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We track Product so you don't have to. Top Podcasts summarised, the latest AI tools, plus research and news in a 5 min digest.

Hey Product Fans!

Welcome to this week’s 🌮 Product Tapas!

If you’ve been forwarded this or just stumbled upon it, you’re in for a treat. For the best reading experience, check out the web version and sign up for future editions here.

What’s on the menu this week? 🧑‍🍳

📰 Not Boring – Another ridiculously jam-packed week. For example; Stripe's making big moves with AI-powered checkout tools, a new business ID system, and an Order Intents API for autonomous AI purchasing. Meanwhile, Amazon's secret "Kiro" project aims to streamline coding with AI agents, Airbnb expands beyond accommodations, and Instacart launches group ordering for party supplies (while their CEO heads to OpenAI). Elsewhere, TikTok democratises AI video creation, Google introduces cost-saving "implicit caching" for AI models (as Alphabet shares drop on Apple search rumors), and—perhaps most surreally—Apple announces support for brain-implant control of its devices. Oh, and flying bikes that hit 124mph are now a reality. The future is wild.

⌚️ Productivity Tapas – This week's tools help you identify perfect-fit prospects for your ICP, build dashboards and internal tools with AI assistance, create professional presentations through conversation, and transform your Notion databases into custom business apps. The productivity revolution continues to accelerate.

🍔 Blog Bites – Peter Ramsey returns with clever micro-interactions that enhance UX (including how Strava uses loss aversion to reduce cancellations), Bill Kerr compiles expert strategies for recruiting all-star talent, and Tim Herbig introduces the "Progress Wheel" framework for connecting strategy, OKRs, and discovery.

🎙️ Pod Shots – Get an exclusive look at Figma Make, the new AI prototyping tool that's changing how we build products. From turning simple prompts into functional prototypes to enabling real-time collaboration, Make represents a significant leap forward in the prototyping space—and might just make your six-year-old the next app developer in the family.

Plenty to get stuck into—off we go! 🚀

📰 Not boring

• Stripe held a big event last week key features include:

  • Checkout Suite and Payments Intelligence: AI tools to improve checkout conversion

  • Stripe Profiles - a public ID for businesses to help with instant invoice payment

  • Order Intents API for AI agents to autonomously handle purchases

• Amazon is working on a secret project called 'Kiro,' a new tool that uses AI agents to streamline software coding

• Airbnb expands into services and experiences, plans more social and AI features [Airbnb for everything!]

• Instacart launches Fizz, a group ordering app for party drinks and snacks

• On Instacart, their Chair and CEO, Fidjii Simo is to join OpenAI as new CEO of applications

• You can now connect GitHub repos to deep research in ChatGPT

• Meta Reportedly Eyeing 'Super Sensing' Tech for Smart Glasses. Not creepy. Nope

• TikTok brings AI video creation to the masses with AI Alive

• Aurora to add night driving, new routes as it ramps driverless trucking. Bit left-field, but there’s so much autonomous vehicle stuff happening in the world it needs the occasional mention

• This week’s Google news:

  • Google launches ‘implicit caching’ to make accessing its latest AI models cheaper. Smart

  • Google's parent company, Alphabet, shares plunge over 8% as Apple explores AI search competition

  • Google is now running small on device LLMs inside Chrome to look for scams

• Apple to support Brain-Implant Control of its devices [every week the news gets more ridiculous. This just casually dropped in mid stream in one of my apps and I barely noticed]

• Elizabeth Holmes’s Partner Has a New Blood-Testing Start-Up. Yes really

• Spotify’s DJ Now Takes Requests, Enhancing Real-Time Music Discovery

• Granola launches for iOS AND launches V2. My favourite AI meeting notes app just got some big updates. Including new save to/sort in folders and much more

• On the same topic (ish) Notion takes on AI notetakers like Granola with its own transcription feature (and stacks more)

• And finally;  Star Wars-styled Airbike take to skies, fly at 124 mph, turn sci-fi into reality. Dear Santa

• OK really finally, Tim Urban (waitbutwhy) updated his infamous 2015 AI chart (original here)

  • original

    

  • New

    

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⌚️ Productivity Tapas: Time-Saving Tools & GPTs

• Ciro: rummages through half-a-billion profiles, figures out who actually fits your ICP, and hands back a ranked list with real emails and phone numbers

• Preswald: AI agent that helps you build dashboards, internal tools, and data apps. It gives you a fast, reactive runtime, built-in UI components (tables, charts, inputs), and one-click deployment to share your app in the cloud or browser

• DeckSpeed: AI presentation tool that creates professional, personalised slides based on your conversations, without templates. In other words, it's "Cursor for Slides", "McKinsey for everyone"

• NotionApps 2.0: I’ve never got the results I wanted from v1.0 but the idea is great, so let’s hope v2.0 delivers on their promise to “Turn Notion data into powerful custom apps for your business”

Remember, as a Product Tapas Pro subscriber you can access the full time saving tools database for fast approaching 400 time-saving tools relevant for product managers and founders 🔥.

Check the link here to access.

🍔 Blog Bites - Essential Reads for Product Teams

UX Design: Clever Micro-Interactions That Enhance User Experience

Once again Peter Ramsey is back with more great UX patterns you can learn from, or dare I say, even try yourself.

From how Cherrypick personalises testimonials based on your diet, Strava uses loss aversion to reduce cancellations, and how Linear dynamically changes navigation for returning visitors (plus more) there's something for everyone.

Hiring Strategy: How to Recruit All-Star Talent

In a recent post, Bill Kerr compiles insights from successful founders and leaders on their approaches to hiring exceptional talent, comparing the process to crafting a perfect dish where each ingredient must be carefully selected and balanced. Read the full article here.

💡 "Building a company is tough. Hiring great talent, even tougher. Think of it like cooking a Michelin-star-worthy dish... When you compromise on these essentials, adding unnecessary or ill-fitting ingredients, your team becomes that ketchup-and-cheddar pasta disaster: confused, ineffective, and far from the excellence you aimed for."

My take? One size certainly doesn’t fit all. Figuring out what works for you and your company (at the current stage) is key.

Product Strategy: The Progress Wheel Framework

In this recent post, Tim Herbig introduces the "Progress Wheel" framework, a holistic approach that helps product teams avoid isolated practices and connect strategy, OKRs, and discovery to drive meaningful progress.

💡 "Real Progress happens when you choose methods because they create value for you in your context, and you can use each domain to improve the others." This insight highlights how effective product management requires interconnected practices rather than siloed optimisation.

🎙️ Pod Shots - Bitesized Podcast Summaries

Remember, Product Tapas Pro subscribers get access to an ever growing database of all the top Podcast summaries we’ve ever created. 

Check it out here

🚀 Figma Make: The AI Prototyping Tool That's Changing How We Build Products

ICYMI Figma recently launched a stack of new updates, including Make. In his latest Podcast, Peter Yang got an exclusive look with David Kossnick, Head of Product for Figma AI. Make is Figma’s take on vibe-coding; basically an AI-powered prototyping solution that could transform how designers, product managers, and engineers bring ideas to life.

From turning simple prompts into functional prototypes to enabling real-time collaboration, Make represents a significant leap forward in the prototyping space.

 🎥Watch the full episode here

📆 Published: May 11th, 2025

🕒 Estimated Reading Time: 3 mins. Time saved: 40 mins🔥

💡 What is Figma Make?

Figma Make is a prototyping tool that can start with a simple prompt, a screenshot, or existing Figma mockups. It's designed primarily for designers and PMs to bring ideas to life quickly, transforming concepts into interactive, functional prototypes.

"Figma Make is a prototyping tool that can start with a simple prompt, with a screenshot, or with mockups," explains David in the interview. "It's designed initially for designers and PMs and engineers to bring ideas to life and to start with concepts that come from Figma and more and get those into something you can play with and feel."

Unlike traditional prototyping tools, Make leverages AI to generate not just visuals but actual functional code, allowing users to create interactive experiences without writing a single line of code themselves.

Key Takeaways for Product Leaders:

• Make bridges the gap between design and code, allowing non-technical team members to create functional prototypes

• The tool supports multiple starting points: text prompts, screenshots, or Figma designs

• Make is particularly powerful when starting from existing Figma designs, as it leverages all the structured data and layers

🔮 How Make Works: From Prompt to Prototype

The process of using Make is surprisingly straightforward. Users can start with a text prompt (like "a modern image gallery where you can tap around on different photos"), upload an image (such as a picture of the solar system), or import designs directly from Figma.

Once given an input, Make begins by reasoning about what the scope might include and planning how to approach the task. It then generates the necessary code, streaming the process in real-time so users can see what's happening. The result is a fully interactive prototype that users can immediately test and refine.

What sets Make apart is Figma's native code composer, complete with syntax highlighting, code autocomplete, and an error console. This allows users to edit the generated code directly if needed, providing a level of flexibility not typically found in AI prototyping tools.

Key Takeaways for Product Leaders:

• Make follows a reasoning-planning-execution process that's visible to users

• The tool streams code generation in real-time, providing transparency into what's happening

• Users can directly edit the generated code, offering flexibility for more technical users

🤝 Multiplayer First: Collaboration at Its Core

One of Make's standout features is its multiplayer functionality. Like other Figma products, Make is designed for collaboration from the ground up.

"Figma is a platform where all of our products are multiplayer first. And this is part of why Figma's been so successful," David explains in the podcast.

In a live demonstration, David showed Peter how multiple users can work on the same prototype simultaneously. Users can see each other's avatars, chat in real-time, make visual changes that update instantly for everyone, and even collaboratively edit code.

This collaborative approach extends to working with AI as well. Users can select elements and use contextual prompts to refine specific aspects of the prototype, with all team members seeing both the prompts and the resulting changes in real-time.

Key Takeaways for Product Leaders:

• Make's multiplayer functionality enables real-time collaboration on prototypes

• Teams can collectively prompt the AI, making the design process more inclusive

• The collaborative code editor allows technical and non-technical team members to work together seamlessly

🧪 Building an AI Product: Lessons from the Figma Team

Developing Make wasn't without challenges. David shared insights into the process, highlighting three main areas of difficulty:

1. Infrastructure: Make builds on years of infrastructure work, including Figma's sites product and code layers project, which involved converting Figma nodes into renderable, publishable elements.

2. Quality, Speed, and Cost: Finding the right balance between model quality, generation speed, and operational costs required constant experimentation and refinement.

3. Non-determinism in AI: The unpredictable nature of AI outputs made debugging challenging. "We had interesting cases where you'd give a design, an image of a design to the agent and ask it to do something, and it would sometimes do a pretty good job and sometimes fail spectacularly, and it was hard to figure out why".

The Figma team addressed these challenges through extensive testing and evaluation. They developed a dual-scoring system for quality assessment, evaluating both design fidelity and functionality separately.

Key Takeaways for Product Leaders:

• Building AI products requires strong infrastructure foundations

• Balancing quality, speed, and cost is a constant challenge that requires experimentation

• Developing clear evaluation criteria is essential for improving AI outputs [see our recent article on how to create Evals here]

• Consider multiple dimensions of quality when assessing AI-generated content

🔄 The Prototype-Driven Development Process

The development of Make itself exemplifies a new approach to product development in the AI era. Rather than following more traditional PRD methods, the Figma team embraced a prototype-driven process.

"A prototype is worth a thousand PRDs," David notes in the conversation, highlighting how the cost of making prototypes is decreasing dramatically thanks to AI.

This approach allowed the team to test ideas quickly, identify issues early, and refine the product based on actual usage rather than theoretical specifications. Interestingly, the team even used early versions of Make to prototype new features for Make itself.

David suggests this prototype-driven approach is becoming the new standard for product development: "In the next year, we're going to see that change to being kind of the new gold standard for the PM artefact of choice."

Key Takeaways for Product Leaders:

• Prototypes are becoming more valuable than written specifications

• AI tools like Make can dramatically reduce the cost and time required to create prototypes

• Testing with actual prototypes reveals issues and opportunities that might be missed in written specs

• Consider using AI prototyping tools early in the product development process

🎯 Finding the Right Path in the "Maze of Choice"

David introduced an interesting metaphor for AI product development: the "maze of choice." When developing AI features, teams face three possible scenarios:

1. The straight path: The feature works as expected right away (rare, perhaps 1% of cases)

2. No entry: The idea simply isn't feasible with current AI capabilities

3. The winding path: The feature works partially, requiring decisions about whether to narrow scope, wait for better models, or invest heavily in solving the hard problems

"A lot of the art of being a modern-day AI PM is figuring out when to take what turns in the maze," David explains. This approach requires comfort with uncertainty and a willingness to pivot based on what's actually possible rather than what was initially envisioned.

Key Takeaways for Product Leaders:

• Be prepared to navigate uncertainty when building AI products

• Prototype early to determine if your idea is feasible with current AI capabilities

• Be willing to narrow scope or pivot if the original vision isn't fully achievable

• Consider whether solving hard AI problems is worth the investment or if simplifying the product would deliver similar value

🌈 Unexpected Use Cases: From Professional Design to Kids' Games

While Make was designed primarily for professional designers starting from existing designs, the Figma team has been surprised by the diversity of use cases that have emerged during testing.

Examples David shared in the podcast include:

• A simple spray painting tool created in five minutes

• A 3D first-person shooter game

• Custom marketing workflow tools

• Personal journaling applications

• Vector field art explorations

• Transit information apps

Perhaps most surprisingly, David's six-year-old son became an alpha tester, creating about ten games with Make. "He comes home from school with sketches of ideas, and he's like, 'Can I give this picture to Make and start making the game?'" 🤯 

Key Takeaways for Product Leaders:

• AI tools often find unexpected use cases beyond their intended purpose - playgrounds and launching AI products with less well defined use-cases is already an approach some players are adopting

• The accessibility of AI prototyping tools is democratising software creation

• Consider how your AI product might serve audiences you hadn't initially targeted

• The simplicity of prompt-based creation opens doors for non-technical creators of all ages

🧠 Lessons from Figma's AI Journey

Figma's path to Make wasn't without missteps. David reflected on the mixed reception to their earlier AI feature, "Make Design," and shared two key learnings:

1. Be transparent about how your system works: With Make Design, users were confused about what models were being used and how their data might be involved. With Make, Figma is explicitly stating that it's powered by Claude 3.7 Sonnet.

2. Be clear about your intent: Some designers perceived Make Design as an attempt to replace them. With Make, Figma has focused on positioning the tool as extending designers' capabilities rather than replacing them.

"We love designers. We are you. We want to give you more powers and make you able to take your vision much further and not be limited by your current tools," David emphasises in the interview.

Key Takeaways for Product Leaders:

• Transparency about AI systems builds trust with users

• Carefully consider how you position AI features to avoid threatening users' professional identities

• Frame AI tools as augmenting human capabilities rather than replacing them

• Even the naming of features can significantly impact how they're perceived

🚀 The Future of Product Development

As the conversation concluded, David offered advice for makers in the AI era: "Just start making. You're going to learn by doing. You're going to build empathy... Build for yourself and your friends. You are the user. You have empathy. It's easy to understand if it's working or not."

This hands-on approach reflects a broader shift in product development. As AI tools like Make become more accessible, the barriers to creating functional software continue to fall. What once required teams of specialists can now be accomplished by individuals with ideas but no coding experience.

For product leaders, this represents both an opportunity and a challenge. The opportunity lies in faster iteration, more inclusive ideation, and the ability to test concepts before committing significant resources. The challenge comes in adapting processes and mindsets to this new reality, where the line between designer, product manager, and developer becomes increasingly blurred.

Key Takeaways for Product Leaders:

• The best way to understand AI's potential is to start building with it

• Focus on creating something playable rather than perfect

• AI is democratising software creation, enabling more people to bring their ideas to life

• Traditional role boundaries are blurring as AI tools make technical tasks more accessible

🔍 Final Thoughts

Figma Make represents a significant step forward in the evolution of prototyping tools. By combining AI's generative capabilities with Figma's collaborative foundation, Make enables teams to move from concept to functional prototype faster than ever before.

As David puts it in the podcast, "It's an incredible time to work in software and to be a maker." With tools like Make, the distance between imagination and implementation continues to shrink, opening new possibilities for innovation and creativity.

Figma Make is rolling out over the coming weeks to paying Figma customers and will appear as a new file type in the Figma file browser.

Key Takeaways for Product Leaders:

• AI-powered prototyping is becoming an essential part of the product development toolkit

• Tools like Make are changing expectations about how quickly ideas can be brought to life

• The combination of AI generation and real-time collaboration creates powerful new workflows

• Consider how your team might leverage AI prototyping to accelerate ideation and validation

 🎥Watch the full episode here

📅Timestamps:

• Timestamps: (00:00)

• Building the best design-to-prototype tool in the market

• 03:17) Demo: From static image to interactive solar system

• (06:05) 3 ways that Make stands out from other prototyping tools

• (12:01) How Make actually works behind the scenes

• (15:21) 4 types of evals to improve Make's AI prototypes

• (17:40) How the "Great Bakeoff" transformed the product

• (23:29) The biggest product challenges in building Make

• (27:23) Why prototypes are now the gold standard for design

• (35:07) How Figma learned from its past AI mistakes

• (40:36) Demo: Drawing apps, games, and more with Makex

That’s a wrap.

As always, the journey doesn't end here!

Please share and let us know what you would like to see more or less of so we can continue to improve your Product Tapas. 🚀👋

Alastair 🍽️.