Every December, I run a two-hour workday demo session for my students.
The Bookshelf Problem
You know, when you walk into someone's home and see 200 books on their shelf? Your first thought is never “I need to read all of those this week.” You just go, wow, they've been around a while. They've had time.
That's the exact same thing as my AI collection.
I've been building since February 2025 — just over a year now. One agent at a time. Some worked great on the first try. Some took three rebuilds to get right. A few I deleted entirely because I thought I needed them, but did not.
The collection did not appear overnight. It accumulated.
Where I Actually Started
My first Lindy agent was an email drafter. Basic. Very basic. All it did was take emails from my inbox, pull context from previous conversations, and draft a reply for me to review.
Saved me maybe 20 minutes a day. That was the whole win.
That is it. I did not automate my calendar at the same time, or build a research pipeline, or set up weekly reports. I just had a thing that drafted email replies and I used it every morning.
Boring, right? But that 20 minutes compounded.
The One Tweak a Week Frame
I teach something called One Tweak a Week for AI adoption. The idea is dead simple: do one more thing with AI this week than you did last week. Not ten things. Not a full automation stack. One thing.
Week one: get an email drafter working. Week two: set up a meeting prep brief. Week three: add a basic weekly digest.
That pace feels slow. But it does not feel slow six months in when you look back at what you have built.
I run workshops in Austin every six weeks. I have watched people go from never using Lindy to running a 5-agent system in 90 days just by following this pacing.
The 55 Hours Moment
Lindy sends me a weekly email with my time savings report. At some point earlier this year, the report said I had saved 55 hours that week. I had to re-read it.
That is what most people miss when they look at someone's complex AI setup. They see the end state. They do not see the two hundred micro-experiments that got it there.
The AI Fluency Framework
When I teach workshops, I describe three stages of working with AI: AI Assisted, AI Workflows, and Building Agents.
Most people try to jump straight to stage three because that is what they see in demos. But you need stages one and two to make stage three work. The skills compound.
What to Do This Week
Pick one thing you do every week that is predictable and annoying. Something with a clear input and a clear output.
Build one agent that does that one thing. Use it for three weeks before you build anything else.
The bookshelf fills up faster than you think once you get going. But it fills up one book at a time.
