Absurd: Building a Billion-Dollar Unicorn Started with Humans Pretending to Be AI

Absurd: Building a Billion-Dollar Unicorn Started with Humans Pretending to Be AI

Absurd Business Validation Strategy — How Fireflies.ai Started by Pretending to Be AI

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Background: Six Startup Failures

In 2017, after six consecutive startup failures — from “cryptocurrency-powered food delivery” to other wild ventures — two entrepreneurs found themselves living in a friend’s home, surviving mostly on pizza.

Their new idea: Build an AI assistant that could automatically take meeting notes.

The problem?

They didn’t have any AI at all.

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The “Be the Product” Experiment

Believing the fastest way to test a business idea was to act as the product themselves, the founders took an unusual path:

  • Pitch the AI
  • Told clients: “We have an AI that automatically joins meetings and takes notes.”
  • Human Impersonation of AI
  • When meetings were scheduled, they manually dialed in.
  • Pretended to be “Fred from Fireflies.ai.”
  • Stayed silent, listened carefully.
  • Took notes manually.
  • Sent transcripts within 10 minutes after the meeting.
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The Result

  • Recorded over 100 meetings manually.
  • Earned enough to cover $750/month rent for a tiny San Francisco living room.
  • Only after proving demand did they begin automating the process.

This unusual MVP experiment became the real founding story of Fireflies.ai, now a billion-dollar AI unicorn — as shared by co‑founder Sam Udotong on LinkedIn.

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Fireflies.ai Today

From a human-powered “AI” to a real AI platform, Fireflies now offers:

  • 95% transcription accuracy
  • Support for 69 languages
  • Intelligent summaries
  • Key point extraction
  • Workflow automation with other tools
  • Strong security & privacy controls

In June 2024:

  • Valuation exceeded $1 billion (official unicorn status)
  • 500,000+ organizations served
  • 20M+ users worldwide
  • Profitable since 2023
  • Achieved growth with minimal marketing spend

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Ethical & Privacy Concerns

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Despite its commercial success, the early practice of replacing AI with human labor sparked controversy.

Key Points of Debate

  • Misrepresentation
  • Claimed an “AI” would join meetings, but humans actually did the work.
  • This is deception, not informed consent.
  • Privacy Violations
  • Real people listened in on private meetings without attendee awareness.
  • Potentially illegal in some jurisdictions.
  • Data Security Risks
  • Raises questions about how recorded data was handled.
  • Could undermine client trust long‑term.
  • Cultural Signal
  • Normalizing deception could damage company culture.

Many online comments were strongly critical, including: “See you in court!”

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Lessons for Startups

Even though Fireflies.ai’s founders succeeded, this method carries ethical and legal risks and is not recommended.

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Reference:

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Broader Takeaway

Stories like this show that bold MVP experiments can lead to breakthroughs — but also demonstrate why startups must ensure ethical design and transparent communication from day one.

Today, creators can validate ideas quickly without deception, using open, transparent AI platforms.

Example: AiToEarn (Open-Source AI Content Platform)

AiToEarn官网 helps teams:

  • Generate AI content
  • Publish across Douyin, Kwai, WeChat, Bilibili, Xiaohongshu, Facebook, Instagram, LinkedIn, Threads, YouTube, Pinterest, X (Twitter)
  • Track analytics & model rankings
  • Monetize across multiple channels
  • All with full transparency and scalable workflows.

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Contact for Reprint Authorization:

liyazhou@jiqizhixin.com

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Final Note:

Early AI startups sometimes relied on human labor behind the scenes, blurring the line between automation and manual intervention. Modern open-source ecosystems now make it possible to experiment rapidly while staying ethical, scalable, and trustworthy.

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