Rolling out AI email assistants at scale is where most plans break.
For years, I struggled with endless meetings. I tried everything, but nothing worked until I discovered how to leverage AI for automated scheduling. In this post, I'm sharing the exact framework that helped me reclaim 5 hours per week and scale my business.
What I've Learned From 100 Companies
A few patterns in AI email assistants come up again and again.
The founders who handle AI email assistants well understand that the best solutions are often the simplest ones.
The Counterintuitive Truth
In AI email assistants, the best practitioners often do less, not more.
The lesson: timing is everything in this game. It sounds simple. It's incredibly hard to execute.
The Numbers Don't Lie
The gap between companies that take AI email assistants seriously and those that don't is usually clear.
Investing early in AI email assistants can be the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around AI meeting notes, AI automation, AI email, AI scheduling, AI tools for founders that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in AI email assistants, but there are smarter paths.
The strongest teams treat AI email assistants as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with AI email assistants, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
Q:How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
Q:How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
Q:What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
Q:What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.