In the last few years, artificial intelligence has moved from novelty to necessity in retail. We’ve seen AI brainstorm product ideas, write marketing copy and even chat with customers. But what happens when AI evolves from supporting roles to running the show? How would we design a retail organisation from a blank canvas if AI agents could autonomously make decisions and execute tasks across the business?
This post explores that question through a timeline of AI agent evolution in retail from early experiments like the viral “HustleGPT” hustle, to today’s AI-generated brand studios, and towards a future where networks of autonomous agents could manage entire brands. Along the way, we consider how organisational structures might be radically reshaped, and why brands and retailers need to start thinking differently now.
2022: The HustleGPT Experiment – ChatGPT-Powered Business
At the end of 2022, as ChatGPT burst onto the scene, an experiment went viral that captured the imagination of entrepreneurs and retailers alike. An enterprising designer gave an AI a simple directive: “You have $100, and your only goal is to turn that into as much money as possible in the shortest time possible.”
Dubbed HustleGPT, this project essentially tried to get a probabilistic language model to act like a scrappy startup founder. The AI (OpenAI’s GPT-4, operating through ChatGPT) proposed a plan launching an affiliate marketing website for eco-friendly gadgets—and the human partner dutifully executed its instructions: buying a domain and generating content.
For a moment, the internet was entranced. Could an AI really hustle its way to business success? It certainly felt like a glimpse of science fiction, an AI agent concocting and guiding a real-world venture.
Yet, despite the hype, HustleGPT ultimately underscored the limitations of the era. GPT-4 could generate a business plan and marketing copy, but it had no true agency or adaptability beyond its prompt. The AI relied on its human partner for every real-world action and lacked the long-term strategic judgement needed to navigate changing market conditions. In practice, the affiliate site itself made only modest revenue, and the experiment plateaued once the novelty faded.
2023: Rise of the AI Brand Studios – AI-Generated Brands
Fast-forward to today, and the landscape is evolving. Rather than one-off experiments, we now see serious ventures exploring AI-generated brands. A new breed of startup studios and e-commerce companies are using AI to design products, build supply chains, develop branding, and orchestrate marketing—essentially incubating brands digitally before launching them into the real world.
One compelling example is Wonder Family, an AI-powered e-commerce brand studio. Their ambition is bold: to invent an AI that creates essential products for humanity and generates returns for investors. In practice, they act as a technology-driven brand factory, using AI to identify product opportunities and handle many operational tasks. The company has reportedly achieved over $13 million in GMV within 18 months, with 88% month-over-month growth, all without traditional marketing efforts. Their moonshot goal? To launch 10,000 products by 2030.
Wonder Family is not alone. Across the sector, AI-powered brand builders are emerging. Some use generative AI to craft brand concepts and visuals in days. Others deploy AI in operations: forecasting demand, optimising online ads, or managing inventory with minimal human input.
Despite these advances, however, true end-to-end autonomy remains elusive. Today’s AI brand studios remain piecemeal. They often focus on specific functions: automating the creative process or streamlining logistics without a unified "brain" tying it all together. AI may generate product ideas and marketing copy, but humans still handle key strategic decisions.
The fundamental point: the tools lack contextual judgement, cross-functional coordination and memory. The orchestra has many talented AI musicians—but so far, no conductor.
The Next Frontier: Fully-Autonomous Retail
Our view is that the real opportunity goes beyond existing applications. Excitingly, we are seeing some, like Honu, thinking about the bigger picture opportunity as we see it too. That is, creating a network of agents, able to make strategic decisions, not just functional, and to action these decisions fully autonomously.
Honu is building what they describe as a “cognitive layer” for businesses—a unified brain that understands a company’s goals, context, and operations, orchestrating a fleet of AI agents accordingly.
Rather than having isolated AI systems for marketing, finance and supply chain, Honu’s platform enables all agents to collaborate and share a common understanding. Instead of following narrow instructions, the agents act with strategic judgement, continuously optimising towards broader business objectives.
Crucially, these systems aim to be proactive. They don’t just execute tasks; they suggest strategic pivots, identify risks and adapt autonomously. They retain context and build organisational memory over time. Imagine an AI that not only buys your ads day-to-day but spots a new market trend emerging and proactively recommends a product pivot—without waiting for human input.
If we were designing a retail brand from scratch with this capability, the organisational chart might not look like a chart at all. Instead of departments, we would have fluid networks of AI services, connected by a shared understanding of the brand’s purpose and goals.
A central AI "CEO" might set high-level objectives. Specialist AI agents would act as Heads of Marketing, Product Development, Customer Service and more – coordinating seamlessly across what are today considered separate siloes. In truth, these agents needn’t have formal job titles like “Head of X”, this is just a means of understanding their orchestration in more human terms. Real humans would still play vital roles in governance, creativity and oversight but the day-to-day operations could largely be executed by AI agents.
Whilst all of this is not to negate the potential value in trying to automate each of the individual workflows that make up brand operations, ultimately the size of prize relative to the input costs are much less attractive.
So What?
The evolution from HustleGPT experiments to AI networks capable of autonomously managing brands signals a profound shift. It challenges leaders to rethink not just how AI is used, but how organisations themselves are designed.
The question is no longer if AI will transform your business structure—but how you will respond. Will you layer AI on top of legacy structures, or seize the opportunity to reimagine your organisation from first principles?
At True, we believe those who engage with this shift early will have a defining advantage. If you are a brand interested in testing autonomous agentic business models—or even just exploring where to start—we would love to hear from you.
Get in touch with us to explore how AI agents could help future-proof and propel your brand into the next era of retail.
