First, a disclaimer: this is NOT a feature recap. If that's what you're looking for, Shopify's Editions site is the place to be. Instead, what we're doing here is what we've done with every Edition for the last few years: analyzing what these updates actually mean for upper-midmarket and enterprise brands, where Shopify created genuine value, and what they could have done better.
In the Winter 2026 Edition specifically, AI stole the spotlight. Sidekick now generates admin apps! It generates theme sections! It supports Skills and third-party integrations! If you read the product announcements, it all feels like success is just one carefully engineered prompt away.
And truth be told, there is substance behind the hype. Shopify Magic, and Sidekick specifically, are powerful tools that are only getting more powerful. Agentic Storefronts are putting every Shopify brand in front of hundreds of millions consumers using LLMs to shop, all with a click of a button. And much-needed infrastructure improvements and platform additions (e.g., A/B testing and theme rollouts) are making life easier for merchants, developers, and consumers.
But when you evaluate these evolutions through the lens of an upper-midmarket brand moving serious volume, there are some nuances to consider. In this article, we're going to talk about those nuances, highlighting some of the biggest opportunities that still lie ahead for the Shopify ecosystem.
Sidekick's Code Generation Is Powerful But Requires Governance
Sidekick's code generation capabilities, for both themes and custom apps, represent an interesting leap forward in operational velocity, but they're not the cure-all some industry pundits are making them out to be.
In our experience, Sidekick excels at rapid theme prototyping. It gets you to about 80% visual accuracy fast, which is valuable when testing concepts or exploring ideas quickly. But when you think about long-term maintenance, you'll run into challenges such as:
- Excessive configuration options for settings that you'll never use.
- Isolated CSS and JavaScript that doesn't use existing utilities or patterns.
- No consideration whatsoever for the build system used by your theme (if any).
Admin app generation comes with similar benefits but also similar challenges.
The app store is littered with low-quality apps solving simple problems for $9.99/month, and we're all happy to see a few of those go away. If merchants can generate custom solutions they actually own, that's a genuine win.
But without a clear governance framework, your stakeholders will start generating apps that solve very similar problems in very different ways, with no consideration of existing patterns or cross-app interactions. As this functionality expands to storefront-facing features, which seems inevitable given the direction Shopify has taken with AI code generation, the stakes will get even higher. While admin apps affect operational efficiency, storefront apps affect revenue.
Moving forward, we'd like to see Shopify invest not just in AI code generation, but also in stronger primitives and better development guidelines that guide the AI, so it can be more considerate of its surroundings and the long-term impact of its output. Shopify should also educate its merchants on proper stewardship of AI-generated functionality, helping them answer questions such as:
- Which challenges are good candidates for AI-assisted solutions and which are not?
- How do we ensure that generated code integrates with existing patterns rather than creating islands of functionality?
- When should we hand off an AI-generated solution to our engineers for polish and maintenance?
At Nebulab, we're starting to establish such processes with our clients and getting the best of both worlds: the speed of AI prototyping combined with the discipline of human oversight and integration.
Without clear handoff processes and governance frameworks, you accelerate the accumulation of technical debt rather than evolution of your store.
Sidekick's Data Analysis Lacks Integration
Sidekick's business intelligence capabilities now come in two forms: the conversational chatbot that answers questions about your store data, and the new Pulse feature where Sidekick proactively suggests business initiatives. Unfortunately, both face the same fundamental limitations around data access and context.
For a $5M brand with a small team and straightforward operations, these tools can provide valuable direction. The suggestions might be generic, but generic advice often works when you're just starting out, your business model is simple, and your data lives primarily within Shopify.
For a $50M operation managing 1,500 SKUs across wholesale, marketplaces and DTC, coordinating 60 employees, and balancing a multi-year positioning shift against quarterly revenue targets, the calculus changes entirely. At this scale, context matters a lot. Generic optimization suggestions that ignore your specific constraints only create noise that your team has to filter through.
Sidekick can't tell you whether increasing email frequency will increase sales or damage your brand perception. It can't factor in that your warehouse is already at capacity and can't support that new sales channel. It doesn't know that your bestselling product line is being phased out next quarter and you should start weaning customers off of it.
More fundamentally, Sidekick is limited to the data that Shopify has. For businesses that integrate data from ERPs, warehouse management systems, customer service platforms, marketing attribution tools, and financial systems, Sidekick's view is necessarily incomplete. It sees transactions and customer behavior within Shopify, but lacks the full picture.
This is our problem with platform-specific chatbots and agents: they all only have a small piece of the truth and a small set of all the tools they could use, which prevents them from orchestrating larger business processes.
While Shopify is nice for smaller brands, we'd also like to see Shopify invest in better data portability—through official partnerships with ETL providers, data warehouses, BI tools, and external LLMs—so that the data can be integrated as part of larger operational workflows. Give enterprises the ability to bring Sidekick's analytical capabilities into environments where it has access to the full context, not just Shopify's limited view.
Without that broader integration, Sidekick is useful for surface-level insights but inadequate for strategic decisions.
SimGym and A/B Testing: A Missed Opportunity
Shopify launched two experimentation features in the Winter '26 Edition: native A/B testing and SimGym.
Native A/B testing is new and useful. You can now natively split traffic between theme variations and measure performance differences directly within Shopify. For smaller brands without dedicated experimentation infrastructure, this means you don't have to use external experimentation platforms and lowers the barrier to entry significantly (although you will still need enough traffic to power your tests).
Still, we were disappointed that Shopify didn't launch an API that other tools could ubuild upon, like they did for example with the Subscriptions API. Instead, external A/B testing solutions will continue to use the same client-side hacks they've always relied on.
This is a shame because large-scale brands doing serious experimentation (multiple treatments, custom metrics, audience exclusions) will never be able to use Shopify's native A/B testing. Allowing third-party tools such as Shoplift or Intelligems to build upon Shopify's offering would have dramatically improved the experimentation experience for merchants (through a more seamless experience) and consumers (through faster page loads).
In addition to native A/B testing, Shopify launched SimGym, which takes a very different approach: rather than testing with real users, it uses AI to generate synthetic user behavior and predict experiment outcomes. The concept is interesting: in theory, brands could use synthetic data to run tens of experiments and move iterate much faster on their UX.
Unfortunately, research from Nielsen Norman Group and other UX practitioners has found that synthetic users exhibit idealized behavior, lack the messiness of human decision-making, and produce overly optimistic results. AI-generated participants are overly agreeable and to miss the contextual nuances that shape actual behavior. In short, they're unreliable for concept testing and business decisions.
This may be a bit far-fetched, but we think Shopify missed a broader and much more interesting opportunity here.
Instead of generating synthetic predictions, imagine if Shopify had opened its A/B testing framework to third parties and then systematically collected and surfaced anonymized data about tests across its entire merchant network. With enough context about the business and the ability for the AI to understand what's being tested (i.e., not just surface metrics, but the strategic intent behind the test) Shopify could offer an invaluable best practices playbook to smaller brands and a sophisticated A/B testing engine to larger ones.
For example, a brand testing a new product page layout could receive insights like: "Among premium skincare brands with AOV above $75, similar layout changes increased conversion by 8-12% when combined with trust signals, but decreased conversion by 3-5% when the change removed product ingredient details." That's actionable intelligence grounded in real behavior seen in similar contexts.
This would have been a win-win-win for Shopify, third-party A/B testing apps, and merchants. The data would have been much more reliable than synthetic predictions and it would have been a true competitive moat for Shopify—proprietary insights that no other platform could match. Instead, we got synthetic predictions of uncertain value and a basic testing framework that doesn't serve the needs of more sophisticated merchants.
Whatever Happened to Hydrogen?
Clearly, Hydrogen is not a focus at Shopify anymore.
If you haven't followed the story, Shopify has made some big moves in the headless space between 2021 and 2024:
- In 2021, they launched Hydrogen, their React-based framework for headless commerce experiences, and Oxygen, their platform to host Hydrogen storefronts.
- In 2022-2023, they acquired Remix and used it to rewrite Hydrogen from scratch, positioning it as a major advancement in their headless commerce strategy.
- In 2024, they announced the Hydrogen Visual Editor, an entry-level alternative to more sophisticated solutions like Sanity and Contentful.
At some point around 2024, Shopify quietly started shifting their focus from headless commerce to AI as the next big thing:
- Hydrogen's GitHub repository has seen minimal activity in the last few months. Most of it was API version updates and dependency maintenance
- The Hydrogen Visual Editor never made it past the early access phase. As far as we can see, the initiative was killed before seeing the light of day.
- The Winter 2026 Edition includes exactly zero Hydrogen announcements.
Our own conversations with Shopify sources confirmed our suspicions: Shopify is discouraging brands from going headless unless they have a very strong reason to do it. In fact, they are telling Hydrogen brands to move back to Liquid.
This is not the disaster it seems. Hydrogen has always been plagued by a number of problems, most of them tied to the dynamics of the Shopify and JavaScript ecosystems rather than the framework itself:
- Most of Shopify's app ecosystem assumes that merchants use Liquid. Brands using Hydrogen often need to implement their own integrations (assuming the tool they're integrating with is kind enough to offer an API).
- While Hydrogen offers an excellent developer experience, the JavaScript ecosystem is famous for being extremely fragmented. It was not uncommon for development teams to ignore Hydrogen in favor of their preferred framework.
- Most Shopify product announcements would make it into Liquid way before making it into Hydrogen, which was a source of endless annoyance.
None of this is to say that you shouldn't go headless, if your brand is complex enough to need it. But you should know that, in 2026, headless is not the default choice anymore. Before going off the beaten path, make sure you have evaluated the pros and cons of doing so. We'll publish a much deeper dive about this in the next few weeks!
Where To Focus Your Attention
If you're running an upper-midmarket brand, here's what actually matters from this release:
- Use Sidekick for rapid prototyping, but establish clear handoff processes before your team generates a dozen isolated apps solving similar problems in different ways. The speed is real, but so is the technical debt if you don't have governance in place.
- Double check the AI's insights. Sidekick is useful for quickly extracting raw numbers from Shopify, but it still hallucinates every now and then and it lacks important context about your business. Don't any results or conclusions at face value.
- Adopt native A/B testing if you're only starting out. It's a solid foundation for brands just starting to build experimentation capabilities. If you're already running complex tests with custom metrics and audience segmentation, you'll still need third-party tools.
- Ignore synthetic data. Synthetic user predictions are interesting in theory but unreliable in practice. If you have the traffic, run real tests with real customers. If you don't have the traffic, stick to e-commerce UX best practices until you do!
- When it comes to headless, thread lightly. Shopify's investment has clearly shifted elsewhere. Unless you have compelling architectural reasons to go headless, the default path is Liquid.
As always, if you need help sorting through adopting the new features or understanding what they mean for your business, let's talk.
