How I AI

• The complete beginner’s guide to coding with AI: from PRD to generating your very first lines of code

  This episode is for complete beginners. I walk you through how to build your very first coding project using AI tools—even if you’ve never written a line of code. Together, we’ll create a personal project hub that automatically generates documentation and lets you build interactive prototypes. I’ll show you the process step by step—from setting up a repository, to creating AI agents that help with specific tasks, to deploying a functional web app locally.What you’ll learn:How to set up a simple Next.js application from scratch using Cursor’s AI agent capabilitiesMy workflow for creating AI agents that generate consistent documentation (like PRDs in Markdown format)How to build and display clickable prototypes without worrying about complex backend functionalityThe basics of using GitHub to track changes and manage your code repository as a non-technical personWhy starting with a personal project hub is the best way to ease into AI-assisted codingMy favorite practical tips for iterating on designs and functionality using AI tools—without needing deep technical expertise—Brought to you by:ChatPRD—An AI copilot for PMs and their teams—In this episode, we cover:(00:00) Introduction(05:11) Starting with a requirements document in ChatPRD(08:22) Attempting to use v0 for initial prototyping(15:02) Pivoting to Cursor for initial prototyping(20:20) Running the app locally and reviewing the initial version(24:07) Setting up GitHub for version control(27:09) Creating an AI agent for writing PRDs(31:04) Using the agent to create a sample PRD(35:00) Building a prototype based on the PRD(37:00) Testing and improving the prototype(40:00) Adding documentation and improving the design(43:20) Recap of the complete workflow—Tools referenced:• Cursor: https://cursor.com/• ChatPRD: https://www.chatprd.ai/• v0: https://v0.dev/• GitHub Desktop: https://desktop.github.com/• Next.js: https://nextjs.org/• Tailwind CSS: https://tailwindcss.com/—Other references:• Lovable: https://lovable.ai/• Bolt: https://bolt.new/• Claude Code: https://www.claude.com/product/claude-code• Markdown: https://www.markdownguide.org/• GitHub: https://github.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  45:01

  --------

  45:01
• “Vibe analysis”: How Faire’s data team uses AI to investigate conversion drops, analyze experiment results, and convert raw data into executive-ready insights

  Tim Trueman and Alexa Cerf from Faire’s data team demonstrate how AI tools are revolutionizing data analysis workflows. They show how data teams, product managers, and engineers can use tools like Cursor, ChatGPT, and custom agents to investigate business metrics, analyze experiment results, and extract insights from user surveys—all while dramatically reducing the time and technical expertise required.What you’ll learn:1. How to use AI to investigate sudden drops in business metrics by searching documentation and codebases2. Techniques for creating a semantic layer that helps AI understand your business data3. How to build end-to-end analytics workflows using Cursor and Model Context Protocols (MCPs)4. Ways to automate experiment analysis and create standardized reports5. How AI can help design and analyze customer surveys6. Strategies for creating executive-ready documents from raw data analysis7. Why every team member should have access to code repositories—not just engineers—Brought to you by:Zapier—The most connected AI orchestration platformBrex—The intelligent finance platform built for founders—Where to find Tim Trueman:LinkedIn: https://www.linkedin.com/in/tim-trueman-99788592/—Where to find Alexa Cerf:LinkedIn: https://www.linkedin.com/in/alexandra-cerf/—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 Tim and Alexa from Faire(02:53) The challenge of analyzing product quality and usage(04:14) Breaking down what analytics actually involves beyond data manipulation(05:46) Demo: Investigating a conversion rate drop using enterprise AI search(09:05) Using ChatGPT Deep Research to analyze code changes(12:40) Leveraging Cursor as the ultimate context engine for code analysis(18:55) Analyzing a new product feature’s performance with Cursor(26:27) How semantic layers make AI tools more effective for data analysis(30:00) Using Model Context Protocols (MCPs) to connect AI with data tools(34:17) Creating visualizations and dashboards with Mode integration(37:04) Generating structured analysis documents with Notion integration(44:39) Building custom agents to automate experiment result documentation(53:10) Designing and analyzing customer surveys(59:40) Lightning round and final thoughts—Tools referenced:• Cursor: https://cursor.com/• ChatGPT: https://chat.openai.com/• Notion: https://www.notion.so/• Snowflake: https://www.snowflake.com/• Mode: https://mode.com• Qualtrics: https://www.qualtrics.com/• GitHub: https://github.com/—Other references:• Model Context Protocol (MCP): https://www.anthropic.com/news/model-context-protocol• Faire Careers: https://www.faire.com/careers—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  1:03:28

  --------

  1:03:28
• Vibe-coding a kid-friendly AI fortune teller for your Halloween festivities | Marco Casalaina (Microsoft VP)

  In this impromptu Halloween special, Marco Casalaina (VP of Products for Core AI at Microsoft) demonstrates how he uses GitHub Spark to quickly build a mobile app that generates kid-friendly fortunes for trick-or-treaters.—Where to find Marco Casalaina:LinkedIn: https://www.linkedin.com/in/marcocasalaina/X: https://x.com/amrcn_werewolf?lang=en—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(00:40) Marco’s Halloween fortune teller tradition(02:54) Using GitHub Spark to create a fortune teller app(04:32) Using Spec Kit for scoping out complex feature specs(06:53) Making fortunes more concrete and kid-friendly(10:20) Closing thoughts—Tools referenced:• GitHub Spark: https://github.com/features/spark• SpecKit: https://github.com/github/spec-kit• GitHub Copilot: https://github.com/features/copilot• Cursor: https://cursor.com/• Claude Code: https://www.claude.com/product/claude-code—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  11:46

  --------

  11:46
• “Cursor is a much better product manager than I ever was”: How this PM uses AI for PRDs, Jira tickets, and replying to coworkers | Dennis Yang (Chime)

  Dennis Yang is the Principal Product Manager for Generative AI at Chime, where he’s pioneered AI workflows that meaningfully increase productivity. While most people use Cursor as a coding tool, Dennis has turned it into a comprehensive product-management system that automates PRD creation, documentation management, ticket creation, status reporting, and even comment responses—without writing code. In this episode, he shares his end-to-end workflow and how non-technical professionals can leverage AI-powered IDEs.What you’ll learn:Why Cursor is the perfect hub for product management (even if you don’t code)How to use MCPs (Model Context Protocols) to push content between Cursor, Confluence, and NotionThe workflow for creating PRDs in Cursor and automatically responding to commentsHow to automate Jira ticket creation directly from your PRDsA system for generating comprehensive status reports without manual workHow to prototype AI products in minutes using Cursor as a “super MVP” environmentWhy source-controlled markdown files might replace traditional SaaS tools—Brought to you by:Zapier—The most connected AI orchestration platformBrex—The intelligent finance platform built for founders—Where to find Dennis Yang:Twitter/X: https://twitter.com/sinnedLinkedIn: https://www.linkedin.com/in/dennisyang/Chime: https://www.chime.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 Dennis Yang(03:00) Why Cursor is ideal for product management workflows(04:53) Setting up Cursor for non-coding use cases with markdown preview(09:35) Creating PRDs in Cursor and using source control for documentation(10:33) Using MCPs to publish content to Confluence and Notion(11:38) Bridging the gap between engineering and product(17:00) Reading and responding to document comments with AI assistance(21:37) Creating comprehensive Jira tickets directly from PRDs(25:51) Generating automated status reports from Jira data(30:23) Building a morning briefing system with ChatGPT(35:03) Generating personal morning briefings using ChatGPT(40:04) The “super MVP” approach to AI product development(46:37) Lightning round and final thoughts—Tools referenced:• Cursor: https://cursor.com/• Confluence: https://www.atlassian.com/software/confluence• Notion: https://www.notion.so/• Jira: https://www.atlassian.com/software/jira• ChatGPT: https://chat.openai.com/• Claude: https://claude.ai/• Git: https://git-scm.com/—Other references:• News API: https://newsapi.org/• Semrush: https://www.semrush.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  50:07

  --------

  50:07
• Claude Skills explained: How to create reusable AI workflows

  Today I dive into Anthropic’s latest feature that lets anyone create reusable workflows for Claude—no coding required. I break down exactly what Claude Skills are, how to build them from scratch, and how to use them inside Claude Code and Cursor to automate recurring AI tasks like generating PRDs, writing changelog summaries, and turning demo notes into follow-up emails.What you’ll learn:What Claude Skills are and how they differ from Claude Projects and custom GPTsHow to structure a Skill (metadata, instructions, and linked files)Why defining workflows in natural language beats rigid automation toolsHow to create Claude Skills using Claude Code and CursorHow to validate your skills with Python scripts and folder referencesHow to upload and use Claude Skills inside Claude’s web or desktop appPractical examples: turning changelogs into newsletters, demo notes into emails, and more—Brought to you by:ChatPRD—An AI copilot for PMs and their teams—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(01:39) What are Claude Skills and how do they work?(08:30) The structure of Claude Skills files(11:00) Demo: Creating Skills using Claude’s built-in skill creator(16:08) A more efficient workflow: Creating Skills with Cursor(17:42) Using Python validation scripts(18:37) Testing Skills with Claude Code(20:52) Creating a changelog-to-newsletter Skill(22:16) Creating a demo-to-follow-up-email Skill(23:45) Uploading Skills to the Claude web interface(26:04) Conclusion and summary—Tools referenced:• Claude: https://claude.ai/• Claude Code: https://claude.ai/code• Cursor: https://cursor.sh/—Other references:• Equipping agents for the real world with Agent Skills: https://www.anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills• Anthropic Skills Documentation: https://docs.claude.com/en/docs/claude-code/skills?utm_source=chatgpt.com• Claude Projects:https://claude.ai/projects—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  27:23

  --------

  27:23

Más podcasts de Tecnología

Podcasts a la moda de Tecnología

Acerca de How I AI