What the survey actually measured

Eb Gargano’s Blogging Income Survey 2025 collected anonymous Typeform responses from 187 bloggers between January 24 and April 21, 2025, drawn mostly from her own email list, course students and Facebook group, skewed toward English-speaking countries and bloggers already focused on monetizing. Alongside total monthly earnings, Gargano’s survey tracks something most income reports skip: RPM, or revenue per thousand pageviews, broken out by how long each respondent had been blogging. RPM strips out the effect of traffic size and asks a narrower question: how much is each visitor worth, on average, once a blogger settles into their monetization mix.

The rate falls exactly where the money should be at its best

Gargano’s cohort breakdown moves in one direction for most of a blog’s life, then reverses. Bloggers under a year in averaged an RPM of $10.99. That climbed to $21.61 for the 1-to-3-year group, $24.97 for 3-to-5 years, and $52.59 for 5-to-10 years — a steady, unsurprising climb as bloggers learn what their audience will pay for. Then, at the 10-year mark, it drops to $43.41. Bloggers who have survived the longest, built the biggest archives and presumably learned the most about their own audience are earning less per thousand pageviews than bloggers who’ve been at it for as little as five years.

Total monthly income follows a different, uninterrupted curve, which is part of why the RPM dip is easy to miss unless a survey specifically isolates it. Average earnings run $2.42 a month under a year in, $205.44 by year one to three, $1,044.91 by year three to five, $2,621.24 by year five to ten, and $5,624.91 past the decade mark. Every stage looks like unambiguous progress if income is the only number on the page. The rate is the number that turns over.

The traffic still wins the month

That drop in rate doesn’t show up as a drop in income, because the 10-year-plus group isn’t playing the same traffic game. Gargano’s data puts average monthly pageviews at 49,841 for the 5-to-10-year cohort and 129,562 for bloggers past year ten — roughly 2.6 times more. Multiply pageviews by RPM and the math resolves the apparent contradiction: $5,624.91 a month for the veterans against $2,621.24 for the 5-to-10-year group, more than double. A decade of accumulated posts, backlinks and search rankings buys enough extra traffic to outrun a worse rate per visitor. It doesn’t buy back the rate itself.

What’s actually dragging the rate down

Gargano’s own read points at monetization mix, not fatigue or algorithm penalties. “Most of the bloggers in this category get the majority of their income from ads,” she writes of the 10-plus-year group. “Many get almost 100% of their income from ads and, according to the data, ads deliver the lowest RPMs of all the different blog monetization methods.” She adds a second, compounding factor: bloggers who’ve been running a site for over a decade are “likely to have a lot of poor quality, out of date and/or unoptimized content” sitting alongside their newer posts, diluting the average value of every pageview the archive generates.

The size of the gap ads are leaving on the table

The survey’s own numbers make the ads-heavy strategy look worse the closer you look. Display ads across Gargano’s full sample averaged an RPM of $33.80. Digital products averaged $283.64 — not a marginal difference but roughly eight times the return per thousand pageviews. A blogger converting even a modest share of ad-supported traffic into email subscribers and a paid product isn’t chasing a nice-to-have upgrade. The survey doesn’t isolate how much of the gap between the 5-to-10-year and 10-plus-year cohorts traces to monetization mix specifically, but it’s Gargano’s own leading explanation for the drop.

What the sample can and can’t tell a reader

Gargano is upfront about who answered the survey: respondents skew toward her own email list, course students and Facebook group, which means the sample leans toward bloggers already treating their site as a business rather than a hobby. A 10-plus-year blogger who never tried to monetize seriously in the first place wouldn’t necessarily show up here at all, and the RPM figures likely understate how much worse the gap looks across the full population of aging, half-abandoned blogs that never had an income-focused audience reading along. If anything, that bias should make the 10-year RPM drop harder to dismiss, not easier — it’s showing up inside a sample stacked with people who are actively trying to monetize well.

This doesn’t mean blogging gets worse with time. The traffic compounds, the archive compounds, and by year ten a blog with any monetization at all is likely earning more in absolute terms than it did at year five. What compounds alongside it, for a meaningful share of long-running blogs, is a growing pile of old content still running the least efficient way to make money on it. The bloggers who avoid the RPM drop are the ones who keep changing what they sell as the decade goes on, rather than letting an aging monetization mix ride on accumulated traffic alone.

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The contradiction softens once you separate two things that get treated as one: reluctance to share, and reluctance to share with a particular person. A person can stay closed off around a parent, a sibling, or a longtime coworker and still write several thousand words a week for an audience of strangers, because the resistance was tied to a specific listener, someone who already keeps a running account of who they are, rather than to disclosure itself.

The audience that doesn’t have a file on you

Everyone who has known you for years carries a version of you built up over time, out of every awkward comment at a gathering, every promise broken, every phase once insisted on as permanent. Tell them something new and you’re not just sharing information. You’re updating a record they already keep, one they’ll measure the new disclosure against. A stranger holds no such record. Whatever you tell them lands on a blank page instead of a file with your name already on it.

That distinction is close to what psychologists John Bargh, Katelyn McKenna, and Grainne Fitzsimons described in a study of why people so often express themselves more freely with strangers than with the people closest to them. Writing in the Journal of Social Issues, they noted that with someone outside a person’s usual circle, “one is free of the expectations and constraints placed on us by those who know us.” The people who know you best are also the people whose reaction you can predict in advance, and a predictable reaction is often exactly what makes a piece of honesty feel too costly to risk.

What the “stranger on the train” idea actually says

The pattern has a long history in psychology, usually illustrated with a simple scene: a traveler tells a seatmate things never told to their own family, because the seatmate will be gone by the next stop. Bargh, McKenna, and Fitzsimons used that exact image to describe what carries over online, writing that “one opens up and self-discloses intimate details to the stranger sitting in the next seat, details that one might never have told one’s colleagues at the office or even one’s family and friends back home.”

Publishing to an audience of strangers works on similar logic, stretched out over time instead of compressed into a single ride. A reader who found a piece through search or a shared link isn’t sitting across the dinner table the following week, waiting to bring it up. They read it, maybe they respond, and then the relationship, if it can even be called that, moves on without them. There’s no ongoing account to settle, no family gathering later where the piece becomes the thing everyone is too polite to mention directly.

Why an audience of strangers can feel like relief

Psychologist John Suler studied a related shift in how people behave once identity and consequence loosen, a pattern he named the online disinhibition effect. In a 2004 paper in Cyberpsychology & Behavior, he wrote that “when people have the opportunity to separate their actions online from their in-person lifestyle and identity, they feel less vulnerable about self-disclosing and acting out,” and described that separation, what he called dissociative anonymity, as “one of the principle factors that creates the disinhibition effect.”

Suler’s research was largely concerned with behavior that turns careless or cruel once nobody feels accountable for it. The same mechanism, though, can serve a much smaller and more ordinary purpose for someone who just wants to say something true without managing a listener’s face while they say it. Publishing to strangers on a regular schedule has less to do with escaping consequences and more to do with escaping a particular kind of memory, the kind that gets attached to a person you expect to see again.

A habit, not a diagnosis

This isn’t a claim that every private writer who publishes regularly is guarding some secret, or that a regular publishing habit always signals discomfort with the people closest to them. Plenty of people publish for reasons that have nothing to do with distance from anyone: curiosity, a deadline, a habit built up over years, the plain pleasure of finishing something. The pattern above describes a narrower case, the writer who genuinely is private, means it, and still can’t stop publishing to an audience they’ve never met. For that writer, strangers aren’t a workaround for shyness. They’re the one audience unlikely to hold anything against them later.

The trade a private person is actually making

What looks like an inconsistency, guarded around people in person, open with strangers in print, holds up better as a trade than as a contradiction. A private person who publishes regularly hasn’t stopped protecting themselves. They’ve found an audience with no real way to use what it learns later, because that audience has no later with them. Strangers don’t sit across from you at a holiday meal. They don’t bring up your worst week during your best one. Whatever you hand them stays where you put it, in the piece itself, instead of becoming part of a running account somebody keeps of who you are.

That doesn’t make publishing effortless, and most writers who do it haven’t reasoned through the mechanics this precisely. Many simply notice, without quite naming why, that the page is easier to be honest with than the people waiting at that holiday meal. The reason holds up under a closer look anyway: distance from an ongoing relationship removes the cost that makes disclosure to someone familiar so much harder to risk. For a certain kind of private person, publishing to strangers fits their own instincts more than it breaks them, the one form of honesty those instincts can actually afford.

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What film school actually costs when it isn’t unofficial

The traditional route has a price tag attached to every stage of it. The American Film Institute’s conservatory program runs $72,954 for the 2025-2026 year, and Columbia’s MFA in film runs $77,840 a year in tuition for the first two full-time years, dropping to a reduced “Research Arts” rate for any additional years spent finishing a thesis — a path that can approach $200,000 in tuition alone before housing. Boston University’s film program runs over $90,000 annually; even an in-state public film degree can land between $7,000 and $23,000 a year before production costs. The debt follows students out the door: the Education Data Initiative puts median debt for a film and photographic-arts bachelor’s degree at $26,005, and for a film master’s at $99,757 — more than double the typical master’s-degree debt load, though it’s not the highest figure in that data set; majors like dance and design carry even more. A YouTube upload costs whatever the camera and the creator’s time are worth, and if it fails, nobody owes a lender anything.

The feedback loop film school can’t match

Tuition buys structured critique, but not much of it. A film student gets maybe a handful of graded screenings a semester, judged by a small faculty and a rotating cast of classmates. A YouTube upload gets judged by however many strangers click on it, within hours, in a comment section that doesn’t grade on a curve.

Curry Barker, who dropped out of the New York Film Academy’s Los Angeles campus with creative partner Cooper Tomlinson to start a channel called That’s a Bad Idea, has described the difference less as quality control and more as a cure for overthinking: “Any aspiring filmmaker’s worst nightmare is being paralyzed,” he told The Wrap, describing how the channel forced him to write things he and Tomlinson could actually shoot that week instead of waiting for a script to feel finished. A festival submission gets one verdict, months later. A YouTube upload gets a verdict by the weekend, and there’s a next one already in the queue.

Practice at a volume no curriculum allows

Barker’s public output before his 2025 breakout, “Obsession,” wasn’t one polished thesis film — it was years of visibly uneven attempts. A nine-episode web series called “Roommates” in 2018 and 2019. A 22-minute short called “The Chair” made for around $2,000 in 2023. Then his actual directorial debut: a found-footage horror feature called “Milk & Serial,” shot for $800 in 2024, that sat without a distributor for a year before Barker put it on YouTube for free. Each one is a public rep, watched and judged in real time, in a way a film-school student doesn’t get to log more than a few times before graduation. Volume is the entire mechanism: a curriculum built around four or five supervised projects over four years can’t replicate what a platform allows when the only cost of another attempt is making it.

When the body can’t do it, the software has to

Parsons’ path shows what that practice looks like when it’s forced rather than chosen. His arthritis diagnosis at 13 limited the kind of physical, hands-on production other teenage filmmakers could do — the running-around-with-a-camcorder version of learning the craft. He leaned into software, animation and VFX tools instead, teaching himself the pipeline a film-school cinematography track would have handed him piece by piece over several semesters. By the time “The Backrooms” went viral, he’d spent years uploading practice work nobody outside his own subscriber base was watching closely, which is precisely the condition under which a person is free to be bad at something without consequence.

Failing on camera, on purpose

Danny and Michael Philippou, who built the horror-comedy channel RackaRacka before either of them had a feature credit, describe the same mechanism more bluntly. “You want to make that initial stuff and fail like that,” Michael told No Film School. “That stuff… is a lesson that you take forward for the next thing.” His own follow-up makes the same point more plainly: “The best advice, really, is to just start making stuff.” Danny’s phrasing in the same conversation was blunter still: “Just get started. You have to.” Neither brother frames their early, rougher videos as embarrassing detours on the way to competence. They frame them as the mechanism competence came from — public, low-stakes, and repeatable in a way no film-school assignment schedule allows.

Film school and YouTube are now running in parallel

That doesn’t mean the traditional path is disappearing. Chapman University’s Dodge College of Film and Media Arts had a higher-than-expected yield this admissions cycle and ended up oversubscribed, according to The Ankler — the opposite of what a “YouTube killed film school” narrative would predict. USC film school dean Elizabeth Daley put the moment in context rather than alarm: “This is a cyclical business in terms of new generations coming up.” One path hasn’t replaced the other. A path that used to require an acceptance letter now also has an on-ramp that only requires an upload button, and both are currently producing directors Hollywood wants.

The two pipelines are optimizing for different things. Film school still teaches the parts of the job that a comment section can’t — sound design theory, production management, how a crew actually runs — and a faculty screening still catches craft problems an anonymous audience won’t articulate. What YouTube supplies is the one input structured education has never been able to offer at scale: enough cheap, public, immediate failure to get good before anyone with a checkbook is watching.

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That version of events isn’t hard to believe. AI detection has gotten good enough to flag machine-written prose at scale, and sightings of obviously synthetic listings, ones with nonsensical author bios or covers that look assembled from the same three templates, have been easy to find in genres like romance and thriller. The assumption that follows feels almost like common sense: more AI books on the virtual shelf should mean more AI dollars landing in someone’s pocket.

A 2026 analysis by Tuhin Chakrabarty and three co-authors at Stony Brook University, Columbia Law School, and the University of Michigan tested that assumption directly instead of taking it on faith. The team ran full-text AI detection across 14,419 self-published genre-fiction ebooks sold on Amazon between January 2023 and March 2026, matching each title to its own daily sales record through the end of June 2026.

They used a detector called Pangram v3.3, which its developers report catches AI-generated text with a false-positive rate of just 0.04 percent, and sorted every book into one of three buckets based on how much of its text the tool flagged as machine-generated: none, light exposure at 25 percent or under, and substantial exposure above that threshold. That threshold matters. A book that used AI for a light copyedit or a few transitional paragraphs lands in a different category than one built mostly from generated text, and the study treats them separately rather than lumping every book that touched a chatbot into one pile.

The results complicate the flooding story rather than confirming it. According to the study, books with substantial AI text made up 20 percent of the catalog analyzed, but captured only 12.1 percent of unit sales and 11.3 percent of revenue. Books with no detected AI text, by contrast, made up 62.9 percent of the catalog and pulled in 72.5 percent of the revenue. As the researchers put it, these books “make up a large share of the catalog but a smaller share of sales.”

That gap is real. It doesn’t cancel out what comes next, though. The same data show AI-heavy books gaining ground over time, winning a growing share of sales and taking more of the scarce top-rank positions once held by books with no detected AI text. A fifth of the catalog earning an eighth of the money looks, at first glance, like proof the flooding strategy is failing. Followed across three years, it starts to look more like a foothold.

The bigger shift might not be about AI-generated books specifically at all. Across the period studied, the researchers found that the cumulative catalog of released titles grew 38.3-fold and the number of books selling in a given quarter grew 19.2-fold, while quarterly revenue grew only 8.9-fold. Thousands of new titles, AI-assisted and human-written alike, poured onto virtual shelves far faster than buyers showed up to pay for them. Revenue per selling book fell across most genres, and books with no AI text lost the most ground specifically in genres where AI-generated titles had spread the furthest, especially where Kindle Unlimited availability was high.

Kindle Unlimited matters here because it changes how a book earns money in the first place. Instead of a single purchase price, KU pays authors per page read from a shared pool, which rewards volume and frequent new releases more than it rewards any single title selling well. A catalog strategy built around publishing often, even with heavily AI-assisted books, can do reasonably well under those incentives even while any individual title underperforms on its own. That helps explain why the erosion for human-written books wasn’t evenly spread. It concentrated in exactly the genres and pricing models most exposed to volume publishing.

A second finding buried in the same dataset speaks less to sales and more to originality. Among top-selling titles, the researchers found that books with substantial AI text drew on more distinctive language already present in existing books than human-written top sellers did, and that this overlap climbed alongside revenue. Books with no detected AI text showed no such pattern. The authors note this bears on the market-effect question at the center of fair-use arguments over copyright, since one legal test for whether a use is fair asks whether it substitutes for the original work in the marketplace.

A browsing reader couldn’t have worked any of this out on their own. Amazon listings don’t disclose whether a book contains AI-generated text, and the researchers needed full-text detection software run against the entire manuscript, not just a skim of the sample pages Amazon shows before purchase, to sort the catalog this precisely. A cover, a blurb, and a few free pages simply don’t carry enough signal either way. That’s part of why the flooding narrative took hold in the first place: the visible evidence, a handful of obviously synthetic listings, was easy to spot, while the actual sales math required a proprietary sales panel and machine detection run across full manuscripts before anyone could see it clearly.

It’s worth sitting with what this data can and can’t tell you. This is one dataset, covering self-published genre fiction specifically rather than all of Amazon’s catalog, and it’s a preprint that hasn’t yet gone through peer review. The findings describe an association between detected AI text and sales performance across a large sample, not a controlled experiment into why any individual reader bought or skipped a given book. Detectors also aren’t flawless. Even at a reported false-positive rate of 0.04 percent, a sample of this size will misclassify some titles in both directions, and genre-fiction ebooks are not the same market as, say, self-published nonfiction or hardcover releases.

What the numbers do support is a narrower claim than the one usually repeated. AI-generated books aren’t quietly draining the same dollars away from human authors, title for title, the way the flooding story implies. They’re doing something slower and, in some ways, harder to counter.

By adding volume the market didn’t ask for, they’re making the whole shelf more crowded and slightly less profitable to sell into, whether or not the book sitting next to them was touched by a machine at all.

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What TikTok actually changed

The Creator Rewards Program, which replaced the Creativity Program Beta, requires creators to be 18 or older, have at least 10,000 followers, and have logged 100,000 views in the trailing 30 days. Only videos longer than one minute qualify, a threshold TikTok tied directly to the fact that its own users now spend half their time on the app watching videos over a minute long. Payout is calculated from four factors — originality, play duration, search value and engagement — plus a separate automatic reward tied to ad watch time. None of those four factors reward a creator simply for publishing more. They reward creators for making videos other people finish watching, which is a much narrower category than “videos that exist.”

TikTok’s own numbers show why the company bothered rewriting the formula at all. When it announced the shift out of beta in March 2024, TechCrunch reported that TikTok claimed total creator revenue had risen more than 250% in the prior six months compared with the old, since-shuttered Creator Fund, which had become notorious for paying creators a few dollars on videos with millions of views. That 250% figure describes the total pool, not what any individual creator took home, and TechCrunch noted the same six months saw viewership of over-one-minute videos climb nearly 40% — meaning some of that revenue growth reflects a platform-wide shift toward longer content, and the formula itself may not have gotten proportionally more generous. The distinction matters: growing the pool and narrowing who qualifies to draw from it are two different moves, and TikTok did both at once.

YouTube’s version of the same fix

YouTube made a structurally similar move in August 2026, when it announced on its official blog that new applicants to the Partner Program will need 8,000 qualified watch hours in the trailing year, or 20 million qualified Shorts views in 90 days, starting February 1, 2027 — double the 4,000-hour bar that had stood since 2018. Creators already inside the program keep their existing status; the new bar only applies to whoever is trying to get in after it takes effect. YouTube framed the reason as scale rather than creator misbehavior, saying it needs to “keep pace with the growth of YouTube,” which now sees over 200 billion daily Shorts views and more than a billion hours of watch time on TV every day. And YouTube said the quiet part plainly: it expects “to pay even more to creators in 2027 than we did in 2026.”

The same update adds a second, ongoing gate that only applies to Shorts earnings: creators already in the program must maintain 10 million qualified Shorts views over a trailing 90 days to keep collecting Shorts revenue specifically. Fall below that and a channel doesn’t get removed from the Partner Program outright — its Shorts payments just pause until the number recovers, a mechanic that recurs on a rolling basis — a standing quality check on the video type YouTube considers easiest to flood with low-effort volume, not a one-time entry exam.

The same lever, pulled two different ways

TikTok’s fix operates on quality — it decides which videos, from an already-eligible creator, are worth paying for. YouTube’s fix operates on eligibility — it decides which channels get to enter the payout pool at all. Both levers do the same underlying job: they reduce the number of claims on a finite amount of ad money, so each remaining claim is worth more. YouTube’s own framing makes the mechanism explicit. Raising the bar to 8,000 hours doesn’t grow ad revenue by itself; it narrows who’s eligible to split it, which is exactly how a platform can credibly promise to “pay even more” without needing advertisers to spend more per creator. TikTok’s originality-and-completion formula does the equivalent work one video at a time instead of one channel at a time.

Why this should worry more than video creators

Every content platform monetized by advertising eventually runs into this same math: ad budgets grow linearly, if they grow at all, while the number of people trying to earn from those budgets grows however fast sign-ups allow. Blogs monetized through display ads and affiliate networks sit inside the identical pool logic — RPMs are a function of how many other publishers are chasing the same advertiser dollars in the same niche, not just how good any one blog is. The platforms with the leverage to police entry, the way TikTok and YouTube just did, will keep doing it whenever the math stops working. The platforms without that leverage, including most blogs, don’t get to raise a bar. They just watch their per-visitor revenue erode as more competitors show up to split it.

What happens to the creators on the wrong side of each line

Neither company frames its change as a loss for anyone, and in a narrow sense that’s accurate: nobody currently earning from either program loses access retroactively. But a channel that would have qualified for YouTube monetization under the old 4,000-hour bar and doesn’t clear 8,000 after February 2027 experiences the change as a wall regardless of how it’s described in a blog post, and a TikTok creator whose videos rack up views without holding attention past the first few seconds experiences the new formula as a pay cut regardless of how TikTok frames “originality.” The two platforms picked different filters — one runs on time served, the other on content judged in the moment — but creators on the losing side of either filter are the ones actually paying for the “pay even more” promise made to everyone else.

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The person who said so out loud was Chris Best, Substack’s co-founder and CEO. Speaking onstage at The Information’s Future of Influence event in Los Angeles in June 2025, Best said “more than 50 people” were making over $1 million a year on the platform. The comment came out unscripted, in the middle of a conversation, the kind of figure a company usually keeps close until legal and marketing have signed off on the wording. It landed the way unplanned numbers tend to land: fast, and everywhere, within hours.

The moment it slipped out

The clearest sign that this was an unplanned disclosure came from inside Substack itself. Within hours of Best’s comment making the rounds online, Hamish McKenzie, Substack’s other co-founder, posted a note of his own: “Oh shit, didn’t realize we were disclosing this.” McKenzie’s note reads like genuine, in-the-moment surprise at watching a private number go public, posted the same evening Best said it.

That kind of reaction rarely happens by accident. Companies generally control what gets said about their own revenue and their own top earners, especially when the number is this flattering. A co-founder’s half-panicked note is a small, human confirmation that the figure was a real answer to a real question, given by someone who hadn’t quite worked out yet what happens once a number like that gets loose in the world.

What five years actually did

Whatever prompted the disclosure, the underlying shift is real, and it shows up in the platform’s own subscription numbers. Axios reported that Substack’s paid subscriptions grew from about 100,000 in July 2020 to more than 5 million by March 2025, roughly a fiftyfold increase in five years. That’s a jump big enough to turn a promising, unproven place to write into one where a few dozen people can apparently run a media business at seven-figure scale, without a network, a studio, or a masthead behind them.

Five years ago, the honest answer to whether someone could make a living writing a newsletter was maybe, for a handful of already-known writers, if the timing worked out. The honest answer now comes with a number attached to the top of that range, and the number is high enough to change what “maybe” means for everyone still climbing toward it.

Why now, and not five years earlier

Part of the answer is timing that had little to do with Substack itself. Newsrooms spent the years between 2020 and 2025 cutting staff on a scale that pushed a lot of experienced reporters and columnists to look for income that didn’t depend on one employer’s ad budget. A subscription newsletter, paid for directly by a few thousand readers instead of approved by an editor, was one of the few options that let an established writer keep a byline and set their own terms.

The other part is simpler. Five years ago, asking a reader to hand over a monthly card payment for a newsletter was still a hard sell, competing against a habit of expecting most writing online to be free. By 2025, that habit had loosened enough that a reader already paying for three or four other subscriptions barely noticed adding one more. Substack didn’t create that shift by itself, but it built the checkout button that a critical mass of readers were, by then, willing to click.

Fifty people, or fifty small operations

It’s worth being precise about what Best’s number does and doesn’t describe. “More than 50 people” earning over $1 million a year is a statement about income at the top of the platform. It says nothing about how that income gets produced. Some of those newsletters are probably one person handling everything: writing, editing, answering comments, running the business side alone. Others are more likely small operations, with an editor, a researcher, or a couple of contributors splitting the byline and the workload. A seven-figure newsletter run by four people and a seven-figure newsletter run by one person both count toward the same total, and they represent very different amounts of individual effort.

That distinction doesn’t make the figure less real. It changes what the figure is evidence of: a ceiling that’s newly reachable on the platform, not a job description that applies evenly to everyone chasing it.

The number also says nothing about how long any of those fifty-plus newsletters will stay above the line. A newsletter’s income depends on renewals, and renewals depend on readers deciding, year after year, that the writing is still worth the price. Crossing seven figures once, in 2025, is not the same as staying there in 2030.

A number that didn’t exist to report

What makes this moment different from a routine growth statistic is that five years ago, there was no comparable figure available to disclose, flattering or not. A platform can’t reveal that dozens of independent writers cleared $1 million a year when the entire platform hadn’t yet proven a handful of writers could clear six figures. The number Best said onstage only became sayable because enough individual newsletters had already gotten there first, one subscription at a time.

Whether that pace holds for the next five years is an open question, and Substack itself doesn’t seem to have a rehearsed answer, going by how quickly its own co-founder reacted to the number getting loose. What’s confirmed for now is narrower and more specific than any claim about the future of media. A threshold nobody could point to in 2020 has a number attached to it in 2025, and that number came from the person best positioned to know it.

For anyone weighing whether to start a newsletter of their own, that number is worth reading as a ceiling rather than a floor. Most writers on Substack do not clear six figures, let alone seven, and the platform has never claimed otherwise. What changed in five years is that the top of the range moved somewhere it hadn’t been before, far enough that even a skeptical audience had to notice.

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What five years of the same survey actually shows

Gargano’s Blogging Income Survey 2026 collected anonymous Typeform responses from 129 bloggers between January 2 and April 29, 2026, drawn largely from her own email list, courses and paid community, and skewing toward bloggers already focused on monetization. Most respondents were based in the UK, US, Canada, Australia and New Zealand. The headline numbers are blunt. It takes an average of 21 months for a blogger to earn their first dollar, though the median is 12 months and just over a quarter of respondents earned something within six months of starting. Reaching what a respondent personally considered a full-time income took an average of 4 years and 1 month, with a median of 4 years — up from a 3-year median last year — and 24% of this year’s bloggers hit that mark within two years, down from 28% last year. Gargano’s own read of the data, after five years of running the same survey, is direct: “it’s clearly getting harder to ‘break in’ to blogging, and it’s taking longer to get to a decent full-time income.”

The other half never earns a cent

That four-year runway assumes the blog eventually turns a profit at all, and a lot of them don’t. In February 2019, Kyle Byers at GrowthBadger surveyed 1,117 self-identified bloggers, split them into bloggers earning over $50,000 a year and everyone else, and found that a little less than half of the lower-income group made any money from their blog at all. Of the roughly 47% who did, the two most common methods were Google AdSense and affiliate marketing, the lowest-effort and lowest-control monetization options on the list. The gap between the two groups traced back to specific, repeatable choices: bloggers earning over $50,000 were 4.3 times as likely to do keyword research, used more than three times as many email list-building tactics, and were 5.6 times as likely to sell a product or service they controlled themselves.

“Full-time” and “financially sustainable” aren’t the same claim

Even a self-reported full-time income doesn’t settle whether the work actually supports someone long-term. A report from the Center for News, Technology & Innovation, published in April 2026, surveyed 43 independent writers and creators and conducted in-depth interviews with 26 of them. Only 5 of the 43 said their content income could fully fund their lifestyle. Just over half, 23 of 43, said they couldn’t fund their lifestyle from the work at all. The report covers independent writers and creators broadly rather than bloggers specifically, but the shape of its finding matches what both blogging surveys show separately: a small top tier making a living, and a much larger group for whom the work is a side project, a portfolio piece, or an experiment that hasn’t paid off yet.

What actually separates the two groups

Byers’ data gets more useful once “over $50,000” stops being treated as a single trait and starts getting read as a bundle of specific decisions. Higher-income bloggers in his survey rated Google organic search 83% more valuable than lower-income bloggers did, and rated email marketing 192% more valuable. Their most popular posts averaged 2,424 words, 83% longer than the top posts from lower-income bloggers, and they paid outside writers $347 per article against $96. The survey measures correlation.

Byers is upfront that adopting these habits out of order or too early can backfire. But it describes a business run with the rigor of any other small business — a different animal from a hobby that occasionally throws off ad revenue.

Gargano’s 2026 data points the same direction from a different angle: bloggers who did email marketing earned roughly twice as much as those who didn’t, and bloggers using four or more revenue streams out-earned single-stream bloggers by a wide margin.

Why the timeline keeps stretching

Neither survey pins down exactly why the under-five-year cohort lost ground this year while the ten-year-plus cohort gained it, but the direction fits what’s been happening to organic discovery generally: a newer site has less accumulated authority, fewer backlinks and a thinner archive to fall back on right as search traffic gets harder for everyone to earn. A blog compounding content, links and an email list since 2016 has a cushion a blog started in 2024 hasn’t had time to build. That lines up with Gargano’s own explanation for the split: bloggers past the five-year mark, she notes, “tend to have more revenue streams than bloggers who have been blogging for less than 5 years and they tend to be monetizing via more lucrative revenue streams.”

Blogging isn’t a bad bet. It’s a slower, less evenly distributed one than the “start a blog, quit your job” pitch suggests. The bloggers clearing $50,000 a year are running a small media business, complete with keyword research, an email list and diversified income streams, and they got there by staying past the point where most people quit, well beyond the four-year mark Gargano’s data says is typical now.

The post Is blogging still profitable? The bloggers who reach a full-time income wait an average of four years to get there, and the wait is getting longer, not shorter appeared first on The Blog Herald.

What the zero-click number actually measures

SparkToro’s analysis covers desktop and mobile web searches, weighted two-to-one mobile-to-desktop, but excludes Google’s mobile app, where zero-click behavior is reportedly even more aggressive. The rise itself isn’t new: zero-click search has been climbing steadily since at least 2016, driven first by featured snippets, knowledge panels, and direct-answer boxes, long before generative AI entered a results page. What’s new is the slope of the climb.

What AI Overviews specifically add

AI Overviews now appear on more than 20% of all Google searches. Ahrefs analyzed 300,000 keywords, split evenly between searches with an AI Overview present and similar informational searches without one, and found that as of December 2025, the presence of an AI Overview correlated with a 58% lower click-through rate for the top-ranking page than a comparable keyword without one — up from the 34.5% reduction Ahrefs measured when it first ran the analysis in 2025. Ahrefs’ Ryan Law was blunt about the gap between that finding and Google’s own public claims: “It seems that Google doesn’t want us to see the clickthrough rate for AI Overviews.” Pew Research found a similar pattern independently: searches that triggered an AI summary produced a click only 8% of the time, versus 15% for searches without one.

The metric change bloggers are already seeing in Search Console

Anyone checking Google Search Console for their own blog has probably noticed a pattern that used to be unusual: impressions climbing while clicks fall, instead of moving together the way they always used to. Ahrefs calls this “the great decoupling” and traces it to two mechanical causes. AI Overviews often cite several source URLs at once for a single query, spreading impressions across multiple sites instead of concentrating them on whichever result ranks first — and when an AI Overview answers the question directly, a person has no reason to click through to any of the cited sources at all. Ahrefs found the correlation between impressions and clicks across its own tracked data flipped from a positive 0.425 in late 2024 to a negative 0.352 by early 2025, around the same time Google’s March 2025 core update roughly doubled how often an AI Overview appeared. A blog’s impressions going up is no longer, on its own, good news.

Who’s actually losing traffic, and who isn’t

The decline isn’t evenly distributed. Digital Content Next tracked Google search referrals for 19 major publishers and found a median year-over-year decline of 10% in May and June 2025 — 14% among non-news publishers, a smaller 7% among news publishers. Branded searches move the opposite direction: according to research from marketing agency Amsive, reported by Search Engine Journal, AI Overviews are associated with an 18% increase in click-through rate when someone searches for a specific site or brand by name rather than a general topic. That split matters more than the headline zero-click number: a blog that ranks for “how to grow an email list” is exposed to the full brunt of the AI Overview effect, while a blog whose readers search by name is largely insulated from it.

What publishers are actually doing instead of waiting it out

The publishers already living with this aren’t treating it as a search-optimization problem to be patched. Reach’s David Higgerson described the shift bluntly in comments to the BBC, reported by Search Engine Journal: “We’ve got millions of people who receive our alerts on WhatsApp. We’ve built newsletters.” Bauer Media’s Stuart Forrest made a related but distinct point about what still works inside search itself, framing it as a content-quality problem rather than a technical one: publishers need to be the site an AI Overview cites instead of a rival, and “it’s amazing the number of publishers that just give up on” doing that well. Both point toward the same underlying shift: an audience a publisher owns directly — a subscriber list, an app, a community — doesn’t lose value when Google changes how a results page looks, because Google was never what was holding that relationship together.

What this means for a blog that lives on organic search

A blogger whose traffic comes almost entirely from Google is exposed to a trend that started before generative AI and has now picked up speed because of it, and neither Google’s own explanations nor a single SEO fix are likely to reverse it. The workable response looks like what larger publishers are already doing at a bigger scale: building a channel Google doesn’t control, whether that’s a newsletter, a podcast feed, or a community, so a chunk of the audience arrives without going through a results page at all. Building that channel won’t recover lost search traffic. It puts a ceiling on how much of the business any single results-page redesign can threaten.

The post Zero-click Google searches passed two-thirds in early 2026, and the newest data shows AI Overviews didn’t start that trend — they just sped it up appeared first on The Blog Herald.

What Beehiiv actually shipped

The centerpiece is Community: a discussion space attached to a creator’s newsletter where subscribers can talk to each other, which creators can moderate and gate behind a paid tier. CEO Tyler Denk’s explanation for building it was specific: “People following your content have a shared interest in what you’re creating, but they can’t communicate with each other… being able to have a community where your audience can actually engage with one another is super valuable.” Alongside it, an AI Copilot analyzes a newsletter’s content and audience metrics to suggest growth moves and draft outreach campaigns, and the editor got a split-screen redesign showing edits and the rendered preview at once. Beehiiv said its programmatic ad network now pays publishers on the platform more than $1 million a month in aggregate.

A creator can export a Beehiiv subscriber list in an afternoon; the conversation history inside a paid community tier stays on the platform. That’s the mechanism behind July’s launch — Community’s real function is making more of a creator’s audience relationship non-portable.

Why a newsletter tool is building a chat room

A newsletter, structurally, is a list — the entire relationship lives in an email address a creator could export and take to a competitor tomorrow. That portability is the whole pitch newsletter platforms make to attract creators away from a rival, and it’s also the thing that keeps any single platform from ever fully owning a creator’s audience. A community feature works against that portability: conversations between subscribers, unlike the email list itself, don’t export. A creator can leave Beehiiv with their subscriber list intact; they can’t take the conversation history, the paid-tier chat access, or the relationships subscribers have built with each other. For a platform competing on retention, that’s close to the entire point of building Community in the first place.

The pitch is ownership, and at least one creator’s numbers back it up

Denk has framed Beehiiv’s difference from Substack and Patreon as being “unopinionated” about how a creator monetizes, rather than steering them toward one model. That pitch has a concrete data point behind it: journalist Frankie de la Cretaz reported a 78.4% increase in net income worth $21,325 a year after migrating a newsletter from Substack to Beehiiv, citing both financial and what they described as ethical reasons for the switch. That move isn’t an isolated case: Nieman Lab has tracked several other writers who left Substack for Ghost and Beehiiv and reported receiving a larger share of subscription revenue after the move. The company is betting that pattern continues — Beehiiv added 50,000 active users and posted its best quarter yet, $4.5 million in new annual recurring revenue, in the first quarter of 2026 alone.

What this means for anyone building an audience on borrowed infrastructure

Bloggers and newsletter writers building on any platform — Beehiiv, Substack, WordPress.com, YouTube — are making the same trade Beehiiv’s own creators are: portable reach in exchange for platform-specific engagement tools that don’t travel if they leave. The $1-million-a-month ad-network figure is early evidence that programmatic advertising can pay real money at scale without a creator selling a single sponsorship themselves, but that revenue is also the newest and least portable part of the arrangement — a sponsor relationship built through a platform’s ad network doesn’t move with an exported subscriber list the way the list itself does.

The useful question isn’t whether to use these tools; it’s tracking which parts of an audience are actually a creator’s to keep and which parts only exist because one specific platform is hosting them.

The retention math behind the community push

Beehiiv has spent the past year adding podcasts, webinars, and paywall options on top of newsletters — the podcasts feature hit its quarterly goal within 24 hours of launch and beat its Q2 target by more than 10x, according to Denk, and half of new podcast hosts on the platform migrated in from elsewhere. That kind of expansion only makes sense if the company expects creators to consolidate more of their business inside one platform rather than spreading it across specialized tools. Community is the piece of that stack least like the others: podcasts and webinars are content formats a creator could rebuild on a different platform, but a community’s value is the specific conversation history that formed inside it — the one part that doesn’t come along when a creator leaves.

The post Beehiiv just gave newsletter subscribers a way to talk to each other, and it’s a hedge against the one thing that makes newsletter platforms replaceable appeared first on The Blog Herald.

Min’s explanation was blunt: “Substack is an incredible launchpad, but we reached a point where it wasn’t built for what we were becoming.”

That is a specific, checkable complaint, and it is not the same complaint as “the rules keep changing under me.”

What actually left, and what didn’t

The Ankler’s departure wasn’t a clean break. The outlet said it would keep a weekly newsletter and live video presence on Substack even after moving its primary infrastructure to Passport — a hedge, not a divorce. That distinction matters, because the same caution applies to the other names attached to this story.

The Bulwark, Mehdi Hasan’s Zeteo, and Emily Sundberg’s Feed Me have been reported as privately frustrated with Substack and quietly exploring alternatives, but none has announced a move.

Treating all four as already gone overstates what’s actually happened; only one has.

Why the math changes as a newsletter becomes a media company

Substack takes a 10% cut of subscription revenue. On a solo newsletter earning $50,000 a year, that’s a rounding error. On an operation earning eight figures with a payroll to cover, it becomes real money fast: media reporter Oliver Darcy, writing in his Status newsletter and relayed by The Wrap, estimated the cut runs to “hundreds of thousands of dollars, if not north of a million each year” for top-tier outlets. Ten percent of The Ankler’s roughly $10 million in revenue lands right in that range. What’s driving the frustration is that a percentage that made sense when the business was one person and an email list stops making sense once the business has 18 salaries to fund.

What Substack is actually offering in return

Substack’s counter is that the fee buys distribution as well as infrastructure: the company says its discovery and recommendation tools drive roughly 30% of new paid subscriptions for creators on the platform. That’s a real number worth taking at face value. The publishers pushing back aren’t disputing it so much as arguing they’ve outgrown its value relative to its cost — they want customization, product control, and a design system that doesn’t make a seven-figure media brand feel like one of, as reporting has put it, the platform’s “sub-brands within its own ecosystem.”

The difference between this and a rules problem

It’s tempting to file this next to YouTube’s monetization-bar increase as another case of platform-dependent creators getting burned by rules changing underneath them. The reporting doesn’t support that comparison. Nothing here describes Substack changing its fee, its recommendation algorithm, or its terms unannounced. What’s described is a handful of publishers outgrowing a fee structure and a design ceiling that were built for a smaller kind of business than the ones they’ve become. That distinction — outgrowing a fee structure versus getting blindsided by one — is what determines whether your own platform risk looks like The Ankler’s or looks like YouTube’s.

Who this actually applies to

For the overwhelming majority of people writing on Substack, this fee fight changes nothing. A newsletter earning $50,000 or $200,000 a year is nowhere near the point where a 10% fee competes with payroll, and the platform’s discovery tools are still doing exactly the job they were built for at that scale. This is a top-of-the-market story about four publications that grew past being newsletters, not a warning sign for the thousands of writers who haven’t.

Ten percent of $10 million is roughly $1 million a year, the size of the line item that turned a platform fee from a rounding error into a decision. The Ankler is the only one of the four so far to act on it.

What this means for anyone building past a one-person operation

The lesson generalizes past media trades and Hollywood newsletters. Any blogger, YouTuber, or newsletter writer who starts as a one-person operation eventually faces the same fork The Ankler did: the platform fee, ad-network cut, or marketplace commission that was invisible at $50,000 a year becomes a line item worth renegotiating once there’s a staff to pay. The math here isn’t really about fairness — a 10% subscription cut, a 30% app-store fee, and a marketplace’s take rate are all defensible prices for the discovery and infrastructure they provide at small scale. What changes is leverage: a platform’s audience-finding tools matter less to someone who already has 150,000 people showing up directly, and that person can afford to pay more to own the relationship outright instead. The useful test isn’t “is this fee too high,” it’s “would I still need this platform’s discovery tools if my audience doubled” — and for most writers, the honest answer is yes, for a long time yet.

The post The Ankler didn’t leave Substack for a bigger audience – it left because the 10% cut that works at newsletter scale stops working at media-company scale appeared first on The Blog Herald.

That is not a normal pace for a law to rise and collapse, and the reason it happened that fast has very little to do with Virginia specifically.

A federal judge went well past a simple pause. She sided outright with NetChoice’s challenge on First Amendment grounds, in a ruling detailed enough that any other state currently drafting its own version of a usage cap now has a fairly precise map of the argument it will have to survive in court.

That turns this from a Virginia story into a preview of the fight headed for every statehouse still working on a similar bill, and into a real complication for any publisher or platform whose audience skews young enough that these laws are the reason they were paying attention to Virginia in the first place.

1. A judge struck down the whole law, not just trimmed it

Virginia’s Senate Bill 854 required social media platforms to cap users under 16 at one hour a day per app by default, with a parent able to adjust that limit, and it required age verification to know who counted as under 16 in the first place.

Governor Youngkin signed it on May 7, 2025, and it took effect January 1, 2026. NetChoice, the trade association representing most major platforms, sued weeks before that deadline. On February 27, 2026, U.S. District Judge Patricia Giles of the Eastern District of Virginia sided with them, blocking the law’s enforcement entirely rather than narrowing it.

2. The reasoning was about speech rights, not really about whether social media is harmful

Judge Giles’s opinion leans toward agreeing that Virginia had a real problem worth solving. “The court recognizes the commonwealth’s compelling interest in protecting its youth from the harms associated with the addictive aspects of social media,” she wrote, “however, it cannot infringe on First Amendment rights, including those of the same youth it aims to protect.”

What sank the law was the method it chose, requiring every user, adult or minor, to prove their age before accessing ordinary speech, rather than any disagreement that teen social media use is worth worrying about. Per the written opinion itself, the law was overinclusive because it “burdens more speech than necessary” by making every user verify their age before reaching content that is protected for everyone, and underinclusive because, despite targeting the addictive pull of social media specifically, it carved out an exemption for interactive gaming, one of the more addictive categories of app there is. A law that fails on both counts at once is a hard one to rescue with a small rewrite.

3. Virginia’s law was blocked well after it already took effect

This part gets flattened in a lot of quick coverage. SB 854 was not stopped before it ever kicked in. It was live for close to two months, from January 1 through late February 2026, before a court froze it.

Any publisher or platform that spent that window building age-gates and usage-tracking specifically for Virginia users got to unwind that work almost as soon as it shipped, which is its own kind of cautionary tale about building compliance infrastructure around a law that has not yet survived a First Amendment challenge.

4. The sponsor is not backing down, and neither is NetChoice

State Senator Schuyler VanValkenburg, who sponsored the bill, made clear this is not over. “Obviously, I disagree with the decision,” he said. “I think our legislation does thread the needle of respecting free speech while also empowering parents and protecting kids. I look forward to the case working its way through the legal system and I think, and hope, that ultimately the courts will agree with my analysis and that of the commonwealth.”

On the other side, NetChoice, the trade group whose members include most of the largest social platforms, framed the ruling through its litigation center co-director Paul Taske as validation of a broader pattern the group has pushed in court after court, in Virginia and well beyond it: “Today’s decision underscores a core truth: unconstitutional laws do not help anyone. Moreover, laws requiring age verification and other privacy-invasive measures actually make everyone less safe and more prone to data breaches.” Both sides are treating this as round one, not the final word.

5. Other states drafting similar caps just got a preview of their own lawsuit

NetChoice is not new to this specific kind of fight, First Amendment challenges to age-verification and usage-limit rules, and Virginia is unlikely to be the last state where the group tries it. A ruling this specific about strict scrutiny and least-restrictive-means gives any legislature drafting a flat usage cap a fairly clear preview of the argument it will face in court, and gives publishers who rely on younger readers a reason to watch which design choices survive. A hard cap that applies to every user regardless of parental input looks legally shaky right now. A rule built around defaults, verified age, and a parent’s ability to opt back in, closer to the shape New York used for its own recent youth social media rules, has not been tested the same way yet, and may hold up differently when it eventually is.

6. If you built anything around Virginia’s law, you can pause that work

Any publisher or marketer who spent late 2025 adjusting a Virginia-facing product for the one-hour cap, adding an age gate, capping session time, rewriting a consent flow, can stand that work down for now without necessarily throwing it away. The law is enjoined, not repealed, and Senator VanValkenburg has already signaled Virginia intends to keep fighting for some version of it.

Treat the pause as exactly that, a pause, and keep an eye on whether a narrower bill shows up in the next legislative session rather than assuming the question is closed. I have gone through more than one platform’s policy change that looked permanent and turned out to be a first draft, so my instinct here is to keep the compliance notes filed away rather than delete them.

None of this settles whether an hour a day is the right number for a teenager, or whether Virginia will pass a narrower version that survives. It just means the law bloggers and marketers were bracing for is not currently in effect, and the fight over what replaces it is only getting started.

The post Virginia’s mandatory one-hour daily limit on teen social media use was struck down by a federal judge less than two months after it took effect, and NetChoice’s First Amendment win over Virginia’s usage caps could stall similar bills in other statehouses that would have limited how publishers reach younger audiences. appeared first on The Blog Herald.

What YouTube actually said, and didn’t say

YouTube’s own explanation for doubling the bar was about scale: the company pointed to more than 200 billion daily Shorts views and over a billion daily hours of watch time on connected TVs as evidence the platform had outgrown its decade-old thresholds. It did not frame the change as a response to spam, low-effort content, or advertiser complaints about where their money was landing, and that connection is this article’s inference — YouTube hasn’t offered it as a reason.

What YouTube confirmed in its own support documentation is narrower than the headline suggests: the doubled bar, 1,000 subscribers plus either 8,000 watch hours in a year or 20 million Shorts views in 90 days, applies to creators applying to the Partner Program on or after February 1, 2027. Current members’ status is not affected by the change.

The separate, ongoing requirement to keep an already-monetized channel active stays at 1,000 watch hours a year, or 1 million Shorts views in 90 days, or a minimum upload cadence, with a 90-day cure window if a channel dips below it — and every creator has until January 31, 2027 to accept updated terms or lose monetization features the next day.

What podcast advertisers are actually paying for

The IAB’s $2.862 billion figure for 2025 is real growth, but it’s decelerating growth: podcast ad revenue grew 72% in 2021 and 26% in 2022, so 17.6% is a much calmer number than the headline “podcast advertising keeps climbing” implies on its own. What hasn’t decelerated is trust among the format’s most engaged listeners. Sounds Profitable found that 86% of podcasting’s most active users recalled hearing an ad in the past week, and that 46% of respondents trust ad-supported podcasts’ moderation and content quality, a figure that only Twitch and streaming music, at 51%, beat among the channels studied. Sounds Profitable partner Tom Webster has made a related point: podcasting’s growth hasn’t come by bloating ad loads past what listeners will tolerate, which is a large part of why the ads that do run get noticed instead of ignored.

Why a doubled bar and a trust premium are the same story

Two hundred billion daily Shorts views describes how much inventory exists — it says nothing about how much of it an advertiser should want their name next to. Podcasting has spent years solving that problem from the demand side: a handful of host-read ad slots per episode, sold by a comparatively small number of shows, produces scarcity by construction, and scarcity is a large part of why podcast ads earn a recall and trust premium that programmatic video hasn’t matched. Doubling YouTube’s monetization bar does the same job from the supply side: it shrinks the pool of channels whose inventory YouTube is willing to sell against, whatever the company’s stated reason for doing so. Both moves push the same direction: toward less inventory, sold at a higher price, to buyers who trust what they’re getting.

The part that doesn’t fit neatly

The picture is messier than a single cause with two effects. Podcast ad dollars are concentrating more heavily toward the largest shows this year: Magellan AI’s ad-spend tracking, reported by Inside Audio Marketing, found the top 500 podcasts captured 52% of Q2 2026 ad spend, up from 48% in Q1 — the opposite of a story where trust and ad dollars spread evenly across the format. And YouTube’s stated reason for its change is platform scale — the company hasn’t described it as curation — so treating the two announcements as coordinated responses to the same market pressure is this article’s read of the pattern; neither company has made that claim about the other.

What this means for anyone selling ad space on their own site or newsletter

$2.862 billion and a doubled monetization bar were announced four months apart, by two companies, for two different stated reasons.

Whatever each company says about its own motives, both numbers move the same lever: less inventory advertisers can verify, sold at a higher price, to buyers who trust what they’re getting.

A blogger or newsletter writer with a smaller, high-completion audience is sitting on the exact asset advertisers are chasing in both of the trends above: attention a sponsor can actually verify shows up and pays attention, rather than attention that merely exists in a subscriber count. A newsletter with a 45% open rate and 3,000 subscribers is a better pitch to most sponsors than one with 30,000 subscribers and an 8% open rate, for precisely the reason a 46% trust score beats a bigger, noisier audience with a worse one: the number that closes a sponsorship deal is verified attention, not raw reach.

The post Podcast advertising rates are climbing and YouTube just doubled its monetization bar – here’s why that might not be a coincidence appeared first on The Blog Herald.

That is not a comfortable thing to admit as someone who writes for a living. It turns out I am not alone in not knowing, and a lawsuit filed this summer is trying to force an answer for a much bigger group of publishers than just me.

What the lawsuit actually claims

On June 24, 2026, a coalition of 34 newspaper companies, representing nearly 400 local publications across 33 states, filed suit against OpenAI and Microsoft in federal court in New York. The Arkansas Democrat-Gazette and its parent company, WEHCO, are named plaintiffs. The complaint alleges that the two companies systematically scraped publisher websites, copied articles without permission, stripped out copyright management information, and fed the material into the datasets that trained ChatGPT and Copilot. The legal claims rest on the federal Copyright Act and the Digital Millennium Copyright Act, and the newspapers are seeking statutory damages along with an injunction that would force the removal of their work from the underlying models and training data, not just a promise to stop scraping going forward.

Part of the newspapers’ evidence is OpenAI’s own words. In written evidence the company submitted to the UK House of Lords in late 2023, OpenAI stated plainly that “it would be impossible to train today’s leading AI models without using copyrighted materials.” The complaint frames that admission as the whole case in miniature: a company that argues copyright is essential to its own product while treating other people’s copyrighted work as free raw material. As the filing itself puts it, the publishers are trying “to hold Defendants to the same standard they insist upon for themselves.”

Why this matters even if your blog is not one of the 400

Most independent bloggers and small digital publishers are never going to be plaintiffs in a case like this one. Joining a coalition lawsuit takes lawyers, resources, and a body of published work large enough to be worth the fight. But the legal theory being tested here does not only apply to newspapers with decades of archives. If a court agrees that scraping a publisher’s site to train a commercial model without permission or payment is copyright infringement, that finding does not stay contained to the plaintiffs named in this one complaint. It becomes a data point every smaller publisher can point to.

A quieter reason this case matters sits beyond whatever legal precedent it eventually sets. Most independent writers have never had the option WEHCO and its co-plaintiffs are exercising, the option to say no and be taken seriously. A newspaper chain with decades of archives and in-house counsel can credibly threaten litigation. A single blogger, or even a small network of them, generally cannot, which means the practical leverage over how AI companies treat smaller publishers’ work has always sat with whoever could afford the lawsuit, not with whoever actually wrote the content.

A quick check on where you actually stand

1. Look at your own robots.txt file

Most AI crawlers, including OpenAI’s, are supposed to respect a robots.txt file that blocks them, at least when a site owner has actually configured one to do so. Check whether your site’s file currently blocks known AI crawler user agents, or whether it was never updated past whatever your CMS shipped with by default. A lot of sites are wide open simply because nobody ever touched the setting.

2. Search for your own content inside publicly available training-data trackers

Several independent researchers and outlets have built lookup tools that let a site owner check whether their domain appears in commonly used AI training datasets, including the kind of web-scrape datasets named in this lawsuit’s complaint. Running your own domain through one of these is a five-minute task that at least tells you whether you are asking a hypothetical question or a concrete one.

3. Decide whether blocking or licensing is actually the goal

Blocking every AI crawler outright is not automatically the right call for every publisher. Some are actively negotiating licensing deals instead, trading access for payment rather than trying to keep every crawler out. Figure out which outcome you actually want before you spend time implementing either one. A blogger who depends on search traffic to survive has a very different calculation than one whose income comes mostly from a newsletter or direct sales, since blocking a crawler can carry search-visibility tradeoffs of its own that have nothing to do with AI training specifically.

4. Keep records now, even if you take no other action

Whatever you decide to do about crawling going forward, save dated screenshots or archived copies of your own published work and your site’s historical robots.txt settings. If this legal theory keeps winning, a record of what you published and when, and what you did or did not authorize, is the kind of thing that turns a vague sense of being wronged into something a lawyer could actually work with later.

Final thoughts

I am not a lawyer, and nothing above is a legal strategy, just the plain, practical version of what I would want to know about my own site before deciding whether any of this is worth acting on.

Whatever happens to this particular case, the underlying question, whether the internet’s smaller publishers get paid or just get scraped, is not going away because the newspapers with the resources to sue are the only ones asking it out loud. I would rather know the answer for my own site now than find out the hard way later that I never bothered to look.

The post Arkansas’s own Democrat-Gazette is among nearly 400 local newspapers now suing OpenAI and Microsoft over claims their articles were scraped without permission to train ChatGPT and Copilot, and the case could set the terms for whether smaller blogs and digital publishers ever get compensated when their content trains someone else’s AI. appeared first on The Blog Herald.

On paper, this reads like a studio discovering a promising young filmmaker. What it actually priced was something else: an audience that had already watched the thing once, said so out loud on three different platforms, and would plausibly show up again without a single dollar spent finding them.

What these deals are actually buying

Call it a spec deal, an option, or an overall deal — the label changes, the object being purchased mostly doesn’t. Linden Lane Films, a new venture pairing traditional studio talent with creator partnerships, signed twin creators Alex and Alan Stokes, who bring 137 million YouTube subscribers between their channels, plus fellow creator Ben Azelart’s 48.6 million. Alan Stokes described the appeal as access to people who could “elevate our game and produce content that can garner new audiences worldwide” — audience-first language from a creator, not a studio, which tells you where the leverage actually sits in these conversations. The screenplay, the pitch deck, the three-minute short: all of it is packaging around the one number that gets a deal signed, which is how many people are already subscribed to finding out what happens next.

Why marketing costs make the arithmetic work

Independent film researcher Stephen Follows has tracked what movies actually spend to find an audience once they’re made, and the numbers explain why a pre-built one is worth paying for. “Hundreds of Beavers” spent roughly $135,000 promoting a $150,000 film — a 90% release-to-production ratio. “You, Me & Her” spent $350,000 marketing a $500,000 production. “Columbus” spent $189,032 on P&A, more than a quarter of it on publicists alone. A24’s “Backrooms,” adapted from Kane Parsons’ viral analog-horror YouTube series, cost under $10 million to make and carried a domestic marketing spend in the teen millions — before the film went on to gross more than $390 million worldwide. A creator who arrives with 15 million people already watching has, in effect, pre-paid a bill that regularly runs as high as the production budget itself.

The ceiling nobody’s pricing in yet

This doesn’t scale the way the trend pieces imply. Digiday’s reporting on the creator-deal wave has found that only the top tier of creators keep any ownership stake in what gets made from their work; most, including creators with audiences in the tens of millions, sign into partnerships where the studio holds the rights. The genres that travel are narrow — horror, comedy, true crime, unscripted — and one industry observer put the limit bluntly: a creator known for chick-flick horror content isn’t the person a studio calls when it wants prestige drama. There’s also a saturation problem building underneath the enthusiasm: multiple deals are getting greenlit on audience size alone, with little vetting of whether the underlying material can sustain a ninety-minute runtime it was never built for.

The number worth trusting is a subscriber count that shows up across unrelated platforms for the same piece of content, because that means the same story pulled attention through three different discovery algorithms and three different audiences. Fifteen million views split across YouTube, TikTok, and Instagram for one three-minute short is a harder thing to fake or inflate than a single platform’s follower total. A studio evaluating a creator deal is, whether it says so or not, running the same due diligence a savvy marketer runs on influencer partnerships: not “how many followers,” but “did this specific thing actually travel.”

What this means for anyone building an audience before they have something to sell

Bloggers and newsletter writers chasing a book deal, a sponsorship, or a syndication pickup are being evaluated on the exact same math, even when nobody involved calls it that. The pitch a studio is paying six figures for is not “this is well-written” — Hollywood has an entire industry of well-written unproduced screenplays sitting in drawers to prove that craft alone rarely closes a deal. The pitch that closes is “these specific people already showed up, on their own, more than once, across more than one place I don’t control.” That is a number a blogger can build years before there’s a book to sell, a course to launch, or a brand willing to sponsor a newsletter — and unlike a screenplay, it doesn’t require anyone’s permission to start compounding.

Fifteen million cross-platform views bought a three-minute short a six-figure development deal with its original writer still attached. A marketing budget that regularly matches or exceeds a film’s production cost is the reason that math works: the audience is the expensive part, and a creator who already has one is selling a studio the one line item it can’t easily discount.

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Most of the coverage since then has framed this as a story about platforms, TikTok and Instagram and whichever app comes next, being forced to rewrite how their algorithms treat minors. That framing captures part of the real story, though it leaves out the people who publish into those feeds, not just the companies that run them.

The assumption most publishers are making

The quiet assumption going around blogging and small-media circles is something like this: this is a platform-level compliance problem, so it belongs to Meta and TikTok’s legal teams, not to a publisher who just posts content and hopes it gets seen.

Under that assumption, a blog with a young readership can treat the SAFE for Kids Act as background noise, a story to read about, not a policy to plan around.

Why that assumption does not hold up

The problem with treating this as someone else’s compliance issue is that it ignores how teen readers actually find content in the first place.

A recent Pew Research Center report on young adults and news found that 70 percent say they get political news because they happen to come across it while doing something else, against just 30 percent who go looking for it on purpose. That report covers young adults broadly rather than minors specifically, but it points at the same mechanism the SAFE for Kids Act is built to interrupt: a huge share of younger readers do not search for what they read, a feed hands it to them.

Once a platform defaults an under-18 account into a plain chronological feed instead of a personalized, algorithmically ranked one, the recommendation engine that used to occasionally surface a publisher’s post to a teenager who had never heard of that blog before stops doing that job by default. A publisher’s own website looks exactly the same as it did yesterday. The part that quietly stops pulling its weight is a channel a lot of publishers never had to think about, because it used to work in the background without anyone touching it.

What the rules actually require

The final rules, released by the Governor’s office and the Attorney General’s office together, restrict two specific things for any account a platform believes belongs to someone under 18: algorithmically personalized feeds, which are now off by default unless a parent consents, and app notifications sent between midnight and 6 a.m., which are blocked under the same default.

Both restrictions hinge on a real age-verification system, and that piece is stricter than a simple birthdate field. Platforms have to offer at least one verification method beyond a government ID, run annual accuracy testing on whatever system they use, and keep verification records for ten years while deleting the underlying data itself as soon as it has served its purpose. A parent can still consent to turn algorithmic feeds and overnight notifications back on for their own teenager, which is the release valve that keeps the law from being an outright ban rather than a default setting.

That default-off design is worth noting for a reason beyond New York. A different approach, a flat one-hour daily usage cap for teens in Virginia, got blocked by a federal judge earlier this year on First Amendment grounds. New York’s law works through a default setting a parent can switch back on, rather than a hard limit nobody can opt out of, which strikes me as a meaningfully different legal shape, though no court has actually tested that distinction yet. Whichever design holds up, the practical effect on a publisher’s reach into a teen audience looks much the same either way.

“Our kids’ mental health isn’t for sale,” Governor Hochul said when the final rules were announced. “We promised action and the SAFE for Kids Act is delivering by ensuring that any platform that targets our children with addictive feeds will face legal consequences.” Attorney General James, whose office built the age-verification framework, put the practical side of it more plainly: “These rules set standards for age verification and parental control to ensure tech companies are doing their part to keep kids safe on their platforms.”

What publishers can actually do about it

A traffic source that was never guaranteed to begin with is not much of a reason to panic. It is, though, a good prompt to stop treating algorithmic discovery as the whole strategy.

A newsletter a teen reader already subscribed to still lands in their inbox at 7 a.m. regardless of what their feed looks like. Content built to actually answer a specific search question still gets found by someone typing that question in, whether they are 15 or 50. And a follow button, the kind that surfaces a publisher’s posts in chronological order rather than an algorithm’s, becomes more valuable than it has been in years, precisely because chronological is about to become the default for an entire age group.

I am not going to pretend to have strong feelings about whether this law is good policy for kids specifically. That is a genuinely hard question and a personal one for a lot of families, including mine, and it is not one a single state’s rulebook is going to settle for anyone. What I do know is that any publisher who has been quietly relying on a young readership finding them by accident has almost exactly five months, as of this writing, to build a channel that does not depend on an algorithm doing them a favor.

The post New York’s SAFE Act now blocks algorithmic feeds and overnight notifications for any user a platform believes is under 18, and the rules Governor Hochul’s office finalized this summer could quietly reshape how blogs and digital publishers reach teen readers who discover content through social recommendations rather than search. appeared first on The Blog Herald.

That’s a measurement, taken with electrodes on real scalps, not a metaphor borrowed from nostalgia or writerly superstition, and it points to something a lot of people who learned to write longhand before typing became the default have quietly suspected for years: the two are not the same activity wearing different outfits.

What the hand is doing that the keyboard isn’t

Van der Meer’s 2024 study, run with high-density EEG caps on university students, compared brain activity while writing by hand versus typing on a keyboard. Handwriting activated far more widespread connectivity across brain regions involved in memory and learning. Her explanation is fairly mechanical rather than mystical: “When we write by hand, we use more of our senses than we do when we use a keyboard.” Forming each letter by hand recruits fine motor control, visual tracking, and the memory of the letter’s shape all at once, in a way that pressing a uniform key does not.

The study itself makes a modest claim: a snapshot of brain activity during the act of writing, captured in a lab, with university students, rather than a general verdict that handwriting makes anyone smarter or that typing is somehow inferior as a technology. What it does suggest is that the physical process of forming letters by hand is doing more cognitive work in the moment than most people assume, precisely because it doesn’t feel like work. It feels like nothing, the way a habit you learned as a child usually does.

What the keyboard is actually good at

None of this is an argument for going back to longhand for everything, and treating it that way would ignore what typing is genuinely better at. A keyboard is faster, which matters enormously for anyone drafting long documents, and it makes editing, searching, and sharing effortless in ways a notebook never will. For plenty of people, a keyboard is also simply the more accessible tool: anyone with dysgraphia, arthritis, or a motor condition that makes handwriting slow or painful is using the tool that actually lets them get their thoughts down at all, regardless of what an EEG cap might show in a lab. What follows is really about a narrower question: what a specific kind of slowness happens to be doing for people in the specific context of learning something new.

The honest tradeoff shows up in a well-known 2014 study out of Princeton and UCLA, where students took notes on lectures either by laptop or by hand. Laptop note-takers wrote close to twice as many words as the longhand group, almost entirely because the keyboard let them keep up with the speaker. That speed sounds like a clear advantage, right up until the actual test scores came in.

Where the two roads split

On factual recall, the two groups performed about the same. On conceptual questions, the ones that asked students to apply an idea rather than just repeat it, the laptop group did noticeably worse. Researchers Pam Mueller and Daniel Oppenheimer concluded that “laptop use can negatively affect performance on educational assessments, even — or perhaps especially — when the computer is used for its intended function of easier note taking.” Their theory is that typing is fast enough to transcribe a lecture almost word for word, while handwriting is slow enough to force a choice: you can’t get everything down, so you’re constantly summarizing, translating, and deciding what actually matters as you go. That slowness appears to be doing real work: it’s the part of the process that seems to make you think.

That distinction, between transcribing and translating, is probably the real reason people who grew up writing by hand describe thinking “differently” on paper, rather than just more slowly. A keyboard rewards getting the words down. A pen, moving at its own unhurried pace, keeps asking you to decide what the words should be before you commit to them.

It’s worth being honest that the original 2014 result hasn’t held up cleanly since. A larger 2019 replication attempt by Kayla Morehead and colleagues ran the same basic comparison across two experiments and reported that “performance did not consistently differ between any groups.” A meta-analysis pooling the direct replications still found an edge for longhand, though a modest one compared to the dramatic gap the original study reported. The honest summary is that the theory (typing invites transcription, handwriting forces translation) is more solid than the exact size of the effect, and the effect itself is probably smaller and less consistent than the original headlines made it sound.

Where nostalgia comes in

I type almost everything now, like most people my age, and I’m not about to start drafting articles in a notebook out of principle. But I still keep a running grocery list and a few scattered notes to myself on paper, and a specific kind of thinking only seems to show up for me in that format: slower, more circular, more willing to sit with an unfinished sentence instead of immediately fixing it. I don’t think that’s proof of anything beyond my own habits. It might just be what happens when the tool matches the pace a particular kind of thought needs.

I’ve never believed that older or slower automatically means better. Plenty of things genuinely improve by moving faster, and romanticizing inconvenience for its own sake is its own kind of trap. But van der Meer’s EEG readings and Mueller and Oppenheimer’s test scores both point at the same quieter idea: sometimes the friction was doing something useful, and it’s worth noticing what gets lost before assuming faster is simply better.

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The setup was deliberately spare. Participants were left in an unadorned room, phones and reading material removed, with instructions to just sit and think about anything they liked for a set period — six or fifteen minutes, depending on the specific experiment in the series. Before that period began, they’d been given a taste of a mild electric shock from a device attached to their ankle and asked to rate it; enough of them found it unpleasant enough to say they’d pay real money to avoid a second one. Then they were left alone with a button that would deliver that same shock, and told the choice to press it was entirely theirs.

What the numbers actually showed

Wilson and his co-authors reported that a meaningful share of participants shocked themselves rather than sit with their own thoughts for the full period — roughly two-thirds of the men and about a quarter of the women, with the pooled rate landing close to 43 percent overall. The researchers’ interpretation was direct: for a lot of people, entertaining yourself with nothing but your own mind for a quarter of an hour is hard enough that a jolt of mild pain is, for some, the more attractive option. That’s a strange enough result to spell out clearly what it doesn’t show: nobody in the study was forced to press the button, nothing bad happened if they simply sat still, and the shock was never framed as a way to end the session early. The only thing on offer was a brief jolt of discomfort in exchange for a brief break from their own unstructured thinking.

Why some psychologists think “boredom” is the wrong word

Not everyone accepted that reading. In a commentary published later that year in Frontiers in Psychology, researcher Kieran Fox and colleagues went back to what shockers actually said when asked why they’d done it. Of the 18 people in that particular sample who administered a shock to themselves, 14 described some form of curiosity about the shock itself — what it would feel like, whether it was as bad the second time — as their reason. The rest gave a mix of other reasons. Fox’s team argued that curiosity and escape from an unpleasant state are different psychological processes, and that Wilson’s framing had collapsed the two.

Why Wilson’s team didn’t buy the curiosity explanation

Wilson and colleagues answered Fox’s critique directly, in a reply in the same journal, and didn’t concede much ground. Their central objection: asking someone why they did something after the fact produces a plausible-sounding story, not necessarily an accurate one. They also pointed out that every participant who shocked themselves had already felt the shock and rated it unpleasant enough to pay to avoid — a strange thing to be merely curious about a second time. And the shock data wasn’t their only evidence: across the broader set of studies, somewhere between a third and just over half of participants broke the instructions altogether, getting up, checking a phone, or doing anything other than sitting and thinking, which is difficult to explain as simple curiosity about electricity. More than a decade later, the disagreement between the two readings hasn’t been resolved in either group’s favor — a reminder that a single, clean number rarely survives contact with the people who actually generated it.

What this means for anyone whose job is holding someone’s attention

Bloggers, newsletter writers, and video creators live and die by a version of the same question the shock study raises: how much unstructured, unentertained time will a person actually tolerate before they’ll do almost anything to escape it. A slow-loading page, a paragraph with no hook, a video with a dead ten seconds in the middle — each one is asking a reader or viewer to sit with functionally nothing, and the shock study’s headline number suggests a meaningful share of people would rather do something mildly unpleasant than tolerate that gap. The disagreement over why doesn’t change the practical lesson: dead air is a cost, whatever the psychological label for the discomfort turns out to be. A newsletter that opens with three throat-clearing sentences before it gets to the point is asking readers to sit through their own smaller version of that empty room, and plenty of them will click away rather than wait it out.

The number worth keeping

Eighteen of the forty-two people in that room chose a shock they’d already said they’d pay to avoid over fifteen minutes of unstructured thinking. Whether that’s boredom, curiosity, or something psychologists haven’t yet named precisely enough to agree on, the number itself hasn’t moved in over a decade of arguing about it.

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Since June 9, 2026, that question has a legal answer in New York, and it is not a gray area. If you made the ad and the person in it is not a real human, you tell people. If you did not make it, and you are just running it on your site, you generally do not have to.

What the law actually requires

New York’s new statute grew out of Senate Bill S8420A, sponsored by State Senator Michael Gianaris and signed into law on December 11, 2025. It took effect 180 days later, on June 9, 2026. The operative line requires that an advertiser “shall conspicuously disclose in such advertisement that a synthetic performer is in such advertisement, where such person has actual knowledge,” according to the bill text itself.

“Conspicuously” is doing real work in that sentence. Per ArentFox Schiff’s reading of the law, a disclosure has to be “reasonably visible and comprehensible, not buried in fine print or flashed briefly on the screen.” A label sitting in a wall of terms and conditions, or on screen for a quarter of a second in a video ad, would not clear that bar.

What counts as a “synthetic performer,” exactly

The bill text defines a synthetic performer as a digitally created asset, built with generative artificial intelligence or a software algorithm, made to look like it is a human performer in an audiovisual or visual ad, while not being recognizable as any actual identifiable person. A fully AI-generated brand mascot or spokesmodel fits that definition cleanly. A real actor whose voice was digitally cleaned up, or whose face is simply filtered, is a murkier case, and one that a lot of small marketing teams have not thought through yet.

Per ArentFox Schiff’s breakdown of the penalties, they are civil rather than criminal, and they scale with repetition: $1,000 for a first violation, $5,000 for every one after that. That is not a number that bankrupts a large agency, but for a blogger running their own sponsored campaigns, or a small brand producing its own ads, it adds up fast if the same undisclosed AI spokesperson runs across a dozen posts before anyone notices.

Notice the phrase “actual knowledge” sitting inside that statutory language quoted above. That is a meaningfully lower bar for liability than it first sounds. An advertiser cannot claim ignorance of a synthetic performer it commissioned and then handed off to a production shop without asking questions. If the ad was built to look human and you never checked whether it actually was, a regulator can reasonably ask what you should have known, not just what you happened to know.

Why publishers are treated differently from advertisers

This is the part of the law that actually matters most for anyone running a blog. The statute exempts media outlets and publishers that simply host or publish someone else’s ad, without being involved in creating it, unless they are given written notice of a violation and five days to fix it. In other words, if a brand hands you a banner ad or a sponsored video that already breaks the disclosure rule, you are not automatically liable for running it. You become liable if you know about the problem and do nothing.

The line gets blurrier the moment a blogger stops just hosting an ad and starts producing one. If you are the one generating an AI spokesperson to sell your own affiliate product, writing the script for a synthetic host to read on your own sponsored video, or building a fully AI-generated testimonial for a brand partnership, you are the advertiser under this law, not a neutral publisher. That distinction turns on who actually made the ad, no matter how big or small your audience is.

What about ads that are exempt from all of this

A few categories sit outside the disclosure requirement entirely, per the bill’s own exemptions. Advertisements for expressive works like films, television, video games, and similar media are exempt, along with audio-only ads and cases where AI is used solely to translate a real human performer’s speech into another language rather than to create a fake one. Those carve-outs exist because the law is aimed specifically at ads that could mislead someone into thinking they are watching a real person, not at every piece of AI-assisted content. Using AI to write ad copy, clean up a product photo, or generate background music does not trigger any of this. The trigger is a fake person, presented as a real one, trying to sell something.

So how do you actually know if this applies to you

Three questions cover most of it. Did anyone on your team, or anyone you hired, generate a performer using AI rather than filming a real person? Would a viewer reasonably believe that performer is human if nobody told them otherwise? And is the disclosure you currently use, if you use one at all, sitting somewhere a reader would actually see it, rather than buried in a caption’s last line or a terms page nobody opens? A yes to the first two and a no to the third is exactly the gap this law was written to close.

I am not a lawyer, and this is not legal advice specific to your situation. But before your next AI-generated spokesperson goes live in a New York-facing ad, it is worth sitting with one plain question: did I make this ad, or am I just running it? If the answer is the first one, the disclosure needs to be visible enough that nobody has to squint to find it.

The post New York’s new AI advertising law took effect June 9 and requires a “conspicuous” disclosure any time a synthetic AI performer appears in an ad, with fines of $1,000 for a first violation and $5,000 for each one after that, and while the law spares publishers who merely host the ad, any blog or brand actually producing AI-generated spokespeople for a New York audience is squarely on the hook. appeared first on The Blog Herald.

my daughter announced to the whole apartment before it was properly light out, standing in our doorway in one sock, dragging a stuffed elephant by its trunk like she was booking it for a crime. She was, very obviously, exhausted. She had not yet been informed of this.

She was right about one thing, in her own way: whatever the rest of the day was going to demand of either of us, that particular window hadn’t been claimed by anyone yet. By the time I get her settled and finally sit down with coffee and a notebook, most of what I write is nothing out of this world. A complaint about my own tiredness. Something one of the kids did. A sentence I liked from a book. Calling it processing gives it too much credit. Most mornings it’s closer to just sitting somewhere that’s mine for a few minutes before it isn’t anymore.

The research everyone quotes is about something else entirely

When people talk about the science behind journaling, they’re usually, without realizing it, quoting research on a very different practice. James Pennebaker, the University of Texas at Austin psychologist whose 1986 study started the whole field, had participants write about a specific trauma for four days, fifteen minutes at a time, against a control group writing about something ordinary. He later described the result himself: “students randomly assigned to write about traumas for 4 days, 15 minutes a day, ended up going to the student health center over the next 6 months at about half the rate of students in the control condition.” He also flagged, decades later, that the original study “was horribly underpowered,” which is a useful reminder that a famous finding and a fully settled one aren’t the same thing.

None of that describes what most people mean when they say they journal every morning. Pennebaker’s paradigm was short, structured, and aimed squarely at one unresolved emotional event. A daily habit of writing a few lines about breakfast, a work deadline, or a kid’s new favorite word is a completely different animal, even though both get filed under the same word. I’m not a psychologist, and this isn’t a diagnosis of what’s happening in anyone’s head. It’s just worth noticing that the famous study people cite to justify their notebook habit was never actually testing the habit most people have.

What’s more likely actually happening

My honest guess, based on nothing more scientific than watching myself and several friends do this for years, is that the appeal has less to do with emotional processing and more to do with ownership. The page doesn’t ask anything of you. It doesn’t need you to be a mother, a wife, or whatever your job title happens to be for those few minutes. “Serve an important psychological function of transitioning from personal to professional role” is how Ashley Whillans, a Harvard Business School researcher who studies time and wellbeing, describes what a commute does for a lot of people, regardless of whether the commute itself is pleasant. A notebook first thing in the morning can do the same job in reverse: a small, private hinge between whatever the night was and whatever the day is about to demand.

I should be upfront that this is my own reframe. Neither researcher made this exact claim, but it fits what I notice in myself. The days I skip the notebook aren’t necessarily worse days. They’re just days that started without a boundary, where the first demand of the morning walked straight in and set the tone before I’d had a say in it.

Why morning, specifically

The timing isn’t incidental. Morning is usually the sharpest role change of the day for anyone with kids or a demanding job, the jump from being fully off duty to being fully needed, often inside the same five minutes. A commute used to sit in that gap for a lot of people, giving the brain a stretch of time to switch modes before the first meeting or the first email. Working from home, or simply having a job that starts the second a small person wakes up, deletes that hallway between sleep and responsibility completely. A notebook, even a bad one filled with half-finished sentences, can end up doing the job that hallway used to do, just compressed into whatever ten minutes are actually available.

That’s also probably why the habit tends to collapse the moment life gets busier instead of surviving it, which seems backward if the point were really stress relief. If journaling were mainly about processing hard emotions, the hardest weeks should be when people write the most. In my experience it works the opposite way. The protected window is usually the first thing to go, precisely because nothing about it is required, which says something about how fragile “the one part of the day that’s mine” actually is once real demands show up.

Why it doesn’t need to be about anything

I think this is where a lot of well-meaning journaling advice goes wrong. It treats the blank page like it has to be earned with a real problem, or optimized with prompts, or aimed at a specific outcome like gratitude or clarity. For a lot of people, the entire value is that it doesn’t have to justify itself. Nobody is grading the pages. Nobody else reads them. Compare that to almost every other part of a working parent’s day, where something is nearly always being evaluated, needed, or divided between other people, and a few unaccountable minutes start to register as basic maintenance for whoever has to run the rest of it.

I’ve never been someone who believes balance means splitting your time evenly across every part of life. Some seasons are lopsided by necessity, and this one, with two small kids in the house, genuinely is. What I do think matters is protecting the handful of things that are actually non-negotiable, even when they’re small. A notebook nobody else reads is a strange thing to defend as non-negotiable, but it’s honestly one of mine right now.

None of this is a claim that journaling can’t also be about something heavier. For plenty of people it genuinely is, and if what shows up on the page some mornings turns out to be more than you expected, a therapist is a much better audience for it than a notebook. But it doesn’t have to be heavy to be worth protecting. Sometimes the only remarkable thing about those ten minutes is that they belong to you, and nobody else got a vote.

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Women whose weddings cost $20,000 or more had roughly 1.6 times the divorce hazard of women in the middle bracket, $5,000 to $10,000.

Men who spent under $1,000 had roughly half the divorce hazard of men in that same middle bracket.

Neither fact describes a straight line running from “spent little” to “spent a lot”; together they describe a pattern where the bracket in the middle behaves differently from the brackets on either side, and where the effect doesn’t even move the same way for men and women in the same marriage.

What the actual bracket data shows

Francis-Tan and Mialon published their findings in Economic Inquiry in 2015, under the title “‘A Diamond is Forever’ and Other Fairy Tales.” Using the $5,000-to-$10,000 wedding-cost bracket as the reference point, they found men who spent under $1,000 had a hazard ratio of 0.492, about half the reference group’s risk, and men who spent $1,000 to $5,000 had a smaller, still-lower hazard of 0.782. Men in the $10,000-to-$20,000 bracket landed close to the reference group, at 1.067.

Only the top bracket, $20,000 and up, showed a higher hazard than the middle for men, and even there the increase, to 1.122, was modest. For women, the pattern looked different across the same brackets: 0.697 in the bottom bracket, 0.913 and 0.970 through the middle brackets, close to flat, then a sharp jump at $20,000 and up, to 1.595. The size of that jump, and the fact that it shows up much more strongly for women than men, doesn’t survive translation into “spending more causes more divorce.”

What the engagement ring numbers add to the picture

The same study looked separately at engagement ring spending, using $500 to $2,000 as the reference bracket, and the ring results undercut a simple story even further. Men who spent $2,000 to $4,000 on a ring had a hazard ratio of 1.334, roughly 33 percent higher than the reference group and the largest ring-related effect in the study’s main full-sample model, yet men who spent more than that showed no consistent climb: the $4,000-to-$8,000 bracket (1.193) was still slightly elevated, though not statistically significant, and only the $8,000-and-up bracket (0.884) dropped below the reference group.

Women’s ring-spending results didn’t show a statistically significant effect at any bracket. A relationship that spikes at one specific bracket and then drops back down as spending increases further isn’t a dose-response curve so much as noise with one loud exception, or a bracket boundary that happens to capture something the study wasn’t designed to measure directly, such as financial strain relative to a couple’s actual means rather than the raw dollar figure.

Why the flattened version of this study spread anyway

“Spend more on your wedding, raise your odds of divorce” is a much easier sentence to repeat than “divorce hazard varies by spending bracket in a pattern that isn’t monotonic and differs by gender,” and outlets covering the study’s release didn’t just simplify the finding, some inflated it. PBS NewsHour reported that spending more than $20,000 on the wedding raised the odds of divorce by 3.5 times compared with couples who kept it between $5,000 and $10,000.

The paper’s main full-sample model puts the figure at 1.6 for women. But 3.5 isn’t invented — it’s the paper’s own result for a different, smaller subsample: recently married women, where spending $20,000 or more carries 3.5 times the hazard of the $5,000-to-$10,000 group. PBS’s actual error was reporting that subsample-specific, women-only figure as applying to “couples” of both sexes generally. 

CNN had run a simpler headline months earlier, when the study first circulated in October 2014: “Want a happy marriage? Have a big, cheap wedding.”Francis-Tan and Mialon’s own conclusion is more careful than either: marriage duration, they wrote, is “either not associated or inversely associated” with wedding and ring spending, a statement that rules out a strong positive line running from cost to risk without claiming that every low-budget wedding is safer than every expensive one.

What this means for anyone quoting a study instead of reading it

Bloggers and content creators cite statistics constantly, usually secondhand, and this study is close to a textbook case of what gets lost in that chain, and occasionally invented along the way. The popular version keeps a headline claim, sometimes with a number nobody can find in the original paper, and drops the part of the paper doing the actual analytical work, the breakdown by bracket that shows the relationship isn’t linear, doesn’t apply the same way to both partners, and is driven almost entirely by one bracket at the very top of the range. Repeating “bigger wedding, bigger divorce risk” without checking the brackets, or the arithmetic, is doing exactly what a source that repeats “research shows” without naming the research does: passing along a conclusion that sounds like the study’s finding but isn’t actually the shape of the data underneath it.

What survives contact with the real numbers is narrower and less quotable: very low spending is associated with somewhat lower divorce hazard, very high spending, north of $20,000, is associated with somewhat higher hazard for women specifically, and everything in between looks close to flat. That’s a real finding, backed by a peer-reviewed sample of over 3,000 marriages. It just isn’t the tidy warning about wedding budgets, inflated numbers included, that keeps getting attached to it.

The post Psychology says the “bigger wedding, bigger divorce risk” finding everyone half-remembers isn’t a straight line at all — the original study breaks it into specific spending brackets, and each bracket carries its own distinct risk multiplier, not a simple “spend more, risk more” appeared first on The Blog Herald.

That is the civil penalty New Jersey attached to selling or licensing sensitive personal data without permission, and it applies whether the seller is a total stranger or a company you have quietly renewed a contract with for years. The law says a violator “shall be liable to a civil penalty of $50,000 for each record sold, offered for sale, or licensed,” with no floor on how small the transaction has to be before the fine applies.

I have spent a fair amount of time throughout my career on the buying end of audience data. Email lists, retargeting pixels, lookalike-audience packages built from somebody else’s list. Most of that happens through a vendor’s dashboard, a few clicks, a monthly invoice, no real visibility into where the underlying data came from. New Jersey’s law is aimed at that exact gap.

What actually counts as a “data broker” here

The statute defines a data broker as a person or entity that “knowingly collects or purchases the personal data of a consumer with whom the person or legal entity does not have a direct relationship and sells or licenses that data to a third party.” That covers a lot more of the ad-tech and email-list ecosystem than the term “data broker” usually conjures up. A company you think of as an audience-targeting platform, or a list-rental service, can meet that definition without ever calling itself a broker. According to Wiley Rein’s reading of the law, it carves out no exemption based on how much data a company handles or how many consumers it touches, and skips a consent-based exception too.

“Sensitive data” is defined broadly too. Per the same alert, it covers information revealing racial or ethnic origin, religious beliefs, mental or physical health conditions, certain financial information, sexual orientation, immigration status, transgender or nonbinary status, genetic or biometric data, precise geolocation, and any data collected from a known child. If a list you bought was built from health-adjacent browsing behavior, or segmented by anything touching those categories, it is worth a second look before you use it to target New Jersey readers specifically.

Picture a fairly ordinary setup: a parenting or wellness blogger pays a third-party platform for a “New Jersey moms, ages 28 to 45” audience segment to run a sponsored newsletter placement. The platform built that segment by combining pregnancy-app data, pharmacy loyalty programs, and a few retailers’ purchase histories, none of which the blogger ever saw or asked about. Under the old assumption, the platform’s terms of service quietly absorbed that risk. Under this law, a segment built that way touches health data, reproductive information, and possibly a known child’s data all at once, and the buyer has no real way to know that from the dashboard alone.

The compliance clock is already running

Most of the law’s obligations took effect immediately once it was signed on June 30, 2026, which is part of what makes it unusual. The sale-and-licensing ban itself came with no grace period at all. A separate piece, the requirement that data brokers publicly register with the state, activates 270 days later, landing on March 27, 2027, with an initial registration window running from April 1 through June 30, 2027, according to Wiley’s analysis. So there are effectively two deadlines to track: the ban that already applies, and the registry that will let you actually check who is compliant starting next spring.

Buying a subscriber list once in a while does not put every blogger in legal danger under this law. What has genuinely changed is how much responsibility now sits with the buyer to know where the data actually came from, instead of trusting the seller by default. If how you do anything is how you do everything, this is one of those quiet backend habits worth tightening even when nobody is watching.

A quick check before you target New Jersey readers

None of what follows is legal advice, just the practical questions I would want answered before I trusted a vendor with my own newsletter targeting.

1. Ask your vendor directly whether they are registered

Once the registry opens next spring, this becomes a simple yes-or-no question you can ask any vendor selling audience data that touches New Jersey residents. Until then, ask whether they are tracking the requirement at all. A vendor who has never heard of the law is not automatically doing something wrong, but it is a signal to look closer.

2. Read what kind of data is actually in the list you bought

Segment names like “health-conscious moms” or “recently divorced” sound like marketing copy, but they can map directly onto the sensitive categories the law names. If a list was built around health, financial situation, immigration status, or a child’s data, treat it differently than a generic newsletter signup list.

3. Check whether the seller relies on consent language you have never seen

The law does not include a consent-based exception, so a vendor’s privacy policy promising that “users consented to data sharing” is not, on its own, a shield. Ask to actually see the consent mechanism rather than taking the bullet point at face value.

4. Put the 2027 registry window on your calendar anyway

Even if none of this feels urgent today, the registration window closing June 30, 2027 is the moment this stops being a hypothetical and starts being a public, checkable list. Vendors who are not on it by then will be a lot easier to spot, and a lot harder to justify still working with.

Final thoughts

I am not a lawyer, and nothing here is legal advice. If any of this genuinely applies to how you run your list or your ad targeting, a privacy attorney can look at your actual contracts in twenty minutes in a way that no blog post, including this one, ever really can.

But knowing the four questions above is enough to figure out whether you need that call in the first place.

The post New Jersey’s new data broker law bans the sale of sensitive personal data outright and fines violators up to $50,000 per record, and any blogger or marketer who buys third-party audience lists to target New Jersey readers now needs to check whether their vendor is registered before the state’s compliance deadlines hit. appeared first on The Blog Herald.

Then I looked into what procrastination technically is, and it turns out my assumption might be wrong.

What tidying is and isn’t doing

“Procrastination is an emotion-regulation problem. It’s not a time management problem. It’s about really dealing with our feelings,” says Tim Pychyl, a psychology professor at Carleton University who has spent his career studying why people delay tasks. In his framing, people put off a task because starting it would trigger boredom, anxiety, or self-doubt, and delaying it offers short-term relief from that feeling, even though it makes the underlying problem worse.

That definition matters, because it draws a real line. Genuine procrastination is a way of not being where the discomfort is. Clearing a desk before writing, when it actually ends with you sitting down and writing, functions more like a bridge into the task than an escape from it.

A cluttered desk can also work against you for a more literal, physical reason, one that shows up before you’ve typed a single word. A 2011 study in the Journal of Neuroscience by Princeton researchers Stephanie McMains and Sabine Kastner found that multiple objects in your visual field compete with each other for processing, and the brain has to actively resolve that competition before attention can settle anywhere. As the researchers put it, “multiple stimuli present in the visual field at the same time compete for neural representation by mutually suppressing their evoked activity throughout visual cortex.” The study was done with abstract lab stimuli, not messy desks, so it doesn’t prove tidying makes anyone a better writer. What it does establish is that visual clutter isn’t neutral background. Your brain spends real resources sorting through it before it can focus on anything else, which is a plausible, if unproven, reason a chaotic desk might cost you more than aesthetics.

None of that makes tidying special or mandatory. Plenty of people warm up with a walk, a cup of coffee made slowly, or five minutes of scrolling their phone before they can sit still, and the same emotion-regulation versus transition distinction applies to all of it. Tidying just happens to be the version that shows up for a lot of writers, maybe because a visual reset is cheap, immediate, and doesn’t require leaving the room where the actual work has to happen. I’ve also come to think it matters to me specifically because I already run a house on routines, mostly out of necessity now that both my husband and I work full time with two small kids in it. A desk that resets the same way every day is one less decision competing for attention I don’t have much spare of these days.

How to tell which one you’re doing

The honest test comes right after the tidying is finished. If clearing the desk is followed by opening the document and writing, even three mediocre sentences, that’s a warmup. If clearing the desk somehow expands into reorganizing a bookshelf, answering emails, and reconsidering your entire filing system, the desk was never the actual obstacle. Pychyl’s research points at the same tell: real procrastination tends to keep finding a new task to hide behind, because the goal was never to arrive at the hard one.

Turning it into a warmup on purpose

If the tidying is doing real work for you, the fix isn’t to fight it. It’s to put a container around it so it stays a warmup instead of drifting into its own afternoon.

1. Give it a fixed, small size

Pick one surface, not the whole room. A cleared 18 inches of desk in front of you does the job. The goal is resetting your visual field, not achieving a magazine-worthy office.

2. Set a timer you actually respect

Five minutes, maybe ten. When it goes off, the ritual is over whether or not the desk looks finished. This is the part that keeps a warmup from turning into the thing Pychyl describes, where one task quietly substitutes for another.

3. Do the same small motions every time

Stack the papers, wipe the surface, open the document. Repetition turns tidying into a cue instead of a fresh decision you have to talk yourself into each morning. Your brain starts treating the ritual as the doorway into the work itself.

4. Let the ritual end where the work begins

The moment the last object is out of your visual field, move your hands to the keyboard before your brain has time to invent a fifth task. This is the actual hinge between warmup and avoidance.

Final thoughts

My own version of this got a lot less precious once I had two kids under two. These days the “ritual” is often just shoving a bottle and a stray sock off the table before I open my laptop, and it takes ninety seconds instead of ten minutes. What hasn’t changed is the principle behind it, which lines up with something I already believe about most of my work: a giant, undefined task is what makes people freeze, while a small, specific, checkable one is what actually gets started. Clearing 18 inches of desk is a small, checkable task. Writing an entire article is not, until you’ve broken your way into it.

None of this means every messy desk is secretly a productivity hack, or that a person who never tidies before writing is doing it wrong. Plenty of writers work fine surrounded by chaos, and plenty of tidying really is just procrastination wearing a nicer outfit.

What actually separates the two is whether the ritual comes with a built-in exit, one that reliably ends in the work getting started rather than in a fresh reason to wait.

The post Writers who can’t start until the desk is clear may not be procrastinating — sometimes the tidying is the warmup the brain actually needs appeared first on The Blog Herald.

What actually happened in the 1977 negotiation

The popular version holds that a shortsighted 20th Century Fox let Lucas keep the merchandising rights to Star Wars as a throwaway concession, on the theory that nobody in 1977 believed toys based on a movie could make real money. Tom Pollock, who was Lucas’s entertainment attorney at the time and negotiated the actual contract, told Deadline in 2015 that this isn’t what happened. In the original deal, Lucas took a reduced fee, $50,000 each to write, produce, and direct, and kept the sequel rights in exchange. Merchandising wasn’t part of that trade. Fox held the merchandising rights to the first film and, in Pollock’s words, “did very well” with them in the year or two after release.

What actually changed by the time of the second film

Lucas won the merchandising rights back separately, during negotiations for The Empire Strikes Back, and only because he had leverage he hadn’t had the first time: Star Wars had become the highest-grossing film ever made, and Lucas proposed to self-finance the sequel entirely through Lucasfilm rather than take Fox’s money. The deal he and Pollock offered Fox traded seven years of theatrical and video distribution rights for everything else, merchandising, soundtrack albums, music publishing, and television rights included. Fox agreed, according to Pollock, because “they wanted the sequel,” and Lucas was under no obligation to bring it to them at all. Merchandising wasn’t handed over as a hedge against a movie nobody believed in; it was taken back deliberately, once the first film had already proven itself and Fox had more to lose by refusing than Lucas did.

Why the revenue figure is harder to pin down than the deal itself

The dollar amounts attached to “Star Wars merchandising” vary enormously depending on the source, and that variance says something on its own. A widely repeated projection that Star Wars merchandise would generate $5 billion in a single year traces back to one 2015 estimate from Morgan Stanley analyst Benjamin Swinburne, a figure Entertainment Strategy Guy later documented being repeated across outlets for years with no new data behind it, even as Hasbro’s “partner brands” segment, which bundles Star Wars together with Frozen and Marvel, reported a 21 percent sales decline in its fourth-quarter 2017 results — a drop the company itself attributed primarily to Star Wars. Separately, a frequently cited $56.6 billion figure is often misattributed to Star Wars merchandise specifically, when it’s actually License Global’s tally of the Walt Disney Company’s total licensed-merchandise revenue across every Disney-owned property in 2016, Marvel, Pixar, and Disney princesses included, not Star Wars alone. Disney doesn’t break out Star Wars-specific merchandise revenue in its public financial filings, which means every circulating total, including the $29 billion License Global estimate, is a trade-industry approximation rather than an audited figure.

What holds up even with that uncertainty

That uncertainty doesn’t change the basic order of magnitude. Even License Global’s more conservative $29 billion estimate is close to three times the franchise’s $10.7 billion box office total, and the box office number is unusually solid by comparison, since ticket sales are tracked and reported film by film. The interesting finding isn’t that merchandising outearned the movies. Almost everyone already assumes that. It’s that the specific number people cite for how much, and the specific story people tell about how Lucas got the rights to it, have both calcified into repeated fact through sheer repetition rather than anyone checking the original sourcing.

The distinction Pollock describes, between a right handed over as an afterthought and a right taken back once leverage exists, maps onto a decision independent writers and creators eventually face: whether to keep publishing entirely on someone else’s platform under someone else’s terms, or to hold onto the parts of the business, an email list, a paid subscription base, a direct relationship with readers, that don’t depend on a platform’s continued goodwill. Lucas didn’t get Star Wars’ most valuable long-term asset as a consolation prize. He got it by building independent leverage, one successful, self-financed film, until the platform needed him more than he needed the platform, and negotiating from there.

The number that was actually decided decades ago

Whichever total figure eventually gets properly audited, if one ever does, the box office comparison was settled a long time ago: merchandising overtook ticket sales for this franchise well before Disney bought Lucasfilm in 2012, let alone before the sequel trilogy arrived.

What took much longer to sort out publicly is the far less repeated fact that Lucas earned that revenue stream by negotiating twice, not by getting lucky once.

The post Star Wars merchandising revenue passed the franchise’s total box office decades ago — but Lucas didn’t get those rights as a 1977 consolation prize, he won them back during the Empire Strikes Back negotiations, when Fox needed him more than he needed Fox appeared first on The Blog Herald.

Her name is Carrie Forrest. She runs a site called Clean Eating Kitchen, and until recently, it was a genuine success story of the kind the early food-blogging internet promised and rarely delivered: a single person, a decade and a half of unglamorous consistency, and a business built entirely on people typing questions into Google.

The blog that grew for fifteen years on the strength of very small questions

Forrest started blogging in 2009, documenting the recipes and habits behind her own health, and kept doing it long enough that documenting her health journey quietly turned into a career. By 2022, Google’s own case study on her site was using her as an example of what a small, independent operation could earn through advertising alone, and by her account in her Food Blogger Pro interview, the site “went from, I don’t know, a few hundred thousand page views and up to about a million page views a month.” A million monthly pageviews is not viral-hit territory. It’s the much less glamorous outcome of writing thousands of specific, useful posts and having Google send people to them, reliably, for years.

That reliability is the part that’s gone. Forrest now puts her traffic at somewhere between 100,000 and 200,000 monthly pageviews, an 80 percent drop she traces almost entirely to one thing.

How to cut a banana was never supposed to be load-bearing

The posts that used to bring in the steadiest traffic on Clean Eating Kitchen were not the ambitious ones. They were the small, almost embarrassingly simple ones: how to freeze sweet potatoes, how to boil an egg, how to cut a banana. Content like that ranks fast, gets searched constantly, and used to be one of the easiest ways for a new or growing blog to build an audience, because the competition for a keyword that small was thin and the intent was crystal clear. Forrest built a meaningful share of her early growth on exactly that logic. In her own words, “I was so keyword focused, they were very kind of simple terms like that.”

Those are also, it turns out, the first questions an AI system can answer with total confidence and zero risk. Nobody needs a nuanced, sourced, multi-paragraph take on banana-cutting technique. They need three steps and a photo, which is precisely the shape of thing a language model can generate from a search index without sending anyone anywhere. “Every single one of those now is answered by an AI overview,” Forrest says of her simple how-to content. The traffic didn’t get redistributed to a competitor. It just stopped needing a destination at all.

She’s the specific case, not the exception

It would be a cleaner story if Forrest had simply built her business on the wrong kind of content. In practice, she’d built it on exactly what the entire industry was told, correctly, to build for a decade. Other food writers are describing the same year in different numbers. Eb Gargano, who runs the UK site Easy Peasy Foodie, told Fortune that her turkey-recipe traffic was down 40 percent year over year. The same AI Overviews, she said, can also be dangerously wrong.

Describing an AI-generated version of her own Christmas cake, she didn’t mince words: “You’d end up with charcoal!” Adam Gallagher of Inspired Taste told Fortune that click-through rates on his cocktail queries specifically dropped 30 percent once AI Overviews started serving up what he calls “Frankenstein AI recipes” – ingredients and steps stitched together from several sites at once and presented as one.

It worked for a while, and now it’s not.

That’s Forrest’s own summary of the last two years, and it’s a strange kind of sentence to have to say about a job you built from nothing. Not bitter, exactly. Just accurate, in the way people get accurate once they’ve stopped arguing with a fact and started living inside it.

What she’s doing with the years she has left of this

The part of Forrest’s interview I keep coming back to isn’t the traffic number. It’s what she’s decided not to do about it. She isn’t suing anyone, and she isn’t writing more content faster in the hope of outrunning the algorithm. She’s leaning on the email list she started building back in 2014, long before anyone treated an inbox as a hedge against a search engine, and she’s putting real effort into video and YouTube, formats an AI overview can summarize but can’t actually replace. She’s also, by her own account, tried to sell her audience workshops, ebooks, and a Substack, and mostly been told no. People came to her for a recipe, not a relationship with a paid product, and that distinction turned out to matter more than any content calendar.

What she’s landed on instead is less measurable and, I think, more honest: content built around transformation and human connection. A search engine has no interest in summarizing a relationship. There’s no clean paragraph to lift out of trust built over a decade, no bullet point that captures why someone keeps coming back to the same person’s recipes. She sounds, in the interview, less like someone who solved a problem and more like someone who’s stopped waiting for the old numbers to come back. “I’m feeling more creative than I was,” she says. “I’m back in touch.”

I think about my own habits again here, the questions I no longer bother clicking through on, and I notice the shape of what got lost isn’t really information. The banana still gets cut correctly. What disappeared is the fifteen years of a specific person’s attention that used to sit underneath the answer, the trial and error, the version that didn’t work, the small human fact that someone tested this enough times to be sure.

An AI overview can tell you what to do. It has never once told you who figured it out, or what it cost them to keep figuring things out long after the internet stopped sending anyone to say thank you.

The post One food blogger watched her traffic fall from close to a million monthly pageviews to under 200,000 after Google’s AI Overviews started answering exactly the questions her posts were built to rank for, down to “how to cut a banana” appeared first on The Blog Herald.

Screens, sweets, all of it. I grew up with some of both and turned out fine, and I say that as someone who fully expects to eat those words in about a decade. Which is exactly why Florida’s social media law for minors caught my attention. Unlike a family’s own screen-time rules, this one plays out as a live legal fight with an actual outcome, decided by judges rather than dinner-table debate, and the outcome just shifted in a way that changes what is actually enforceable right now, not just what lawmakers intended when they wrote it.

What Florida’s law actually does

Florida’s HB 3 bars anyone under 14 from holding a social media account at all, and requires parental consent for accounts held by 14 and 15 year olds.

The law is aimed specifically at platforms built around features like infinite scroll and autoplay video, the design choices lawmakers argue are engineered to keep young users scrolling past the point they intended to stop. Violations carry fines of up to $50,000 apiece. The law does not rely on parents or users to flag a problem after the fact. It puts the burden on the platform itself to know, or to have had every reasonable chance to know, that an account holder falls under the age restriction, which is part of why the age-verification question keeps surfacing in every court fight over the law.

The legal fight so far

NetChoice and the Computer and Communications Industry Association sued to block the law on First Amendment grounds, and initially won a preliminary injunction that kept it from taking effect.

That changed on November 25, 2025, when a divided panel of the 11th Circuit Court of Appeals lifted that injunction in a 2-1 ruling, clearing the way for Florida to start enforcing the law while the underlying case continues. The majority found that HB 3’s restrictions “likely satisfy the intermediate scrutiny test for content-neutral regulations, so the Attorney General has made a strong showing he is likely to succeed on the merits.” Judge Robin Rosenbaum dissented, warning that verifying which users are under 14 effectively requires verifying the age of every user, adults included, which raises its own privacy and speech concerns.

The fight is not over. The same appeals court heard full oral arguments on the merits on March 10, 2026, and the industry side has not backed down. NetChoice attorney Erin Murphy told the panel plainly, “This law violates the First Amendment.” Florida Attorney General James Uthmeier has been just as blunt in the other direction, posting that “the time for negotiations is over.” No ruling on the merits has come down yet, which means the law is currently enforceable, but the deeper constitutional question is still technically open.

The core legal argument on both sides has not really moved since the injunction was lifted. NetChoice’s position is that age-gating an entire category of speech, even for minors, still has to survive a demanding First Amendment standard, while Florida’s position is that regulating a product design feature like an infinite scroll is closer to regulating conduct than regulating speech itself, and should be judged by an easier standard. Which of those framings a court accepts changes almost everything about whether the law ultimately survives.

Where I land on this, and where I genuinely do not

I am not going to pretend I have a tidy answer here, because I do not think one exists yet. The instinct behind the law is not hard for me to understand.

An algorithm engineered to keep a 12 year old scrolling past bedtime is a different animal than a bag of candy on a counter, and treating every form of “protect kids from a thing” as the same overreach flattens a real distinction.

At the same time, Judge Rosenbaum’s dissent names something that genuinely unsettles me: a law that has to verify everyone’s age to protect a subset of users is quietly changing what it costs, in privacy terms, for an adult to just use the internet. I do not think both of those things can be fully true and the policy question still be simple, and I am genuinely suspicious of my own certainty on either side of it, since my own kids are still years away from making this anything but theoretical for our family.

What it means for anyone whose feed reaches a Florida teenager

None of this is legal advice, and I am not the person to tell any platform, blog, or app how to interpret its own exposure under a law that is still being litigated. But the practical shape of the risk is worth naming plainly.

As of right now, Florida can enforce HB 3. Any product whose feed, notifications, or account-creation flow reaches a Florida user under 16 is operating under a live law, not a paused one, and the fact that the constitutional question is unsettled at the appellate level does not mean enforcement is paused too.

A publisher or platform in that position is one adverse ruling, or one enforcement action taken now while the law stands, away from a very different conversation with a lawyer than the one they might be having today. Waiting for the 11th Circuit to settle the constitutional question before taking the law seriously is a bet, not a strategy, and it is a bet against a court that has sided with Florida once already.

The post Florida’s ban on social media accounts for anyone under 14 is now moving toward enforcement after challengers lost their court fight and an appeals court cleared the way, and even as industry groups keep filing new motions, any platform, blog, or app whose feed reaches a Florida teenager is one ruling away from facing the state’s fines directly. appeared first on The Blog Herald.