What accelerates prototyping AI-driven product ideas?

Most answers emphasize rapid iteration through feedback, prototyping, or direct user engagement, though approaches range from prompt engineering to AI-assisted coding and customer collaboration.

6 answers

Answers

  • Ben Celebicic

    Chief Product and Technology Officer (CPTO) · Hinge

    Rapid feedback loop

    Ben Celebicic says the biggest value he sees is the feedback loop, because it lets him learn much quicker whether something is worth building by prototyping without engineering support and putting it in users' hands.

    Product School · Watch on YouTube

  • Jonathan Evens

    Product Lead · Google Deepmind

    Prompting

    Jonathan Evens points to prompting, saying a lot can be done by iterating on prompts and building eval sets.

    Mind the Product · Watch on YouTube

  • Paweł Huryn

    Author, Founder · The Product Compass

    Prototyping with Claude

    Paweł Huryn recommends teams discover, discuss, research and prototype with Claude, letting the agent run spikes to confirm what's technically possible, instead of adopting heavy software development processes.

    The Product Compass · The Product Compass · Read

  • Sabrina Ramonov 🍄

    Creator · Sabrina Ramonov

    AI-assisted coding

    Sabrina Ramonov says she shifted to AI-assisted coding, where she drives and AI helps with scaffolding, brainstorming and tests, because vibe coding produced spaghetti code she couldn't maintain.

    Sabrina Ramonov 🍄 · Sabrina Ramonov 🍄 · Read

  • Todd Olson

    CEO / Founder · Pendo.Io

    Engineering mindset

    Todd Olson says an engineering mindset is the answer: when the technology doesn't do things automatically, you iterate and improve it—maybe provide more data—to solve the problem.

    DataFramed · DataFramed · Listen at 34:45

  • Faith Forster

    Chief Maker · Discoveree For Product Leaders & Managers

    Working alongside customers

    Faith Forster says teams should work alongside customers — watching how they use the product, spotting friction and improving it — because AI has made building and changing features so quick that the definition of done is now adoption, not shipping.

    Mind the Product · Watch on YouTube

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