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Many people try AI, enjoy it briefly, then struggle to make it genuinely useful. In this episode, John Bennett talks with Dr Dan Maggs about the shift from experimenting with AI to building practical tools, and what that makes possible for non-technical founders. They discuss how AI has moved from novelty to something you can actually build with, why context degradation causes long AI chats to break down, and how working with projects and workflows helps address those limits. Dan shares his own journey, from early experimentation to developing a working meal planning app, despite having no formal coding background. The conversation also looks at choosing AI tools without chasing every new release, using AI as a non-judgemental sounding board, and what this shift means for people who want to build personalised products. The episode closes with a listener question on structuring AI for complex tasks like business plans, and why thinking in terms of projects matters more than writing ever-longer prompts. If you have a question you’d like us to pick up in a future episode, you can get in touch at frmdb.ly/pod In this episode: Why AI often starts as a novelty and then disappoints What changes when you add context and think in projects Moving from prompts to building real tools Building applications without traditional coding skills Context degradation, and why AI chats “forget” Designing around AI limits with apps and workflows A real example, building a meal planning app Choosing tools without chasing shiny objects AI as a non-judgemental thinking partner Listener question, structuring AI for business plans Chapters 00:00 Introducing Dr Dan Maggs 05:33 From fun to functionality 12:24 Building solutions with AI 19:42 Working around context degradation 25:28 New tools and shiny objects 34:30 Using AI as a non-judgemental sounding board 38:56 AI is making customised products achievable 48:09 Listener question: business plans