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

How I AI

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محتوای ارائه شده توسط Claire Vo. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Claire Vo یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

How to Be a Better Human

1
How to make the most of a finite life (w/ Oliver Burkeman) 40:22

27 weeks پیش40:22

پخش در آینده

لیست ها

پسندیدن

دوست داشته شد

40:22

There’s only so much you can do in a week – or, according to Oliver Burkeman, in the roughly 4,000 weeks the average human lives. Oliver is a journalist and author of the books Four Thousand Weeks: Time Management for Mortals, Meditations for Mortals, and the newsletter “The Imperfectionist.” Chris and Oliver discuss the paradox of why change can only occur once we accept that we might not be able to change. Oliver also shares how life’s mishaps can become our most treasured memories and why sharing your imperfections is an act of generosity. For the full text transcript, visit go.ted.com/BHTranscripts For the full text transcript, visit go.ted.com/BHTranscripts For a chance to give your own TED Talk, fill out the Idea Search Application: ted.com/ideasearch . Interested in learning more about upcoming TED events? Follow these links: TEDNext: ted.com/futureyou Hosted on Acast. See acast.com/privacy for more information.…

حدود یک سال پیش 32:07

MP3•خانه قسمت

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.

18 قسمت

#Tech #Claire Vo

How I AI

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

How I AI

25 subscribers

published حدود یک سال پیش

اشتراک گذاری

MP3•خانه قسمت

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.

18 قسمت

#Tech #Claire Vo

Alle episoder

How I AI

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

1 day پیش40:11

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

1
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

۵ روز پیش48:54

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

12 روز پیش46:31

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

19 روز پیش44:56

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

26 روز پیش45:12

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.…

How I AI

1
Mastering ChatGPT: Advanced techniques for workplace communication and productivity | Hiten Shah 42:53

۵ weeks پیش42:53

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.…

How I AI

1
How to build prototypes that actually look like your product | Colin Matthews (Product leader, AI prototyping instructor at Maven) 32:07

۶ weeks پیش32:07

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

۷ weeks پیش40:28

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.…

How I AI

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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

۸ weeks پیش35:07

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

۹ weeks پیش36:20

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.…

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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

10 weeks پیش44:24

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

11 weeks پیش34:44

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

12 weeks پیش36:08

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

13 weeks پیش20:55

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.…

How I AI

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Vibe coding a 3D multiplayer game in 15 minutes—with no game dev experience | Cody De Arkland (Senior Director of Developer Experience at Sentry) 31:32

14 weeks پیش31:32

31:32

Cody De Arkland is the senior director of developer experience at Sentry, leading a team that empowers developers to build and ship software with greater safety and efficiency. Watch him speed-run the creation of a 3D multiplayer flight simulator—from scratch—in just 15 minutes, demonstrating the power (and creativity) that vibe coding enables. What you’ll learn: • How to approach building complex applications with AI by starting broad and iterating on specific features • The process of using multiple AI coding assistants simultaneously to build different components • Techniques for learning new technologies and frameworks through AI-assisted exploration • How to troubleshoot and fix issues when AI implementations don’t work as expected • The parallels between building fun projects and enterprise software with AI assistance • Strategies for keeping AI tools focused when they go off track or add unwanted features • The incredible velocity and productivity gains possible with modern AI coding tools • How anyone can now build sophisticated applications with minimal prior experience — Brought to you by: ⁠ Enterpret ⁠ —Customer superintelligence platform for product and CX teams ⁠ WorkOS ⁠ —Make your app enterprise-ready today with WorkOS — Where to find Cody De Arkland: Website: https://codyde.io/ LinkedIn: https://www.linkedin.com/in/codydearkland/ X: https://x.com/Codydearkland GitHub: https://github.com/codyde — 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 Cody (02:45) AI tools he’s using (04:38) How Cody vibe coded a multiplayer game: Spaceflight (09:37) Demo: Starting a new flight simulator project from scratch (13:49) How to learn about libraries and technologies for projects (17:06) First run of the new flight simulator game (19:26) Using multiple AI coding assistants simultaneously (20:43) Unexpected features and visual improvements (21:26) Testing the multiplayer functionality (22:31) Reflecting on the development process and iteration (26:47) Lightning round and final thoughts — Tools referenced: • Cursor: https://www.cursor.com/ • Windsurf: https://windsurf.com/ • Claude: https://claude.ai/new • Bolt: https://bolt.new/ • React: https://react.dev/ • v0: https://v0.dev/ — Other references: • Sentry: https://sentry.io/ • MCP: https://www.anthropic.com/news/model-context-protocol • Spaceflight: http://spaceflight.gg/ • Three.js: https://threejs.org/ • Socket.io: https://socket.io/ — 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 this former NYT columnist uses ChatGPT to brainstorm ideas, do research, and find the perfect metaphor | Farhad Manjoo 25:45

15 weeks پیش25:45

25:45

Farhad Manjoo , a former New York Times and Wall Street Journal columnist, reveals his AI-enhanced writing workflow, from research to finding the perfect metaphor, and how these tools have transformed his creative process without replacing his unique voice. What you’ll learn: • How AI evolved from a simple tool to an essential writing companion • Using ChatGPT as a research assistant with web search capabilities • The “super-thesaurus” technique for finding the perfect words and idioms • How AI helps brainstorm ideas and refine arguments • The benefits of having an “always-on” writing partner in a remote work world • Using AI as a first reader to evaluate drafts in progress • Why AI enhances rather than replaces a writer’s unique voice • Practical tips for getting unstuck when AI doesn’t deliver • How AI speeds up the writing process while improving quality • The future improvements that would make AI even more valuable for writers — Brought to you by: • Enterpret —Customer SuperIntelligence Platform for Product and CX teams • Vanta —Automate compliance and simplify security with Vanta — Where to find Farhad Manjoo: • LinkedIn: https://www.linkedin.com/in/farhad-manjoo-161229/ • X: https://x.com/fmanjoo — 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 (02:40) Farhad’s journey from skepticism to adoption of AI tools (04:20) Brainstorming with ChatGPT (06:54) Assessing the quality of AI-sourced information (08:34) How ChatGPT helps identify new angles and perspectives (10:52) Using ChatGPT to find alternatives to clichéd expressions (16:44) The “super-thesaurus” technique for finding perfect words and idioms (20:12) Using AI as a first reader for draft evaluation (22:15) Lightning round — Tools referenced: • ChatGPT: https://openai.com/chatgpt/overview/ • Cursor: https://www.cursor.com — Other references: • New York Times : https://www.nytimes.com/ • The Wall Street Journal : https://www.wsj.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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Gumroad CEO's playbook to 40x his team's productivity with v0, Cursor, and Devin | Sahil Lavingia 45:13

16 weeks پیش45:13

45:13

Sahil Lavingia is the founder and CEO of Gumroad, where AI agents are already writing 41% of all code commits, and he’s targeting 80% by year’s end. Sahil demonstrates how this approach allows him to transform what would typically be two-week projects into two-hour implementations—a 40x productivity increase. What you’ll learn: The exact AI workflow Sahil uses to build features 40x faster—from prototyping in v0 to implementation with Devin How Gumroad incentivizes AI adoption across the organization with $33,000 bounties for engineers who outperform the CEO How to use component libraries like shadcn/ui for effective AI development How AI is shifting engineering roles toward architecture and tech-debt removal while enabling designers and PMs to ship features directly Why spending more time on UX iteration becomes possible (and necessary) when implementation costs drop dramatically Which organizational functions will be transformed by AI next — Brought to you by: Enterpret —Customer SuperIntelligence Platform for Product and CX teams Vanta —Automate compliance and simplify security with Vanta — Where to find Sahil Lavingia: Gumroad: https://gumroad.com/ Website: https://sahillavingia.com/ LinkedIn: https://www.linkedin.com/in/sahillavingia X: https://x.com/shl — 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) Sahil’s background (⁠02:31⁠) How soon will AI do most engineering? (⁠04:08⁠) Live demo: redesigning with v0, Devin, and Cursor (⁠09:30⁠) Using the right tools (⁠11:03⁠) Prototyping and iteration with AI (⁠19:45⁠) Incentivizing AI adoption in teams (⁠24:50⁠) “Magical” date-picker component development (⁠31:47⁠) AI’s impact on marketing, sales, and support (⁠36:50⁠) Deciding what to build when AI builds everything (⁠40:02⁠) Conclusion and final thoughts — Referenced: • Devin: https://devin.ai/ • Cursor: https://www.cursor.so/ • v0: https://v0.dev/ • Tobi Lütke’s tweet on how AI usage is now a baseline expectation at Shopify: https://x.com/tobi/status/1909231499448401946 • Flexile: https://app.flexile.com/ • shadcn: https://github.com/shadcn/ui • Gusto: https://gusto.com/ • GitHub: https://github.com/ • Figma: https://www.figma.com/ • Slack: https://slack.com/ • Vercel: https://vercel.com/ • Next.js: https://nextjs.org/ — Production and marketing by https://penname.co/ . For inquiries about sponsoring the podcast, email jordan@penname.co.…

How I AI

1
Introducing How I AI 2:03

16 weeks پیش2:03

2:03

How I AI, hosted by Claire Vo, is for anyone struggling to keep up with the latest AI advancements, and wondering how to actually use these magical new tools to improve the quality and efficiency of their work. In each episode, guests will demonstrate a specific, practical, and impactful way they’ve learned to use AI in their life. Forget theoretical debates—this podcast is about real, concrete suggestions. Expect 30-minute episodes, live demos, and tips/tricks/workflows you can implement immediately. Whether you’re building products, leading teams, or just want to level up your AI game, this show helps demystify AI and give you the skills you need to thrive in this new world.…

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How I AI « » How to build prototypes that actually look like your product | Colin Matthews (Product leader, AI prototyping instructor at Maven)

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How I AI « »
How to build prototypes that actually look like your product | Colin Matthews (Product leader, AI prototyping instructor at Maven)