This episode of Vision Pros Live features a conversation between host Jackson Callum and Jonathan Goodman about the future of AI in retail.

Key themes and takeaways:

• AI as a foundational shift
  • Jonathan frames AI as a transformation on the scale of the wheel, impacting nearly every domain (medicine, therapy, legal, accounting, content), with his current focus on retail applications.
• Trigonal’s pivot: from gallery to AI-enabled product business
  • Trigonal began as a modern art gallery, shut down during COVID, and then pivoted into crypto/NFTs and AI-generated art.
  • The strategy became: don’t just make AI art for galleries—make art people want in their homes, starting with throw pillows, with plans for t-shirts, skirts, jackets, and more.
• Sustainability + print-on-demand as a business advantage
  • Jonathan emphasizes sustainability (especially important to younger buyers) and contrasts old-school inventory risk (bulk ordering, screen setup costs) with print-on-demand:
    • Create designs → list products → if they don’t sell, no sunk inventory cost.
  • The model enables rapid experimentation with minimal financial downside.
• Workflow for AI product design
  • The process starts with ChatGPT for market/category discovery (e.g., holidays and themes).
  • Then prompts are refined into Midjourney for image generation and heavy curation (hundreds/thousands rejected to select winners).
  • A key point: AI helps uncover what customers actually want, not just what creators feel like making.
• Custom Instructions = “aiming” ChatGPT
  • Jonathan explains Custom Instructions as a way to constrain the AI to a specific persona/role (e.g., visual artist), like navigating to a specific “aisle” in the Library of Congress.
  • He argues it’s not boxing yourself in permanently—you can swap personas depending on the task (artist vs. accountant vs. marketer).
• Web browsing via Bing inside ChatGPT (paid plan)
  • They demo the difference between “offline” model knowledge and web-browsing mode, where ChatGPT can research live sources through Bing and compile findings.
  • Example: investigating how Amazon’s marketplace dynamics can squeeze small sellers by pulling current articles and summarizing patterns.
• Who Jonathan thinks should listen
  • He targets entrepreneurs and aspiring entrepreneurs, emphasizing the real-world value of learning through failures and pivots.
  • He highlights the underused opportunities: SBA resources, loans, grants, and investments, and the importance of a strong business plan.
• Closing guidance
  • Jonathan encourages connecting via LinkedIn (follow first), and following Trigonal plus its newsletter for limited collaborations.
  • Final principle: belief in yourself, in the project, and in earning others’ belief.

Overall, the interview positions AI as both a creative engine (design generation) and an operational accelerator (market research, messaging, content), with print-on-demand enabling a low-risk path to monetize AI-generated product design.