There are certain kinds of companies that everyone has heard of, that everyone has an opinion about, yet almost no one has actually studied them in depth. Reddit might be the most recent, purest example of this.
Say the name at a dinner party, and you'll get a knowing smirk, a GameStop joke, maybe a comment about the weird corners of the internet. Say it to a value investor and watch them wince at “high price.” Say it to a growth investor and they'll mutter something about Google killing the traffic.
Everybody knows Reddit. Almost nobody has bothered to actually look under the hood, because the reputation does the thinking for them, and the reputation says meme stock, too expensive, too strange, move along.
Psychologists call this the availability heuristic – in investing, a mental shortcut where people judge a business based on whatever vivid stories, recent headlines, or cultural stereotypes easily come to mind, rather than doing the hard work of analyzing the actual data and qualitative insights.
It takes deliberate cognitive effort to look past the noisy, available anecdotes and evaluate a company on its cold, hard fundamentals, so most people simply take the path of least resistance and let the popular consensus do the thinking for them.
I was, at first, shrugging off Reddit too. Then I looked, and what I found was so far from the caricature that I plan to share my fingins and thoughts in a deep dive series on this fascinating company.
Let me show you what changed my mind, starting with the most recent quarter, because it captures the whole paradox in a single afternoon of trading.
Reddit reported earnings on July 30, 2026, and here’s what happened. Revenue grew 61% year over year to $805 million (beating the $730 million estimate), the eighth straight quarter above 60%.
Earnings per share came in at $1.25 against expectations closer to $0.95. Next quarter’s guidance sailed past what analysts were modeling. Net income more than doubled. Free cash flow landed at $261 million. By almost any measure, it was a blowout, the kind of print a growth investor daydreams about.
The stock fell 21%.
A company beat on revenue, beat on earnings, beat on guidance, doubled its profit, and the market took a fifth of its value off in a session.
What spooked everyone wasn’t the money. It was a single sequential number: U.S. daily active users ticked down from 53.5 million to 53.2 million, and management described its search referral traffic as choppy and hard to forecast, particularly late in the quarter.
That’s it.
A rounding-error dip in domestic users, blamed on volatility in how Google and AI Overviews funnel people to the site, was enough to erase a quarter that was otherwise close to flawless.
Pull back and the pattern is even starker. As I write this, Reddit sits more than 44% below its peak, and the drawdown chart looks less like a stock and more like a seismograph.
This is a name that has fallen 50-plus percent from a high, recovered, and done it again, more than once, inside two years of being public.
Again, as alluded to above, my honest starting point, and I suspect it’s yours too, was a shrug.
Reddit? The GameStop forum? The meme-stock poster child trading at some absurd multiple?
I’m a value-leaning investor by temperament, no great Reddit user myself, and every reflex I’ve built over the years told me to file this in the “too hard, too hot, too expensive” drawer and move on.
Die-hard value types laugh at the premium multiple. Growth investors have half-convinced themselves that Google has quietly put a lid on the whole story. It seems neither camp seems to actually want the stock.
And that, more than anything, is what made me look closer.
When a genuinely high-quality business gets orphaned by both tribes at once, and then hands you a 44% drawdown on top, my curiosity tends to override my reflexes.
Moreover, Advertising businesses, and digital ones especially, are supposed to be right up my alley. I owed it a proper look before dismissing it.
What I found is a business that is far, far better than its reputation, and a valuation story that is a lot more subtle than the headline multiples suggest.
Because here’s the thing the “it trades at 35x earnings” crowd misses: Reddit only just switched the monetization on.
This is a 20-year-old platform that spent almost its entire life not really trying to make money, turned profitable for the first time in late 2024, and is now sitting on levers it has barely touched. It runs a 91% gross margin business.
91%!
It’s the seventh most visited website on earth, built almost entirely on content its users generate for free and moderated for free by tens of thousands of volunteers, which is the same reason its economics resemble YouTube’s more than any traditional media company’s.
Out of 300-plus public tech companies, it’s arguably the only one combining 60%-plus revenue growth, 90%-plus gross margins, and real free cash flow with essentially no capital intensity. Reddit itself hence refers to it as a one of a kind model.
Trailing multiples on a business whose earnings power is still mostly ahead of it will lie to you.
That’s one of the central puzzles this series is going to work through.
There’s another reason I got interested … Reddit has in a way become the internet’s repository of ground truth. Siyu Li, an investor I respect for his analytical rigor and the kind of names he gravitates toward, put it better than I could (see tweet below), and he too seems to have taken an interest around this drawdown. He described being at Lollapalooza in Chicago and wanting to know which sets people actually loved. Where do you go for that? Reddit!
Not a magazine, not an AI summary, not a Google blue link. A thread of real humans saying what they really thought, in real time. As Siyu put it, Reddit often holds the ground truth to people’s real-time opinion on sports, music, restaurants, everything, and increasingly everywhere globally, and there isn’t even a close second competitor.
He floated an analogy too: that this unique position could earn Reddit serious bargaining power, something like Airbnb’s relationship to Google, or WeChat’s to Apple. People predict the future by pattern-matching to the past, he noted, and in this case Reddit might just be the exception. That’s roughly where I’ve landed too. As the open web fills with synthetic AI slop, the one thing a language model can’t fake is what it’s actually like to have done the thing, and Reddit is where that lived experience is shared, expressed, and discussed.
It’s now the single most-cited domain by AI models across the entire internet.
“In fact, 80% of users in a recent survey [said] that they believe some questions can only be answered by humans as opposed to AI-generated summaries. For LLM and AI search engines, these conversations and the knowledge they create are essential for training. Platforms like Reddit where people discuss every aspect of life from the trivial to the transformative of a backbone of building AI that actually works. That's why Reddit is the #1 most cited domain for AI across all models per data collected by Profound. In an automated world that depends on human knowledge, we view Reddit as one of the most important and differentiated data sources.“ - Call Transcript
Management likes to say there’s no artificial intelligence without actual intelligence, and however self-serving that sounds, no major LLM has been built without training heavily on Reddit’s 26 billion posts and comments.
Every month, its communities generate the equivalent of all of Wikipedia in new material.
Enough for the intro. I will presumably split this analysis into four parts.
First, the heart of the bull case, the five pillars of the investment hypothesis, delivered in the “Bam Bam Bam Bam Bam” style I borrow from Bill Miller (I’m aiming for about 5,000-8,000 words; call me out in the comments below this post if I failed; update: this piece ended up with 15,000 words of valuable insights (sorry 😉)).
Second, a comprehensive walk-through of the business, how Reddit actually works and makes money, unit economics, etc., etc.
Third, valuation, where I’ll try to make sense of those multiples and put a number on it.
Fourth, the entire analysis distilled into a visual slide deck for those who’d rather see it than read it.
Let’s get into it; this will be fun, I promise.
What this deep dive series covers:
The five-part bull case (”Bam Bam Bam Bam Bam”)
What went wrong
Investment Slide Deck – the deep dive in a highly compressed + visualized form
Every deep dive now comes with a companion slide deck. It’s the whole argument in compressed form – the hypothesis, the business, the competitive position, the valuation, and the case against – for the days when you don’t have an hour to spare but still want the shape of the thing. Paid subscribers get both, the long piece and the deck, on every deep dive from here on.
The origin story
The business itself
Unit economics analysis
The customer
Legal structure, cyclicality, and operating leverage
The moat
Is it a good business in a good industry
Management and governance
Growth drivers and forecasting
Margins outlook
Valuation (including a downloadable model)
Other interesting findings
Disclaimer:
As of the date of publication the author owns no shares in the company; but that may change. The analysis presented in this blog may be flawed and/or critical information may have been overlooked. The content provided should be considered an educational resource and should not be construed as individualized investment advice, nor as a recommendation to buy or sell specific securities. I may own some of the securities discussed. The stocks, funds, and assets discussed are examples only and may not be appropriate for your individual circumstances. It is the responsibility of the reader to do their own due diligence before investing in any index fund, ETF, asset, or stock mentioned or before making any sell decisions. Also double-check if the comments made are accurate. You should always consult with a financial advisor before purchasing a specific stock and making decisions regarding your portfolio.
The Bill Miller-Style “Bam Bam Bam Bam Bam”-Hypothesis
As always, I will start with Bill Miller who once made a point about pitching stocks that has stuck with me ever since I first heard it, and it shapes how I approach every write-up on this blog. Portfolio managers, he explained, have ultra-short attention spans. Miller’s advice for what to say in that window was refreshingly blunt. You walk in and you say something like, “I want to talk to you about Homestore. It’s at $2.25. The 52-week range is $2 to $4 and the all-time high was $100 back in 2000. I think it’s a buy for five reasons: one, bam; two, bam; three, bam; four, bam; five, bam. The stock trades at $2 and change. I think it’s worth $6 or $8. Here’s why. And here are the risks.”
That’s the spirit I want to bring to Reddit.
For Reddit (Ticker: RDDT 0.00%↑), the pitch centers on a company that has spent 20 years building a singular “city” of human knowledge and is now, for the first time, turning on the monetization engines. Reddit sits at a historic inflection point in its business model, where two decades of accumulated human data is finally meeting a sophisticated ad-tech stack and a high-margin licensing market. You should care because Reddit is a “one-of-one” business. It pairs 60%-plus revenue growth with 90%-plus gross margins and inflecting free cash flow, and yet the market stays skeptical about whether its user base growth is durable over the long haul.
Right now the market treats Reddit as a risky social media play, or as a platform dangerously hooked on Google traffic that AI will eventually cannibalize. What that view misses is that Reddit is a utility for human perspective, and it becomes more scarce and more valuable precisely as the rest of the web fills up with synthetic AI slop.
If Reddit can fold its conversational data into its own search product while continuing to close the ARPU gap with its peers, it graduates from meme-stock territory into something closer to a foundational internet utility with defensive, recurring cash flows.
Also, I’m deliberately calling this an investment hypothesis rather than a thesis. As my regular readers will know, a thesis tends to be a statement of belief, and belief has a way of nudging investors toward information that validates the view they already hold. A hypothesis is different in that it’s more of a proposition you actively try to falsify. That’s the attitude I want to adopt throughout this piece.
Bam #1: Data is “oil” of the AI era & Reddit is sitting on the ultimate AI oil well
If you want to understand why Reddit may be interesting right now, start with what it actually owns: The company sits on the internet’s largest archive of authentic, human-to-human conversation, and that archive has become foundational raw material for training nearly every major large language model on earth.
“Reddit is the most trusted source of authentic human knowledge, built for people and powered by real human perspectives“ - 2026 Q2 letter
Where most social platforms live off high-velocity scrolling (aka doomscrolling with the compulsive consumption of often negative or emotionally charged content) and interruptive ads – the precise ad load on Instagram of course varies by individual user, but across the main placements (Feed, Stories, and Reels) the average user sees one ad for every 3 to 5 organic posts (god, I hate this experience) –, Reddit spent two decades accumulating something different: a structured record of human experience that AI developers now can’t build without (“Reddit’s content is in demand, and it’s not commodity content“ - call comment).
And for the first time, Reddit is charging for access.
Let me start with scale, because the numbers here are genuinely hard to wrap your head around:
As of early 2026, Reddit’s corpus runs to more than 26 billion posts and comments.
Every month, Reddit’s 100,000+ active communities generate the equivalent of Wikipedia’s entire content library in new, human-written information.
That’s not a static dataset gathering dust. It’s a constantly regenerating feed of how people actually talk, argue, recommend, and reconsider.
LLM developers reach for that data at every layer of the AI stack.
They use it in pre-training to build the initial world model.
They use it in post-training to teach models how to speak like an ordinary human rather than a corporate press release.
They use it for grounding, so that answers reflect what real people think and experience rather than what a model hallucinates.
And they use it as a live search index, pulling up-to-the-minute information on sports, news, and fast-moving trends.
Four distinct jobs, one source.
“And so Reddit is used in pretraining, right, create the whole model. It’s used in post-training, like teach the model how to speak like a normal person. It’s used in grounding, like what do people actually think. And then on top of that, these models are running on a live search index of like what’s going on, on Reddit. So it’s essential for the entire stack.“ - Call Transcript
This is where management’s favorite line comes in, and I think it’s more than a slogan:
“There is no artificial intelligence without actual intelligence”
…, they argue, and the actual intelligence is sourced from Reddit.
The logic holds up when you look at where the open web is heading. As more of it fills with sanitized, synthesized, bot-generated filler – the stuff people have started calling “AI slop” – authentic human perspective grows more scarce and, by simple economics, more valuable.
Reddit is currently the single most cited domain on the entire internet across all AI models.
Think about that for a second! When an AI hands you a recommendation or a summary, it’s more likely to be drawing from a Reddit thread than from any other source on the web.
“I think one of the dynamics we’re seeing in the modern Internet is the more it becomes sanitized and summarized and optimized for attention by AI, the more that people crave the human, the human information that’s both AI that crave it and also the Internet consumer or people in general that crave it. And that’s our business … those human connection and conversations.“ - Call Transcript
There’s a reason for that. For a whole category of questions – which bike helmet should I buy, how do I deal with a difficult kid, is this movie worth watching in cinema – there is no clean objective answer. People want the messy, contradictory, honest spread of viewpoints, shared by actual humans, that you only get from a real discussion, and so, increasingly, do the models trained to answer on their behalf.
“So both AIs and Internet consumers love Reddit content. This is because that basically human verification of what AI is telling people is really important. At the end of the day, you can get a surface level answer from AI, but you need the context. For many questions, there isn’t an answer. There are multiple perspectives describing that answer and multiple reasons why different parts of that answer might be relevant to you or not. For example, take a simple question. What movie should I watch tonight?“ - Call Transcript
Recently, Reddit has flipped this asset from a free public API into a high-margin, recurring revenue business (contributing around 5-6% of revenue in recent quarters), reported inside the “other revenue” line. That line grew from $15.2 million in 2023 to $140 million in 2025 ($153.5 million over the LTM).
“Other Revenue: In our content licensing arrangements, we provide customers with the right to access content from our platform over the contractual period. The transaction price in content licensing arrangements is generally a fixed fee or usage-based fee. We recognize content licensing revenue as our content partners consume and benefit from their use of the licensed content, which is generally ratably over the license period. Revenue from products sold directly to users, including Reddit Premium and Reddit Gold, was not material for the periods presented.“ - 10-K
For context on the underlying scale, the licensed archive exceeds two billion posts and 22 billion comments, and importantly, it also refreshes constantly rather than aging out. The anchor partnerships are with Google and OpenAI, structured as deep, multi-year deals spanning model training, post-training, and search grounding.
Context on the deals:
In February 2024, Reddit signed an AI licensing deal with Google worth approximately $60 million annually. The agreement grants Google real-time access to Reddit’s Data API, allowing it to train its Gemini AI models on vast streams of human-generated conversational data. Beyond AI training, the deal deepened their cloud infrastructure collaboration via Google’s Vertex AI and improved how Reddit content is organized and displayed directly within Google Search results.
In May 2024, OpenAI struck a similar licensing and technology deal with Reddit, giving ChatGPT real-time access to Reddit posts and discussions via the Data API. This allows OpenAI to incorporate fresh user conversations into its models and directly showcase Reddit content to ChatGPT users. In return, OpenAI became a Reddit advertising partner and provided Reddit with access to its AI models to build enhanced user and moderator tools, such as automated thread summarization and moderation assistance.
Beyond the marquee names, Reddit has pushed into verticals. In 2024, it partnered with Intercontinental Exchange to build data products for the financial industry, mining real-time sentiment from communities like r/WallStreetBets to feed insights to traders.
It also runs agreements with social-listening and enterprise firms like Meltwater, Cision, and Sprinklr. The marketplace is broadening, not narrowing.
“We continue to address the data licensing opportunity and are in contact with potential partners In Q3, we entered into a new partnership with Meltwater, a media and social intelligence company Meltwater accesses Reddit’s content through our data API, which allows their customers to uncover brand insights, monitor industry trends, and tap into the discussions happening on the platform“ - 2024 Q3 letter to shareholders
What makes this a genuinely attractive business, rather than just a novel one, is the economics. The data already exists on the platform. Reddit isn’t manufacturing anything incremental to license it, so the marginal margin is close to pristine, and this line is a meaningful contributor to the company’s 90%-plus gross margins.
Then there’s the pricing, which is where it gets a little wild. According to expert-network interviews (I’ve read about this second-hand so best to treat this data point with some caution), standard API data might run around $0.24 per 1,000 calls, while Reddit’s licensing deals reportedly command a 50x to 500x markup. That premium isn’t really about the raw bytes. The argument is that Reddit isn’t only selling data – it’s selling legal immunity, an exclusive and litigation-friendly path to the world’s largest public archive of human conversation, organized and delivered through a clean API.
In a world where scraping is increasingly contested in court, a signed license has real value on its own.
The pricing model itself looks poised to evolve, and this is worth watching closely. Early deals leaned on flat fees (see added context on the OpenAI and Google deal above). Reddit is now signaling a shift toward usage-based, metered pricing, which would tie revenue to how much data models actually draw and add a variable kicker linked to how often Reddit content gets synthesized into products like Google’s AI Overviews.
Google Deal: Reached its initial expiration/renegotiation window in mid-2026. Discussions around renewing or extending the terms are currently ongoing, with reports indicating Reddit executives are pushing for usage-based pricing models rather than flat annual fees.
OpenAI Deal: Reaches its initial renewal window later in 2026. Because it was signed shortly after Google’s deal, renegotiations for its next multi-year phase follow a similar timeline.
If that transition materializes, revenue stops being a fixed high-margin annual check and starts scaling with the actual usage of Reddit’s intelligence across the AI ecosystem. Broadly speaking, that’s a better place to be in.
None of this comes without a fight, and the value of the asset is exactly what invites the trouble. Reddit has had to lean hard into what you might call API defense, blocking crawlers and search engines that won’t be transparent about how they use platform content, and it has commenced litigation against entities that built LLMs on Reddit data without a license.
“In terms of third-party search, the ecosystem is evolving with search, summarization, and training blending. We are seeking the right balance between openness and protecting our users and platform. Our partnerships with Google and OpenAI illustrate how commercial agreements aligned with our content policies can be mutually beneficial. They help people discover communities on Reddit while safeguarding our users’ information. We’ve restricted access where transparency is lacking in how Reddit content is utilized. The internet and search benefit from Reddit’s content, and we are open to finding solutions that serve our users, Reddit, and the broader internet community.“ - 2024 Q2 letter
There’s a regulatory dimension too. In March 2024, the FTC opened a non-public inquiry into Reddit’s sale and licensing of user-generated content for AI training – a reminder that this business operates on genuinely new legal terrain, where the rules are still being written.
“In addition, we are in the early stages of our content licensing efforts and are exploring content licensing opportunities where we believe the opportunity does not conflict with our values and the rights of Redditors. These programs may subject us to evolving approaches to the regulation of this data and implicate complex and developing data privacy and data protection, misappropriation, and intellectual property laws, rules, and regulations. Given the novel nature of these technologies and commercial arrangements, we have received and expect to continue to receive inquiries regarding our content licensing efforts from regulators. For example, in March 2024, we received a letter from the FTC advising us that the FTC’s staff is conducting a non-public inquiry focused on our sale, licensing, or sharing of user-generated content with third parties to train AI models. The Dutch data protection authority, the Autoriteit Persoonsgegevens, has also inquired about our content licensing efforts. Given the novel nature of these technologies and commercial arrangements, we are not surprised that regulators have expressed interest in this area. We do not believe that we have engaged in any unfair or deceptive trade practice, we expect to receive continued regulatory interest in our plans, and any regulatory engagement can be lengthy, unpredictable and may cause us to incur substantial costs. It is possible for any regulatory engagement to result in reputational harm or fines, cause us to discontinue or modify our products, services, features, or functionalities, require us to change our policies or practices, divert management and other resources from our business, or otherwise adversely impact our business, results of operations, financial condition, and prospects.“ - 2025 Q3 Results
Management, for its part, frames the partnerships as a flywheel rather than a pure cash grab, using partner resources and infrastructure to sharpen its own machine translation and search capabilities.
“And second, on data licensing, things other than dollars. But, obviously, it’s citations, it’s mind share. It’s just general partnership. Like these companies have the data centers, the foundational models. And so our partnerships with all of these companies are multifaceted.
And so there’s a lot we can do in terms of beyond just the dollars. It’s how can these relationships help Reddit achieve its mission. So bringing in new users, advancing our own AI technology. So things like the machine translation, the LLM powered onboarding, all of the safety things, all of these things are kind of part of what we get through these relationships, which is why they’re so meaningful to us beyond just the core dev relationship or the business relationship.“ - Call Transcript
So the same deals that generate revenue are meant to upgrade the product.
We’ll test that claim later.
How big could this line of business get?
Naturally, I was wondering how big this revenue stream could realistically get?
Start with what's contracted, because the base is smaller and less mysterious than the headlines imply. In January 2024 Reddit signed licensing deals worth an aggregate $203 million over two-to-three-year terms, and as of June 30, 2026 it still carried $92.1 million in remaining performance obligations, roughly $62 million of which lands in the back half of 2026. Strip away the "other revenue" fog and essentially the entire AI licensing business is two contracts – Google at around $60 million a year and OpenAI near $70 million – with Premium subscriptions and a fragmented long tail of social-listening buyers like Meltwater and Cision making up the residual. That last group is small and unglamorous, but it's recurring and far less counterparty-concentrated than the marquee AI deals, and I'd treat it as the more durable part of the line.
Now the upside, which is where it could get genuinely large, but admittedly also genuinely uncertain. The bull case rests on a pricing model change rather than more customers: Reddit is pushing to move off flat annual fees toward usage-based metered pricing, tied to API volume plus a variable kicker for how often its content gets synthesized into AI answers like Google's Overviews. If that shift lands, insider chatter has a renewed Google deal alone reaching $150–200 million a year, and a fully renegotiated book – Google, OpenAI, plus settlements with the likes of Anthropic and Perplexity – reaching $400–600 million annually, with Wells Fargo publicly modeling roughly $550 million on renegotiation.
I'd hold those numbers loosely, because they ask you to believe two Reddit contracts will dwarf the entire disclosed publisher-licensing market several times over (OpenAI's News Corp deal, the largest on record, runs about $50 million a year).
The way I'd actually frame the ceiling is as a share of AI-lab economics rather than a count of deals: labs pay essentially zero for content today while Spotify pays labels around 70% of revenue, and the whole question is whether that equilibrium settles nearer 0.5% or 3%. On a $200 billion lab-revenue pool by 2030, a 1% content take is $2 billion, of which the single most-cited source on the internet might capture 15–25%, so $300–500 million; at 3% the math runs past a billion.
Such a wide range is maybe the most honest forecast I can make here, and I want to be upfront that it's a legal and negotiating outcome, not something more diligence on Reddit itself will narrow.
What I can say with more confidence is the direction. This is a line that could plausibly grow multifold on renewal. It may still remain a rounding error on Reddit's total revenue, or become a defensive, high-margin annuity worth as much as a mid-sized ad business – and which of those it becomes will be decided in negotiating rooms over the next four quarters, not on a date you can pencil into a model.
PS: Besides the size and mechanisms of the new deals, Siyu flags another interesting set of considerations below:
Inversion
Now to the caveat I’d put front and center: How recurring is this revenue, actually going to prove to be? The current major deals are short- to medium-term, roughly two to three years, and a fair question is whether the fees endure or fade once the models move past the data-hungry training phase. If the industry’s center of gravity shifts from training toward inference – running models rather than building them – you could imagine a world where an LLM has already learned what it needs from Reddit’s back catalog and no longer pays up for another pass. That’s the bear case on the durability of this revenue stream, and I don’t want to wave it away.
"Also playing chicken re: a new data licensing agreement is probably not a great idea if that's what management is doing. The second LLMs become less dependent on Reddit they lose all leverage. And they are likely at peak leverage right now. Dependence on Reddit for training is declining rapidly while synthetic data and transfer learning is reducing the importance of Reddit's content even more.” - Adam Wilk on X
But I’d push back on it, at least partway, from my own experience as a user. The thing that reliably frustrates me about LLMs is stale knowledge. You ask a question, you get a confident answer, and you can feel that the training data stopped a couple of months before you sat down to type. The model doesn’t know what happened last week, and sometimes it doesn’t know what happened last quarter. That staleness is precisely the gap Reddit fills. Its archive isn’t a frozen textbook you learn once and set aside. It’s closer to a live feed of the most current human read on almost anything – which phone actually has battery problems, which policy just broke, which trend is real and which is hype. As long as the world keeps changing and users keep wanting up-to-date, ground-truth human perspective, there’s a structural reason for models to keep coming back rather than coasting on a two-year-old snapshot. So the training-to-inference shift is a genuine risk to the flat-fee version of this business, and it’s also the strongest argument for why usage-based pricing on live data could turn out to be the more durable model.
One more concern belongs here: Licensing Reddit’s data into AI Overviews may cannibalize Reddit’s own traffic. If users get their answer straight from the AI summary, they have less reason to click through to the thread itself. So the same deals that light up the “other revenue” line could, at the margin, erode the engagement that feeds the advertising business. That’s not a footnote. It’s a real strategic tension inside the company’s own strategy, and it should be considered when reading about my projections for how big this line of business could become.
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