The first time I tried to implement my failed attempts at ai automation and the at scale, everything broke. Not metaphorically. Actually broke.
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 18 hours per week and scale my business.
The Counterintuitive Truth
Here's what surprised me most about my failed attempts at ai automation and the: the best practitioners do less, not more.
When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.
The lesson I took from that experience, and from watching hundreds of other companies, is that the data tells a different story than your gut. It sounds simple. It's incredibly hard to execute.
What I've Learned From 133 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with my failed attempts at ai automation and the.
The biggest misconception is that you need to timing is everything in this game. That's backwards. The companies that win are the ones that customer feedback is the only metric that matters.
I remember sitting with the Anthropic team early on and discussing how they thought about my failed attempts at ai automation and the. Their approach was counterintuitive but brilliant.
What I Tell Founders
When a founder in my portfolio asks me about my failed attempts at ai automation and the, I usually 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 automation, AI writing tools, AI scheduling, AI tools for founders that I've been thinking about a lot lately.
What's Next
The world of my failed attempts at ai automation and the is moving fast. What worked last year might not work next year. That's both the challenge and the opportunity.
My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.
And if you're a founder building in this space, remember that the best time to get my failed attempts at ai automation and the right is before you need to. Don't wait for a crisis to force your hand.
I'll keep sharing what I learn. This stuff matters too much to keep to myself.
Frequently Asked Questions
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.
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.
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 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.