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.
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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
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:
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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
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:
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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
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:
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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
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:
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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
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:
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And 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
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.