How to Design & Build AI Prototypes with No-Code Tools
Welcome to the latest edition of the AI Community Learning Series! In our most recent session, Polly Allen (Ex-Principal PM at Alexa AI) and Rupa Chaturvedi (AI UX Leader, ex-Amazon, Google, Uber) shared invaluable insights on AI prototyping with no-code tools. If you missed it, here are the highlights – and don’t forget to check out the session replay! 🎥
💡 5 Key Takeaways from the Event
1️⃣ Prototypes Drive Alignment Faster
Prototypes are more than just a visual aid; they are essential for getting buy-in from leadership and cross-functional teams. Rather than lengthy discussions and documentation, an interactive prototype can illustrate AI functionality and bridge the gap between concept and execution. Polly and Rupa emphasized that a well-crafted prototype can eliminate misunderstandings between design, engineering, and leadership teams, making discussions more concrete and actionable. By using no-code tools, teams can efficiently build interactive models that provide a shared vision, reducing time spent on speculative discussions.
2️⃣ Start with the Right Use Case
Before jumping into AI prototyping, clearly define the problem you are solving. Not every application benefits from AI, and it’s crucial to determine if an AI-powered solution truly enhances the user experience or if a simpler approach is more effective. Polly and Rupa cautioned against diving straight into AI coding tools like Cursor and Replit without a solid product hypothesis. They highlighted how no-code tools can achieve similar results at a fraction of the time and complexity.
3️⃣ No-Code Tools Make AI Prototyping Accessible and Efficient
Polly and Rupa went on to demo how non-technical product builders can use non-code tools to prototype a solution. Tools like Notion AI, UX Pilot, CustomGPTs, and Voiceflow allow teams to quickly build and iterate on AI-driven interactions, making them more accessible to designers and product managers.
During the demo, Polly and Rupa walked through the creation of a Shopping AI Assistant, designed to help users research and shop for athletic shoes. They structured the process using a hypothesis-driven approach: capturing user inputs, offering top 3-5 recommendations, and completing the shopping journey.
They began with Notion AI, generating structured user flows to define the assistant’s key interactions. By leveraging AI-powered prompts, they outlined a conversational decision tree that guided users through their shopping experience.
Next, they transitioned to UX Pilot, where they transformed the initial concept into wireframes. These visual prototypes allowed the team to iterate on the user experience, refining the assistant’s ability to suggest the best shoes based on user preferences such as activity type, budget, and comfort level.
Moving into CustomGPTs, they demonstrated how to fine-tune an AI assistant to provide personalized responses. The assistant was trained to ask clarifying questions and suggest relevant products, ensuring a more interactive and helpful experience for the user.
Finally, they used Voiceflow to bring the prototype to life as a structured AI chatbot. By integrating user inputs, decision points, and AI-driven recommendations, the assistant could now seamlessly guide users through the entire shopping journey—from discovery to final selection. The demo highlighted how no-code tools can transform an idea into a fully functional AI prototype, helping teams validate and refine AI-driven experiences before full-scale development. See the demo recording here.
4️⃣ Structured vs. Open-Ended Interactions MatterChoosing between a structured chatbot (with guided user flows) and an open-ended AI assistant (which allows free-form conversations) depends on your goals. Structured designs are great for clarity and efficiency, while open-ended AI offers a more flexible but potentially unpredictable experience.
5️⃣ Validate Early & Iterate OftenSuccessful AI prototyping involves continuous validation. Testing multiple interaction styles with real users helps refine the experience and ensure alignment with user expectations. Prototypes should not just look good; they should help teams gather insights and optimize before full-scale development.
🛠 Tools & Techniques to Try
💬 Voiceflow – No-code platform for designing conversational AI workflows
📌 Notion AI – Generate structured user flows for AI applications
⚡ Figma/FigJam – Quick sketching for AI-driven UX
🖥 Replit, V0, Bolt, & Cursor– Prototyping more advanced, interactive AI experiences
🎯 Other Goodies
Tool Guide: Get AI Design & Prototyping Toolkit - scroll down to right above the instructor bio to see the download instructions
Exclusive Offer: Get 25% off Polly & Rupa’s AI Prototyping Course until Feb 18: Learn more
Join Polly’s upcoming free Masterclass on Feb 18th: “The Path to AI Product Leadership”
Join Rups’ upcoming Lightening Lesson on Mar 28th: Demystifying Human-Centered AI: A Practical Framework
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