Silicon Valley Girl$6.6B AI CEO: How to Make Your First $10,000 with AI
CHAPTERS
- 0:00 – 1:23
Why voice is becoming the default interface for AI
Marina and Mati open by framing the shift from text-first AI (ChatGPT era) to voice-first interactions. Mati argues voice carries more information than text—emotion, intent, and nuance—making it both a richer input and a more natural output.
- 1:23 – 2:28
Voice agents for support and sales: real business use cases
Mati describes how companies replace IVR and basic call handling with voice agents that understand callers and respond quickly. He also explains how voice agents can assist across the user journey—from product guidance to inbound/outbound lead handling—and can sometimes convert directly on self-serve tiers.
- 2:28 – 5:22
Measuring impact: conversion lift and net-new lead capture
Marina presses on whether AI voice sales materially improves conversions. Mati notes they measured it, but the bigger win was capturing leads that would otherwise wait days/weeks—or never convert—because agents can respond instantly at scale.
- 5:22 – 7:14
Picking a domain that fits: the .online sponsorship segment
A sponsored interlude explains why .com domains are often unavailable and positions .online as a flexible alternative used by millions of businesses. Marina highlights discoverability, examples of notable .online sites, and a limited-time coupon offer.
- 7:14 – 12:00
How to set up an ElevenLabs voice agent: platform + business logic
Mati outlines the practical setup: create an account, use their agentic platform that abstracts speech/LLM/TTS orchestration, then add the business knowledge and workflows. He gives examples like appointment scheduling, routing, and embedding agents into a website experience.
- 12:00 – 15:18
Multilingual sales and language learning: using your own voice across languages
Marina explores using her voice to sell courses in multiple languages and reduce anxiety for non-native speakers. Mati confirms multilingual support and suggests an adjacent use case: AI-powered speaking practice and personalized tutoring that feels less judgmental than a human call.
- 15:18 – 17:37
Voice marketplace: earning money by licensing your cloned voice
Mati explains ElevenLabs’ voice marketplace: users record ~30+ minutes, complete authentication, and can publish their voice under defined terms. Creators earn royalties when others use their voice; the company has paid millions back to the community and is expanding language coverage.
- 17:37 – 21:37
Voice cloning quality issues: matching a specific scene and audio mix
Marina describes a real creator workflow—patching a line in a video while traveling—and the difficulty of matching the exact tone of a particular scene. Mati explains why clones reflect an “average” voice profile and previews future conditioning features; meanwhile he suggests regenerating or training from shorter, scene-specific samples.
- 21:37 – 25:10
The future of voice AI: personal agents and hyper-personalized voices
Mati predicts most people will have an authenticated voice clone and eventually a personal voice agent that can act on their behalf. He also describes personalization at scale: businesses adapting voice style to caller demographics and users selecting preferred “service voices,” with examples from Korea/Japan and travel/navigation apps.
- 25:10 – 27:35
Deepfakes and trust: the three-layer safeguard model
Marina raises impersonation risks, especially if voice could authorize payments. Mati argues we must assume perfect cloning will be possible and outlines a three-layer approach: prove human/device identity, watermark authenticated AI, and treat anything else as untrusted AI by default.
- 27:35 – 31:23
What keeps an AI founder up at night: research race, safety, and labor impact
Mati balances optimism about a once-in-a-generation platform shift with the pressure of staying ahead in research. He cites responsibility for safeguards and concern about job disruption, while describing ecosystem approaches (like the marketplace) to share upside more broadly.
- 31:23 – 33:50
Jobs at risk and how to adapt: “replaced by people who use AI”
Mati argues the key divide won’t be AI vs. humans, but AI-augmented workers vs. those who don’t adopt tools. He expects routine, recipe-based tasks to be automated first while complex, regulated, or expert judgment work remains higher-value—at least initially.
- 33:50 – 36:49
Top 3 AI tools Mati recommends (besides ElevenLabs)
Mati names tools he finds especially useful across creation and building: Black Forest Labs for image generation, Anthropic’s Claude for reasoning and engineering-like help, and Lovable (plus similar tools like v0/Replit) for rapid prototyping. He emphasizes how these tools let non-engineers build demos and get closer to product implementation.
- 36:49 – 41:53
The $10k/month opportunity: deploying voice agents for SMBs (no coding required)
Asked for immediate, practical ways to earn money, Mati points to a deployment gap: tools exist, but small businesses don’t know how to implement them. He suggests selling setup and operation of appointment-booking voice agents to dentists, doctors, and mechanics—businesses where missed calls equal lost revenue.
- 41:53 – 43:58
Startup advice + the origin of ElevenLabs, and whether language learning survives translation tech
Mati advises founders to obsess over a real, burning user problem, validate demand early, and choose co-founders/early hires carefully. He recounts starting from a dubbing pain point (flat Polish voiceover) but pivoting based on creator feedback; they close by debating language learning’s future as translation becomes ubiquitous, shifting from necessity to self-development and cultural connection.
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