# Jonathan Gladbach

Jonathan Gladbach works with ecommerce clients and writes about Shopify, AI automation, and the tradeoffs businesses face when adopting new technology.

- Profile: https://b2binfluencer.marketing/creators/jonathan-gladbach/
- LinkedIn: https://www.linkedin.com/in/jonathangladbach
- LinkedIn followers: 3,814
- Topics: artificial-intelligence, ecommerce, ai-in-ecommerce
- Based on 10 dated posts, latest 2026-07-08

## Summary

Jonathan Gladbach is most useful for grounded ecommerce, Shopify, and AI automation analysis for operators.

- Best for: A DTC ecommerce brand with a live Shopify store planning practical AI automation.
- Not for: A mass-market consumer brand wanting high-reach sponsored posts and fast paid-social results.
- Check first: Confirm scope, fees, disclosure, approval steps, and recent post performance before committing spend.

### Takeaways

- Short-term growth plays can crowd out brand value, product quality, and useful content.
- An AI tool took over an hour for reporting that usually takes 20 to 30 minutes.
- AI that can change a live Shopify store needs permission and preview before acting.

## Main ideas

- **Short-term growth plays are crowding out the thinking that differentiates a brand**: Gladbach argues that ecommerce differentiation is shifting away from quality and features toward long-term thinking, while the attention economy — reinforced by AI — makes that harder. The post lists five decisions seen across the market: scaling on Facebook or TikTok for fast results instead of investing in brand or community; making a mass-produced product cheaper by substituting a lower-quality ingredient; cutting content that helps customers to fund an AI takeover of customer support; building brand identity and critical UX with AI; and choosing the flashy brand template over the higher-converting one. The conclusion: the highest-growth brands in the next few years will think beyond the next quarter.
- **Test AI on real work before believing it saves time**: Gladbach tried handing monthly client reports — GA4, Klaviyo, conversion metrics, insights and recommendations — to Claude Cowork. The job normally takes 20 to 30 minutes. They wrote instructions for the reports, loaded assets through the browser plugin, and watched the run go past an hour as it stalled on simple steps such as changing a date in GA4. Their expectation: AI should do this work faster and mostly more accurately. The post ends with a choice: pull the data manually and finish in 20 minutes, or let the tool run overnight.
- **AI that can change a live store needs permission and preview before it acts**: After Shopify released its MCP, Gladbach argued that connecting AI to a live store to make changes is risky: it could delete every product or damage the codebase, especially when non-technical ecommerce staff make the changes. Rather than reject the technology, they propose a 'safe-mode' MCP with automated testing, deployment only after permission, and a change log plus preview mode spanning code, design, and Shopify objects. They close by offering to partner with a store to build it.
- **Judge platform announcements by whether a merchant can act on them**: Gladbach calls a Shopify press release one of the most confusing they've seen. Shopify announced something it had already teased six months earlier as 'coming soon'; now it is described as both 'new' and 'coming soon,' without clarifying what it is or whether people can buy inside ChatGPT. The screenshots leave that question open. The ask: marketers should release things that make sense.

## Work to read

- [Why long-term ecommerce strategy is getting harder](https://www.linkedin.com/posts/jonathangladbach_ive-been-reading-and-thinking-a-lot-about-activity-7450707922227052544-eO2W)
- [Reading Shopify announcements with a skeptical eye](https://www.linkedin.com/posts/jonathangladbach_this-is-one-of-the-most-confusing-press-releases-activity-7443089706386345984-YxDn)
- [Testing AI on monthly client reporting](https://www.linkedin.com/posts/jonathangladbach_today-i-was-wondering-if-claude-cowork-could-activity-7444853651082276865-2EzK)
- [The case for a safe-mode MCP in Shopify](https://www.linkedin.com/posts/jonathangladbach_everyone-raced-towards-an-mcp-shopify-just-activity-7452846245351694336-Io7H)

## Brand relationships

- **Shopify** (mention)
- **Anthropic** (mention)

## Partnerships

Gladbach’s posts do not describe a sponsorship, paid-placement or affiliate format, and no partnership page, rate card or media kit is published. They do show a working relationship with brands: Gladbach describes running monthly client reports that draw on analytics, email and conversion data, turning the results into insights and recommendations. They use the 20 to 30 minutes this normally takes as a benchmark for judging AI tools. Separately, Gladbach has publicly offered to partner with a store to build a safer way to connect AI to Shopify, with automated testing and a preview mode covering code, design and objects before deployment. For a brand planner, the realistic route is a systems-and-automation engagement with a defined store or stack, not a sponsored post. Ask Gladbach directly about rates, deliverables, exclusivity, disclosure and approval terms.

## Alternatives

- Maqsood Hussain: When the store's problem is conversion—people arrive and leave—not the systems behind reporting. Hussain's two posts take the same approach: find the root cause at the page level, then fix it. One is a Shopify CRO audit of a homepage with a 23-second hero video. It mismatched fast-scrolling feed traffic with a slow, passive page, slowed load speed, stacked two USPs, a product category and a CTA into one sequence, and put a clickable-looking button inside the video that could not be clicked. The fix: remove the video and test a static image with one clear message and one clear CTA. The other applies root-cause analysis to bank and PayPal disputes in Shopify stores, tracing most disputes to customers unsure whether or when a product will arrive—often after late delivery. It recommends two fixes: show the expected receiving time on the product page before checkout, and send a connected sequence of emails from order confirmation through warehouse, parcel location, city and delivery day. Choose Hussain if the brand wants concrete page and email changes it can test in weeks, and values diagnosing why a page fails over deciding what to build.
- Asad Khan: When the problem is paid acquisition and creative, not store operations. Khan's posts argue that dropshipping is not dead, but cheap-looking stores are. The difference, they say, is building the store like a real brand, answering customer questions before they are asked, testing multiple creative angles instead of relying on one winning ad, and scaling gradually rather than forcing growth. The other post targets the underlying skill: ads do not convince people to buy; messages do. Platforms change, but human behaviour does not, so marketing is about understanding desires, fears, motivations and emotions. Khan also offers free Shopify and Meta Ads audits as personalised Loom reviews of a store, product page and ad funnel. Choose Khan when the brand wants its ad funnel and creative tested, with the case framed around consumer psychology and trust rather than tooling.
- Alex O.: When the need is content produced at scale with AI, not store operations. Alex O.'s posts are closest to Gladbach's on AI tooling, but apply it to a different job: running Claude Cowork as a UGC content backend for mobile apps. A folder setup gives the tool persistent memory of the brand, creators and tested angles, while six automated workflows run weekly, covering customer-language mining, hook generation, creator briefing, angle rotation, comment seeding and identifying ads whose comment sections could yield more angles. The other post focuses on content–market fit before filming: describe the real user through situations and behaviours rather than demographics, mine Reddit, TikTok search and App Store reviews for the words users already use for the problem, and study top competitor videos for the angle nobody covers. The cited results are app numbers, such as 6 million installs. Choose Alex O. if the need is a UGC or content engine for an app and the automation target is script and angle production.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/