AI Product Kitchen

Sauce AI

0.0 (0)
TECHNOLOGY

AI Product Kitchen is Sauce AI's way of connecting our community of next gen Product Leaders, PMs, Designers, and Engineers - who are seeking answers on how AI is changing product. Tune in to hear us ask the spiciest questions to the best minds in AI and Product.

21/08/2025

Hiring More Humans Because of AI: The Counterintuitive Reality as We Build Trust in AI

Join us in the AI Product Kitchen this week as we talk to Ilan Frank, Chief Product Officer at Checkr. We explore the realities of building AI products in highly regulated industries, the counterintuitive challenges of AI implementation, and why most product teams are still in the early innings of the AI transformation. Ilan brings a wealth of experience from his previous roles as VP of Product at Slack (where he launched Slack Connect) and Head of Product at Airtable, giving him unique insights into scaling AI product organisations across different contexts. Learn about the practical challenges and unexpected discoveries that come with deploying AI in mission-critical applications, as Ilan shares honest insights on moving beyond the ChatGPT magic to building AI features that solve real customer problems. In this episode, we dive into: The 30-Inning Game of AI Product Development: Why most teams are only in inning 2 or 3 of AI adoption, what separates teams shipping AI products successfully, and the long journey ahead to truly AI-native organisations.Hiring More Humans Because of AI: The counterintuitive reality of how Checkr actually increased headcount in the short term due to AI implementation, requiring specialists to validate AI outputs.Building AI Products in Highly Regulated Industries: The critical importance of guardrails, compliance considerations, and why "we're wrong only 1% of the time" isn't acceptable when employment decisions are on the line.From Hack Day Brilliance to Production Reality: How a promising AI feature required careful reconsideration to ensure regulatory compliance, and the gap between AI demos and production-ready products.Data Moats and AI Strategy: How Checkr is transforming from a background check API into a comprehensive people intelligence platform, leveraging their unique data collection infrastructure to build sustainable competitive advantages in the AI era.Here's how to connect with us: Find Ilan on LinkedIn⁠Follow Matt on LinedIn⁠ and ⁠X⁠Learn more about CheckrAnd make sure to check out Sauce AI⁠ and follow us on LinkedIn⁠!Timestamps: 00:00 - Introduction to Ilan Frank and the 30-Inning Game of AI 01:02 - What Separates Successful AI Product Teams: Overcoming Fear 01:51 - Checkr's First AI Product: Charge Classification Success 03:00 - The Journey from Manual to AI-Powered Background Checks 04:36 - Customer-Driven Innovation: Speed vs Accuracy Trade-offs 06:18 - The Second AI Product: Charge Explainer Development 07:20 - When AI Features Go Wrong: Legal Compliance Challenges 09:05 - Identifying Problems Through Customer Feedback 10:18 - Building AI in Highly Regulated Industries: Zero Error Tolerance 11:11 - Human-in-the-Loop: Why AI Increased Hiring at Checkr 12:01 - Operations Specialists: The New AI Quality Assurance Role 12:42 - Future of AI Confidence: When Human Review Won't Be Needed 13:33 - Checkr's Evolution: From API to Comprehensive Platform 15:58 - The Data Advantage: Building Moats in Background Checks 16:52 - TAM Analysis: Expanding Beyond Background Checks 17:43 - AI Implementation Challenges: Magic vs Production Reality 20:11 - Hiring AI Product Managers: Skills and Imagination Over Experience 22:28 - Why AI Hasn't Transformed Product Management Yet 25:04 - Designing AI-Native Organizations for the Future 27:27 - The Next Five Years: Automation vs Human Oversight 32:08 - Competitive Threats: Startups vs Incumbents in AI 33:01 - Slack Connect and Enterprise Product Lessons 39:34 - Airtable's AI Strategy: Builders vs End-Users Decision 42:55 - Product Leader Advice: Just Do It and Focus on Pain Points 44:21 - Internal AI Tools: Design, Research, and Product Management 46:09 - The Unseen Pain: What AI Can't Yet Discover 48:09 - Product Beliefs: Being an AI Skeptic While Embracing AI 48:39 - Looking Ahead: Building the Human Data Graph

50 min
06/08/2025

Agents as Teammates: Linear’s AI Vision

Join us in the AI Product Kitchen this week as we talk to Nan Yu, Head of Product at Linear. In this episode, we talk about how Linear is transforming product development by turning AI agents into first-class team members and revolutionising how the highest-performing tech teams organise their work. Nan leads product at Linear, the modern issue tracking platform trusted by companies like OpenAI, Scale AI, and Ramp. Learn about Linear's unique approach to AI product development, from replacing manual taxonomies with intelligent systems to deploying synthetic actors that participate in software workflows just like human colleagues. In this episode, we dive into: Agents as First-Class Team Members: How Linear is building AI agents that can be assigned tasks, review code, and communicate through the platform like human teammatesThe Death of Manual Taxonomy: Why AI will make current approaches to organising backlogs, labelling issues, and categorising product ideas feel "obviously archaic" within five years.Diligence on Tap: How AI unlocks true product management by handling the consistent, repetitive work that currently requires large teams, freeing humans to focus on strategy and product taste rather than mundane tasks.Low-Cost AI Experimentation: Linear's bottom-up approach to AI development, running multiple prototype experiments simultaneously and scaling the winners based on real usage patterns from their own team.Counter-Positioning Against Giants: How Linear successfully competed with industry incumbents like Jira and Asana by focusing obsessively on the individual contributor experience over middle management’s reporting needs. Here's how to connect with us: Find Nan on LinkedIn⁠ and XFollow Matt on LinedIn⁠ and ⁠X⁠Learn more about LinearAnd make sure to check out Sauce AI⁠ and follow us on LinkedIn⁠! Timestamps: 00:00 - Introduction and Guest Welcome 00:28 - What Will Feel Archaic in Five Years 01:00 - Building Better Products vs Shipping More Features 02:05 - Decision Making and Product Clarity 03:07 - High-Performing vs Low-Performing Product Teams 04:23 - The Problem with Traditional Backlogs 07:12 - Understanding Taxonomies and Organization Systems 09:03 - The Journey from Old to New Ways of Thinking 10:27 - Customer Behavioral Shifts and On-Ramps 12:42 - Linear's Engagement Strategy: Distinct Issue Creators 15:16 - AI Strategy Part 1: Sharpening Existing Data 17:02 - AI Strategy Part 2: Synthetic Actors and Agents 18:42 - Which Workflows Will AI Take Over First 20:26 - Barriers to AI Adoption in Development 21:57 - Building AI Products: Augmentation vs Replacement 23:58 - Measuring Success with AI Products 25:10 - Business Model Evolution with AI 26:26 - Low-Cost AI Experimentation Process 28:01 - AI Project Examples: Winners and Failures 30:15 - Integrating AI Without Compromising Simplicity 32:32 - ROI and Impact of AI Products 33:17 - Future Impact on Product Team Structure 37:00 - Starting with Customer Problems in AI Development 39:46 - Customer Development and Beta Testing Process 41:27 - Focusing on Individual Contributors vs Buyers 44:15 - Effective Customer Interview Techniques

51 min
24/07/2025

From Meeting Bots to Revenue AI: Building Gong's $7B Platform

Join us in the AI Product Kitchen this week as we talk to Eilon Reshef, Co-Founder and Chief Product Officer of Gong. We dive into topics like building AI products before the current boom and Gong’s journey creating the leading revenue AI platform that's transformed how sales teams operate. Eilon shares fascinating insights from Gong's 10-year journey, starting when customers were genuinely scared of AI technology, through to building a multi-billion dollar platform that processes millions of sales conversations. As one of the pioneers who saw AI's potential back in 2015 (he even bought NVIDIA stock!), Eilon offers unique perspectives on what it takes to build world-class AI products that customers actually love. In this episode, we go deep on: Building AI Before It Was Cool: How Gong pioneered conversation intelligence when buyers were skeptical of AI, and the strategies they used to overcome early market resistance.The Design Partner Philosophy: Eilon's extreme approach to customer collaboration, where every PM works with a dozen design partners to iterate rapidly and ensure product-market fit before launch - his "secret sauce" for building AI products that provide real value.AI Augmentation vs Replacement: Why Gong deliberately chose to augment rather than replace salespeople, and Eilon's contrarian view on why the obsession with AI SDRs and replacement technology misses the bigger opportunity.From Single Feature to AI Platform: The strategic journey from simple call recording to a comprehensive revenue orchestration platform, including lessons on when to expand beyond your initial wedge and how to build defensible moats in AI.Measuring AI Product ROI: Practical approaches to demonstrating value from AI products, from talk ratio insights that became viral LinkedIn posts to building multiple value propositions tailored to different stakeholders (productivity, predictability, growth).Here's how to connect with us: Find Eilon on LinkedInFollow Matt on LinedIn and XLearn more about GongAnd make sure to check out Sauce AI and follow us on LinkedIn!Timestamps: 00:00 - Introducing Eilon Reshef 02:15 - Building AI Before It Was Hot 04:45 - Early AI Conviction and NVIDIA Investment 07:20 - The Inefficiency Problem in Sales Organizations 09:50 - Meeting Bots and Customer Fear 12:30 - Overcoming Early AI Skepticism 15:10 - Creating the Conversation Intelligence Category 18:25 - Category Creation Strategy and Naming 21:40 - Climbing Everest: Lessons and Mistakes 24:20 - The Power of Design Partners 27:45 - Design Partner Execution and Rituals 31:10 - Talk Ratio: The First Breakthrough Insight 34:30 - Big Brother Problem and Seller Value Creation 38:15 - One-Click Call Sharing Product Loop 41:00 - Expanding Beyond Single Product 44:20 - Measuring AI Product ROI 47:35 - Killing Products: Talk Tracks Feature 50:45 - Augmentation vs Replacement Philosophy 54:10 - Revenue Orchestration Platform Vision 57:25 - Building Product Moats in AI Era

53 min
14/05/2025

Vrushali Paunikar from Carta: The AI Revolution Meets Private Capital

This episode, Vrushali Paunikar - Chief Product Officer at Carta, joins us in the AI Product Kitchen. We talk about Carta's transformation from cap table management to becoming the ERP for private capital, and how they're leveraging AI to revolutionize financial systems stuck in the 80s and 90s. With nearly a decade at Carta, Vrushali has led product at the company through its journey from being rejected by almost every Series A investor to now powering over half of all VC-backed companies and managing over $2.5 trillion in equity. In this episode, we dive into: AI for Document Intelligence: How Carta evolved from early, unsuccessful AI experiments with legal documents to now extracting critical data and automating financial workflows using advanced AI models.AI Agents in Finance: Exploring how AI agents can orchestrate complex financial processes and resolve failing health checks automatically, transforming how private capital finance teams operate.Reimagining UX for AI: The challenges of designing user experiences for AI-powered workflows, from asynchronous processes to potential chatbot interfaces and the future of finance software.The ERP Vision for Private Capital: How connecting disparate systems through an ERP platform can eliminate the current practice of manually verifying numbers across systems, freeing finance teams from just "making sure the math is doing math correctly."Incumbent Advantages vs. Startup Opportunities: Why data-rich incumbents like Carta have an edge in AI, while AI-native startups can differentiate through new design paradigms and aggressive integration strategies. Here's how to connect with us: Find Vrushali on ⁠⁠⁠LinkedIn⁠⁠⁠⁠ and ⁠⁠⁠X⁠⁠⁠⁠Follow Matt on ⁠⁠⁠LinkedIn⁠⁠⁠⁠ and ⁠⁠⁠X⁠⁠⁠Learn more about CartaAnd make sure to check out ⁠⁠⁠Sauce AI⁠⁠ and follow us on ⁠⁠LinkedIn⁠⁠!⁠ Timestamps 00:00 - Introduction to Vrushali, CPO at Carta 01:15 - Carta's origin story: Rejected by every Series A investor 03:30 - Business model innovation: Changing the payer from law firms to companies 05:45 - Tackling "market too small”, objections in startups 07:20 - The pivot from liquidity marketplace to infrastructure platform 09:40 - Learning from product-market fit failure in private market liquidity 12:15 - Systems thinking approach to identifying new opportunities 14:30 - The "startup of startups" org structure at Carta 16:10 - From building new products to connecting the platform 17:45 - "Never Enter Data Twice" as a product philosophy 19:20 - Early AI experiments with legal document processing 21:30 - How AI is accelerating innovation at Carta today 23:40 - Executing on AI bets: From thesis to experimentation 25:15 - AI agents for orchestrating financial workflows 27:50 - Augmentation vs replacement debate in AI 29:30 - User experience challenges with AI-powered workflows 32:10 - AI's impact on design paradigms and information delivery 34:20 - Startup advantages in an AI-first world 36:45 - Using data to build opinionated products and decision guides 38:15 - The future of private capital finance: Beyond "making sure numbers tie up" 40:30 - CFOs evolving from back office to strategic operators

57 min
22/04/2025

Jeff Seibert: The Era of AI Accounting at Digits

Join us in the AI Product Kitchen this week as we talk to Jeff Seibert, CEO and co-founder of Digits. In this episode, we dive into topics like Jeff's time as Head of Consumer Product at Twitter and his mission to revolutionise the accounting industry with Digits, the first end-to-end accounting platform of the AI era. In this episode, we go deep on: In-house AI models vs off-the-shelf solutions: the importance of developing in-house AI models tailored to specific business needs, rather than relying solely on off-the-shelf solutions.Optimising user experience with AI: Creating an intuitive user experience where AI works seamlessly in the background, allowing users to focus on understanding their business rather than managing tedious accounting tasks.Product moats in the AI era: How AI can create durable competitive advantageCommon mistakes in AI product development: The pitfalls of putting AI at the forefront of the product narrative without addressing the core problem first.Lessons from Twitter and AI opportunities: Missed opportunities to leverage AI and the need for a broader mindset in recognizing AI's potential in product development. Here's how to connect with us: Find Jeff on ⁠⁠LinkedIn⁠⁠⁠, ⁠⁠X⁠⁠⁠ and on his websiteFollow Matt on ⁠⁠LinkedIn⁠⁠⁠ and ⁠⁠X⁠⁠Learn more about DigitsAnd make sure to check out ⁠⁠Sauce AI⁠ and follow us on ⁠LinkedIn⁠!⁠ Timestamps 00:00 - Introduction to Jeff Seibert and Digits 00:33 - Jeff's Journey and the Launch of Digits 01:42 - The Vision Behind Digits and AI in Accounting 03:11 - The Decision to Build in Stealth Mode 05:42 - The Importance of Product Quality and Timing 06:46 - The Evolution of Accounting Software 08:26 - Building AI Models for Accounting 10:39 - Defining Success: What is "Good Enough"? 12:18 - In-House Models vs. Off-the-Shelf Solutions 13:36 - User Experience and Automation in Digits 15:40 - Augmenting Accountants, Not Replacing Them 17:03 - Common Mistakes in AI Product Development 18:36 - Differentiating True Innovation from Noise 19:36 - Sustaining Competitive Advantage in AI 21:52 - Unique Team Structures and Agile Practices 24:12 - The Role of Product Managers in Digits 25:15 - Go-to-Market Strategy and Launching Products 26:38 - Lessons from Twitter and AI Opportunities 27:52 - Reflections on Apple and Product Design Principles 30:25 - The Importance of Product Obsession 32:32 - Prioritization Strategies for Product Development 34:32 - Future of Accounting and Automation

42 min
15/04/2025

Rachel Wolan (CPO Webflow): What's Changed Building AI Products in 10 Years

Join us for our very first episode of AI Product Kitchen from Sauce, where we welcome Rachel Wolan - Chief Product Officer at Webflow. With over a decade of experience in the AI space, Rachel shares her journey from launching her first AI product at Talkdesk to leading the development of multiple AI products at Webflow. In this episode, we discuss the intersection of AI and Product, exploring how AI can supercharge Product teams and enhance user experiences. Come take a deep dive into: The evolution of AI in product development: Understanding how AI has transformed from machine learning-based products to generative AI solutions.The importance of solving customer problems: Rachel emphasizes that regardless of advancements in AI, the core focus must always be on addressing user needs effectively.Differentiating between leading and following in the AI space: Insights on when to innovate and when to enhance existing products with AI capabilities.Building a strong AI team: Strategies for upskilling existing teams and integrating AI fluency across product management, design, and engineering.The future of Product in an AI world: Predictions on how AI will reshape the product lifecycle, including the roles of QA, prompt engineering, and user experience design. Here's how to connect with us: Find Rachel on ⁠LinkedIn⁠⁠ and ⁠X⁠⁠Follow Matt on ⁠LinkedIn⁠⁠ and ⁠⁠X⁠⁠And make sure to check out ⁠Sauce AI and follow us on LinkedIn!⁠ Episode timestamps 00:00 - Introduction to Rachel Wolan 00:37 - Rachel's AI Journey: A Decade of Experience 01:18 - The Evolution of AI Product Development 03:31 - Leading vs. Following in the AI Space 05:25 - Webflow's Initial Product Launch Strategy 06:51 - Transitioning to Multi-Product Offerings 08:37 - Building the First AI Team at Webflow 10:34 - Upskilling Teams for AI Fluency 12:11 - Investing in AI: Strategic Considerations 14:57 - Trends Reshaping Product Development 17:22 - Adapting Product Organization Structures 18:24 - Measuring Product Signal and Success 20:06 - Evaluating ROI on AI Investments 21:54 - Inspirations and Influencers in AI 23:10 - The Role of Human Augmentation in AI 25:25 - Designing Unique AI Experiences 27:03 - Go-to-Market Strategy for SMBs and Enterprises 30:48 - Prioritizing Features for Diverse User Personas 32:18 - The Concept of PM as GM 39:49 - Hiring PMs from Adjacent Functions 41:49 - Surprises in Building AI Products 42:42 - User Experience Challenges in AI 43:51 - Concerns and Excitement about AI's Future 44:56 - Future Predictions for Webflow Users 46:11 - Closing Remarks and Reflections

42 min
03/04/2025

How Linktree is Powering 50M+ Next Gen Creators with Jiaona Zhang, CPO of Linktree

Jiaona Zhang (JZ) is the Chief Product Officer at Linktree, who pioneered the 'link-in-bio' category and is one of the world's fastest growing product companies. JZ was previously the Senior VP Product at Webflow, VP Product at WeWork and Head of Product at Airbnb. JZ is also a Lecturer at Stanford University and a Program Creator at Reforge.

29 min

7 Episodes

AI Product Kitchen is Sauce AI's way of connecting our community of next gen Product Leaders, PMs, Designers, and Engineers - who are seeking answers on how AI is changing product. Tune in to hear us ask the spiciest questions to the best minds in AI and Product.

Creator

Sauce AI
Years Active

2K
Episodes

7
Rating

Clean
Copyright

© Sauce AI
Show Website

AI Product Kitchen