Turning Everyday Moments into Shoppable Experiences with Catalog API

Shopify now lets developers build end-to-end agentic commerce apps with Catalog API and the Universal Commerce Protocol. In plain English: the bot is getting closer to discovering products, choosing products, and checking out with less human babysitting in the middle. That is the revealing part. AI shopping stops sounding like a gimmick once the infrastructure is there for the whole transaction, not just the recommendation widget. Everyone talks about agents as if they live in demos. Commerce is where they either become real or become fraud with nicer UX. The agent economy gets less theoretical the moment the bot touches a card.

Shopify’s Spring ’26 Edition is a big one for developers, and it’s clear they’re betting hard on agentic commerce. The most important update for me is Shopify Catalog + UCP. Shopify is now structuring product data and feeding it directly into AI surfaces like ChatGPT, Copilot, and Google’s AI Mode. That changes how we think about building apps, checkout flows, and product schemas — product data is now a core part of the discovery layer, not just the store. A few developer-focused highlights: Catalog API improvements: image search, product lookup, Shop sign-in support, and richer product attributes for agentic experiences. 𝐔𝐂𝐏 𝐂𝐋𝐈 𝐚𝐧𝐝 𝐀𝐏𝐈𝐬: Tools to build carts across merchants, power agent-to-agent purchasing, and create new shopping experiences on top of the Universal Commerce Protocol. 𝐒𝐢𝐝𝐞𝐤𝐢𝐜𝐤 𝐚𝐩𝐩 𝐞𝐱𝐭𝐞𝐧𝐬𝐢𝐨𝐧𝐬 (𝐆𝐀): Data and app-action extensions for Sidekick, which opens up new ways to integrate your app into the AI-powered admin. 𝐃𝐞𝐯 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝 𝐨𝐯𝐞𝐫𝐡𝐚𝐮𝐥: Better store/team management, observability with the App Events API, rebuilt logging, and smoother deployments. 𝐍𝐞𝐱𝐭-𝐠𝐞𝐧 𝐞𝐯𝐞𝐧𝐭𝐬 𝐫𝐞𝐩𝐥𝐚𝐜𝐢𝐧𝐠 𝐰𝐞𝐛𝐡𝐨𝐨𝐤𝐬: A more robust event system for app developers. 𝐒𝐡𝐨𝐩𝐢𝐟𝐲 𝐀𝐩𝐩 𝐏𝐫𝐢𝐜𝐢𝐧𝐠: Usage-based pricing and meters, which impacts how we design app architecture and monetization. 𝐌𝐲 𝐭𝐚𝐤𝐞: Shopify is moving from “sell on your store” to “sell everywhere via AI agents.” That means clean product schemas, strong checkout extensibility, and AI-ready integrations are going to matter more than pretty themes alone. If you’re building Shopify apps, extensions, or catalog-heavy solutions, this edition is a clear reason to start thinking about agentic commerce now. #ShopifyDeveloper #ShopifyEditions #Spring26 #AgenticCommerce #AICommerce #ShopifyApps #ShopifyPlus #AI

Most brands spend a lot of money driving traffic to their store. But what happens after a visitor lands on a product page? Usually, customers browse collections and multiple pages to find similar products, but many simply buy that one product or leave. →What if AI could automatically understand what a customer is interested in and recommend the most relevant products in real time? That's exactly what WeUpsell's AI-powered upselling does. 🧠 AI analyzes customers browsing history , data and Shopping intent. and AI recommends: → Similar products → Product bundles → Relevant upsells Built for Shopify brands to grow smarter, create smoother shopping experiences, and unlock more revenue from existing traffic. You can try it free by installing it from the Shopify App Store. #Shopify #eCommerce #D2C #AI #ProductRecommendations #Upselling #ShopifyApps #ConversionRateOptimization #AOV #RevenueGrowth

One feature almost didn't make it into our product. When we started building our AI Virtual Try-On app, we were focused on one thing: Making the technology work. Like many founders, we spent hours discussing AI models, performance, APIs, and accuracy. But then we started talking to Shopify merchants. The conversations changed everything. No one asked us, "Which AI model are you using?" Instead, they asked questions like: "Will this help customers buy with more confidence?" "Will it work for my products?" "Will it improve the shopping experience?" "Is it easy for customers to use?" That was a turning point. We realized merchants don't buy technology. They invest in outcomes. So every product decision became much simpler. If a feature didn't make shopping easier... If it didn't reduce customer hesitation... If it didn't help merchants grow... It didn't belong in the product. Building software has taught me that the best features aren't always the most advanced. They're the ones customers actually use because they solve a real problem. That's a lesson I'll keep carrying into every product we build. What's one product lesson you've learned that completely changed the way you build? I'd love to hear your experience. #FounderJourney #Shopify #SaaS #ProductManagement #ArtificialIntelligence

Unpopular opinion: if you moved to headless commerce purely for page speed, you solved the wrong problem. For years, "go headless" meant one thing: strip out Shopify's Liquid rendering, build a custom frontend, shave seconds off load time. That's still true, but it's no longer the main event. Shopify's own 2026 positioning has shifted - Hydrogen is now described as the React frontend for Shopify's commerce graph, built for an agent-readable, AI-mediated future. Storefront MCP, released in December 2025, lets AI shopping agents read live catalog, cart, customer, and order data directly from Hydrogen storefronts running on Oxygen. Why does that matter more than a Lighthouse score? Because AI-mediated shopping traffic is growing fast - some reports put AI-driven order volume up roughly 11x year-over-year and AI-referred traffic up nearly 4x in the same window. Chat assistants and shopping agents are becoming a real discovery channel, and they can only transact with storefronts that expose structured, machine-readable data. A beautifully fast storefront that a shopping agent can't parse is invisible to that channel entirely. A client recently faced exactly this tension. They were debating a headless migration purely on Core Web Vitals numbers, treating it as a performance project with a fixed ROI ceiling. We reframed the conversation: the real architectural decision was whether their commerce data - products, pricing, inventory, cart state - was structured in a way that both humans and AI agents could reliably act on. Speed was a side effect of getting that right, not the goal itself. The takeaway: headless architecture decisions in 2026 need to account for two audiences - the human on the page and the agent that might be shopping on their behalf. Optimizing only for the first one is optimizing for last year's internet. Have you audited whether an AI shopping agent could actually complete a purchase on your storefront today? #ShopifyPlus #HeadlessCommerce #EcommerceDevelopment #ShopifyDevelopment #AIAgents

Google has introduced Universal Cart, a new AI-powered shopping cart designed to make online shopping less scattered across apps, websites, videos, emails, and search results. The feature was announced at Google I/O 2026 in May as part of Google’s wider push into agentic commerce, a growing area where AI tools do more than recommend products. They help users compare prices, track deals, manage carts, and move closer to checkout....

Most people have an online store idea. They just never launch it. The problem is not the website. The problem is everything around the website: products, checkout, payments, analytics, fulfillment, email, inventory, and all the plugins you have to connect before you can make one sale. That is why we built Daybot. Daybot is an AI-native e-commerce platform where you can create and run a store by chatting with AI agents. Describe what you want to sell, and Daybot builds the store, adds products, writes listings, sets up checkout, and lets you keep editing everything through chat. We used Daybot ourselves to launch Polar Parts, our robotics parts store. Polar Parts has done CAD $3,558.18 in GMV across 39 orders, and our users have now created 500+ stores on Daybot. Shopify starts with a theme. Daybot starts with a working store. Try it free: https://daybot.ca

You may have seen yesterday that Abra is now part of Shopify Sidekick’s new app integrations launch. Building sophisticated promotions through AI is genuinely exciting. But that's not what excites me most. The part I’m most excited about is what happens when you start feeding your AI workflows richer business data and context. That's when you start getting signals, not stats. Real insight into what’s driving revenue, conversion, margins, and customer behavior. When we tested it, we asked about our highest performing promotion. Sidekick didn't just answer the question. It also referenced the store data and came back with specific recommendations for optimizing the discount. That’s the kind of actionable data merchants need to move fast.

You might not have customer data yet. That's okay — your products already tell us enough." This is the question I hear most from new businesses building an online store or app: "We just launched. We have no purchase history. How can recommendations even work for us?" Here's the answer most people don't expect: you don't need user history to start recommending well. There are actually two ways recommendation engines work: 1. Collaborative Filtering — learns from what similar customers bought → Works great once you have data, but struggles on Day 1. 2. Content-Based Filtering — learns from the features of your products and customers → Works from the very first customer, the very first product. Here's what Content-Based Filtering actually uses: -- Product attributes — category, price range, brand, specifications -- Customer signals — location, browsing behavior, stated preferences -- A neural network that matches the two — even with zero rating history So a brand-new customer who tells you they like "running shoes" can get a relevant recommendation immediately — no waiting for months of data to accumulate. Why this matters for your business: -- New stores can offer personalization from launch day — not 6 months later -- New products get recommended fairly, even with zero reviews yet -- You're not stuck waiting for "enough data" before customers see value This is the same architecture used by major commercial platforms today — adapted to work at the scale that fits your business, whether that's hundreds of products or hundreds of thousands. I build these systems end-to-end — from feature design to model training to integration with your existing website or app. If you're building or scaling an online store, food delivery app, or content platform — let's talk. #ContentBasedFiltering #MachineLearning #RecommenderSystems #Ecommerce #AIForBusiness #WebDevelopment

I just started exploring the Shopify Spring '26 Edition, working through it topic by topic. First stop: Agentic. It's the area I'm most focused on right now, so it made sense to start there. But the update that really caught my attention sits under Sidekick. Sidekick now works with your apps. Starting with partners like Judge.me, Klaviyo, Loop, and Smile, Sidekick can read context from your installed apps and take action inside them. This runs on Sidekick app extensions, which let third-party apps expose their capabilities to Sidekick directly. Why this matters technically: Instead of every app living in its own silo with its own UI, app extensions give Sidekick a structured way to call into them. You describe what you want in natural language, and Sidekick maps that to actions across the connected apps. So rather than context-switching between dashboards, you stay in the admin and operate across tools through one interface. Moderate a Judge.me review, trigger a Loop return flow, pull Klaviyo segment data, all from the same conversation. This is the part of agentic commerce I find most interesting. Not a chatbot layered on top, but an orchestration layer that sits across your app stack and executes. For developers, it also signals where the platform is heading. If your app exposes the right extension surface, it becomes something Sidekick can act through, not just something merchants click into. I'm one topic in and already rethinking how store operations get built. Next, I'll go deeper into the rest of the Agentic section, including Shopify Catalog and the Universal Commerce Protocol, and share what stands out. If you build on or run a Shopify store, the Sidekick app extensions are worth studying. What part of Spring '26 are you digging into first? #Shopify #ShopifyEditions #AgenticCommerce #Sidekick #Ecommerce #AI #RetailTech #ShopifyDevelopers #AIagents #CommerceTech #kolachiTech