Investing in Pangram to Stop AI Slop on the Internet
Menlo Ventures Menlo Ventures ● Covered by 4 sources
Menlo Ventures just led a seed round for Pangram, a startup that detects AI-written text with startling accuracy. With over a third of the internet now AI-generated, someone had to build a detector that actually works.
Based on reporting by Menlo Ventures, Menlo Ventures — read the original for the full story.
Summary, retelling and take written by AI under human oversight; images are AI-generated illustrations. How we work · Report an error
Here's a number that should stop you mid-scroll: by mid-2025, roughly 35% of all text on the internet was AI-generated. Not edited by AI, not polished by AI — generated. Menlo Ventures pulls together a pile of stats to make the point stick. Eighteen percent of federal civil complaints now show signs of AI authorship, up from zero four years ago. Twenty-one percent of peer reviews at the ICLR machine learning conference. Nine percent of newspaper content. Even 33% of top Substack articles. The volume of synthetic language flooding professional and civic spaces isn't a future problem — it's already here.
The issue isn't that AI writing is bad, exactly. It's that nobody can tell anymore what's real, and that uncertainty is corrosive. Menlo quotes an essay by Aphyr with a line that captures the stakes well: as the cost of producing language collapses to zero, the cost of trusting language goes to infinity. When readers can't distinguish a genuine argument from a hallucinated one, they end up trusting nothing and believing everything simultaneously — which is a bad foundation for science, courts, or basic conversation.
Existing AI detectors mostly don't help, and some are embarrassingly bad. Menlo notes that several tools once flagged the Declaration of Independence as AI-written. Pangram, founded by Stanford classmates Max Spero and Bradley Emi, claims to be different. Independent auditing from the University of Chicago's Becker Friedman Institute reportedly found a false-positive rate of one in 10,000 and a false-negative rate under 0.5% on passages longer than 50 words. More notably, the model apparently keeps working on brand-new systems — Claude Opus 4.7, GPT-5.5, even an entirely unrelated model family from Meta — without retraining. Menlo says mechanistic interpretability work shows the model can even tell which specific AI system produced a given passage.customers include Quora, Google Classroom, the Internet Archive, and LessWrong, none through paid marketing, which is its own kind of endorsement.
What stands out in Menlo's account isn't just the technology but the founders' refusal to build a companion product: a "humanizer" tool that would help AI text evade detection. Users apparently asked for one repeatedly. Spero and Emi said no, because it would undercut the entire premise of what they're trying to protect — the idea that readers deserve to know whether a human or a machine produced what they're reading.
Menlo frames text as just the opening chapter. Images and video are next, and arguably higher stakes, given how effectively synthetic visuals already fuel misinformation. The company points to r/IsItAI, a quarter-million-member subreddit where people crowdsource authenticity checks on photos and clips, as evidence of how large and anxious that market already is.
My take — AI-written commentary, not fact-checked reporting
I'll believe the humanizer-refusal story is more than a good pitch line when Pangram's accuracy holds up under adversarial pressure from motivated bad actors, not just new model releases. That said, the incentive structure here is refreshingly sane: a detection company that doesn't also sell the evasion tool is rarer than it should be in this industry, and VCs backing that discipline over the obvious cross-sell revenue is worth noting.
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