Wolf & Badger CEO and co-founder George Graham says he has spent hundreds of hours learning about AI and commerce, returning to hands-on product work as he considers how the marketplace can serve shoppers and independent brands. His experiments range from coding assistance and internal prototypes to image recognition and product tagging. He also sees agentic commerce as a potential future route for customers to discover and buy from the company’s brand partners—not as a channel Wolf & Badger has confirmed implementing.
Why George Graham is getting hands-on with AI
In a 3 March 2026 interview with Computer Weekly, Graham described himself as a non-engineer who has returned to working closely with product and technology colleagues. “I have personally spent many hundreds of hours over the past three months getting my head around AI and the future of commerce – with agentic commerce in mind,” he said.
His interest is practical as well as strategic: using AI to understand the marketplace’s shoppers, brands and products, and to improve the way customers find relevant items. Graham said, “There’s tremendous opportunity to improve the efficiency and discovery on Wolf & Badger by better understanding our shoppers and our brands and the products they sell.” That is his assessment of the opportunity, not an independently measured comparison of productivity.
What AI work does Wolf & Badger describe?
Coding help and internal assistant
Graham said Claude Code has become his “go-to app.” He also described an internal AI “chief of staff” connected to tools through MCPs or APIs. These accounts describe how he and the company say they are experimenting; the interview does not independently verify the assistant’s configuration, capabilities or effect on work. Anthropic’s documentation explains Claude Code setup and describes MCP support in Claude Code. MCP is an open protocol for connecting applications and providing context to language models; that general documentation does not confirm how Wolf & Badger uses it.
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The interview also mentions Microsoft Copilot and Cursor as tools explored by the team, but it does not report a controlled comparison between them and Claude Code. They should be understood as tools under consideration, not as ranked alternatives.
Prototypes and marketplace applications
Graham described prototypes for assessing brands and vetting sustainability. The marketplace applications discussed also include image recognition, product tagging, adding richer product attributes and personalization intended to improve discovery. The interview does not establish that every prototype is a production feature or provide an independent technical assessment of accuracy.
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What the company says the results are
Wolf & Badger reported £3.2m in directly attributable incremental sales from recent AI initiatives, according to the figures presented in Computer Weekly’s March 2026 interview. That is the company’s attribution: the interview does not provide an independent audit or enough detail to assess how the impact was measured, which initiatives were counted or over what period.
The same interview gives business context from company-reported figures: more than $500m in cumulative sales since inception and almost 40 million website visits in 2025, both from a Wolf & Badger performance update in January 2026; $100m (£75m) annual sales in 2024; and more than 2,000 brand partners. These figures describe the company’s reported scale, not evidence that AI caused its overall growth.
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What agentic commerce could mean for independent brands
Agentic commerce refers to shopping experiences in which AI agents can help people discover products and, as systems develop, take actions in a transaction. Graham frames it as a future channel opportunity: independent brands need to be findable if customers increasingly shop through AI-led services. His comment, “You just have to try to stay ahead,” captures the company’s stated rationale for exploring the space, not proof that a particular channel will generate sales.
Google describes its Universal Commerce Protocol (UCP) as an open standard that provides a common language for platforms, agents and businesses across commerce, from discovery to checkout. Its merchant guide directs businesses to implementation information and a waitlist, while its UCP overview explains the standard’s intended scope. Those documents establish Google’s description of UCP; they do not show that Wolf & Badger has implemented it or that the company’s brands are available through it.
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What the interview does—and does not—show
| Approach | Role | Status and evidence in the interview |
|---|---|---|
| Claude Code | Coding assistance | Graham calls it his go-to app; this is his account, not an independent productivity evaluation. |
| Internal AI assistant and prototypes | Connected internal support, brand assessment and sustainability vetting | Described by Graham as internal work and prototypes; the interview does not independently test them. |
| Image recognition, tagging and personalization | Product data and shopper discovery | Marketplace use cases discussed; no independent accuracy or impact evaluation is supplied. |
| Google UCP | A commerce protocol intended to support agentic experiences | Google documents the standard and merchant pathway; the interview does not confirm Wolf & Badger adoption. |
The evidence therefore separates three things: Graham’s personal experimentation, company descriptions of prototypes and marketplace initiatives, and a prospective commerce channel whose standards are still being presented by their providers. The reported £3.2m figure is a company-attributed outcome, not an independently audited finding.
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