The Future of Web Search
AI, Discovery, Ads and upheaval of the Internet Economy - Investment Thesis #1
Hey there,
As a quick reminder from the previous edition, in the past year, I’ve co-founded an investment firm targeted at operators: C-levels, VPs, etc. of tech companies who want to get together to invest in early-stage companies and roll up their sleeves to help them become future giants. If that sounds like you, do get in touch!
As a result, I’d like to add new lines of content to Chasing Paper and to expand on investment theses for deals that we invest in. I’m a big believer of building in public for companies, as am I of investing in public. So here it goes.
I’m sure you noticed that AI was all the rage these days in VC-land and tech in general – and so I’d like to talk about something pivotal – search. Specifically, the way web search, a massive ecosystem driven by advertising dollars (Alphabet, anyone?), is about to undergo radical transformations.
Shifts in Search
For decades, search has been fairly straightforward — Google ranks pages, and advertisers monetize them, bidding on keywords, acquiring traffic, etc. And for a long time, it worked perfectly, with a noticeable impact on all of our lives. Quoting directly from Alphabet’s 2023 Annual Report:
Larry and Sergey first wrote down our mission 25 years ago: to organize the world’s information and make it universally accessible and useful. They had an ambitious vision for a new kind of search engine to help people make sense of the waves of information moving online.
It’s been inspiring to see what people have done with the answers to their questions, be it to find health care or comfort in difficult times, learn new skills, pursue new career paths, or start new businesses. The idea that a student in rural Indonesia could access the same information as a professor at Stanford was revolutionary and has changed lives and our world for the better. It’s opened up access to education and entrepreneurship like nothing else before it or since.
Google’s revenue from search ads hit $175 billion that same year, making up 57% of its aggregate revenue. But we’re at the start of something new: a seismic shift powered by AI and LLMs.
Whereas the traditional model feeds users results from crisp prompts, we’re now looking at systems that interpret queries in natural language and generate answers on the fly. And this matters because it transforms user experience from “best salmon recipes” or “how to calm crying twins” (oh yeah, this also happened last year) to receiving directly the top 3 best recipes, all integrated into one streamlined response, or, y’know, some methods that do not “actually” make babies stop crying but give you hope it can work. The AI doesn’t just show you where to find it; it serves it to you on a silver platter.
Obviously Google/Alphabet itself is at the forefront of that seismic shift, having gradually integrated AI into its products over the last decade and poured billions of dollars into cutting-edge AI research.
And yes, it is very unlikely that in order to get the same information you start typing “good day to you Ser GPT/Claude/Llama, could I interest you in providing me thorough details to turning a hen’s offspring into a deliciously seasoned pan-fried dish, colloquially known as sunny-side up egg? Thank you very much in advance, dear friend” instead of “omelet recipe”. What matters is that the format in which your result will be provided will be transformed. Right now, you’ll get a complete reply with the recipe you need from ChatGPT.
In time, you might receive an AI generated step-by-step video of how to actually make it, or an audio file, or whatever is most convenient for you to consume in your current setting, whether you’re on your computer, your phone, your VR glasses (have you seen those Meta Raybans?) or your connected fridge. Again, serving you the content you need on a silver platter.
A fundamental challenge here is that the web was designed for human users, not AI systems. Current AI approaches rely on mimicking human behavior - scraping pages designed for humans, complete with their visual layouts and ad placements. This inefficiency highlights the urgent need for AI-optimized frameworks that bypass traditional crawling methods, offering structured, machine-readable data instead.
But a more pressing question also arises: what happens to content providers? Those who make the recipes, blogposts, articles, reviews? Right now, the web runs on ad dollars: content creators rely on traffic to their websites, where ads generate revenue and/or content is paywalled. Every click is an opportunity for a site to display paid advertisements, with creators earning a portion of that spend, or to rake in payments or subscriptions. The more users visit, the higher the revenue: eyeballs have value. But if people aren’t clicking through to websites because they get their answers directly, how do creators make money?
Hold that thought and save it for later, if you please.
Veridis Quo
The same shift, possibly bigger even, could happen to Discovery.
A key change here is not just in how we search, but how we stumble upon things — whether it’s content, products, or services. Historically, platforms like Google and Amazon have perfected this balance through algorithms that mix content and ads so seamlessly, we hardly notice. Looking for “best headphones” on Google, get hit with results where you can click and buy directly. Search “headphones” on Amazon and receive most relevant products but also highest-ad-bidder’s product.
Discovery is even more complex with social products, where your “feed” algorithmically pushes content that you might be interested in: Instagram, X, TikTok, etc. all use this mechanism to keep you hooked on their products, doomscrolling for hours and monetizing
your attention all along.
You know the drill, we all do and have been used to it for decades now. With AI, things get messier—but potentially more exciting.
Product Discovery is already starting to change: TikTok is experimenting with automated product identification. Imagine uploading a picture of a pair of sneakers you saw a random person wearing in the streets, and AI finds the best deal for you for that pair immediately. Boom, conversion. No need to sift through links, search what brand/color/model those were.
Also notable, AI-driven search engines like Perplexity have begun integrating shopping features, allowing users to receive product recommendations directly within search results.
Content Discovery is also bound to change. If you type in on a LLM engine “what’s happening in the Middle East right now?”, an ideal result would yield a synthetic and balanced view of recent developments in the Gaza strip sourced through a number of articles from neutral and partisan journalists, local and international news outlets or official organizations - all narrated or put together by a single AI model. But you wouldn’t be able to access those articles, cross-check, fact-check, build your opinion on how one piece explains things more precisely than another, how one journalist writes in a style that is more enticing to you, etc.
To use a (slightly dystopian) culinary analogy; if all content is pre-hashed by LLMs, it might end up being like blending your entire meal before eating it. You get the same nutrients (sorta), but the taste is bland and you can’t identify the raw ingredients.
Let’s leave it at that for the considerations of what the shift entails for individuals or for democracy, as albeit fundamental, it is not the topic of the article. Another aspect for which this is important is that when you perform search, you do not want low-value, generic replies as much as you do want the exact thing you are looking for.
For companies, it would mean that they need to rethink their entire sales and marketing strategies because their product could (or couldn’t) get “discovered” without traditional ads ; and for content creators it means finding new routes to monetizing what they do.
Advertise Aeternam
OpenAI, Perplexity, and Google are all racing to build the next-gen search experience, making it multimodal—essentially browsing the web on your behalf and giving you ready-made answers in palatable format. Great for users, right? But what about the creators? High-quality content takes real effort, and advertising is what keeps the lights on. It’s the engine behind news, social media, even paid streaming platforms.
Now, here’s the multi-billion-dollar question: if AI starts delivering answers directly, how does this impact the advertising machine? Google’s empire, fuelled by its advertising engine, is now under siege. If AI answers replace web traffic, who foots the bill for the creative effort content providers make? Where do the ads go? We could be heading toward an internet where quality content hides behind paywalls while AI regurgitates low-value, generic stuff for everyone else.
As AI replaces human browsing, the ad-based economic foundation of the web begins to crumble. AIs neither view ads nor interact with content as humans do, creating a vacuum in the revenue models that have sustained free content and services for decades. Without innovative monetization strategies, many content creators face existential threats.
Part of the solution might be that advertisers now start to pay directly for their products/contents to appear in AI-generated replies. And pretty surely the winner of the LLM race would love to rake in B2B ad revenue from placing ads in its replies, optimizing placement, algorithmically offering biddings, performance tracking, etc. But without safeguards and with the current state of AI (you know, hallucinations, etc.) this would mean pushing more dubious content into the cesspool.
Here’s where things get interesting for investors. If AI gets in the middle of this ecosystem, someone needs to pay content providers directly for them to keep providing quality content: scrapping the entire web without the suppliers making a dime is neither legal, nor sustainable from a value creation standpoint. Moreover, the web was built for humans, with UX and UI improving over time – not for robotic web agents crawling pages to retrieve information. Illegal, inefficient, costly, parsed: web access for AI is nowhere near where it needs to be for Search & Discovery to be displaced because of the economic equation in a world (potentially) without ads.
This is where Linkup comes into play. Linkup aims to build a tech-enabled infrastructure where AI can access content from providers, who get compensated directly, all in a format that’s adapted for a machine. It’s a transparent ecosystem that ensures creators aren’t squeezed out of the equation and get a revenue share in the value of the content they put in effort to provide.
Monetizing content through AI will surely require a fair and trusted intermediary that acts as a neutral third-party between content providers and LLMs.
This is why we decided to make Linkup our first investment; with a stellar team of ex-operators turned founders paving the way to the future of search & discovery in this AI-powered world.
Conclusion
The rise of AI demands a radical rethink of how the web operates : a new framework for browsing. Linkup envisions a future where APIs, licensing agreements, and AI-specific interaction layers replace the outdated scraping methods. These advancements will not only make AI browsing more efficient but will also provide transparency and fairness to content providers, ensuring everyone benefits from this shift.
Linkup’s model could be a key to preserving the economic equation of the web: content, eyeballs, value. The exciting part? This opens up new frontiers for advertising, where users are guided by AI but content creators, and brands get paid for the value they bring, traceably.
It’s a more rational model that could prevent the “enshittification” of platforms / AI models, a term coined by Cory Doctorow to describe what happens when platforms prioritize ads over user experience.
So where does this leave us? In a space that’s exciting and uncertain. AI’s transformative power in search is inevitable, but we must shape it to ensure it benefits everyone — users, platforms, brands and content creators alike. As we edge into this future, companies like Linkup are the linchpins, offering a model where discovery, compensation, and transparency align.
In the end, AI won’t just change how we find answers. It’ll reshape how we discover everything – from your next favorite book to the new pair of sneakers you didn’t even know you needed, to maybe your next partner or who knows, how to put a baby to sleep? And for that, we need to change the Internet’s very architecture.
Until next time, Younes
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