Every week, about 30 minutes before my allergy appointment, my phone rings.
Wait, no. That’s wrong. My phone doesn’t ring at all.
A Lindy agent does the calling. It dials the clinic. Navigates their automated phone menu. Tells the receptionist that Thanh Pham is on his way and will arrive in about 30 minutes. Then hangs up.
When I walk through the door, my shot is ready.
I save 25 minutes. Every single visit.
Why This Works (and Why It Took Me a While to Build It)
Here’s the thing about allergy shots: they have to be freshly prepared. The clinic can’t batch them ahead of time. So if you show up without warning, you sit in a waiting room while they mix it.
For a long time, I’d just wait. It was annoying, but what are you going to do? Call ahead every single time? I’d forget. Or I’d be rushing to leave the house.
The first time I thought about automating this, I almost didn’t bother. It seemed too small. Too weird. Not the kind of “AI automation” I was supposed to be building.
But that’s exactly the point.
The 80/20 of Automation
I’ve built a lot of AI agents at this point. I have about 40 that I use regularly. And the ones that actually compound in value aren’t the impressive-sounding ones.
They’re the boring ones.
The allergy clinic call. The weekly briefing from my calendar. The follow-up email that drafts itself. The Todoist task that creates itself from a meeting transcript.
None of these are sexy. None would make a great LinkedIn post about “disruption” or “the future of work.” But they run quietly, every week, without me thinking about them. And they add up.
This is what I call the 80/20 of agent building: automate the things that happen every week, not the things that would look good in a demo.
When I was helping a client named Hudson set up his scheduling automation, the breakthrough wasn’t some complex system. It was two constraints he added: he only takes calls between 1 and 5 PM, and he limits himself to three calls per day. Baking those two rules into the agent changed everything. Suddenly the automation worked with his life instead of against it. Small configuration, massive difference.
The best automations respect how you actually live and work. They don’t require you to change your behavior.
How I Built the Allergy Clinic Call
The workflow is simpler than you’d think.
The trigger is a calendar event containing the words “allergy clinic.” When that event appears, Lindy fires off a phone call 30 minutes before the scheduled time.
The tricky part was navigating the clinic’s automated phone system. When you call them, a robot answers: “For appointments, press 1. For the Westlake location, press 1. For the downtown location, press 2.” And so on.
I had to learn something called DTMF tones. That stands for Dual-Tone Multi-Frequency — it’s the technical name for the tones your phone generates when you press buttons. Turns out you can include these in a Lindy prompt to simulate pressing numbers during an automated call.
I called the clinic myself once, timed how long each menu step took, and built the timing into the prompt. “Wait approximately 20 seconds, then press 1. Wait approximately 15 seconds, then press 1 again.” Then I had Claude help me convert my rough notes into a clean, reliable prompt.
The message the agent leaves: “Hi, this is Lindy calling on behalf of Thanh Pham. He’s on his way and will arrive in about 30 minutes. Just wanted to give you a heads up. Thank you, have a great day.”
That’s it.
The staff at the clinic now recognize the automated calls. When I walk in, they don’t ask my name. They just say “your shot is ready” and point me to the chair.
The Part Most People Get Wrong About Building an AI Stack
When I show people my Lindy setup, they see 40+ agents and get overwhelmed. They think they need to build all of that from scratch, all at once, with some master plan.
That’s not how it happened.
I started with the default Lindy meeting notetaker template. That’s it. Over the next several months, I expanded it one frustration at a time.
My notetaker wasn’t joining meetings from my second calendar. So I added a second trigger.
Some hosts don’t allow external notetakers. So I connected it to Granola, an app that records meetings locally. When Granola saves a transcript, it auto-uploads to a Google Drive folder, and the same notetaker workflow processes it.
I realized I was manually copying CRM updates after calls. So I added an HTTP request to my CRM.
Each expansion solved exactly one problem. None of them required knowing the next one was coming.
The first thing I’d tell anyone starting with AI automation: don’t design the whole system upfront. Use a template. Use it for a few weeks. Let your own frustrations tell you what to add next.
“Life gets better one agent at a time” sounds cheesy, but it’s genuinely how this works. The compounding is real. You build one thing, and it reveals the next thing worth building.
Start With the Most Annoying Weekly Task
If you want to know where to start with AI automation, here’s the question I use: what’s the most annoying thing that happens to you every single week?
Not the most impressive thing. Not the thing that would look good in a case study.
The thing that makes you groan a little every time it shows up.
For me, it was waiting 25 minutes for an allergy shot that was supposed to take 5 minutes.
Now I just walk in and it’s ready.
That’s the dream. Small, specific, invisible.
If you want help mapping your first (or next) automation, the Productivity Academy is a good place to start. We cover exactly this process — identifying high-frequency pain and turning it into a running workflow.
Or just start with the allergy clinic problem. Whatever annoys you every week. That’s your first agent.
