Why E.U. Ecommerce Rules Seem Complex

Merchants often ask me to explain E.U. ecommerce regulations. I usually start with a warning: There is no single framework. Instead, an ecosystem of overlapping rules now shapes how online commerce operates in Europe and how consumers behave.

That ecosystem has largely succeeded from a policy perspective. But it’s increasingly difficult for merchants.

I’m the co-founder of an ecommerce marketing firm in Poland. Here is my operator’s explanation of ecommerce laws in Europe.

European Commission home page

The European Commission proposes most E.U.-wide ecommerce regulations.

Consumer Trust

E.U. ecommerce regulation is not accidental or piecemeal. It reflects a deliberate policy choice of building consumer trust through enforceable rights, transparency obligations, and accountability across borders.

Legal and academic practitioners support this direction. Rules around seller identification, truthful pricing, authentic reviews, product safety, and complaint handling aim to close loopholes that once allowed unsafe or misleading offers. The result is a market where consumers expect to know who they are buying from, what they are paying for, and what happens if something goes wrong.

Those expectations stem largely from regulation rather than culture. European consumers are trained by law to demand clarity and redress. Foreign sellers often allege excessive consumer caution when, in reality, it is compliance-driven behavior.

Overlap

Observers largely agree on the objectives but differ in the extent to which regulation has expanded.

What used to be governed primarily by the E.U.’s E-Commerce Directive and the General Data Protection Regulation (GDPR) is now supplemented by the Omnibus Directive, the Geo-blocking Regulation, the Digital Services Act, the General Product Safety Regulation, accessibility rules, packaging and environmental requirements, and, soon, the Digital Product Passport.

Each addresses a specific risk. Together, they affect nearly every operational layer of ecommerce: marketing, product pages, review systems, onboarding, fulfillment, customer service, data handling, and documentation.

In my experience, merchants usually understand individual rules, but not multiple overlapping requirements.

Part of the confusion is institutional. Various offices of the European Commission propose most major rules. Laws are adopted legislatively through the European Parliament and the Council of the E.U., both consisting of representatives from member states. Some rules, such as the Digital Services Act and GDPR, apply directly to all E.U. countries. Others, including many consumer-protection measures, are E.U.-level goals requiring country adoption. Hence merchants face a combination of E.U.-wide rules and country-level enforcement. Compliance is centralized theoretically but fragmented in practice.

Industry executives are clear-eyed about the consequences. Compliance now requires sustained operational investment, not just legal review. Seller verification, review transparency, pricing history disclosures, and risk management processes are resource-intensive, particularly for marketplaces.

Large sellers can absorb those costs. Smaller ones often can’t.

This is where E.U. regulation risks undermining its own objectives. Small-to-midsize businesses face higher relative compliance costs, increasing documentation demands, and greater exposure to takedowns or account suspensions. Even formally proportionate rules are, practically, overwhelming.

E.U.-based merchants often fear unfair competition, as their businesses are easier to supervise and sanction than foreign rivals. The result, the merchants assert, is the opposite of the level playing field that policymakers intend.

Accessibility and More

One area of consensus is accessibility.

What was once a “nice to have” is rapidly becoming a legal requirement under the European Accessibility Act and national implementations. Ecommerce interfaces, checkout flows, customer communications, and terms and conditions increasingly fall within scope.

From my perspective, accessibility is also an operational tactic. Merchants that invest early tend to have better user experiences, fewer complaints, and stronger trust metrics. Latecomers often find that remediation is far more expensive.

Moreover, clear disclosures, transparent pricing, verified reviews, accessible design, and robust documentation increasingly function as trust indicators, differentiating serious merchants from opportunists.

In that sense, E.U. regulation indirectly drives performance. Merchants who integrate compliance into operations and brand strategy tend to perform better over time.

The trajectory of E.U. ecommerce regulation is toward more accountability and oversight — consumer protection over transactional speed. Whether that balance is ideal remains open to debate. For merchants selling into Europe, however, it’s a fixed condition of success.

WooCommerce WordPress Plugin Exploit Enables Fraudulent Charges via @sejournal, @martinibuster

The popular WooCommerce Square plugin for WordPress vulnerability enables unauthenticated attackers to uncover credit cards on file and make fraudulent charges. The vulnerability affects up to 80,000 installations.

WooCommerce Square WordPress Plugin

The WooCommerce Square plugin enables WordPress sites to accept payments through the Square POS, as well as synchronize product inventory data between Square and WooCommerce. Square plugin enables a WooCommerce merchant to support payments through Apple Pay®, Google Pay, WooCommerce Pre-Orders, and WooCommerce Subscriptions.

Insecure Direct Object Reference

The vulnerability in the plugin arises from an Insecure Direct Object Reference (IDOR) vulnerability, a flaw that happens when critical data is exposed in URL file parameters, such as identification numbers, which then enables an attacker to manipulate that data without proper access that would normally prevent them from accessing those files.

The Open Worldwide Application Security Project (OWASP) defines IDOR as:

“Insecure Direct Object Reference (IDOR) is a vulnerability that arises when attackers can access or modify objects by manipulating identifiers used in a web application’s URLs or parameters. It occurs due to missing access control checks, which fail to verify whether a user should be allowed to access specific data.”

Exploiting the vulnerability does not require that the attacker acquire any level of authentication or permission levels, making it easier for them to launch an attack on affected websites.

According to a Wordfence advisory:

“The WooCommerce Square plugin for WordPress is vulnerable to Insecure Direct Object Reference in all versions up to, and including, 5.1.1 via the get_token_by_id function due to missing validation on a user controlled key. This makes it possible for unauthenticated attackers to expose arbitrary Square “ccof” (credit card on file) values and leverage this value to potentially make fraudulent charges on the target site.”

There are multiple versions of the WooCommerce Square plugin that are patched, it’s recommended that users of the plugin update to at least one of the following versions:

  • 4.2.3
  • 4.3.2
  • 4.4.2
  • 4.5.2
  • 4.6.4
  • 4.7.4
  • 4.8.8
  • 4.9.9
  • 5.0.1
  • 5.1.2

The CVSS severity vulnerability score is rated at 7.5, indicating it’s a dangerous vulnerability that can be remotely exploitable but is mitigated by a constraint that keeps it from being rated as “Critical.”

Featured Image by Shutterstock/IgorZh

Apple Selects Google’s Gemini For New AI-Powered Siri via @sejournal, @MattGSouthern

Apple is partnering with Google to power its AI features, including a major Siri upgrade expected later this year.

The companies announced the multi-year collaboration on Monday. Google’s Gemini models and cloud technology will serve as the foundation for the next generation of Apple Foundation Models.

“After careful evaluation, Apple determined that Google’s AI technology provides the most capable foundation for Apple Foundation Models and is excited about the innovative new experiences it will unlock for Apple users,” the joint statement said.

What’s New

The partnership makes Gemini a foundation for Apple’s next-generation models. Apple’s models will continue running on its devices and Private Cloud Compute infrastructure while maintaining what the company calls its “industry-leading privacy standards.”

Neither company disclosed the deal’s financial terms. Bloomberg previously reported Apple had discussed paying about $1 billion annually for Google AI access, though that figure remains unconfirmed for the final agreement.

By November, Bloomberg reported Apple had chosen Google over Anthropic based largely on financial terms.

Existing OpenAI Partnership Remains

Apple currently integrates OpenAI’s ChatGPT into Siri and Apple Intelligence for complex queries that draw on the model’s broader knowledge base.

Apple told CNBC the company isn’t making changes to that agreement. OpenAI did not immediately respond to a request for comment.

The distinction appears to be between the foundational models powering Apple Intelligence overall versus the external AI connection available for certain queries.

Context

The deal arrives as Google’s AI position strengthens. Alphabet surpassed Apple in market capitalization last week for the first time since 2019.

The default-search deal between Google and Apple has been under scrutiny after U.S. District Judge Amit Mehta ruled Google holds an illegal monopoly in online search and related advertising. In September 2025, he did not require Google to divest Chrome or Android.

Apple had originally planned to launch an AI-powered Siri upgrade in 2025 but delayed the release.

“It’s going to take us longer than we thought to deliver on these features and we anticipate rolling them out in the coming year,” Apple said at the time.

Google introduced its upgraded Gemini 3 model late last year. CEO Sundar Pichai said in October that Google Cloud signed more deals worth over $1 billion through the first three quarters of 2025 than in the previous two years combined.

Why This Matters

I covered this partnership in November when Bloomberg first reported Apple was paying Google to build a custom Gemini model for Siri. Today’s joint statement confirms what was then unattributed sourcing.

The confirmation matters because it extends Gemini’s reach into one of the largest device ecosystems in the world. Apple has said Siri fields 1.5 billion user requests per day across more than 2 billion active devices. That installed base gives Gemini distribution Google couldn’t match through its own products alone.

The competitive signal is clearer now too. Apple evaluated Anthropic and chose Google. Eddy Cue testified in May that Apple planned to add Gemini to Siri, but today’s announcement frames it as a deeper infrastructure partnership, not just another assistant option.

If Siri becomes meaningfully more capable at answering queries directly, the implications mirror what’s happening with AI Overviews and AI Mode in search. More queries could be resolved without users reaching external websites.

Looking Ahead

The upgraded Siri is expected to roll out later in 2026. The companies haven’t provided a specific launch date.

Apple maintaining its OpenAI integration alongside the Google partnership suggests both relationships will continue, at least for now. How Apple balances these two AI providers for different use cases will become clearer as the new features launch.

Google’s UCP Checkout Brings New Tradeoffs For Retailers via @sejournal, @MattGSouthern

When Google announced that shoppers could complete purchases directly in AI Mode, the focus was on convenience and technical capability. A retailer who emailed Search Engine Journal raised different questions about what gets lost when the transaction moves to Google’s surfaces.

The retailer cited concerns that customers never visit the store, see accessory recommendations from other sellers, and lose brand connection when making purchases on Google.

The concern shows a tradeoff in Google’s Universal Commerce Protocol. Retailers gain potential access to customers at the moment of purchase intent. However, they may lose some of the brand environment, discovery patterns, and relationship-building that occur when shoppers visit owned sites.

What Changes When Checkout Leaves Your Site

The change affects several parts of how retailers interact with customers.

Cross-selling

Cross-selling may change shape. A customer buying a camera on your site might see lens recommendations, memory cards, or cases based on your merchandising strategy.

Google says it plans to add capabilities like discovering related products, applying loyalty rewards, and powering custom shopping experiences on Google, but it hasn’t detailed reporting, fees, or data-sharing for AI Mode checkout.

If loyalty rewards, saved preferences, and checkout work more smoothly on Google surfaces, some shoppers may prefer that experience even if retailers have less control over it. Whether that tradeoff benefits retailers depends on details Google hasn’t disclosed yet.

Brand Connection

Brand storytelling can get compressed into whatever product data feeds into Google’s systems. Retailers invest in site design, content, and navigation to communicate what makes them different. That investment may not fully transfer when the interaction happens in AI Mode’s standardized interface.

The customer relationship dynamics change. Retailers traditionally owned the full transaction flow: discovery, consideration, purchase, and post-purchase communication. For orders completed inside AI Mode, Google would host more of the discovery and checkout experience on its own surfaces, while retailers remain the seller of record.

The degree to which retailers can access customer journey data that normally informs merchandising and marketing is unknown.

The Amazon Parallel

The situation resembles dynamics that already exist with Amazon marketplace sellers. Third-party sellers on Amazon get access to massive customer traffic. Marketplace sellers often accept less control over the customer experience and limited access to relationship signals compared with selling on their own sites.

Google’s protocol creates similar dynamics but extends them across the open web rather than within a single marketplace. Google positions UCP as an open standard, in contrast to Amazon’s closed marketplace model. The key difference: Amazon requires sellers to list products on its platform. UCP lets Google insert checkout capabilities into AI Mode while products technically remain on participating retailers’ inventory systems.

Whether that distinction leads to more data for retailers or a different platform dependency depends on reporting and data-sharing details Google hasn’t specified.

When It Makes Sense, When It Doesn’t

Some retail business models rely heavily on price, convenience, and fulfillment speed. For these retailers, losing the site visit may matter less if UCP delivers customers when they’re ready to buy.

Other retailers compete on curation, brand experience, and discovery. A customer visiting a specialty outdoor gear retailer expects to explore complementary products, read buying guides, and engage with brand content. Moving more of the purchase flow onto Google surfaces could reduce how much of that value proposition happens on a retailer’s site.

The calculation also depends on customer acquisition costs. For example, if you’re paying $30 to acquire a customer through Google Ads and they buy a $50 product on your site, the unit economics work when you can cross-sell or build long-term relationship value. If checkout happens on Google’s surface and you can’t cross-sell or retarget, the same acquisition cost may not be worth it.

What’s Known Versus What’s Speculation

Google said eligible U.S. retailers will be able to participate in UCP checkout through AI Mode in Search and the Gemini app. Google says retailers remain the seller of record and can customize the integration.

A separate Google Developers blog post explains that merchants remain the Merchant of Record and highlights an embedded option for a customized checkout experience. But the announcement didn’t detail the data-sharing arrangement, fee structure, or the funnel-level reporting retailers will receive for AI Mode checkout events.

The protocol is described as “open,” but adoption requirements, integration complexity, and whether non-Google AI systems can use it are unclear.

Google’s Business Agent feature demonstrates one use of the new protocol: branded AI chat appears in Search results for participating retailers, but the interaction occurs on Google’s platform.

Some analysts frame the change as existential, using terms like “extinction event” for certain retail models. That’s based on assumptions about adoption rates, customer behavior, and competitive dynamics that haven’t played out yet.

The more measured question retailers are asking: Does this create fragmentation where they need to optimize for multiple checkout flows, or consolidation where Google becomes the dominant transaction layer for product searches?

Questions Without Clear Answers

Three implementation details will likely determine how disruptive AI Mode checkout becomes for retailers:

  1. Merchant Center control: whether participation is explicitly opt-in and retailers can limit checkout to specific products or categories.
  2. Measurement: what reporting retailers get for actions on Google surfaces and whether AI Mode orders can be distinguished from standard site conversions.
  3. Customer and journey data: what signals, if any, come back to retailers to support lifecycle marketing and merchandising decisions.

Google has outlined the direction for UCP but hasn’t detailed these operational components.

Looking Ahead

Google said UCP checkout will roll out to eligible U.S. retailers soon, but hasn’t provided specific timing. Business Agent, which puts branded AI chat on Search results, went live Jan. 12.

Retailers questioning the tradeoffs between visibility and control face a pattern that’s played out before with Amazon, Google Shopping, and social commerce. Early participants gain access to new traffic sources but accept platform rules they don’t control. Late adopters may find themselves at a disadvantage.

The core question several retailers have raised is: Can they maintain the brand differentiation and relationship-building that justified creating owned channels when the transaction occurs on someone else’s platform?

The protocol is too new to know yet.


Featured Image: michnik101/Shutterstock

10 Hard Truths About PPC: Insights From Last Year’s Best Debates For 2026 via @sejournal, @siliconvallaeys

Hosting my podcast, gives me a front-row seat to the unfiltered reality of our industry, the gritty, “in-the-trenches” reality shared by experts who manage millions in spend.

Last year, my guests, including Greg Finn, Christine “Shep” Zirnheld, Julie Friedman Bacchini, Andrew Lolk and Shawn Walker didn’t hold back. They dismantled “best practices,” called out platform biases, and highlighted exactly where the algorithms fail without human hands.

Here are the 10 most interesting (and sometimes uncomfortable) things my guests shared last year that you can take forward for 2026.

1. Google Is “Shaking The Couch Cushions” (And You’re The Couch)

We need to stop pretending Google’s incentives are perfectly aligned with ours. As Greg Finn and Christine Zirnheld from “Marketing O’Clock” pointed out, Google is, ultimately, a for-profit company, and while it remains an important advertising partner, its objectives don’t always perfectly align with what’s best for advertisers.

Finn put it perfectly: Have you ever noticed that the “Recommendations” tab always suggests raising your budget but never lowering it? That bias is literally built into the UI. With CPCs hitting record highs, “success” for the platform often just means “more revenue” for the shareholder.

And we’ve seen this play out in the data. Optmyzr analyzed more than 17,000 Google Ads accounts and found no consistent correlation between a high Optimization Score and strong performance. In fact, many of the best-performing accounts improved not by accepting Google’s recommendations, but by selectively rejecting them and focusing only on fixes that actually moved CPA, ROAS, or profit.

So, the takeaway is simple: Stop treating recommendations as gospel. Treat them as upsells, because the data shows that blindly following them doesn’t reliably help advertisers, but it does reliably help Google.

2. Automation Without Guardrails Is Just “High-Speed Waste”

The consensus from Shawn Walker from Symphonic Digital, Finn, and Julie Friedman Bacchini, President & Founder of Neptune Moon & Managing Director of PPC Chat, was unanimous: AI can execute, but it cannot strategize.

Walker noted that without strict conversion quality thresholds, Smart Bidding inevitably chases “cheap junk leads” because they are the easiest conversions to get. Meanwhile, Julie warned about “algorithm drift,” where a campaign slowly expands into irrelevant search terms because it thinks it’s being helpful.

Automation is necessary for modern account management, but that doesn’t mean “set it and forget it.” Your job isn’t moving bids anymore, it’s designing the right layers of automation and guardrails so the algorithms work, not the other way around.

I recently tested how well AI could diagnose a drop in conversions, and it confidently identified the campaign’s limited budget as the cause. The reasoning was simple: Some keywords were still receiving impressions while others weren’t, so the budget must be the bottleneck. But that didn’t make sense. Budget constraints usually affect campaigns broadly, reducing visibility across the board rather than selectively shutting off individual keywords.

When only certain keywords go dark, the more plausible explanation is a bidding issue. And if bidding is automated, that often indicates the algorithm deems those keywords as lower quality, resulting in lowered bids and ultimately, disappearing impressions.

The bigger point is this: AI often answers with confidence before it answers with accuracy. It can absolutely help you refine ad copy or strengthen relevance, but it still struggles to understand the nuanced and often counterintuitive interdependencies within a PPC account. In other words, it can assist with execution, but it’s not yet as reliable as a strategist.

3. The “Rule of 30” Is The New Law Of Gravity

One of the most practical takeaways of the year came from Walker. We often debate how much data Smart Bidding needs, but Shawn gave us the math:

You need ~30 conversions per campaign, per 30 days.

Not per account. Not across shared budgets. Per campaign. Below that threshold, the machine is just guessing. If you’re wondering why your small campaigns are volatile, it’s not bad luck; it’s bad math. You are starving the algorithm.

In Optmyzr’s 2024 study on the impact of bidding strategies on performance, we saw the same. 50+ conversions per month are ideal. 30+ is good, and anything less isn’t great. However, I would like to add one refinement to Shawn’s point. The real threshold isn’t “30 conversions per campaign,” but enough volume on the conversion goal/actions Smart Bidding is optimizing toward. Google’s systems can use broader, account-level conversion patterns to reduce data scarcity, and account-default goals and portfolio strategies are designed to expand the learning set beyond a single campaign.

What truly matters is having enough volume for the action you want Smart Bidding to optimize toward. If multiple campaigns are all working toward the same conversion event, they can effectively “pool” their learnings. In other words, campaigns don’t have to hit 30+ conversions individually as long as the underlying conversion action has enough aggregate volume for the system to learn and make reliable decisions.

4. “Soft Conversions” Are The Backbone Of SMB Success

So, what do you do if you can’t hit that magic number of 30? You have to feed the beast something else.

Guests heavily advocated for moving up the funnel. Walker detailed the necessity of “engaged visitor” signals, custom metrics like a user scrolling to a certain depth or spending time on site, fired only once per unique user to prevent inflation.

Whether it’s a PDF download, an add-to-cart, or a pricing page visit, these “soft” signals are no longer optional crutches; for smaller accounts, they are the only way to generate enough data density for Smart Bidding to function.

In other words, micro conversions still matter. They give Smart Bidding a richer sequence of intent signals to learn from: Did the user compare products? Did they view pricing? Did they return within 24 hours? Did they engage with interactive tools? In my experience, these micro-signals are what prevent smaller accounts from starving the algorithm and ultimately help it recognize high-quality users earlier in the journey.

5. SKAGs Are Finally, Truly Dead

If you are still using single keyword ad groups (SKAGs) in 2025, you are fighting a war that ended years ago. Bacchini was blunt: SKAGs have “run their course.”

The granular control we used to prize is now a liability. It fragments your data, making it harder for the AI to learn. Andrew Lolk, Founder at SavvyRevenue, backed this up, warning that over-segmenting campaigns destroys shared learnings. The winning structure for 2025 is radically simple: Consolidate until the data proves you need to separate.

What does that mean? Well, you should split campaigns when there are business reasons, like different bid targets, different promotions, etc. Put simply, you separate campaigns only when there’s a strategic reason, such as assigning different ROAS targets to products with different margins, or isolating seasonal inventory, like ski jackets, from evergreen categories like swimwear, so each can be optimized on its own performance curve.

And while single-keyword ad groups are outdated, single-theme ad groups (STAGs) have become the modern, more effective alternative. Instead of isolating each keyword, STAGs cluster queries that share the same intent and require the same message, giving Google enough data to learn without sacrificing relevance.

A better way to think about it:

A STAG isn’t just “all running shoes terms,” but it’s “all running shoes for distance training terms,” or “all waterproof trail-running shoes terms.” Each theme represents a specific user intent that warrants a specific ad and landing page combo

So, a more realistic STAG example might look like:

Theme: Long-distance running shoes

  • “best long-distance running shoes”
  • “marathon training running shoes”
  • “long-distance running shoes men”

All different keywords, but they relate to the same core motivation, the same benefits to highlight, and the same landing page experience.

STAGs preserve the messaging control SKAGs once offered, but without the data fragmentation that hinders Smart Bidding from working at its best. They give you messaging precision while still feeding the algorithm enough volume to learn.

6. Stop Splitting Performance Max

Speaking of consolidation, Lolk had some strong words for how we manage Performance Max. A common mistake is splitting PMax campaigns by asset group, brand, or generic themes without a distinct ROAS target.

His take? “Splitting = Starving.”

PMax campaigns don’t share data well. If you split them, you force each new campaign to learn from scratch, requiring double the volume to stabilize. Unless you have a radically different ROAS target for a specific category, keep it together. And for the love of PPC, stop running “feed-only” PMax, he says. Just use Standard Shopping if you need that control.

7. Search Is Making A Quiet Comeback

In a surprising twist, we repeatedly heard that ecommerce brands have overemphasized PMax and Shopping, leaving money on the table in Search.

Lolk argued that Search is reclaiming its role as the high-intent workhorse because it offers what PMax cannot: diagnostic visibility and true messaging control. You can’t capitalize on a weather trend or a specific seasonal moment if you’re waiting for PMax to “learn” about it. Search lets you move fast, and it lets you control the landing page, a lever we’ve severely undervalued lately.

8. Your Competitive Advantage Is Now “Post-Click”

With Google automating bids, targeting, and even the creative process, what is left for us? Bacchini says the answer lies after the click.

Differentiation is the new battleground. If your offer is weak or your landing page is generic, no amount of bid tweaking will save you. Clients often dramatically underestimate their competitors and overestimate their own value propositions. As PPC pros, our value add is shifting from “technical setup” to “business consultancy,” fixing the offer, the positioning, and the user experience.

9. Generative AI Is Your New Junior Strategist

We moved past the “AI will write my ads” hype and got into real use cases.

  • Zirnheld explained that AI has become her go-to tool for smoothing the communication gap between complex PPC work and client understanding. She uses it to draft clearer explanations, refine messaging, and spark creative concepts she can develop further. AI helps her accelerate the early stages, allowing her to spend more time on higher-value thinking.
  • Walker described how AI has become a true technical force multiplier inside his workflow. He now uses it to write Google Ads scripts, build custom tools, generate and debug code, and automate tasks that previously required days of manual effort. AI effectively turns his ideas into working prototypes, allowing him to iterate faster and push the boundaries of what one PPC manager can build.
  • Bacchini shared that AI has transformed how she researches competitors and analyzes positioning. Instead of manually combing through search results and landing pages, she can feed everything into AI and instantly see patterns, themes, and gaps. It gives her a strategic overview in seconds, helping her craft sharper messaging and understand where clients stand in a crowded landscape.

The consensus? AI won’t replace you, but an expert using AI will absolutely replace an expert who refuses to touch it.

In Silicon Valley, we used to lionize the idea of the 10x engineer, the kind of person who could out-code an entire team, see around corners in the architecture, and somehow ship things at a pace that felt almost unfair. But lately, the stories I’m hearing in my own network tell a different tale: Many of those “10x” engineers are starting to fall behind the so-called mediocre ones who are simply pushing the limits of what they can do with AI by their side.

And this no longer applies just to engineering. In every role, those who learn to partner with AI will outperform those who rely solely on talent and hustle.

10. The “Search” We Knew Is Disappearing

Finally, we touched on the existential shift. Shep mentioned she now uses Perplexity.ai for research more than Google. Greg Finn highlighted the instability of AI Overviews.

As I’ve been saying all year, we’re witnessing a dramatic shift from keywords to prompts. Search is no longer just about matching a query to an ad; it’s about connecting users who do complex prompts with solutions, and maybe showing an ad if that would be helpful.

In an AI-driven ecosystem, the “prompt” becomes the new keyword: a richer, more contextual signal that reflects not just what users type, but what they’re trying to accomplish. Advertisers who still think in terms of isolated keywords will fall behind; those who think in prompts, tasks, and intent paths will thrive.

The Bottom Line

The work of the modern PPC marketer continues to shift from pulling levers to thinking critically about the levers being pulled on our behalf. Automation is no longer optional, but neither is oversight. The winners this year were the advertisers who understood where algorithms shine, where they stumble, and where a human needs to step in with context that the machine simply doesn’t have.

And this evolution is far from over. As we head into 2026, I expect the debates on PPC Town Hall to get even more interesting. We’ll likely spend less time arguing about whether to adopt AI, and more time unpacking how to direct it, how to measure it, and how to prevent it from homogenizing every account it touches. We’ll explore what happens when prompts truly become the new keywords. And we’ll hear from practitioners who find creative, sometimes surprising ways to bend automation back toward profitability and strategy, rather than convenience.

If 2025 was the year we learned to tell the machine “No,” then 2026 may be the year we learn how to tell it “Do this and here’s why.” The marketers who thrive will be those who don’t just manage campaigns, but manage systems, using judgment, experimentation, and clear intent to guide increasingly powerful tools.

I’m looking forward to another year of unfiltered conversations on PPC Town Hall and to seeing what new hard truths (and opportunities) we uncover together.

More Resources:


Featured Image: Anton Vierietin/Shutterstock

Agentic Commerce: What SEOs Need To Consider (ACP & UCP) via @sejournal, @alexmoss

In my last post, I referenced how there is now a growing split between the “human” web and the “agentic” web, where AI agents are becoming an additional audience/profile alongside the “traditional” human visitors we have been optimizing for for years.

This shift is now becoming more aggressive, especially when it comes to the transactional web in the form of agentic commerce. 2026 will see the accelerated adoption of this method, where store owners will now have to cater to and optimize for both the human and agentic visitor concurrently.

The recent launch of Universal Commerce Protocol (UCP) from Google underlines the push towards this integration of AI and ecommerce experiences.

What Is Agentic Commerce?

Agentic commerce is when agents complete purchases autonomously on behalf of users. Now, a human can engage with a large language model platform, where the agent will browse and purchase from a site on behalf (and with approval) of the human. Not only is the agent acting as the gatekeeper for information gain and influencing decisions, but they are also acting as the gatekeeper for the transaction itself.

This is a step beyond delegating an LLM to act as a recommendation agent or a method of validation, but now transfers authority to actually transact.

Enter ACP (Agentic Commerce Protocol)

On Sept. 29, 2025, OpenAI and Stripe announced their partnership and, within this, launched ACP, an open standard that defines how AI agents, merchants, and payment providers interact to complete agentic and programmatic purchases.

On the same day, OpenAI detailed platforms that were immediately able to benefit from agentic commerce, including Shopify and Etsy, with others following suit using the protocol, including Walmart and Instacart.

From a CMS point of view, Shopify hit the ground running by enabling ACP for over 1 million merchants from the day of the announcement. WooCommerce has followed suit more recently by announcing it will be part of Stripe’s launch of Agentic Commerce Suite, which will allow even more merchants the ability to sell products through various AI-based platforms.

But ACP was launched three months ago, and as we now know, things move fast…

UCP: Google’s Answer To The Immersive Agentic Commerce Experience

Google just announced the launch of Universal Commerce Protocol, which widens some boundaries applied by ACP by tackling a broader problem, providing any AI surface (like Search AI Mode or Gemini) a common language to discover merchants, understand their capabilities, and orchestrate full journeys from discovery through order management, as well as engagement beyond a purchase (also made seamless using Google Pay). This is also done by integrating with other existing standards, including APIs, Agent2Agent (A2A), and the Model Context Protocol (MCP).

Aspect ACP (OpenAI) UCP (Google)
Primary focus Agent‑led commerce in ChatGPT and ACP‑aware agents.​ Unified rail for many agents/surfaces talking to merchants.
Journey Coverage Product feed, checkout, fulfillment, delegated payment. Discovery, checkout, discounts, fulfillment, order management, payments.
Driver OpenAI + Stripe & ecosystem partners. Google + retailers/platforms (Shopify, Etsy, Walmart, etc.).

Here, Google adds to the possibilities of the commerce experience, where SEOs can adopt both ACP and UCP in order to accommodate both platforms and ecosystems.

This will only become more immersive as 2026 progresses. Google has a great advantage of knowing a lot about individual users, and features such as AI features inside Gmail illustrate Google can utilize and understand much more context about individuals in order to provide an even more frictionless experience.

Why This Matters For SEOs

As SEOs, we’ve spent over a generation optimizing for humans, albeit for various personas or ICPs. While we are still required to do this, we must now include the agent as an additional consideration. This does pose another challenge: that AI agents don’t browse pages but instead query APIs, parse product feeds, and evaluate structured data.

As such, we need to optimize for this. Maybe I can give it a name…

ACO: Agentic Commerce Optimization

I don’t want to trigger you by introducing yet another acronym to what seems to be a previous year of new acronyms, but for the sake of this post, let’s pretend that ACO is something you’ve been told to do now, as well as SEO, even though this is still SEO.

What would I need to consider and optimize for for successful ACO?

  • Crawlability: Agents still follow links, take journeys, and understand IA.
  • Format: Content needs to be concise with less fluff, but enough to ensure unique value has been added, and that it provides consistency throughout the site as a whole.
  • Structured Data: Agents will become more reliant on existing standards, especially if they’re open source.
  • Brand Authority And Sentiment: Populating your products well is, of course, paramount, but without positive brand sentiment, you have the challenge of convincing the agent to cite you as part of that discovery, then have to convince the human who will have that feedback presented to them. Third-party perspectives will become a larger contribution towards some of the agents’ grounding procedures before any agentic commerce begins.

Sounds familiar, right? While ACP is a connector between your site and the platforms that allow agents to use it, and CMSs are out there to make that connection as seamless as possible, this isn’t just a switch where, when switched on, is automatically optimized.

ACO = SEO.  

Schema.org Is The Glue

Pascal Fleury presenting structured data options at Search Central Live Zurich December 2025
Image Credit: Alex Moss, January 2026

Last month at Google Search Central Live in Zurich, Pascal Fleury went into detail about structured data for Shopping, where we can see that, while “schema.org is the glue that holds [structured data] together,” there are still other industry standards, such as GS1, that will add even more granular detail to products that will not only help inform agents on really specific details but also understand that you’re a great source of information to continue ingest from.

Product schema, pricing, availability, reviews, FAQs, shipping options, and other logistics, loyalty schemes –  all of this structured data will need close optimization. If it’s missing or incorrect, you’re invisible to agent-mediated discovery.

Test The Agents

Even before your store is ACP-enabled, test how agents perceive your products. Ask platforms about products in your category. Do they surface your brand? How do they describe your products and complementary offerings? What information are they presenting, from both first-party and third-party perspectives? And more importantly, what is missing that you expected to be present?

Then, enable. What are the differences? Compare the results.

What Can I Do About It Now?

ACP

For WooCommerce and Wix, you will unfortunately need to join Stripe’s waitlist for ACS. Shopify users also have to join their own waitlist. Until then, we will have to wait until full rollout, but expect this to accelerate in Q1 of 2026.

If you work with a site where you have to integrate ACP directly into your CMS, any early adopters will perhaps benefit from early discovery, while the other CMSs catch up and competition is lower. So here, while this will require more resources, you will be able to take advantage of what ACP has to offer while most wait for their CMS platform to create the solution for them.

UCP

This is extremely fresh information, but I suggest that some time to understand it in detail, as well as experiment where possible using their documentation and GitHub repo, I know that’s how a lot of my time will be spent in the next few weeks.

More Resources:


Featured Image: Koupei Studio/Shutterstock

WordPress X Account’s ‘Childish’ Trolling Causes Backlash via @sejournal, @martinibuster

An official WordPress.org social media account was used to troll the open source movement to decentralize the WordPress plugins and themes repository, creating what some feel was an undignified, even “childish”, representation of the WordPress community.

What Is The FAIR Project?

The Federated And Independent Repositories project is an open-source initiative that was launched in 2025 in response to actions by Matt Mullenweg and Automattic that exposed a weakness in how plugins and themes are distributed to WordPress sites. The project was initiated after Mullenweg cut off WP Engine from updating their plugins, disrupting the proper functioning of thousands of websites.

The FAIR goal of the FAIR project is to decentralize the distribution of WordPress plugins and themes to protect against one person from disrupting the free distribution of software.

FAIR is backed by open source giant Linux, announced in June 2025. The official announcement explained that the purpose of FAIR is to create a “vendor-neutral” method for distributing WordPress software within a trusted environment, writing:

“Vendor-neutral package management for content management systems like WordPress provides critical universal infrastructure that addresses the new realities of content, e-commerce and AI.

The FAIR Package Manager project helps make plugins and tools more discoverable and lets developers choose where to source those plugins depending on the needs of their supply chain. By giving commercial plugin developers, hosts, and application developers more options to control the tools they rely on, the FAIR Package Manager project promotes innovation and protects business continuity.”

What Caused An Issue With FAIR?

A WordPress user recently experienced a temporary problem updating their website using the FAIR repository, forcing them to manually SFTP the software updates to their server.

They posted on X:

“Here I am updating one of my sites for the new year, and it looks like FAIR broke my plugin and theme updates.”

After updating their site they returned to X with more thoughts about their experience with FAIR:

“Glad this was just a “for fun” site and not something critical. I like experimenting with stuff in the WordPress ecosystem, but this is a bit too experimental for my taste. Going back to stock updates, at least until 2.0.

…This is making me rethink how I organize my domains and sites. Should probably just set up a sandbox for things like this, but then again… the squeaky wheel gets the grease. If it’s all locked away in a sandbox, I’ll forget to ever touch it.”

There was an issue with an update to FAIR version 1.2.2. According to the release notes:

“FAIR Connect 1.2.2 Release Announcement

Version 1.2.2 of FAIR Connect is a fast follow up to our version 1.2.1 release. This release fixes a fatal error introduced in 1.2.1 that impacts the updating process.

If you previously updated to 1.2.1, you will need to perform this update manually.”

So apparently there’s an issue with updating the FAIR Connect plugin which requires manually deactivating the FAIR Connect plugin, downloading the updated version of the plugin from the FAIR repository, then manually uploading the plugin from the WordPress admin plugin dashboard (unless the site is unavailable, which necessitates SFTP’ing the updated plugin).

WordPress Trolls The FAIR Project

The official WordPress.org X account posted the following comment about the FAIR project:

“Looks like the Federated and Independent Repository project is going great. This is clearly going to rock the WordPress world. We don’t know how we’ll continue without these contributors. Maybe they need some REST.”

The post was highly unusual for the WordPress X account because it’s normally a feel-good destination of announcements and inspiration related to WordPress. The unprofessional tone of the post caught many in the WordPress community by surprise.

One person shared their disappointment:

“Hi Matt! These comments aren’t clearly going to rock the atmosphere in our community too. So, http://WP.org never had issues?”

RapidLightnings responded:

“These people working at or for WordPress are so childish and unprofessional. Professional people wouldn’t care or would not post stuff like that on official accounts.”

Responses Hidden By WordPress

There were additional responses that were hidden by WordPress:

Like this by o_be_one:

“For an OpenSource project, your take is toxic af.”

Rohan K called the post by the official WordPress account immature:

“Growing pains. Why are you gleefully gloating about this, when your immature and short-sighted actions led the creation of it? It makes you look bad.

Grow up.”

Aron Prins posted a one-word response:

“Ewww”

Thisbit commented on how it reflects poorly on the WordPress leadership:

“Shameful leadership.”

Jono Alderson reflected on the childishness of the tweet:

“Oh hush. Your misuse of this account for sniping is childish and tedious. Be better.”

Other posts were directed at Matt Mullenweg, with this one prematurely dancing on WordPress’s grave:

“SO HAPPY that AI is ending WordPress for good.
Ciao CattyMatty”

And this one:

“I’d say get a clue, but you’d probably steal it from another developer.”

Jono Alderson’s Response

Alderson started a new discussion to express his opinion about the WordPress troll-post:

“I love WordPress-the-software, but this kind of childish nonsense makes me ashamed and embarrassed to be associated with WordPress-the-brand. What childish, petty, unprofessional, shameful, amateur nonsense. All of these people need firing and replacing with capable grown-ups.”

The responses to Jono’s post generally expressed disappointment that the official WordPress account was used for trolling, with one person responding that it seemed crazy.

Featured Image by Shutterstock/AYO Production

Early AI Signals from Holiday Sales

Traffic from various AI sources to ecommerce shops leapt significantly during the 2025 Christmas season, yet still accounted for a tiny share of actual, direct visits.

Adobe reported a record $257.8 billion in U.S. 2025 online sales from November 1 through December 31, up 6.8% from 2024. The data reflects U.S. merchants on the Adobe Analytics platform, which excludes Amazon and most smaller sellers.

The report provides many holiday highlights. In 2025 mobile commerce drove more than 50% of online sales during the Christmas shopping season for the first time. Buy-now-pay-later loans hit a milestone, reaching $20 billion in online spending, up 9.9%.

Thus given the overall holiday sales activity, why focus on AI at all? The answer is because AI’s impact will likely be massive. Salesforce, for example, reported that AI influenced 20% of U.S. Christmas retail sales in 2025.

Vivek Pandya, lead analyst at Adobe Digital Insights, stated, “This 2025 holiday season, consumers embraced generative AI more than ever as a shopping assistant in their purchasing decisions.”

Image from Salesforce of a male and female holiday shopper

According to Salesforce, AI influenced 20% of U.S. Christmas retail sales in 2025. Image: Salesforce.

The Caveat

Adobe reported a striking 693% increase in AI-driven holiday traffic to ecommerce sites in 2025. But the report does not provide the baseline volume, AI’s share of total referrals, or AI’s share of total revenue.

That omission matters. Growth off a small baseline can produce dramatic percentages. Adobe itself reported a much larger jump — roughly 1,300% — for AI traffic during the 2024 holiday season.

The takeaway is not that AI drove the 2025 holiday season. It did not. But AI-related shopping is rising quickly enough to warrant attention, even if the raw totals remain small for now.

Zero Click Risk

AI’s direct ecommerce value is difficult to quantify today, but merchants can learn from industries where AI discovery is having an impact.

Consider digital publishing. In September 2025, Penske Media — owner of Rolling Stone, Billboard, Variety, and other outlets — sued Google, arguing that AI Overviews used Penske’s content while reducing click-through traffic and revenue. Penske’s affiliate revenue was allegedly down by more than a third from peak levels. Traffic to its websites had halved.

The case highlights a critical shift: AI-driven discovery does not always result in traffic.

In the traditional search pattern, users click links. In AI search, users often get what they need directly on the results page. It is the same “zero-click” dynamic publishers have dealt with for years. AI answers now amplify this impact.

Ecommerce may be heading in a similar direction. Even if AI referrals remain small, AI systems may increasingly influence purchase decisions without always sending shoppers to a retailer’s website.

AI Traffic

AI-driven store visitors may behave differently from shoppers arriving via traditional channels, and Adobe’s holiday data offers a few early clues.

One notable change is device usage. Some 73.4% of AI referrals came from desktop devices, even as mobile accounted for most overall ecommerce transactions.

At least for now, AI chat interfaces and search tools are often more usable on larger screens. Long-form responses, product comparisons, and multi-step research fit naturally into desktop workflows. Consumers may be comfortable researching with AI on a desktop and completing purchases on mobile.

Category patterns reinforce that behavior. AI referrals were most common in product groups where research and comparison matter, such as electronics, toys, appliances, video games, and personal care. These are not necessarily impulse buys. They benefit from explanation, differentiation, and context, all of which are strengths of AI answer engines.

There is also a reasonable theory that AI-referred shoppers are more qualified. A consumer who clicks after querying an AI assistant may have narrowed her choices. But AI interfaces and ads may alter what answer engines recommend, how they compare products, and which merchants appear.

Essentially, AI traffic patterns are still forming, attribution remains murky, and performance may swing quickly. It is worth monitoring, not overreacting.

What to Do

The Adobe and Salesforce data reinforce what many merchants already sense. Product discovery is changing, and AI may become a bigger part of it. Small-to-midsize merchants can respond without betting the business on speculative numbers.

Use platforms. The single best AI-commerce move for many SMB sellers is to use what their ecommerce platforms provide.

Shopify, for example, announced AI discovery integrations that pass structured product data directly to AI systems and support purchases inside chat and AI commerce experiences.

For merchants, that means AI readiness may increasingly be operational: maintain a “clean” product catalog with accurate attributes and structured product data so platforms can access and distribute it properly.

Use marketplaces. Marketplaces will likely become even more important in an AI-mediated shopping environment.

Amazon, Walmart, and similar marketplaces have the data and the scale to integrate AI shopping assistants. Merchants who sell in these channels can expect AI-powered recommendations to amplify the importance of quality product data, accurate inventory, and positive reviews.

Use ads. Paid acquisition has long been a reliable traffic source for online merchants. The reliance could increase in an AI era, particularly if organic discovery becomes less predictable.

Ads are already appearing in AI chat experiences. Merchants can garner at least some AI-driven recommendations and purchases from paid placements, sponsored suggestions, or marketplace advertising.

Measure carefully. AI discovery adds tracking ambiguity. Merchants should ensure analytics capture as much detail as possible in referral sources, landing page engagement, and conversion paths, even if AI traffic is small.

Keep optimizing. Finally, merchants should not give up on optimization.

The goal is to extend traditional search engine optimization techniques to AI. Setting aside the muddy definitions of SEO, GEO (generative engine optimization), and AEO (answer engine optimization), the desired outcome is the same. When shoppers ask, “Which air fryer is best for a family?” or “What toy is right for a seven-year-old?” the stores that provide the best answers for AI will be more likely to appear in the results.

Strong SEO practices carry over well. Clean product catalogs, accurate attributes, structured data, clear descriptions, and buyer-focused content marketing can help AI answer engines and ecommerce platforms understand a store’s goods.

Optimizing for AI commerce, then, is less about chasing new tactics and more about feeding platforms and AI systems better data.

Google Announces AI Mode Checkout Protocol, Business Agent via @sejournal, @MattGSouthern

Google announced tools that let shoppers complete purchases directly within AI Mode and chat with branded AI agents in Search results.

Users can purchase from eligible product listings on Google. Retailers are still the seller of record, while the checkout happens on Google surfaces instead of the retailer’s website.

Universal Commerce Protocol Powers AI Mode Checkout

Google launched the Universal Commerce Protocol, an open standard for what it calls “agentic commerce.” The protocol will power checkout on eligible Google product listings in AI Mode in Search and the Gemini app.

Google developed UCP with Shopify, Etsy, Wayfair, Target, and Walmart. More than 20 additional companies endorsed it, including Adyen, American Express, Best Buy, Mastercard, Stripe, The Home Depot, and Visa.

Shoppers will use Google Pay with payment methods and shipping info from Google Wallet. PayPal support is coming. UCP checkout starts with eligible U.S. retailers, with global expansion planned.

Business Agent Brings Branded Chat To Search

Business Agent lets shoppers chat with brands in Search results. Google describes it as a “virtual sales associate” that can answer product questions in the brand’s voice.

The feature goes live January 12 with Lowe’s, Michael’s, Poshmark, Reebok, and others. Eligible U.S. retailers can activate and customize the agent through Merchant Center.

Google plans to add capabilities for training agents on retailer data, providing product offers, and enabling purchases within the chat experience.

Direct Offers Pilot Tests Ads In AI Mode

Google also announced Direct Offers, a new ad pilot in AI Mode. It allows advertisers to offer exclusive discounts to people searching for products.

Google gave an example of a rug search where relevant retailers could feature a special 20% discount. Retailers set up offers in campaign settings, and Google determines when to display them.

Early partners include Petco, e.l.f. Cosmetics, Samsonite, Rugs USA, and Shopify merchants.

Why This Matters

Checkout in AI Mode means a user searching for a product can research, compare, and buy without ever reaching the retailer’s site.

For ecommerce sites, this changes the traffic equation. The sale still happens, but the site visit may not. Retailers participating in UCP gain access to high-intent buyers at the moment of decision. Those who don’t participate may find their products harder to surface when users expect to complete transactions without leaving Google.

Looking Ahead

Checkout in AI Mode rolls out to eligible U.S. retailers soon. Business Agent launches January 12. Direct Offers is in pilot with select advertisers.

Google said it plans to add new Merchant Center data attributes designed for discovery in AI Mode, Gemini, and Business Agent. The company will roll out the new attributes with a small group of retailers soon before expanding more broadly.


Featured Image: hafakot/Shutterstock

A new CRISPR startup is betting regulators will ease up on gene-editing

Here at MIT Technology Review we’ve been writing about the gene-editing technology CRISPR since 2013, calling it the biggest biotech breakthrough of the century. Yet so far, there’s been only one gene-editing drug approved. It’s been used commercially on only about 40 patients, all with sickle-cell disease.

It’s becoming clear that the impact of CRISPR isn’t as big as we all hoped. In fact, there’s a pall of discouragement over the entire field—with some journalists saying the gene-editing revolution has “lost its mojo.”

So what will it take for CRISPR to help more people? A new startup says the answer could be an “umbrella approach” to testing and commercializing treatments. Aurora Therapeutics, which has $16 million from Menlo Ventures and counts CRISPR co-inventor Jennifer Doudna as an advisor, essentially hopes to win approval for gene-editing drugs that can be slightly adjusted, or personalized, without requiring costly new trials or approvals for every new version.

The need to change regulations around gene-editing treatments was endorsed in November by the head of the US Food and Drug Administration, Martin Makary, who said the agency would open a “new” regulatory pathway for “bespoke, personalized therapies” that can’t easily be tested in conventional ways. 

Aurora’s first target, the rare inherited disease phenylketonuria, also known as PKU, is a case in point. People with PKU lack a working version of an enzyme needed to use up the amino acid phenylalanine, a component of pretty much all meat and protein. If the amino acid builds up, it causes brain damage. So patients usually go on an onerous “diet for life” of special formula drinks and vegetables.

In theory, gene editing can fix PKU. In mice, scientists have already restored the gene for the enzyme by rewriting DNA in liver cells, which both make the enzyme and are some of the easiest to reach with a gene-editing drug. The problem is that in human patients, many different mutations can affect the critical gene. According to Cory Harding, a researcher at Oregon Health Sciences University, scientists know about 1,600 different DNA mutations that cause PKU.

There’s no way anyone will develop 1,600 different gene-editing drugs. Instead, Aurora’s goal is to eventually win approval for a single gene editor that, with minor adjustments, could be used to correct several of the most common mutations, including one that’s responsible for about 10% of the estimated 20,000 PKU cases in the US.

“We can’t have a separate clinical trial for each mutation,” says Edward Kaye, the CEO of Aurora. “The way the FDA approves gene editing has to change, and I think they’ve been very understanding that is the case.”

A gene editor is a special protein that can zero in on a specific location in the genome and change it. To prepare one, Aurora will put genetic code for the editor into a nanoparticle along with a targeting molecule. In total, it will involve about 5,000 gene letters. But only 20 of them need to change in order to redirect the treatment to repair a different mutation.

“Over 99% of the drug stays the same,” says Johnny Hu, a partner at Menlo Ventures, which put up the funding for the startup.

The new company came together after Hu met over pizza with Fyodor Urnov, an outspoken gene-editing scientist at the University of California, Berkeley, who is Aurora’s cofounder and sits on its board.

In 2022, Urnov had written a New York Times editorial bemoaning the “chasm” between what editing technology can do and the “legal, financial, and organizational” realities preventing researchers from curing people.

“I went to Fyodor and said, ‘Hey, we’re getting all these great results in the clinic with CRISPR, but why hasn’t it scaled?” says Hu. Part of the reason is that most gene-editing companies are chasing the same few conditions, such as sickle-cell, where (as luck would have it) a single edit works for all patients. But that leaves around 400 million people who have 7,000 other inherited conditions without much hope to get their DNA fixed, Urnov estimated in his editorial.

Then, last May, came the dramatic demonstration of the first fully “personalized” gene-editing treatment. A team in Philadelphia, assisted by Urnov and others, succeeded in correcting the DNA of a baby, named KJ Muldoon, who had an entirely unique mutation that caused a metabolic disease. Though it didn’t target PKU, the project showed that gene editing could theoretically fix some inherited diseases “on demand.” 

It also underscored a big problem. Treating a single child required a large team and cost millions in time, effort, and materials—all to create a drug that would never be used again. 

That’s exactly the sort of situation the new “umbrella” trials are supposed to address. Kiran Musunuru, who co-led the team at the University of Pennsylvania, says he’s been in discussions with the FDA to open a study of bespoke gene editors this year focusing on diseases of the type Baby KJ had, called urea cycle disorders. Each time a new patient appears, he says, they’ll try to quickly put together a variant of their gene-editing drug that’s tuned to fix that child’s particular genetic problem.

Musunuru, who isn’t involved with Aurora, does not think the company’s plans for PKU count as fully personalized editors. “These corporate PKU efforts have nothing whatsoever to do with Baby KJ,” he says. He says his center continues to focus on mutations “so ultra-rare that we don’t see any scenario where a for-profit gene-editing company would find that indication to be commercially viable.”

Instead, what’s occurring in PKU, says Musunuru, is that researchers have realized they can assemble “a bunch” of the most frequent mutations “into a large enough group of patients to make a platform PKU therapy commercially viable.” 

While that would still leave out many patients with extra-rare gene errors, Musunuru says any gene-editing treatment at all would still be “a big improvement over the status quo, which  is zero genetic therapies for PKU.”