What Vibe Coding Gets Right—and What Still Takes Real Work
In this Tinker Club session, Leigh-Anne Nugent and Micah Adler dig into what modern product building looks like when AI can generate apps, presentations, videos, and workflows in minutes. But the bigger insight is not just speed. It is understanding the gap between a fast prototype and a truly usable product and why refinement, testing, and real-world feedback still matter.
LESSONS YOU CAN TAKE FROM THIS:
1. AI can get you to a working prototype faster than ever
From coffee community apps to assessment tools and presentation decks, this conversation shows how quickly new AI builders can turn an idea into something visible and usable. That changes the game for founders, consultants, and creators who want to validate ideas without waiting on traditional development cycles.
2. Fast output does not mean finished product
A major takeaway here is that generation is only the beginning. Even when a tool creates something impressive, the real work often shows up in the last mile: fixing behaviors, tightening UX, validating order of execution, testing permissions, and making sure the product actually performs the way users expect.
3. Good products are shaped through user stories and iteration
Leigh-Anne’s Assessify example makes this clear. Building with AI is not just prompting once and calling it done. It means walking through user stories, checking expected behavior, improving mobile experience, validating saved data, and refining the flow until the experience feels clear and useful.
4. The next advantage is not just building—it is connecting the dots
This session goes beyond app creation into the bigger opportunity: linking what you build to CRM data, lead generation, workflows, and real business outcomes. The tools are getting faster, but the strategic value comes from knowing how to integrate, validate, and use them inside a larger system.
KEY TAKEAWAYS:
AI builders can dramatically reduce the time it takes to prototype new ideas.
The difference between a demo and a real product is refinement.
User stories, QA, and expected behavior still matter in AI-assisted builds.
Mobile experience, permissions, and data persistence can make or break usability.
The real opportunity is turning AI-built tools into connected business systems.
