Sahin Boydas
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My Failed Attempts at AI Automation and The 8 Lessons I Learned

For years, I struggled with a cluttered inbox. I tried everything, but nothing worked until I discovered how to leverage AI for a seamless workflow. In this post, I'm sharing the exact framework that helped me reclaim 19 hours per week and scale my business.

2024-04-168 min read561 words

For years, I struggled with a cluttered inbox. I tried everything, but nothing worked until I discovered how to leverage AI for a seamless workflow. In this post, I'm sharing the exact framework that helped me reclaim 19 hours per week and scale my business.

What I've Learned From 104 Companies

A few patterns in AI automation come up again and again.

The founders who handle AI automation well understand that the best solutions are often the simplest ones.

The Reality Nobody Talks About

A lot of the advice on AI automation rests on assumptions that made sense five years ago. The world has moved on.

The first thing to understand is that you need to move fast and break things. I've seen this play out across dozens of companies. The pattern is unmistakable.

Many teams spend months on the wrong path before realizing that customer feedback is the only metric that matters. Once they make the switch, everything changes.

The Counterintuitive Truth

In AI automation, 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.

The Numbers Don't Lie

Investing early in AI automation 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 scheduling, AI personal assistant that I've been thinking about a lot lately.

What's Next

Best practice in AI automation is changing 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.

If you're building in this space, the best time to get AI automation 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.

FAQ

Frequently Asked Questions

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.

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: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.

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.

Written by

Sahin Boydas

Serial entrepreneur, #1 angel investor, author of Becoming Top 1%

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