How A 91-year-old Vibe Coded A Complex Event Management System Using Claude And Replit

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הוסף לפני sixteen שבועות

תוכן מסופק על ידי Claire Vo. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Claire Vo או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

The Knowledge Project with Shane Parrish

1
Katharine Graham: The Woman Who Took Down a President [Outliers] 57:36

לפני 15 ימים57:36

הפעל מאוחר יותר

רשימות

לייק

אהבתי

57:36

When Katharine Graham took over the Washington Post in 1963, she was a shy socialite who'd never run anything. By retirement, she'd taken down a president, ended the most violent strike in a generation, and built one of the best-performing companies in American history. Graham had no training, no experience, not even confidence. Just a newspaper bleeding money and a government that expected her to fall in line. When her editors brought her stolen classified documents, her lawyers begged her not to publish. They said it would destroy the company. She published them anyway. Nixon came after her, attacking her with the full force of the executive. Then Watergate. For nearly a year she was ridiculed and isolated while pursuing the story that would eventually bring down the president. Graham proved that you can grow into a job that initially seems impossible and no amount of training can substitute for having the right values and the courage to act on them. ------ 10 Lessons from Katharine Graham: ⁠⁠ ⁠https://fs.blog/knowledge-project-podcast/outliers-katharine-graham/ ------ Approximate timestamps: (0:00) Start (02:19) The Making of an Unlikely Heiress (10:15) The Education of a Publisher’s Wife (22:16) Learning to Lead (30:46) Becoming a Media Titan (44:12) Legacy (47:59) Reflections + Lessons ------ Thanks to ReMarkable for sponsoring this episode. Get your paper tablet at reMarkable.com today ------ Upgrade : Get a hand edited transcripts and ad free experiences along with my thoughts and reflections at the end of every conversation. Learn more @ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/membership⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠ ------ Newsletter: The Brain Food newsletter delivers actionable insights and thoughtful ideas every Sunday. It takes 5 minutes to read, and it’s completely free. Learn more and sign up at ⁠⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/newsletter⁠⁠⁠⁠⁠⁠ ------ Follow Shane Parrish X ⁠@ShaneAParrish⁠ Insta ⁠@farnamstreet⁠ ⁠LinkedIn⁠ ------ This episode is for informational purposes only and contains the lessons I learned reading her memoir, Personal History and watching Becoming Katharine Graham. ------ Check out our website for all stock video and photo credits. Episode photo sourced from: iwmf.org/community/katharine-graham/ Learn more about your ad choices. Visit megaphone.fm/adchoices…

How I AI « »
How a 91-year-old vibe coded a complex event management system using Claude and Replit | John Blackman

לפני שנה 40:28

שתפו

MP3•בית הפרקים

John Blackman, a 91-year-old retired electrical engineer, shares how he used Claude and Replit to build a complex application for his church’s community service events—with no prior software development experience and for less than $350. His app allows event organizers to create events, recruit volunteers, and manage sign-ups, with a standout feature for organizing free oil changes for participants.

What you’ll learn:

How John used Claude to create detailed product requirements and user stories
John’s philosophy on embracing new technology throughout his career
The exact process for integrating third-party APIs (like VIN lookup for oil changes) with minimal technical knowledge
How he automated report generation for volunteer management and resource planning
How the software generates personalized Impact Passports for event participants
Why letting AI build without preconceived notions of “correct” implementation can lead to faster, more functional results
How to troubleshoot common development-to-production issues when working with AI coding tools

—

Brought to you by:

WorkOS—Make your app enterprise-ready today

Orkes—The enterprise platform for reliable applications and agentic workflows

—

Where to find John Blackman:

Website: http://johnbeng.com/

—

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

—

In this episode, we cover:

(00:00) Introduction to John Blackman and his background

(02:55) John’s impressive career

(03:59) How the church project started

(05:06) Using Claude to create a development roadmap and requirements document

(07:29) The concept of the Impact Passport for event participants

(08:57) Generating user stories and requirements with Claude

(10:32) The multi-tenant architecture with system and local church administrators

(12:54) Building the application with Replit

(13:32) Demo of the administrator interface and event management features

(17:56) Specialized reports for different services (food pantry, vision center, oil changes)

(20:30) The participant registration flow with QR code scanning

(21:55) Adding new features like volunteer name tag generation

(24:40) Troubleshooting AI “rabbit trails” during development

(26:09) Challenges moving from development to production

(27:13) John’s lack of coding experience

(29:42) The advantage of having no preconceived notions about implementation

(30:25) Total development costs and timeline

(31:31) Impact and reception from the church community

(32:42) Lightning round and final thoughts

—

Tools referenced:

• Claude: https://claude.ai/

• Replit: https://replit.com/

• SendGrid: https://sendgrid.com/

• AutoCAD: https://www.autodesk.com/products/autocad/

—

Other references:

• OpenAI API: https://openai.com/api/

• VIN (vehicle identification number): https://en.wikipedia.org/wiki/Vehicle_identification_number

• Multi-tenant architecture: https://en.wikipedia.org/wiki/Multitenancy

• Role-based access control: https://en.wikipedia.org/wiki/Role-based_access_control

• Excel: https://www.microsoft.com/en-us/microsoft-365/excel

• Docusign: https://www.docusign.com/

—

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

19 פרקים

#Tech #Claire Vo

How I AI

How a 91-year-old vibe coded a complex event management system using Claude and Replit | John Blackman

How I AI

24 subscribers

published לפני שנה

שתפו

MP3•בית הפרקים

What you’ll learn:

How John used Claude to create detailed product requirements and user stories
John’s philosophy on embracing new technology throughout his career
The exact process for integrating third-party APIs (like VIN lookup for oil changes) with minimal technical knowledge
How he automated report generation for volunteer management and resource planning
How the software generates personalized Impact Passports for event participants
Why letting AI build without preconceived notions of “correct” implementation can lead to faster, more functional results
How to troubleshoot common development-to-production issues when working with AI coding tools

—

Brought to you by:

WorkOS—Make your app enterprise-ready today

Orkes—The enterprise platform for reliable applications and agentic workflows

—

Where to find John Blackman:

Website: http://johnbeng.com/

—

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

—

In this episode, we cover:

(00:00) Introduction to John Blackman and his background

(02:55) John’s impressive career

(03:59) How the church project started

(05:06) Using Claude to create a development roadmap and requirements document

(07:29) The concept of the Impact Passport for event participants

(08:57) Generating user stories and requirements with Claude

(10:32) The multi-tenant architecture with system and local church administrators

(12:54) Building the application with Replit

(13:32) Demo of the administrator interface and event management features

(17:56) Specialized reports for different services (food pantry, vision center, oil changes)

(20:30) The participant registration flow with QR code scanning

(21:55) Adding new features like volunteer name tag generation

(24:40) Troubleshooting AI “rabbit trails” during development

(26:09) Challenges moving from development to production

(27:13) John’s lack of coding experience

(29:42) The advantage of having no preconceived notions about implementation

(30:25) Total development costs and timeline

(31:31) Impact and reception from the church community

(32:42) Lightning round and final thoughts

—

Tools referenced:

• Claude: https://claude.ai/

• Replit: https://replit.com/

• SendGrid: https://sendgrid.com/

• AutoCAD: https://www.autodesk.com/products/autocad/

—

Other references:

• OpenAI API: https://openai.com/api/

• VIN (vehicle identification number): https://en.wikipedia.org/wiki/Vehicle_identification_number

• Multi-tenant architecture: https://en.wikipedia.org/wiki/Multitenancy

• Role-based access control: https://en.wikipedia.org/wiki/Role-based_access_control

• Excel: https://www.microsoft.com/en-us/microsoft-365/excel

• Docusign: https://www.docusign.com/

—

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

19 פרקים

#Tech #Claire Vo

כל הפרקים

How I AI

1
How Amplitude built an internal AI tool that the whole company’s obsessed with (and how you can too) | Wade Chambers 40:26

לפני יומיים40:26

40:26

Wade Chambers , Chief Engineering Officer at Amplitude, shares how his team built Moda—an internal AI tool that gives employees access to enterprise data across multiple systems, enabling faster product development and decision-making while fostering cross-functional collaboration. What you’ll learn: 1. How Amplitude built a powerful internal AI tool in just 3 to 4 weeks of engineers’ spare time 2. A social engineering approach that made their AI tool go viral company-wide in just one week 3. How product managers use AI to analyze customer feedback across multiple data sources and identify key themes 4. A streamlined workflow that compresses research, PRD creation, and prototyping into a single meeting 5. Why role-swapping exercises with AI tools build empathy and cross-functional fluency across product, design, and engineering teams 6. How AI tools are helping engineering teams tackle persistent tech debt challenges more effectively — Brought to you by: CodeRabbit —Cut code review time and bugs in half. Instantly. Vanta —Automate compliance and simplify security — 25k giveaway: To celebrate 25,000 YouTube followers, we’re doing a giveaway. Win a free year of my favorite AI products, including v0, Replit, Lovable, Bolt, Cursor, and, of course, ChatPRD, by leaving a rating and review on your favorite podcast app and subscribing to the podcast on YouTube. To enter: https://www.howiaipod.com/giveaway . — Where to find Wade Chambers: LinkedIn: https://www.linkedin.com/in/wadechambers/ Amplitude: https://amplitude.com/blog/meet-the-team-wade-chambers — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to Wade Chambers (02:53) The build vs. buy decision for internal AI tools (04:55) What Moda is and how it works (07:19) The social engineering approach to adoption (09:17) Demo of Moda in Slack (10:58) Data sources Moda has access to (12:43) Analyzing customer feedback themes with Moda (17:41) Behind the scenes: how Moda works technically (23:24) Creating a PRD from a single customer insight (27:30) How teams actually use AI-generated PRDs (29:09) Impact on product development velocity (32:37) Engineers, designers, and PMs swapping roles (34:38) Recap of creating Moda (36:00) Lightning round and final thoughts — Tools referenced: • Glean: https://www.glean.com/ • ChatGPT: https://chat.openai.com/ • Cursor: https://cursor.com/ • Bolt: https://bolt.new/ • Figma: https://www.figma.com/ • Lovable: https://lovable.dev/ • v0: https://v0.dev/ — Other references: • Amplitude: https://amplitude.com/ • Slack: https://slack.com/ • Confluence: https://www.atlassian.com/software/confluence • Jira: https://www.atlassian.com/software/jira • Salesforce: https://www.salesforce.com/ • Zendesk: https://www.zendesk.com/ • Google Drive: https://drive.google.com/ • Productboard: https://www.productboard.com/ • Zoom: https://zoom.us/ • Asana: https://asana.com/ • Dropbox: https://www.dropbox.com/ • GitHub: https://github.com/ • HubSpot: https://www.hubspot.com/ • Abnormal Security: https://abnormalsecurity.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

1
An exclusive inside look at GPT-5 40:11

לפני 6 ימים40:11

40:11

In this episode, I share my hands-on experience with OpenAI’s GPT-5, the company’s new frontier model. As one of the first users outside of OpenAI to test the model, I put GPT-5 head-to-head with GPT-4.1 across real-world product use cases—from writing PRDs to generating code to assisting with visual design work. This is my unfiltered look at what GPT-5 can (and can’t) do—and how it changes the game for builders. What you’ll learn: 1. How GPT-5 differs from previous models with its engineering-focused approach to problem-solving and tendency to prioritize technical details over business context 2. A comparative analysis of how GPT-5 and GPT-4.1 generate different types of product requirement documents and prototypes for the same prompt 3. Why GPT-5 excels at technical writing, functional requirements, and code generation while potentially skipping important business discovery questions 4. The model’s impressive spatial awareness capabilities when generating images for interior design and other visual tasks 5. Practical considerations for choosing the right model based on your specific use case and audience 6. How GPT-5’s extensive tool-calling behavior and bullet-point communication style reflect its engineering-oriented design — Brought to you by ChatPRD —an AI copilot for PMs and their teams: https://www.chatprd.ai/howiai — 25k giveaway: To celebrate 25,000 YouTube followers, we’re doing a giveaway. Win a free year of my favorite AI products, including v0, Replit, Lovable, Bolt, Cursor, and, of course, ChatPRD, by leaving a rating and review on your favorite podcast app and subscribing to the podcast on YouTube. To enter: https://www.howiaipod.com/giveaway — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to GPT-5 (04:34) Testing GPT-5 in ChatPRD for document generation (07:10) Comparing GPT-5 and GPT-4.1 on business vs. technical orientation (11:22) Side-by-side comparison of PRDs generated by both models (15:23) Where GPT-5 excels: Technical considerations and documentation quality (17:35) Comparing prototypes generated from different model outputs (19:57) Testing homepage critique capabilities between models (23:14) OpenAI’s strengths in API design and developer support (25:37) GPT-5’s performance as a coding assistant (27:26) Examining GPT-5 in ChatGPT’s interface (28:50) Testing GPT-5’s front-end design capabilities (31:17) Personal use case: bathroom remodel planning (33:45) Comparing GPT-5 vs. GPT-4 for interior design visualization (38:10) Summary of key findings and recommendations — Tools referenced: • OpenAI: https://openai.com/ • ChatGPT: https://chat.openai.com/ • Claude: https://claude.ai/ • Gemini: https://gemini.google.com/ • Cursor: https://cursor.sh/ • v0: https://v0.dev/ • Lovable: https://lovable.dev/ • Bolt: https://bolt.com/ • LaunchDarkly AI Configs: https://launchdarkly.com/docs/home/ai-configs — Other reference: • Benjamin Moore paints: https://www.benjaminmoore.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

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How a VC and tech founder used AI to launch a brick-and-mortar business in their spare time | Andrew Mason (CEO of Descript) & Nabeel Hyatt (Partner at Spark Capital) 48:54

לפני 9 ימים48:54

48:54

Andrew Mason (founder of Groupon, now CEO of Descript) and Nabeel Hyatt (General Partner at Spark Capital) teamed up to open a physical board-game social club in Berkeley, with AI as their business partner. In this episode, they break down how they used Claude to generate a full business plan, model financials, plan the space layout, navigate Berkeley permitting, categorize hundreds of games using a custom Dewey Decimal–style system, and build an AI concierge that matches players with games via text. They also share how working on this side project helped rewire how they use AI in their day jobs—and why more people should use AI to build real-world things. What you’ll learn: 1. How to use Claude Projects as your business copilot to create comprehensive business plans, financial projections, and space layouts 2. A workflow for categorizing hundreds of board games using an AI-generated “Dewey Decimal System” that makes game discovery intuitive 3. How they built an AI concierge service that matches players with games and coordinates group play sessions via text message 4. Why AI enables side projects that would otherwise be impossible due to time constraints and specialized knowledge requirements 5. A simple system for creating customer personas that inform your business model and event programming 6. How to use model context protocols (MCPs) to connect AI assistants to business tools like Airtable without complex coding — Brought to you by: Lovable —Build apps by simply chatting with AI Persona —Trusted identity verification for any use case — Where to find Andrew Mason: LinkedIn: https://www.linkedin.com/in/andrewmason/ X: https://x.com/andrewmason — Where to find Nabeel Hyatt: LinkedIn: https://www.linkedin.com/in/nabeelhyatt/ X: https://x.com/nabeel — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to the board-game social club concept (02:44) How AI made a challenging side project possible (06:14) Using Claude as a business copilot for planning (12:53) Developing customer personas with AI (15:45) Using AI to determine business viability (21:02) Navigating Berkeley real estate and permitting (25:18) Building an AI concierge for game matchmaking (28:10) Database design with Airtable for non-technical founders (32:04) Creating a custom board-game categorization system (36:20) Demo of the text-based AI concierge service (40:38) Enabling experiences that wouldn’t exist without AI (43:42) Lightning round and final thoughts — Tools referenced: • Claude: https://claude.ai/ • Airtable: https://airtable.com/ • n8n: https://n8n.io/ • Twilio: https://www.twilio.com/ • Cursor: https://cursor.sh/ • Windsurf: https://www.windsurf.io/ • Python: https://www.python.org/ — Other references: • Model context protocol (MCP): https://www.anthropic.com/news/model-context-protocol • Tabletop Library: https://tabletoplibrary.com/ • Descript: https://www.descript.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

1
How Block’s custom AI agent supercharges every team, from sales to data to engineering | Jackie Brosamer & Brad Axen 46:31

לפני 16 ימים46:31

46:31

VP of engineering Jackie Brosamer and principal engineer Brad Axen join me to demo Goose, Block’s open-source AI agent that runs locally, plugs into your existing tools through model context protocol (MCP) servers, and peels away the rote parts of work so people can focus on insight and impact. This episode is packed with in-depth demos: starting with a messy farm-stand sales CSV, Goose analyzes the data, builds visualizations, and generates a shareable HTML report. We then spin up an MCP that lets Goose talk to Square’s dashboard for inventory management, vibe code an email MCP that can send payment links automatically, and unpack how environment setup, debugging, and tool orchestration get handled behind the scenes. What you’ll learn: A practical, repeatable workflow for turning any working script or function into a custom MCP—and exposing it to natural-language control How to transform messy CSVs into visualizations, HTML reports, and actionable business insights without needing a data science background Ways to hook Goose into live business systems (e.g. Square inventory, payments) so analysis flows directly into operational action The thinking behind Block’s decision to open-source Goose Lessons from Block’s bottom-up meets top-down adoption model Why organizational transformation, not just picking the right LLM, will separate AI winners from laggards over the next few years How to scale an internal MCP catalog The organizational transformation required to fully leverage AI capabilities — Brought to you by: CodeRabbit —Cut code review time and bugs in half. Instantly. Lenny’s List — Hands-on AI education curated by Lenny and Claire — Where to find Jackie Brosamer: LinkedIn: https://www.linkedin.com/in/jbrosamer/ — Where to find Brad Axen: LinkedIn: https://www.linkedin.com/in/bradleyaxen/ — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to Goose and its data analysis capabilities (02:27) How Block embraced AI across the organization (04:48) What Goose is and why Block open-sourced it (07:45) Demo: Analyzing farm-stand sales data with Goose (12:18) Creating shareable HTML reports from data analysis (14:15) Model context protocols (MCPs) that Goose uses (18:56) Demo: Using Square MCP to create a product catalog (23:35) Creating payment links from analyzed data (26:30) Demo: Building a custom email MCP (31:18) Testing the new email MCP with Goose (36:09) Debugging and fixing MCP code errors (38:44) Connecting workflows: sending payment links via email (41:30) Lightning round and final thoughts — Tools referenced: • Goose: https://block.github.io/goose/ • Pandas: https://pandas.pydata.org/ • Plotly: https://plotly.com/ • Python: https://www.python.org/ • ChatGPT: https://chat.openai.com/ • Claude: https://claude.ai/ • Cursor: https://www.cursor.com/ • Mailgun: https://www.mailgun.com/ — Other references: • Block: https://block.com/ • Model context protocol (MCP): https://www.anthropic.com/news/model-context-protocol • GitHub: https://github.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

1
Successfully coding with AI in large enterprises: Centralized rules, workflows for tech debt, and training your team | Zach Davis (Director of Engineering at LaunchDarkly) 44:56

לפני 23 ימים44:56

44:56

Zach Davis is a product-minded engineering leader and builder at heart, with over 12 years of experience building high‑performing teams and crafting developer tools at companies like Atlassian and LaunchDarkly. In this episode, he shares how he’s helping his 100-plus-person engineering team successfully adopt AI tools by creating centralized documentation, using agents to tackle technical debt, and improving hiring processes—all while maintaining high quality standards in a mature codebase. What you’ll learn: 1. How to create a centralized rules system that works across multiple AI tools instead of duplicating documentation 2. A systematic approach to using AI agents like Devin and Cursor to analyze and reduce test noise in large codebases 3. How to leverage AI tools to document your codebase more effectively by extracting knowledge from existing sources 4. Why “what’s good for humans is also good for LLMs” should guide your documentation strategy 5. A custom GPT workflow for improving interview feedback quality and coaching interviewers 6. How to approach tech debt reduction with AI by creating prioritized task lists that both humans and AI agents can work from — Brought to you by: WorkOS —Make your app enterprise-ready today Lenny’s List on Maven —Hands-on AI education curated by Lenny and Claire — Where to find Zach Davis: LaunchDarkly: https://www.launchdarkly.com LinkedIn: https://www.linkedin.com/in/zach-davis-28207195/ — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to Zach Davis (02:44) Overview of AI tools used at LaunchDarkly (04:00) The importance of having someone responsible for driving AI adoption (05:44) Why vibe coding isn’t acceptable for enterprise development (06:42) Making engineers successful with AI on their first attempt (07:55) Creating centralized documentation for both humans and AI agents (10:19) Using feature flagging rules to improve AI outputs (12:33) Advice for getting started with rules (14:28) Demo: Setting up Devin’s environment in a large codebase (24:33) Devin’s plan overview (27:55) Demo: Creating a prioritized tech debt reduction plan (36:40) Demo: Using AI to improve hiring processes and interview feedback (40:34) Summary of key approaches for integrating AI into engineering workflows (42:08) Lightning round and final thoughts — Tools referenced: • Cursor: https://www.cursor.com/ • Devin: https://devin.ai/ • ChatGPT: https://chat.openai.com/ • Claude: https://claude.ai/ • Windsurf: https://windsurf.com/ • Lovable: https://lovable.dev/ • v0: https://v0.dev/ • ChatPRD: https://www.chatprd.ai/ • Figma: https://www.figma.com/ • GitHub Copilot: https://github.com/features/copilot — Other references: • Jest: https://jestjs.io/ • Vitest: https://vitest.dev/ • MCP: https://www.anthropic.com/news/model-context-protocol • Confluence: https://www.atlassian.com/software/confluence — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

1
How this PM streamlines 60k-page FDA submissions and saves millions with Claude, Streamlit, and clever AI workflows | Prerna Kaul 45:12

לפני 30 ימים45:12

45:12

Prerna Kaul is a product and platform leader who has spent over 14 years turning machine-learning research into consumer and B2B products at Amazon Alexa, AGI, Moderna, and now Panasonic Well. In today’s episode, she explains how she’s using AI to slash some of the most time-consuming, expensive tasks in life sciences—from generating 60,000-page FDA submissions to crafting communication frameworks that help product managers navigate complex stakeholder dynamics. Her innovations are saving millions of dollars and helping lifesaving treatments reach the market faster. What you’ll learn: How Prerna built an AI system that automates the creation of 60,000-page regulatory documents for the FDA—reducing a process that took 4 to 6 months and 20 specialists to just minutes A step-by-step system for detecting and redacting PHI (protected health information) in clinical trial data using Claude How to build user-friendly interfaces for non-technical colleagues using Streamlit to democratize AI tools How to use Claude’s prompt generator to create powerful communication frameworks that help PMs navigate complex stakeholder situations Why transparency about AI costs is crucial for gaining organizational buy-in and tracking ROI A practical framework for approaching AI safety and ethics in highly regulated industries — Brought to you by: CodeRabbit —Cut code review time and bugs in half. Instantly: https://lovable.dev/ Lovable —Build apps by simply chatting with AI: https://lovable.dev/ — Where to find Prerna Kaul: LinkedIn: https://www.linkedin.com/in/prernakkaul/ — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to Prerna (03:01) The FDA submission challenge: 60,000 pages, months of work, millions in costs (05:20) Getting started in Claude: from prompt to production-ready prototype (10:13) How Claude selected the right models for medical entity recognition (12:04) Using Streamlit to create accessible UIs for non-technical users (16:04) Detecting and redacting PHI in unstructured clinical notes (18:44) Generating the Common Technical Document (CTD) for FDA submission (21:54) Tracking and displaying AI operation costs for stakeholder buy-in (24:38) Real-world impact on vaccine development timelines and costs (26:12) Creating an AI communication coach for product managers (30:22) Training Claude on classic literature and persuasion techniques (31:53) Analyzing a complex stakeholder scenario with multiple competing priorities (34:40) Getting personalized communication strategies inspired by tech leaders (35:40) Summarizing strategic approaches (38:26) Conclusion and final thoughts — Tools referenced: • Claude: https://claude.ai/ • Streamlit: https://streamlit.io/ • Anthropic Console: https://console.anthropic.com/ • Claude Sonnet 4: https://www.anthropic.com/claude/sonnet — Other references: • Claude project chat (AI Product Management Stakeholder Challenges): https://claude.ai/share/caba4ab0-b28a-480c-8633-71920b12999e • XML: ⁠https://www.w3.org/XML/⁠ • Python: ⁠https://www.python.org/⁠ • RegEx: ⁠https://regex101.com/ • Moderna: https://www.modernatx.com/ • FDA: https://www.fda.gov/ • Project Gutenberg: https://www.gutenberg.org/ • FDA Biologics License Application: https://www.fda.gov/vaccines-blood-biologics/development-approval-process-cber/biologics-license-applications-bla-process-cber • Protected health information (PHI): https://www.hhs.gov/hipaa/for-professionals/privacy/laws-regulations/index.html — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

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Mastering ChatGPT: Advanced techniques for workplace communication and productivity | Hiten Shah 42:53

לפני 5 weeks42:53

42:53

Hiten Shah is a serial founder who has started several analytics and security companies, including Crazy Egg and KISSmetrics. The latest one, Nira, was acquired by Dropbox in 2024. In this episode, he shares how he turns ChatGPT from a simple chatbot into a personal workplace coach, sales strategist, and productivity multiplier. What you’ll learn: How to create AI versions of your boss by loading operating manuals and personality tests into ChatGPT projects A simple approach for turning sales frameworks into customized discovery call scripts for any product Why context is everything—and how to load ChatGPT with the right information before asking for outputs The “show it what great looks like” technique that dramatically improves AI responses How to build a personal AI coach using your own personality assessments and communication style Why you should use temporary sessions for random queries to keep your main ChatGPT memory clean — Brought to you by: Paragon —Ship every SaaS integration your customers want Notion —The best AI tools for work — Where to find Hiten Shah: Blog: https://hitenism.com/ X: https://twitter.com/hnshah LinkedIn: https://www.linkedin.com/in/hnshah/ — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to Hiten (02:55) Why Hiten primarily uses ChatGPT (04:12) The importance of context and memory management (07:58) Demo: Creating “What Would Morgan Do” project (13:30) Using personality types to improve AI coaching (16:20) Building a personal operating system in ChatGPT (20:55) Mixing structured frameworks and personal context (23:20) Demo: Winning by Design sales framework implementation (30:00) Creating discovery call scripts (31:44) Using ChatGPT’s deep research feature to understand Claire’s leadership style (36:30) Lightning round and final thoughts — Tools referenced: • ChatGPT: https://chat.openai.com/ • Claude: https://claude.ai/ — Other references: • Hiten's Google Doc: https://docs.google.com/document/d/1j15hoR3qZLQMJuW-mtfYFyhXM0CpYHQkZJuUgqHBsZs/edit?tab=t.0 • Winning by Design: https://winningbydesign.com/ • Enneagram: https://www.enneagraminstitute.com/ • Human Design: https://humandesign.tools/ • Myers-Briggs: https://www.myersbriggs.org/ • DISC: https://www.discprofile.com/ • Lex: https://lex.page/ • The Lean Startup: https://theleanstartup.com/ • Sean Ellis score: https://pmfsurvey.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

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How to build prototypes that actually look like your product | Colin Matthews (Product leader, AI prototyping instructor at Maven) 32:07

לפני 6 weeks32:07

32:07

Colin Matthews is a product manager, founder, and hobbyist engineer. After spending the past eight years in healthtech, he recently left his role as a PM at Datavant to go full-time on building his own products. He is currently a top Maven instructor, helping PMs build their first AI prototype. In this episode, he shares a step-by-step workflow for creating component libraries from screenshots that stay true to your brand and reveals a clever Chrome extension trick for extracting code from any website to build reusable components. What you’ll learn: 1. How to create component libraries from screenshots that match your brand’s design system 2. A Chrome extension that can extract components directly from any website with a single click 3. Why forking prototypes is the key to efficient iteration without breaking your baseline 4. The structured prompting technique that makes AI tools actually listen to your instructions 5. How to introduce AI prototyping to your team without stepping on designers’ toes 6. The debugging approach that solves 90% of AI prototyping errors — Brought to you by: WorkOS —Make your app enterprise-ready today Notion —The best AI tools for work — Go deeper with Colin’s in-depth post in Lenny’s Newsletter: https://www.lennysnewsletter.com/p/how-to-get-your-entire-team-prototyping — Where to find Colin Matthews: LinkedIn: https://www.linkedin.com/in/colinmatthews-pm/ Tech For Product newsletter: https://colinmatthews.substack.com/ Tech For Product one-day team workshop: https://teams.techforproduct.com/ Maven course: AI Prototyping for PMs: https://bit.ly/3FQgZmw — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to Colin Matthews (02:46) Creating component libraries from screenshots in v0 (05:50) Using prompts to extract components from existing products (06:31) Building an Airbnb prototype from component libraries (11:36) Using the Magic Patterns Chrome extension to extract components directly from websites (18:38) The importance of improving components rather than the composed application (20:15) Using forks and versions for iterative prototyping (25:05) Managing team dynamics when introducing AI prototyping (26:54) Final thoughts — Tools referenced: • v0: https://v0.dev/ • Magic Patterns: https://magicpatterns.com/ • Magic Patterns Chrome Extension: https://chromewebstore.google.com/detail/html-to-react-figma-by-ma/chgehghmhgihgmpmdjpolhkcnhkokdfp?hl=en • Cursor: https://cursor.sh/ • ChatGPT: https://chat.openai.com/ • Bolt: https://bolt.new/ — Other references: • Colin’s AI prototyping prompt library: https://technical-foundations.notion.site/16c8fafdb669800ea6eeca11f40d046c?v=16c8fafdb6698069a6e4000c84a9ff2c • Airbnb: https://www.airbnb.com/ • Notion: https://www.notion.so/ • Amplitude: https://amplitude.com/ • PostHog: https://posthog.com/ • Figma: https://www.figma.com/ • GitHub: https://github.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

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How a 91-year-old vibe coded a complex event management system using Claude and Replit | John Blackman 40:28

לפני 7 weeks40:28

40:28

John Blackman , a 91-year-old retired electrical engineer, shares how he used Claude and Replit to build a complex application for his church’s community service events—with no prior software development experience and for less than $350. His app allows event organizers to create events, recruit volunteers, and manage sign-ups, with a standout feature for organizing free oil changes for participants. What you’ll learn: How John used Claude to create detailed product requirements and user stories John’s philosophy on embracing new technology throughout his career The exact process for integrating third-party APIs (like VIN lookup for oil changes) with minimal technical knowledge How he automated report generation for volunteer management and resource planning How the software generates personalized Impact Passports for event participants Why letting AI build without preconceived notions of “correct” implementation can lead to faster, more functional results How to troubleshoot common development-to-production issues when working with AI coding tools — Brought to you by: WorkOS —Make your app enterprise-ready today Orkes —The enterprise platform for reliable applications and agentic workflows — Where to find John Blackman: Website: http://johnbeng.com/ — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to John Blackman and his background (02:55) John’s impressive career (03:59) How the church project started (05:06) Using Claude to create a development roadmap and requirements document (07:29) The concept of the Impact Passport for event participants (08:57) Generating user stories and requirements with Claude (10:32) The multi-tenant architecture with system and local church administrators (12:54) Building the application with Replit (13:32) Demo of the administrator interface and event management features (17:56) Specialized reports for different services (food pantry, vision center, oil changes) (20:30) The participant registration flow with QR code scanning (21:55) Adding new features like volunteer name tag generation (24:40) Troubleshooting AI “rabbit trails” during development (26:09) Challenges moving from development to production (27:13) John’s lack of coding experience (29:42) The advantage of having no preconceived notions about implementation (30:25) Total development costs and timeline (31:31) Impact and reception from the church community (32:42) Lightning round and final thoughts — Tools referenced: • Claude: https://claude.ai/ • Replit: https://replit.com/ • SendGrid: https://sendgrid.com/ • AutoCAD: https://www.autodesk.com/products/autocad/ — Other references: • OpenAI API: https://openai.com/api/ • VIN (vehicle identification number): https://en.wikipedia.org/wiki/Vehicle_identification_number • Multi-tenant architecture: https://en.wikipedia.org/wiki/Multitenancy • Role-based access control: https://en.wikipedia.org/wiki/Role-based_access_control • Excel: https://www.microsoft.com/en-us/microsoft-365/excel • Docusign: https://www.docusign.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

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A designer's guide to Cursor: How to build interactive prototypes with sound, explore visual styles, and transform data visualizations | Elizabeth Lin 35:07

לפני 8 weeks35:07

35:07

Elizabeth Lin is an independent design educator who has crafted learning experiences for Khan Academy, Primer, and Lambda School. She currently runs design is a party , an alternative online design school where she teaches courses like The Art of Visual Design and Prototyping with Cursor . In this episode, she shares how designers can leverage Cursor to create interactive prototypes with sound, explore different visual aesthetics, and transform basic designs into polished interfaces—all without deep coding knowledge. What you'll learn: How to use Cursor to explore different design aesthetics—from brutalist to Y2K to cyberpunk A simple workflow for creating interactive sound elements in prototypes that would be difficult with traditional design tools A step-by-step process for transforming an ugly dashboard into a polished design using strategic prompting Why broadening your inspiration sources helps Cursor generate more unique and creative design Techniques for teaching AI tools to understand your design preferences and taste A practical approach to creating data-driven prototypes by connecting Cursor with Notion databases How to use Cursor Rules to streamline your prototyping workflow and avoid repetitive setup tasks — Brought to you by: Lovable —Build apps by simply chatting with AI Retool —AI that's designed for developers, and built for the enterprise — Where to find Elizabeth Lin: Website: https://www.lalizlabeth.com/ LinkedIn: https://www.linkedin.com/in/elizabethylin/ X: https://x.com/lalizlabeth — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction to Elizabeth (02:20) Demo: Exploring different visual styles with Cursor (08:20) Comparing different design iterations from the same prompt (12:35) Building a working piano prototype with one prompt (16:30) Understanding what’s happening behind the scenes (18:28) Practical design team scenarios using Cursor (21:00) Step-by-step walkthrough of transforming an ugly finance dashboard (27:29) Using targeted prompts to improve layout and visual design (29:22) Building data-driven prototypes powered by Notion databases (31:12) Lightning round and final thoughts — Tools referenced: • Cursor: https://cursor.sh/ • Notion: https://www.notion.so/ • v0: https://v0.dev/ • ChatGPT: https://chat.openai.com/ — Other references: • Edward Tufte: https://www.edwardtufte.com/ • Robinhood: https://robinhood.com/ • Cash App: https://cash.app/ • Stripe: https://stripe.com/ • Neopets: https://www.neopets.com/ • Goodreads: https://www.goodreads.com/ • Shad CN: https://ui.shadcn.com/ • Sketch: https://www.sketch.com/ • Figma: https://www.figma.com/ • Goodreads: https://www.goodreads.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

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Gamma’s head of design shares how his small team uses AI to synthesize feedback, generate on-brand imagery, and maintain design quality while serving users in 60+ countries | Zach Leach 36:20

לפני 9 weeks36:20

36:20

Zach Leach , head of design at Gamma, reveals how his small team uses AI to analyze global feedback, create on-brand imagery, and maintain design quality while serving users in more than 60 countries. What you’ll learn: How Gamma analyzes feedback from their 60% international user base using ChatGPT’s deep research capabilities How to transform hundreds of multilingual feedback items into actionable design insights A simple workflow for creating on-brand imagery using Midjourney-style references How to use AI to maintain brand consistency across a globally distributed product The secret to removing image backgrounds instantly using Replicate How to create consistent, high-quality job descriptions in minutes using AI templates — Brought to you by: WorkOS —Make your app enterprise-ready today Retool —AI that’s designed for developers and built for the enterprise — Where to find Zach Leach: LinkedIn: https://www.linkedin.com/in/zleach X: https://x.com/thisiszach — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Intro (02:42) Building the Gamma AI image editing feature (05:25) Using ChatGPT’s deep research for feedback analysis (09:10) How feedback was analyzed before AI tools (10:10) Benefits of deep research vs. basic scripting (12:40) Insights from ChatGPT's deep research (16:41) Demo of Midjourney workflow for creating on-brand art (23:54) Using Replicate for background removal (25:40) Style references (SREF) and brand consistency in Midjourney (29:19) An AI workflow for creating consistent job descriptions (32:27) Conclusion and final thoughts — ChatGPT feedback prompt “This is some feedback we’ve received about our AI image editing feature. I want you to analyze the feedback and find where we are doing poorly and where we are doing well. Break down for our product team what kinds of things we are doing well and why, and what kinds of things we are doing poorly and why. What do people love? What do people hate? Where can we improve?” — Tools referenced: • Gamma: https://gamma.app/ • ChatGPT: https://chat.openai.com/ • Midjourney: https://www.midjourney.com/ • Midjourney Style Reference (SREF): https://docs.midjourney.com/hc/en-us/articles/32180011136653-Style-Reference • Replicate: https://replicate.com/ • Figma: https://www.figma.com/ • Claude Projects: https://claude.ai/projects • GPT 4o image model https://openai.com/index/introducing-4o-image-generation/ — Other reference: • LaunchDarkly: https://launchdarkly.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

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The exact AI playbook (using MCPs, custom GPTs, Granola) that saved ElevenLabs $100k+ and helps them ship daily | Luke Harries (Head of Growth) 44:24

לפני 10 weeks44:24

44:24

Luke Harries , Head of Growth at ElevenLabs, the leading AI voice technology company, shares how he’s automating marketing workflows with AI—from case studies to translations to WhatsApp integrations—saving his company over $140,000 while making everything a launch. What you’ll learn: 1. How to create polished case studies in minutes using AI transcription and a custom GPT 2. How ElevenLabs built a custom AI translation system that saved them $140,000 annually and eliminated agency headaches 3. How to use Model Context Protocols (MCPs) to connect AI assistants to your WhatsApp messages 4. The “everything is a launch” philosophy that helps ElevenLabs maintain consistent marketing momentum 5. Why marketers should learn to code with AI tools like Cursor 6. How to create effective custom GPTs by focusing on prompt engineering rather than output editing — Brought to you by: Orkes —The enterprise platform for reliable applications and agentic workflows Retool —AI that’s designed for developers, and built for the enterprise — Where to find Luke Harries: Website: https://harries.co/ LinkedIn: https://www.linkedin.com/in/luke-harries/ GitHub: https://github.com/lharries X: https://x.com/lukeharries — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Intro (02:41) The future of AI in marketing (04:22) Using Granola and custom GPTs to write case studies (12:10) Generating tweet threads using ChatGPT (13:58) Building case studies into a systematic workflow (15:14) Best practices for prompt engineering (19:39) Building a custom translation system that saved $140k (25:10) Open sourcing the translation solution (29:47) Building a WhatsApp MCP (38:07) Creating specialized AI agents on demand (41:08) Lightning round and final thoughts — Tools referenced: • Granola: https://www.granola.ai/ • ChatGPT: https://chat.openai.com/ • Cursor: https://www.cursor.com/ • Claude: https://claude.ai/ • ElevenLabs: https://elevenlabs.io/ • WhatsApp: https://www.whatsapp.com/ • GitHub: https://github.com/ • Zapier: https://zapier.com/ • Calendly: https://calendly.com/ • Salesforce: https://www.salesforce.com/ — Other references: • MCP (Model Context Protocol): https://www.anthropic.com/news/model-context-protocol • WhatsApp MCP repo: https://github.com/lharries/whatsapp-mcp • Whatsmeow library: https://github.com/tulir/whatsmeow • LaunchDarkly: https://launchdarkly.com/ • Introducing ElevenLabs MCP: https://elevenlabs.io/blog/introducing-elevenlabs-mcp • Ordering a pizza using the ElevenLabs MCP server: https://x.com/elevenlabsio/status/1909300782673101265 • Chess.com: https://www.chess.com/ • Lovable: https://lovable.ai/ • v0: https://v0.dev/ • Figma: https://www.figma.com/ • Launch and launch again — how to launch your products: https://harries.co/launch-your-product • Your first growth hire: https://harries.co/first-growth-hire — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

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A 3-step AI coding workflow for solo founders | Ryan Carson (5x founder) 34:44

לפני 11 weeks34:44

34:44

Ryan Carson is a five-time founder who has spent the past 20 years building, scaling, and selling startups. In this episode, he shares his playbook for using AI to build products, turning “vibe coding” into a structured and scalable approach that can replace full engineering teams. What you’ll learn: 1. A simple three-file system that transforms chaotic AI coding into a structured, reliable process 2. How to create AI-generated PRDs and task lists that actually work 3. A step-by-step workflow using Cursor to build features systematically 4. Why slowing down to provide proper context is the secret to speeding up your AI development 5. How to use model context protocols (MCPs) to extend your AI’s capabilities beyond just coding 6. Why founders can now build entire companies with minimal engineering teams and how Ryan is doing it himself — Brought to you by: ChatPRD —An AI copilot for PMs and their teams Notion —The best AI tools for work — Where to find Ryan Carson: Website: https://www.ryancarson.com/about LinkedIn: https://www.linkedin.com/in/ryancarson/ X: https://x.com/ryancarson — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Introduction and Ryan’s recent AI projects (03:25) Demo: Creating a PRD with Cursor (05:00) Ryan’s open source links: https://github.com/snarktank/ai-dev-tasks (09:23) Repo Prompt: https://repoprompt.com/ (09:53) Quick recap and common mistakes to avoid (11:00) Demo: Generating a task list from the PRD (15:31) The importance of context when working with LLMs (18:07) Demo: Working through tasks systematically using Cursor (18:56) Change management (20:00) How task lists save time for product managers (21:50) Demo: Using MCPs for front-end testing (24:50) Specific MCPs and what to use them for (26:45) Demo: Using Repo Prompt to gain precise control over context (31:23) Music’s role in Ryan’s development stack (32:10) Lightning round and final thoughts — Tools referenced: • ChatGPT: https://chat.openai.com/ • Claude: https://claude.ai/ • Gemini 2.5 Pro: https://deepmind.google/models/gemini/pro/. • Repo Prompt: https://repoprompt.com/ • Taskmaster: https://github.com/nooqta/taskmaster • Browserbase: https://browserbase.com/ • Stagehand: https://docs.stagehand.dev/integrations/mcp-server — Other references: • PostgreSQL: https://www.postgresql.org/ • Prisma: https://www.prisma.io/ • SQL: https://www.sql.org/ • MCP: https://www.anthropic.com/news/model-context-protocol • VS Code: https://code.visualstudio.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

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How custom GPTs can make you a better manager | Hilary Gridley (Head of Core Product at Whoop) 36:08

לפני 12 weeks36:08

36:08

Hilary Gridley , Head of Core Product at Whoop, shares how she uses dozens of custom GPTs for her team that think and give feedback like her, allowing her to scale herself up and create time for higher-value work. What you’ll learn: 1. A step-by-step process for creating GPTs that “think like you” by reverse engineering your own decision criteria 2. How to turn your management expertise into clear evaluation rubrics that AI can consistently apply 3. Practical techniques for improving team writing and presentations with AI-powered feedback 4. Why GPTs are the perfect tool for scaling good management practices without requiring prompt engineering skills 5. How to use AI to get invited to more strategic meetings by improving your written point of view — Brought to you by: Orkes —The enterprise platform for reliable applications and agentic workflows Vanta —Automate compliance and simplify security — Where to find Hilary Gridley: Newsletter: https://hils.substack.com/ LinkedIn: https://www.linkedin.com/in/hilarygridley/ X: https://x.com/yourgirlhils — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Intro (02:52) Creating GPTs that think like you (04:23) Demo: Reverse engineering a recommendation algorithm (13:06) The value of articulating taste (15:33) Demo: Creating a slide deck evaluator GPT (19:19) Testing your new GPT (21:32) Scaling GPTs across your team (23:52) Demo: Using AI to improve your writing (30:32) Lightning round and final thoughts — Tools referenced: • GPTs: https://chat.openai.com/gpts • ChatGPT: https://chat.openai.com/ • Claude: https://claude.ai/ • Bolt: https://bolt.new/ — Other references: • Whoop: https://www.whoop.com/ • Norwegian School of Economics: https://www.nhh.no/en/ • Researchers at NHH have uncovered significant gender disparities in the adoption of generative AI tools like ChatGPT: https://www.nhh.no/en/nhh-bulletin/article-archive/2024/september/study-reveals-gender-gap-in-ai-tool-usage-among-students/ • How to Become a Supermanager with AI: https://maven.com/hilary-gridley/ai-powered-people-management • Girls in the Loop: https://grrlsintheloop.ai/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

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A designer's guide to AI: Why designing in Cursor lets you prototype 10x faster, simplifies collaboration, and accelerates getting ideas out of your head | Joel Unger 20:55

לפני 13 weeks20:55

20:55

Joel Unger , design director at Atlassian, shares how AI is transforming the way he designs Trello and other products. He walks through real-world workflows using tools like Midjourney and Cursor to prototype complex interactions, re-create brand assets, and explore creative directions faster than ever. You’ll hear how AI is helping designers focus on higher-level thinking, communicate better with developers, and push creative boundaries—all without replacing the human touch. What you’ll learn: How to prototype complex UI interactions using AI A workflow for re-creating animated brand assets without motion design tools How to leverage image generation tools like Midjourney to explore design directions and create mood boards How to use Cursor to re-create animated SVG assets Why AI frees designers to operate at a higher level of creativity How AI improves designer-developer collaboration by showcasing interactive intent Why embracing AI is key to staying ahead in the evolving design landscape The limitations of current AI tools and where they still fall short — Brought to you by: • ⁠Paragon⁠ —Ship every SaaS integration your customers want ⁠• WorkOS⁠ —Make your app enterprise-ready today — Where to find Joel Unger: Website: https://joelunger.com/ LinkedIn: https://www.linkedin.com/in/joelunger/ — Where to find Claire Vo: ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo — In this episode, we cover: (00:00) Intro and Joel's background (02:46) Trello's new productivity features (04:24) Traditional design process limitations in Figma (05:22) Using Cursor to prototype interactive panel systems (07:39) From prototype to production: collaborating with developers (08:52) How Joel used AI to prepare for the podcast (10:50) How AI saves designer time for deeper thinking (11:23) Last-minute logo animation using Cursor (13:50) Using Midjourney for character design exploration (14:56) Creating a mood board for Taco: the Trello husky mascot (16:49) How AI is changing design thinking and workflows (18:18) Lightning round and closing thoughts — Tools referenced: • Confluence: https://www.atlassian.com/software/confluence • Bitbucket: https://bitbucket.org/product/ • Trello: https://trello.com/home • Figma: https://www.figma.com • Cursor: https://www.cursor.com/ • ChatGPT: https://chatgpt.com/ • Midjourney: https://www.midjourney.com/ — Other reference: • Atlassian: https://www.atlassian.com/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

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