The AI Shopping Wars Are Here. Creators Need a Better Answer Than a Link Tree.

Three trillion-dollar companies want to sell your audience's next purchase

In the last six months, something fundamental shifted in how people discover and buy products online.

Amazon launched "Buy for Me" — an AI agent that scrapes third-party websites, lists their products on Amazon, and completes purchases on behalf of shoppers without those brands' consent. Retailers woke up to find their products listed on Amazon with a "Buy for Me" button they never approved. Shopify and WooCommerce stores were automatically opted in. The backlash has been loud, but the feature keeps expanding.

OpenAI turned ChatGPT into a shopping assistant. Their Shopping Research feature builds personalized buyer's guides by researching products across the internet, then signed deals with Walmart, Target, Instacart, DoorDash, Etsy, and Shopify merchants for Instant Checkout — buy without leaving the chat. McKinsey found that 40-55% of consumers now use AI-based search for purchasing decisions.

Google pushed Lens to 20 billion visual searches per month, 4 billion of them shopping-related. Snap a photo of a product, get instant identification, pricing, reviews, and purchase links. Their AI Mode now inserts interactive product panels directly into conversational search results.

This is agentic commerce — AI that doesn't just help you find products but actively brokers the transaction. And the numbers behind it are staggering: the visual search market alone is projected to grow from $40 billion to $150 billion by 2032. U.S. social commerce sales will surpass $100 billion this year.

The race is on to become the default middleman between every person and every product they buy.

So what does this mean for creators?

Here's the part that matters if you recommend products for a living — or even casually.

A McKinsey study found that brand websites show up in only 5-10% of AI search sources. Affiliates and user-generated content do 90-95% of the heavy lifting. That means when ChatGPT recommends a camera or Amazon's AI agent suggests a golf club, the recommendations are being shaped by creator content, review sites, and community discussions.

Creators are the supply chain of product intelligence. Your reviews, your gear lists, your "what's in my bag" videos — that's the training data and source material for every AI shopping agent being built right now.

But here's the problem: most creators still manage their product recommendations with tools that were designed for something else entirely.

Why Linktree, Beacons, and Stan Store aren't built for product recommendations

Linktree has 50 million users. It does one thing well: organize links. You get a page of clickable rectangles that point to your other stuff — YouTube, Spotify, merch store, podcast. It's a routing tool, not a product tool.

To their credit, Linktree is trying to evolve. They acquired Fingertip in late 2025. They're using the AI agent Devin internally (300 PRs merged, mostly bug fixes and analytics). They've announced plans for AI-powered product suggestions and smart link placement. But the fundamental architecture is still "here are my links" — a directory, not a product experience.

Beacons goes further with an all-in-one approach — link-in-bio, digital product store, email marketing, media kits, invoicing, AI content generation. It's ambitious and genuinely useful for creators who sell courses or ebooks. Free plan with a 9% transaction fee, or paid plans starting at $10/month. But when it comes to physical product recommendations — the gear, the equipment, the things you actually use — it's still fundamentally a link page with extras bolted on.

Stan Store is the most focused on monetization: $29/month, zero transaction fees, built for selling digital products, courses, and memberships. Great if you're selling your own stuff. Not designed for "here's the camera I use and why."

Kit (formerly ConvertKit) pivoted hard into creator tools with email marketing and monetization features. They have a generous free plan for up to 10,000 subscribers. But again — this is an email/newsletter platform that added commerce, not a product curation tool.

The pattern is clear: every major creator platform started as something else (links, email, digital products, newsletters) and is now bolting on product features as an afterthought. None of them started by asking "how should a creator share the products they actually use?"

A thread on r/SaaS titled "link-in-bio tools are a scam and here's why" captured the growing frustration. The core argument: these tools charge you monthly for what amounts to a styled list of hyperlinks on someone else's domain. They don't understand what your links point to. They don't know a Sony A7IV from a Titleist TSR3. They're dumb pipes.

What AI shopping agents get right — and what they miss about trust

The agentic commerce wave is solving a real problem: product discovery is broken. Googling "best mirrorless camera 2026" returns a wall of SEO-optimized listicles written by people who haven't held the cameras. The AI shopping agents cut through that by synthesizing real reviews, comparing specs, and delivering personalized recommendations.

But they get something fundamentally wrong: they remove the human from the recommendation.

When you watch a photographer you trust explain why they switched from Canon to Sony, that context matters. When a golfer you've followed for years breaks down their bag change, the story behind each club matters. The "why" is the product.

AI agents can tell you the Sony A7IV has 33 megapixels and costs $2,498. They can't tell you that the photographer you admire chose it specifically because the autofocus tracks their kid running across a soccer field and the file size plays nicely with their Lightroom workflow. That lived experience — the personal context — is what makes a recommendation worth following.

Criteo's new Agentic Commerce Recommendation Service showed a 60% improvement in recommendation relevancy over generic approaches. That's impressive for cold product matching. But relevancy isn't the same as trust. And trust is what creators have spent years building.

The $235 billion opportunity nobody is building for

The creator economy will hit $234.65 billion globally this year. Creator monetization platforms specifically are a $13.94 billion market growing at 20.5% annually. Paid amplification of creator content will jump 48% to $13.2 billion.

But look at where the money is flowing: social commerce, AI agents, ad tech, influencer matching platforms. The infrastructure being built is designed to extract value from creator recommendations, not to help creators share them better.

The entire "what's in my bag" genre — one of the most popular and enduring content formats on YouTube, Instagram, and TikTok — still relies on creators manually typing out gear lists, finding product links, formatting descriptions, updating prices, and replacing dead URLs. Thomas Frank maintains a gear page. Jeff Su maintains a gear page. Every tech YouTuber, every golf influencer, every photographer with an audience maintains some version of a gear page. And they all do it by hand.

Meanwhile, 70% of shoppers have used AI tools for purchasing decisions, and the platforms those shoppers use can identify products from a photo in milliseconds. The gap between what AI can do with product identification and what creators have access to for sharing their recommendations is enormous.

What would an AI-powered gear page actually look like?

Start with the product, not the link.

Instead of a page of URLs, imagine a collection where every item is understood — brand, model, category, specs. Where adding a new product means describing it or photographing it, and AI fills in the rest. Where the creator's job is to add the only thing AI can't generate: why they chose it.

Now add context. Not a product card with a price tag — a story. "Switched to this driver after my back surgery. The lighter shaft makes a real difference at 18 holes." That's the recommendation. That's the trust signal no AI agent can replicate.

Make it permanent. Not a feed that scrolls past in 24 hours. Not a story that disappears. A living collection that evolves as the creator's gear evolves — with a stable URL that works in YouTube descriptions, email signatures, and Instagram bios for years.

And then — and this is the part the link-in-bio tools fundamentally miss — make the products themselves intelligent. Know that a TaylorMade Qi35 is a golf driver. Know that a Sony A7IV is a mirrorless camera. Know that when someone adds a "Rode VideoMic Pro+" to their bag, it's an on-camera microphone in the audio category. Because once you understand the products, you can do things no link page can: surface related items across creators, help visitors discover gear by category, and give creators analytics that go beyond "someone clicked your link."

That's what we're building at Teed. Not another link-in-bio. Not an AI shopping agent. A product curation platform where creators own their recommendations and AI handles everything else.

The landscape is splitting in two

On one side: the AI shopping agents. Amazon, OpenAI, Google, Criteo — fighting to become the default product discovery interface. Their value proposition is efficiency: "We'll find the right product for you faster." They'll win on convenience and scale. They'll also increasingly commoditize product recommendations into interchangeable data points.

On the other side: the creator tools. Linktree, Beacons, Stan Store, Kit — fighting for creator monetization. Their value proposition is "we'll help you make money from your audience." They'll win on breadth of features and existing user bases. They'll also keep treating products as dumb links.

The gap in the middle — a platform that combines AI product intelligence with human curation, that understands both what the product is and why the creator chose it — is wide open.

The AI in the creator economy market is growing at 31.4% annually and will reach $4.35 billion this year. But most of that investment is going into content generation, influencer matching, and ad optimization. Almost none of it is going into helping creators do the thing their audiences actually want: share credible, contextual product recommendations.

How creator platforms compare in 2026

| Feature | Teed | Linktree | Beacons | Stan Store | Amazon Storefront | |---------|------|----------|---------|------------|-------------------| | AI product identification | Yes | No | No | No | Own catalog only | | Video-to-collection pipeline | Yes | No | No | No | No | | "Why I chose this" context | Yes | No | No | No | Video reviews only | | Multi-retailer affiliate links | Yes | Partial | Partial | No | Amazon only | | Auto affiliate tag insertion | Yes | No | No | No | Yes | | Embeddable on external sites | Yes | No | No | No | No | | Digital product sales | No | Partial | Yes | Yes | No | | Free tier | Yes | Yes | Yes (9% fee) | No ($29/mo) | Yes | | Product categorization | Yes | No | No | No | Yes | | Cross-creator discovery | Yes | No | No | No | Yes |

The pattern: Teed leads on product intelligence and curation. Linktree leads on brand recognition. Beacons and Stan lead on digital product sales. Amazon leads on checkout conversion. Nobody else combines AI identification with human context.

Where this goes

Every piece of content a creator makes about products — every YouTube video, every Instagram post, every "link in bio" — is training data for the next generation of AI shopping agents. The creators who have structured, intelligent product collections will be the ones whose recommendations surface in AI results. The ones with flat lists of affiliate links on Linktree will be invisible.

The shift from "link pages" to "product intelligence" isn't optional. It's the difference between being a source that AI shopping agents cite and recommend from, and being a generic link that gets bypassed entirely.

The AI shopping wars will be won by whoever controls the relationship between people and products. For creators, the play isn't to compete with Amazon's AI or ChatGPT's shopping feature. It's to be the trusted source those systems rely on — and to own a platform that makes that trust visible, permanent, and shareable.

That's the bet we're making. Not on links. On curation.

Frequently asked questions

What is agentic commerce?

Agentic commerce is AI that doesn't just recommend products — it discovers, compares, and purchases them on your behalf. Amazon's "Buy for Me" agent completes transactions on third-party websites. ChatGPT's Shopping Research builds personalized buyer's guides and offers Instant Checkout with Walmart, Target, and Etsy. Google's AI Mode inserts shoppable product panels directly into search results. The term emerged in late 2025 as AI agents moved from product discovery into autonomous purchasing.

Is Linktree still worth using in 2026?

Linktree is still useful as a link organizer — it does that well for 50 million users. But it doesn't understand what your links point to. It can't tell a camera from a golf club. If your primary use case is sharing product recommendations or gear, Linktree treats every product the same as every other link. It acquired Fingertip in late 2025 and is adding AI features, but the core architecture remains a directory of URLs, not a product intelligence platform.

What is the best link-in-bio tool for product recommendations?

Most link-in-bio tools (Linktree, Beacons, Stan Store) were designed for links, digital products, or email marketing — not physical product recommendations. For creators who recommend gear, equipment, or products they use, the best tool depends on what you need: Amazon Storefronts if you only sell on Amazon, LTK if you're in fashion, or a purpose-built product curation tool like Teed if you want AI-powered identification, multi-retailer affiliate links, and the ability to add personal context to every recommendation.

How does AI change creator product recommendations?

AI is reshaping creator recommendations in two ways. First, AI shopping agents (ChatGPT, Google AI Mode, Amazon) are becoming how consumers discover products — and they primarily source from affiliate content and user-generated content, not brand websites (only 5-10% of AI sources are brand sites). Second, AI product identification lets creators add products to their collections by describing or photographing them instead of manually finding links. Creators with structured, AI-readable product pages will surface in AI shopping results. Those with flat link lists won't.

What's the difference between a link-in-bio page and a gear page?

A link-in-bio page (Linktree, Beacons) is a list of clickable URLs — your YouTube, your podcast, your merch store, maybe some product links. It's a directory. A gear page is a curated collection of products you use, organized by category, with context about why you chose each one. The difference matters because AI shopping agents can parse structured product collections but can't extract meaning from a flat list of affiliate links.