My Thoughts on AI Voice Tech

Published 2024-03-18 · Updated 2026-05-23 · 6 min read · AI Voice and Speech · By Sahin Boydas

I’ve tried different AI voice tools and faced some challenges before finding what works. In this article, I share my experience and practical tips to help you get started quickly.

The best advice I ever got about my thoughts on ai voice tech came from a founder who'd failed at it three times.

I’ve tried different AI voice tools and faced some challenges before finding what works. In this article, I share my experience and practical tips to help you get started quickly.

The Counterintuitive Truth

Here's what surprised me most about my thoughts on ai voice tech: 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 timing is everything in this game. It sounds simple. It's incredibly hard to execute.

The Reality Nobody Talks About

Most people approach my thoughts on ai voice tech with assumptions that made sense five years ago. The world has moved on. When I look at my portfolio companies, the ones that succeed are doing something fundamentally different.

The first thing to understand is that the data tells a different story than your gut. I've seen this play out across dozens of companies. The pattern is unmistakable.

At RemoteTeam, we learned this the hard way. We spent months going down the wrong path before realizing that most founders overthink this and underspend on execution. Once we made the switch, everything changed.

Why Most Approaches Fail

Let me be direct: about 70% of the approaches I see to my thoughts on ai voice tech are fundamentally flawed. Not slightly off. Fundamentally flawed.

The root cause is usually one of three things:

  • Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
  • Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
  • Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.

Lessons From the Trenches

I want to share a few specific lessons I've picked up over the years. These aren't theoretical. They come from real companies, real failures, and real successes.

Lesson 1: The best time to start thinking about my thoughts on ai voice tech was yesterday. The second best time is now. Don't wait until you have the perfect plan.

Lesson 2: Hire for attitude, train for skill. The best my thoughts on ai voice tech practitioners I've met weren't the most technically gifted. They were the most curious and persistent.

Lesson 3: Your competitors are probably getting this wrong too. That's your opportunity. While everyone else is following the same playbook, you can zig when they zag.

This connects to broader themes around AI podcasting, text-to-speech, AI voice cloning that I've been thinking about a lot lately.

What's Next

The world of my thoughts on ai voice tech 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 thoughts on ai voice tech 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

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.

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.

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.

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