Prompted: Builder Stories

Build AI Agents in 30 Minutes (Cursor, Codex, or Claude Code) - PROMPTED Ep 44

In this episode, we break down how to build a working AI agent in about 30 minutes using modern AI coding tools like Cursor, Codex, or Claude Code. Matthew Stein walks through a real, end-to-end example of building an agent from scratch. No fluff. No theory. Just a practical workflow you can follow and adapt to your own ideas. RESOURCES & LINKS 👉 Agent AI Build Kit (GitHub): https://github.com/Chefmattrock/agent-ai-build-with-cursor [https://github.com/Chefmattrock/agent-ai-build-with-cursor] 👉 Agent.ai Community (get help, share what you build): https://community.agent.ai/ [https://community.agent.ai/] You will see how to go from a rough idea to a functional agent using a simple but powerful process: * Define the problem and user * Generate a PRD (Product Requirements Doc) * Use AI coding tools to build the agent logic * Debug and refine outputs * Ship a working version fast This is not just about Cursor. The same approach works across today’s AI coding tools and models. If you have ever wanted to build your own agents but did not know where to start, this episode gives you a repeatable system. This is best suited for intermediate users, but beginners can follow along by pairing this with your favorite LLM to guide setup and implementation. If you are in GTM, product, marketing, or operations, this is one of the fastest ways to start turning AI into real workflows. WHAT YOU’LL LEARN * How to build an AI agent from scratch in ~30 minutes * Why everything starts with a simple PRD * How to use AI coding tools to generate agent workflows * How to debug and iterate when things break * How to turn ideas into usable agents quickly * A repeatable framework you can apply to your own use cases Building AI agents is no longer slow or complex. If you can clearly define the problem, AI can help you build the solution faster than ever. Start simple. Ship fast. Improve from there.

She Entered an AI Hackathon With No Technical Background… and Won - Ep 43

In this episode of PROMPTED, Kyle James sits down with go-to-market strategist Kat Hill Contag to talk about the experience that completely changed how she thinks about AI and building products. Kat is a GTM consultant who works with SaaS companies on product launches and market expansion. Like many operators, she was curious about AI but did not come from a technical background. Then she decided to try something new. Kat entered a women’s AI hackathon using the platform Lovable, gave herself two days to figure it out, and built a tool called AI Recess, a Duolingo-style platform designed to help teams learn practical AI workflows at work. What happened next surprised even her. In this conversation, Kyle and Kat explore: 1. What it is really like to participate in an AI hackathon 2. How non-technical professionals can start building with AI 3. Why operators may become the next generation of product builders 4. The mindset shift required to experiment with AI tools 5. Why more women need to be part of the AI conversation If you have ever wondered whether you could actually build something with AI, this episode might change how you think about it. Connect with Kat 1. LinkedIn - https://www.linkedin.com/in/khillcontag/ [https://www.linkedin.com/in/khillcontag/] 2. TikTok - https://www.tiktok.com/@kathillcontag [https://www.tiktok.com/@kathillcontag] 3. Personal Website - https://kathillcontag.com/ [https://kathillcontag.com/] 4. Try AI Recess - https://ai-recess.com/ [https://ai-recess.com/]

AI Won’t Fix Your Go-To-Market. It Will Amplify It. | Dale Zwizinski Ep 42

Most companies think their go-to-market is solid. It’s not. In this episode, Dale Zwizinski of Revenue Reimagined breaks down why AI will not fix a broken GTM foundation. It will expose it or amplify it. We dive deep into why startups and growth-stage companies skip stabilization, rush toward scale, and avoid pressure-testing their ICP, value proposition, and sales motion. Dale explains the four stages of the Go-to-Market Gap framework, why repeatability cannot happen without foundations, and how AI should be used to eliminate blank-page work, not replace strategic thinking. You’ll learn: 1. Why founders overestimate their GTM maturity 2. The difference between stabilization, foundation, repeatability, and scale 3. How AI can accelerate GTM work without creating chaos 4. Why most companies never revisit their ICP or value prop 5. How to build a human + agent collaboration model for 2026 If you care about building repeatable revenue in a rapidly shifting market, this conversation is essential. 🔗 Connect with Dale on LinkedIn: https://www.linkedin.com/in/dalezwizinski/ [https://www.linkedin.com/in/dalezwizinski/] 🔗 Visit Revenue Reimagined: https://www.revenue-reimagined.com/ [https://www.revenue-reimagined.com/] 🔗 Run the GTM Gap Report for your company: https://www.revenue-reimagined.com/gtm-gap [https://www.revenue-reimagined.com/gtm-gap] 🎙 Subscribe for more conversations on AI, go-to-market strategy, and building modern revenue engines.

AI as a Judgment-Free Strategy Room — For Work’s Hardest Decisions - Ep 41

What if AI wasn’t just a productivity tool… but a judgment-free strategy room? In this episode, I sit down with longtime friend and B2B SaaS executive Jeanne Hopkins to explore how she actually uses AI. Not for prompts. Not for hacks. But as a thinking partner. Jeanne has spent decades leading marketing, sales, and revenue teams as a multi-time VP of Marketing and Chief Revenue Officer. In our conversation, she shares how she uses AI to pressure test decisions, challenge assumptions, and run weekly retros on her own performance. We also go deeper. Jeanne opens up about navigating grief, complex family dynamics, and how AI helped her de-emotionalize and think clearly through some of the hardest decisions of her personal life. This is not a tools episode. It’s a mindset episode. If you want to understand what executive-level AI fluency actually looks like, this conversation is for you.

AI Turned a Product Designer Into a One-Person Startup | Building HerDiabetes - Ep 40

AI is changing how we work. For some, that means fear. For others, it means reinvention. In this episode, Kyle James sits down with Riley Gerszewski, a longtime product design leader who used AI tools to go from designing products to actually building and shipping a full iOS app himself. Not a prototype. Not a concept. A real healthcare app approved by Apple. Riley shares what it felt like to be part of a reduction in force, how AI accelerated his learning curve, and how he transitioned from specialist to generalist in real time. We talk about identity shifts, go-to-market uncertainty, ethical guardrails, and what it means to build responsibly in the healthcare space. The app he built, HerDiabetes, is designed specifically for women living with diabetes, a group of over 13 million in the United States alone, and addresses an underserved intersection of glucose data and hormonal cycle tracking. This conversation is not about hype. It’s about figuring it out as you go. If you’re a product leader, GTM professional, designer, or anyone trying to understand what AI means for your career, this episode is for you. LEARN MORE 🔗 HerDiabetes Website: https://www.herdiabetes.com/ [https://www.herdiabetes.com/] 🔗 Connect with Riley on LinkedIn: https://www.linkedin.com/in/rileygerszewski/ [https://www.linkedin.com/in/rileygerszewski/] If this episode resonated with you, consider subscribing, leaving a review, or sharing it with someone navigating their own AI reinvention. We’re all working through this shift together.