The Growth Podcast – Episode Summary

Episode Title: How to AI Prototype Well | Masterclass from $5.5B Founder, Nadav Abrahami (Wix)
Host: Aakash Gupta
Guest: Nadav Abrahami (Co-founder, Wix & Founder, Dazzle)
Date: February 27, 2026

Episode Overview

This masterclass dives into the evolving world of AI-powered prototyping for product managers, featuring Nadav Abrahami, co-founder of Wix and founder of Dazzle. He shares practical, deeply technical, and strategic insights on leveraging AI tools to empower PMs to build better, faster, and more experimental product prototypes—even in organizations with limited engineering resources. Nadav and Aakash focus on concrete workflows, common pitfalls, and the shifting roles of product and technical stakeholders in an era of rapid AI advancement.

Key Discussion Points & Insights

1. The Promise & Reality of AI for Product Managers

AI as a Tool, Not a Total Replacement (00:37, 01:45)
- Nadav distinguishes between the hype and real capabilities of current AI systems:
  
  "AI is a tool...but it's not anybody can build anything tool. It is an amazing tool for some things...amazing for PMs that build prototypes." (Nadav, 01:45)
- While AI can accelerate and unlock prototyping, a baseline of product and technical understanding remains essential.
Skill Shift: Understanding Over Construction (00:09, 70:35)
- PMs must “level up the skill of understanding what they're building”—knowing the why and how behind features, not just stringing prompts together.
- The ability to communicate intent and clarity becomes more critical than ever.

2. Where and When to Use AI Prototyping Tools

For Functional, Testable Prototypes (04:15, 06:36)
- AI prototyping (like Dazzle) gives more than Figma or classic visual editors; you get interactive, testable, user-facing workflows:
  
  "You get an experience that is more functional...that you can put users in front of and they can actually get the real experience." (Nadav, 04:15)
- This shift drastically reduces the investment required for realistic prototyping—making iterative user testing and experimentation much more commonplace.
Strategic Use Cases (03:06, 06:36, 52:12)
- For fast ideation, divergent solution exploration, and validating "feel" early.
- High-fidelity prototypes become critical for selling ideas internally and user validation.
- Low-fidelity, quick passes are fine for initial team exploration.

3. The Product Development Lifecycle & Pitfalls

Don’t Skip the Problem Space (06:06, 06:36)
- Critique: Jumping straight to prototyping risks shallow problem understanding.
- PMs must first define the problem, user story, and basic feature shape.
  
  "There's a lot to do before you even get to prototyping, and I would never give up that step..." (Nadav, 06:36)
AI Tools = New Opportunities, But Same Product Discipline
- Avoid the “hammer for everything” trap.
- Prototyping comes after user and market research, and aids—not replaces—classic PM activities (research, stakeholder alignment, documentation).

4. Live Demo: Prototyping in Dazzle (08:05 – 30:00)

A. Setting Up the Environment (08:05 – 12:37)

Recreating Existing Products:
- Start by replicating the actual application's visuals and flows (LinkedIn was demoed).
- Saves time, ensures context and design-system fidelity.
Template Creation:
- Save and reuse templates across the org for consistency.

B. Visual and Functional Editing (12:50 – 17:09)

Matching Design:
- Quick tweaks via eyedroppers and direct manipulation.
- AI plus designer input yields best results.

C. Adding Features via Prompts (17:09 – 27:47)

Prompting for New Functionality:
- Example: Sentiment analysis attached to LinkedIn posts.
Divergent Solution Exploration:
- Instantly branch or create variant implementations (e.g., two sentiment analysis display approaches).
"What this tool unlocks is your ability to do these different solution explorations...come up with three or four so quickly..." (Akash, 26:46)

D. Deep Dive: Editing & Code Integration (28:00 – 43:04)

Component/Instance Distinction:
- Visual editor shows both component and instance context—a huge win for PM/developer handoff and clarity of changes.
Code Edits & Real-Time Sync:
- Direct editing in code is possible but should not be first resort for PMs.
- Most changes should be made visually or via prompt for speed and accuracy.
"I don't think PMs should be ever editing in code. When PMs get to the point where they have to edit in code, it's not their ideal flow. It means something did not work as expected." (Nadav, 43:04)

E. Multi-Page Prototypes and Realism (49:00 – 57:34)

Building End-to-End Flows:
- PMs can build multi-page, interactive prototypes—essential for uncovering usability and edge-case risks.
Edge Cases:
- Use the prototype for main flows, PRD for detailed exceptions.

5. Prompting Best Practices & Common Mistakes

Clarity Over Complexity (22:28, 22:53)
- Focus on communicating the WHAT, not the system level HOW.
- AI can misunderstand ambiguous prompts—clarity trumps verbosity:
  
  "Anything that can be misinterpreted will statistically be misinterpreted." (Nadav, 22:53)
Iterate and Discuss with AI (46:01)
- Before making major changes, use AI's “plan/discuss” capabilities to confirm understanding.
- For complex or important prompts, clarify intent by asking the AI to paraphrase back.
Splitting Flows for Better AI Results (48:47)
- Avoid giant, multi-goal prompts. Sequence your requests for better outcomes.

6. User Testing, Internal Buy-in, and Organizational Impact

The Power of High-Fidelity Prototypes (52:12)
- For selling the idea, getting user validation, and internal clarity—visual realism drives belief and better feedback.
Rapid User Validation (55:18)
- Best test group: your existing engaged users; supplement with usertesting.com if needed.
- Always go beyond internal “playground” testing for real insight.

7. Handoff to Engineering

From Prototype to Production (58:24 – 62:47)
- AI prototypes with Dazzle produce standard code that can be directly handed off.
- Downloadable projects, git integration, and in-app specs (text and prototype co-located) ease developer transition.
- Clarify that main flows are in prototype; supplement with PRD for edge cases:
  
  "Cover the main 90% flows with the prototype and make sure that all of the edge cases are in the PRD." (Nadav, 66:27)

8. The Future: AI’s Trajectory in Product Development

Developers Won’t Disappear, But Roles Change (70:07)
- AI will “replace some very simple things,” but the big shift is more tech-savvy PMs and designers contributing to the codebase.
- The barriers between roles blur—more collaboration, more ownership at all levels.
  
  "Writing code is not a limiting factor anymore...I think what PMs really need to do is level up the skill of understanding what they're building." (Nadav, 70:35)

Notable Quotes & Memorable Moments

On AI Prototyping’s Sweet Spot

"We were just gotten a huge get out of no developers jail card." (Nadav, 26:00 & 17:09)
On PM Upskilling

"The fact that you're not a developer doesn't mean that you don't write code anymore...you don't even have to type anything, just put it on speaker and talk to it." (Nadav, 70:35)
On Workflow

"Explore three to four divergent solutions. ... Then you're going to test it with real people, ideally your own users. And then you're going to share that prototype with a developer team." (Akash, 66:38)
On Clarity in Prompting

"If you're super technical and you do know what you're saying, maybe tell it what to do, but otherwise it's really better to explain very coherently what you want." (Nadav, 22:53)
On the Evolution of Prototyping

"We used to have all department for this...three developers doing all of the prototypes for so many features in Wix. ... Now [AI] is magic." (Nadav, 57:34)
On Having Fun and Experimentation

"Have fun with it. ... I think about how much work I needed to do to create my first Flash game...now you get the most magical genie that can build things for you." (Nadav, 67:13)

Timestamps – Important Segments

00:37 – 02:32: Nadav’s core thesis on AI as a lever for PMs
04:15 – 06:36: When/why to use AI prototyping versus Figma or other tools
06:36 – 07:25: Danger of skipping the “problem” phase
08:05 – 17:09: Live walkthrough of Dazzle setup and visual editing
17:09 – 27:47: Feature addition and divergent solution exploration
28:00 – 43:04: Visual, prompt-based, and code editing explained and compared
49:00 – 57:34: Multi-page app prototyping and covering edge cases
58:24 – 62:47: Handoff to developers, the role of PRD vs prototype
70:07 – 74:13: Forecast: AI’s impact on developers and PMs in the next 3-5 years

Actionable Workflow Summary (Ideal AI Prototyping Flow)

Explore the Problem Space (research, user stories, context)
Define the Feature (clear problem, rough shape)
Match to Your Design System (recreate product visuals in tool)
Create 3-4 Divergent Solutions (AI-powered prototypes)
Visually Edit & Refine the Best Solution
Test with Real Users (ideally your own)
Share with Developer Team (via prototype & PRD for edge cases)

Final Takeaways

AI prototyping dramatically accelerates and democratizes product experimentation.
Successful PMs in the AI era will focus on clarity, communication, and embracing new technical fluency—not becoming coders, but understanding enough to guide and leverage new superpowers.
Use AI workflows to do what was never possible: rapid, high-fidelity, multi-variant testing and feedback gathering, with minimal engineering bottlenecks.
The PM/Dev/Design lines are blurring: everyone can shape products more directly—embrace it, have fun, and deliver better outcomes for users and businesses.

For more resources, full episode, and tool recommendations:
Visit www.news.aakashg.com