I did something that feels like it’s straight out of a sci-fi movie. I created a digital clone of my own voice. And no, it doesn’t sound like a robot from a 1980s film. It sounds like me. So much like me that it’s already doing work for my portfolio companies, recording podcast intros and even creating personalized audio messages for new investors.
Just five years ago, I was advising one of my startups, and we burned through nearly $50,000 on voice actors for a series of marketing videos. The process was slow, expensive, and a logistical nightmare. Today, I can generate that same content in a couple of hours, in any language I want, for the cost of a monthly subscription. This isn't just an incremental improvement. It's a complete transformation of how we create and consume content.
For years, we’ve been promised the “year of voice,” but it always fell flat. The technology was clunky, the voices were robotic, and the applications were limited. I remember the early days at MovieLaLa, trying to use a text-to-speech engine for a feature. It was so bad we scrapped it after a week. But now, the technology has finally caught up to the hype. The shift from robotic narration to lifelike, emotive speech is the single biggest opportunity in content creation I’ve seen in a decade.
It’s Not Just Text-to-Speech Anymore
What we're seeing now is fundamentally different from the old text-to-speech (TTS) systems. Those were based on concatenative synthesis—basically stitching together pre-recorded sounds. It’s why they always sounded a bit disjointed. The new wave of AI voice is built on deep learning. These models aren’t just playing back sounds; they’re generating them.
Think about it this way: the AI learns the unique characteristics of a voice—the pitch, the cadence, the subtle pauses, the way your voice rises at the end of a question. It learns the essence of the voice. Then, it can use that understanding to generate entirely new speech from any text you give it. It can even capture emotion.
I’ve invested in over 200 companies, including some of the foundational AI players like Anthropic and OpenAI. The progress in this specific vertical of AI is staggering. Companies like ElevenLabs have made it possible for anyone to create a high-quality voice clone with just a few minutes of audio. You don't need a studio or expensive equipment. You just need a laptop and a clear microphone.
This has massive implications:
- For Creators: Imagine a YouTuber who can produce videos in multiple languages, all in their own voice. Or a podcaster who can fix a mistake in an episode by simply typing the correction, instead of re-recording the entire segment. This is happening right now.
- For Businesses: Think about personalized marketing at scale. Instead of a generic ad, imagine a potential customer hearing a message in a familiar, trusted voice. Or a company creating training materials for a global workforce, localized in dozens of languages but maintaining the consistent voice of their lead instructor.
- For Accessibility: This technology is opening up a world of content for people with visual impairments or reading difficulties, turning every article, book, and document into a personal audiobook.
The Rise of the Voice AI Assistant That Actually Assists
For a long time, voice assistants like Siri and Alexa have felt more like glorified search engines. They could tell you the weather or play a song, but they weren't true assistants. That’s changing, and it’s because the same AI that powers voice cloning is making these assistants conversational.
We're moving from simple command-and-response to genuine dialogue. An AI assistant can now understand context, manage complex tasks, and even anticipate your needs. For an entrepreneur, this is huge. I can have my AI assistant schedule meetings, draft emails in my style, and even provide a verbal briefing on my portfolio's performance while I’m driving. It’s like having a chief of staff that works 24/7 and never gets tired.
Podcasting Will Never Be the Same
I love podcasts, both as a creator and a listener. But the production process can be a grind. AI is completely overhauling that workflow.
I recently helped a podcasting startup in my portfolio implement an AI-first strategy. Here’s what it looks like:
Recording: They still record the conversation with a human host.
Editing: An AI tool automatically removes all the filler words (
Recording: They still record the conversation with a human host.
Editing: An AI tool automatically removes all the filler words ("uhms" and "ahs"), tightens up the pauses, and balances the audio levels. This used to take a human editor hours.
Transcription & Show Notes: The audio is instantly transcribed. Another AI model then summarizes the key points, identifies the main topics, and generates a full set of show notes with timestamps.
Repurposing: This is where it gets really interesting. The host’s cloned voice is used to create short audio clips for social media, promotional ads for the next episode, and even a summarized audio version of the podcast for people who are short on time.
The result? They’ve tripled their content output without hiring a single new person. Their production costs are down 70%. This isn’t a far-off future; this is what’s possible today.
This Is Not a Drill
I’ve seen a lot of tech trends come and go. I was there for the dot-com boom and bust. I saw the rise of mobile and the social media explosion. The current AI revolution, particularly in voice, feels different. It’s more immediate, more personal, and the barrier to entry is incredibly low.
My advice is simple: don’t wait. If you’re a creator, an entrepreneur, or a business leader, you need to be experimenting with this technology now. Clone your voice. Build a simple AI assistant. Automate a piece of your content workflow. The cost of trying is minimal, but the cost of being left behind will be enormous. The future isn’t just coming; it’s speaking to us. And it sounds a lot like you.
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.
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.
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.
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.