yourself).
The setup I use with Lindy takes less than an afternoon. You define your availability windows, set your meeting preferences, connect your calendar, and give the agent some context about how you like to communicate. After that, you cc it on threads where scheduling needs to happen, and it takes over.
A few weeks in, you’ll stop noticing it. Which is the point.
That’s what I mean when I say AI agents aren’t tools you use — they’re more like teammates you manage. The goal is eventually you don’t have to manage them much either.
The 15-cent meeting was just the beginning. Now my agents handle email triage, weekly transcript synthesis, meeting prep docs, and a bunch of other things I used to spend real time on.
It compounds fast once you start.
Want to build your first scheduling agent? I cover this in my AI workshops and also do one-on-one implementation sessions. You can reach me at [email protected] or check the Productivity Academy for more resources.
