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Pangram CEO: Internet is 'dangerously close' to dead internet theory, and AI detection is harder than 'real or fake'

Pangram co-founder and CEO Max Spero told TechCrunch's Equity podcast that the internet is 'dangerously close' to the dead internet theory becoming reality within a few years. He argues that measuring how much AI went into content is harder and more useful than a simple human-or-AI label, as Pangram ramps up detection partnerships like its new deal with Substack.

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Pangram CEO:互联网正“危险地接近”死互联网理论,AI检测比“真假判断”更难
Image source: techcrunch.com

Pangram co-founder and CEO Max Spero joined TechCrunch's Equity podcast on September 2 to warn that the internet could be 'dangerously close' to the dead internet theory becoming reality within a few years. The episode digs into the promise of AI detection tools and where to draw the line between AI-assisted and AI-generated content.

Spero argues that measuring how much AI went into a piece of content is harder and potentially more useful than simply labeling it human or AI. That nuance matters, he says, because AI-generated text and images are now showing up in job applications, product reviews, and even insurance claims, leaving platforms and users scrambling to figure out what is real.

TechCrunch positions Pangram among a handful of startups that have emerged over the past couple of years to become the 'trust layer' the internet needs. According to the episode's description, Pangram recently raised $9 million for its AI detection system and landed a partnership with Substack, which now uses Pangram's technology to show readers which of their favorite authors use AI to write their newsletters.

The startup has also recently released a new AI image detection tool, extending its focus beyond text. That expansion matters because the stakes of detection errors are uneven: Spero argues that false positives are especially dangerous when they involve sensitive images, where wrongly flagging authentic content can destroy trust in the tool itself.

Spero also offered a blunt prediction for the writing profession. He thinks the 'bottom tier' of writing jobs may be gone for good, while genuinely good human writing could become more valuable as machine-generated output floods feeds.

The conversation is a useful snapshot of an AI-detection market moving from debate to deployment. Substack's author labeling is a concrete example of a major platform embedding detection into its product rather than just debating it.

What to watch next is how widely Pangram's labels spread, how accurate its image detection proves in the wild, and where platforms and regulators ultimately draw the line between AI assistance and AI generation. The full episode is available on YouTube, Apple Podcasts, Spotify, Overcast and other podcast platforms.

Why it matters

AI detection is spreading from text to images and from startup tools to platform-level deployments like Substack's author labeling. Accuracy and the cost of false positives will shape how platforms design trust mechanisms.

PangramAI detectionSubstack
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