For years, I struggled with context switching. I tried everything, but nothing worked until I discovered how to leverage AI for an AI-powered inbox. In this post, I'm sharing the exact framework that helped me reclaim 14 hours per week and scale my business.
What I've Learned From 60 Companies
A few patterns in AI scheduling come up again and again.
The founders who handle AI scheduling well understand that you should focus on one thing and do it exceptionally well.
The Framework That Actually Works
Here is a simple framework for evaluating AI scheduling. It's not complicated, but it requires discipline.
Step 1: the data tells a different story than your gut
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: timing is everything in this game
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get AI scheduling right treat it as an ongoing process, not a one-time project.
The Counterintuitive Truth
In AI scheduling, the best practitioners often do less, not more.
The lesson: the best solutions are often the simplest ones. It sounds simple. It's incredibly hard to execute.
What I Tell Founders
Before deciding anything about AI scheduling, start with three questions:
What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around AI personal assistant, AI scheduling, AI automation that I've been thinking about a lot lately.
The Bottom Line
None of this is rocket science. But it does require intentionality, consistency, and a willingness to learn from mistakes.
If you take one thing from this article, let it be this: start now, start small, and iterate. The founders who win at AI scheduling aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
Companies that take AI scheduling seriously tend to pull ahead of the ones that don't.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
Frequently Asked Questions
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: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: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:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.