Back in August, I ran a report from Lindy to see how much time my AI agents had saved me that week.
73 hours. Across over 1,000 tasks.
The number that surprised me most wasn’t the total. It was the breakdown. One single agent — my email inbox manager — had done 198 tasks and saved me almost 18 hours in that one week.
Just email. Nothing fancy.
I share that screenshot in workshops now. People stare at it for a second and then ask: “What kind of complicated system did you build for that?”
And I have to tell them… it was just the inbox.
Why Email Is the Right Place to Start
Most people I talk to want their first AI agent to be impressive. Something that monitors multiple data sources, synthesizes information, and outputs strategic recommendations. Something they can show people at a conference.
But the 80-20 of agent building says: start with frequency, not sophistication.
What you do every single day is worth more to automate than something you do once a quarter. Email is the thing most knowledge workers touch the most, groan about the most, and almost never think to automate.
I’ve spent a lot of time teaching this stuff, and the pattern is consistent. People skip email because it feels too basic. And then they wonder why their fancy automation isn’t saving them much time.
What the Email Agent Actually Does
Here’s what mine handles:
- Reads every new email as it arrives
- Categorizes it: needs action, FYI only, can delete, needs follow-up later
- Drafts a reply in my voice if a response is needed
- Flags anything that actually requires my judgment
What I do: open the review queue, check the drafts, edit if needed, click send. Maybe 20 minutes total. For a day of email.
The first time I taught this in a workshop, someone raised her hand and said: “But isn’t it scary to have AI handling your email?”
I get that reaction. A lot of people are worried the agent will send something on their behalf without them approving it. Mine never does that. It drafts. I review. That’s the human-in-the-loop setup I always recommend for anything that goes out with your name on it.
Once you trust the drafts — once you see they actually sound like you — that’s when you start moving faster.
The Telegram Piece Nobody Expects
Here’s the part that surprised even me.
I interface with my email agent through Telegram. It’s just a messaging app I already used, so adding this layer felt natural.
Walking to a meeting, I’ll dictate: “Draft an email to Evan introducing Lauren Goldstein as a potential guest for the members club. She’d be a great fit.” Thirty seconds later there’s a draft in my inbox. Ready to review.
I didn’t sit down. Didn’t open my laptop. Just talked.
Combine that with Whisperflow — which uses AI to understand intent, not just transcribe words literally — and dictating emails while walking between things became genuinely faster than typing at a desk.
That’s the shift I didn’t fully expect. It’s not just that email takes less time. It’s that email gets handled at times of day when it previously couldn’t happen at all.
You Don’t Have to Be Technical
This one I want to say clearly.
I am not a developer. I can’t write code. A year ago I had no idea how to build any kind of automated workflow.
The barrier has dropped that fast.
Lindy, the tool I use for most of this, has a visual interface and a chat editor. You describe what you want in plain language and it builds the workflow. The most common fear I hear from workshop participants — “I’m not technical enough for this” — disappears pretty quickly once they’re actually in the tool.
I’ve watched accountants, salon owners, and real estate agents build working agents in a single afternoon. None of them had a technical background.
What it does take is willingness to start small. Most people want to build everything at once. The agents that actually get used are the ones that do one thing reliably.
Email is that one thing for a lot of people.
The Progression
If you want to get here, the path is pretty simple.
Start with AI-assisted work: use ChatGPT or Claude to help you draft individual emails. Just that. Get comfortable with what good outputs look like in your voice.
Then build a simple workflow: something that drafts replies to a specific category of email automatically. Maybe just client inquiries. Or meeting requests. Pick one.
Once that’s running and you trust it, expand.
This is what I call the AI fluency progression. Assisted, then automated, then agents. You build trust at each level before moving to the next. Skipping to agents without the earlier stages usually means the first thing you build doesn’t get used because you don’t trust it yet.
The 18 hours didn’t happen overnight. They built up over a few months of incremental improvements.
But at some point you add up the weekly numbers and the total is 73 hours in a week, and you go back and look at which agent is doing the heavy lifting.
Almost always, it’s email.
Try This Week
Pick the email category you spend the most time on. For most people that’s client questions, scheduling requests, or follow-ups after calls.
Spend 30 minutes building one draft agent for just that category.
Don’t try to make it perfect. Just see if it drafts something you’d actually send with a small edit.
That’s the whole experiment. And if it works, that one agent will save you more time than anything else you build for a while.
Want to learn how to build this for yourself? The Productivity Academy has workshops on AI agent building, including the exact setup I use for the email inbox manager.
