I made a stupid mistake in 2015. A founder, practically vibrating with excitement, pitched me on a voice-activated to-do list. I sat there, in a conference room that probably cost more than my first car, and all I could think was, 'This is ridiculous. No one is going to talk to their phone like a person.' I passed. Hard pass. That company sold for over $100 million two years later. Ouch. It was a dumb miss, but a lesson I haven't forgotten: the most awkward-feeling tech is sometimes the one that's about to change everything.
For the longest time, voice AI was a party trick. You'd ask it the weather, it would get it wrong, and everyone would laugh. It was a gimmick. But something has shifted. We're past the awkward teenage years of voice tech. It's not just a feature on your phone anymore; it's the bedrock of whole new industries. I'm not just talking about smart speakers. I'm talking about a seismic shift in how we interact with machines. And I'm not just talking, I'm investing. I've made over 200 angel investments in companies that are on the bleeding edge of this stuff, including some you've definitely heard of, like Anthropic and OpenAI.
The Dark Ages of Voice
My first real go at voice tech was a disaster. Back in the early 2000s, I was trying to get a machine to transcribe my meeting notes. I spent weeks, actual weeks of my life, messing with some janky open-source software I found on a forum that probably doesn't even exist anymore. The output was gibberish. It was like the computer was trying to write a Dadaist poem. I spent more time fixing the 'transcription' than if I'd just typed the whole thing out myself. I was done. Voice tech, I decided, was a joke.
That failure colored my thinking for years. Siri came out. Alexa came out. I yawned. 'Toys,' I thought. 'Not for real work.' I was busy building companies like RemoteTeam, which Gusto later acquired, and MovieLaLa, which we sold to Gfycat. These were businesses built on screens and keyboards. Voice was just noise in the background.
Then I started angel investing, and everything changed. I was seeing pitches that blew my mind. Founders weren't building better to-do list apps. They were building real-time translators, AI sales coaches that could read the emotion in a person's voice, and even tools that could diagnose a cough. It was a tidal wave of innovation, and I was standing right in the middle of it. I'd been so wrong. My past failures had blinded me to the future. I had to relearn everything I thought I knew about voice. You can read more about how I got into angel investing in my post about my investment in OpenAI.
The Podcasting Gold Rush
Podcasting is one of the most obvious places where AI voice is a real shift. It used to be a whole production. You needed a quiet room, a fancy microphone, and hours of editing. Now? You can turn a blog post into a podcast in minutes, with an AI voice that's almost indistinguishable from a human's. This is a massive unlock for creators. Suddenly, anyone can have a podcast.
And it's not just about making podcasts. It's about how we listen to them. I'm an investor in a company that's basically creating a personalized radio station for your life. You tell it what you're into, and it finds articles and news and reads them to you in a voice that sounds like a real person. My commute is now my personal tech news briefing. It's awesome.
This is just the beginning. I'm seeing pitches for AI that can edit your podcast for you, taking out all the 'ums' and 'ahs'. I'm seeing pitches for interactive podcasts where you can ask the host questions. It's a completely new medium being born, and the potential is staggering.
The Unseen Engine: Speech Recognition
Everyone's focused on the output, the voice itself. But the real magic is in the input: speech recognition. For years, this was the part that just didn't work. It was terrible. I remember trying to use a dictation tool in the late 2000s and wanting to throw my computer out the window. I'd say 'hello,' and it would type 'yellow.' It was infuriating.
Deep learning changed everything. Speech recognition is now shockingly good. It can understand different languages, accents, you name it. This is a huge deal for accessibility. For people who can't type, this is freedom. It's a way to work, to create, to be part of the conversation.
And it's not just about accessibility. Businesses are using this to transcribe every phone call, every meeting. All that data, which used to just disappear into thin air, is now searchable and analyzable. You can learn so much about your customers and your own team just by listening. The future of work is being built on this, and you can read more of my thoughts on that in my post about the future of remote work.
The Next Chapter: Conversational AI
So what's next? The last ten years were about teaching computers to hear. The next ten will be about teaching them to understand. We're moving beyond simple commands. We're moving towards real conversations. I'm not talking about the clunky chatbots you argue with on customer service websites. I'm talking about AI that you can actually talk to, that remembers what you've said, and that can even figure out what you need before you do.
I've put my money into a few companies in this space, and the tech is just... wow. They're building AI assistants that can help you do real work. Plan a trip. Negotiate a deal. Write a book. These aren't just search engines with a voice. They're creative partners.
I have no idea where this is all going. Anyone who says they do is lying. It feels like 1995 all over again, with the internet. We all knew something big was happening, but we couldn't have predicted what it would look like. All I know is that it's going to be a wild ride, and I'm buckled in for it.
My advice to you? Pay attention to voice. It's not a toy anymore. It's the future. And if you're not thinking about how to use it, you're already being left behind.
Frequently Asked Questions
How do I measure success with this approach?
Pick one or two metrics that directly tie to your goal and track them weekly. Vanity metrics like page views or follower counts rarely matter. Focus on metrics that reflect real engagement or revenue impact.
How long does it take to do even more with ai voice - 84?
The timeline varies depending on your starting point and resources. For most founders, expect 2-4 weeks for initial setup and 2-3 months to see meaningful results. I've seen teams move faster when they focus on one thing at a time rather than trying to do everything at once.
What are the most common mistakes when doing even more with ai voice - 84?
The biggest mistake I see is overcomplicating things early on. Start with the simplest version that works, get real feedback, and iterate from there. Another common trap is copying what worked for someone else without understanding the context behind their decisions.