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The non-technical PM’s guide to building with Cursor | Zevi Arnovitz (Meta)

75 min episode · 2 min read
·
Zevi Arnovitz

Episode

75 min

Read time

2 min

Topics

Design & UX, Artificial Intelligence, Software Development

AI-Generated Summary

Key Takeaways

  • Slash Command Workflow: Create reusable prompts in Cursor for each development phase: create-issue captures ideas to Linear mid-development, exploration-phase analyzes requirements, create-plan generates markdown templates, execute-plan builds features, review catches bugs, and peer-review uses multiple AI models to validate code quality systematically.
  • Multi-Model Code Review: Run code reviews using Claude, GPT Codex, and Gemini simultaneously, then use peer-review slash command to have Claude evaluate feedback from other models. This approach catches different bug types since each model has distinct strengths—Claude excels at communication, Codex solves complex bugs, Gemini handles UI design.
  • Progressive Exposure Therapy: Start with ChatGPT projects as a CTO copilot, graduate to Bolt or Lovable for contained features, then move to Cursor in light mode before attempting full development. This gradual progression prevents code intimidation and builds technical understanding through controlled exposure to increasing complexity levels.
  • Documentation-Driven Improvement: After bugs or failures, ask AI what in its system prompt or tooling caused the mistake, then update documentation and slash commands to prevent recurrence. This continuous postmortem process compounds learning and creates increasingly intelligent prompts that reduce future errors across the entire development workflow systematically.
  • Learning Opportunity Command: Use slash learning-opportunity prompt configured for mid-level engineering knowledge with eighty-twenty rule explanations. This transforms every confusing technical decision into a teaching moment, building genuine understanding rather than blind reliance on AI outputs, essential for maintaining code quality and making informed architectural decisions independently.

What It Covers

Zevi Arnowitz, APM at Meta with zero coding background, demonstrates his complete workflow for building production apps using Cursor and Claude Code, including custom slash commands for planning, execution, and multi-model code review.

Key Questions Answered

  • Slash Command Workflow: Create reusable prompts in Cursor for each development phase: create-issue captures ideas to Linear mid-development, exploration-phase analyzes requirements, create-plan generates markdown templates, execute-plan builds features, review catches bugs, and peer-review uses multiple AI models to validate code quality systematically.
  • Multi-Model Code Review: Run code reviews using Claude, GPT Codex, and Gemini simultaneously, then use peer-review slash command to have Claude evaluate feedback from other models. This approach catches different bug types since each model has distinct strengths—Claude excels at communication, Codex solves complex bugs, Gemini handles UI design.
  • Progressive Exposure Therapy: Start with ChatGPT projects as a CTO copilot, graduate to Bolt or Lovable for contained features, then move to Cursor in light mode before attempting full development. This gradual progression prevents code intimidation and builds technical understanding through controlled exposure to increasing complexity levels.
  • Documentation-Driven Improvement: After bugs or failures, ask AI what in its system prompt or tooling caused the mistake, then update documentation and slash commands to prevent recurrence. This continuous postmortem process compounds learning and creates increasingly intelligent prompts that reduce future errors across the entire development workflow systematically.
  • Learning Opportunity Command: Use slash learning-opportunity prompt configured for mid-level engineering knowledge with eighty-twenty rule explanations. This transforms every confusing technical decision into a teaching moment, building genuine understanding rather than blind reliance on AI outputs, essential for maintaining code quality and making informed architectural decisions independently.

Notable Moment

Zevi built a complete student quiz platform with payment processing, multi-language support, and AI-generated assessments as a weekend project. His engineers at Meta now ask him to teach them his vibe coding techniques, reversing the traditional technical mentorship dynamic entirely.

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Episode Transcript

You are a product manager shipping product without knowing how to write code, barely knowing how to review code. I have zero technical background. Did music in high school when Sonnet 3.5 came out. I remember watching a YouTube video building apps using Bolt or Lovable. It basically felt like someone came up to me and said, you have superpowers now. These days, you're using Cursor with Claude Code. If you're nontechnical like me, code is terrifying, but AI just makes so much possible. In the next coming years, I think everyone's gonna become a builder. Titles are gonna collapse, and responsibilities are gonna collapse. The main challenge people have is reviewing the code that AI has written. It's very difficult for me to catch mistakes. What I'll do is basically slash review. This tells Claude to start reviewing its own code, but what's even cooler is I have codex as well as cursor open. I will have each of them review the code. This comes back to this quote I think everyone's always hearing. It's not that you will be replaced by AI. You'll be replaced by someone who's better at using AI than you. It's the best time to be a junior, contrary to what a lot of people are saying, how there's no more junior roles out there. Yeah. That's true. But also, when else in history could you get out of school and just build a startup on your own? Today, my guest is Zevi Arnowitz. Zevi's APM at Meta. Prior to that, he was APM at Wix. And this is a truly remarkable conversation that every non technical product person needs to hear. Zevi is super young and has no technical background, but as a smart, young, ambitious person, has learned how to use cursor and cloud code to build significant and real products completely on his own, and he's created his own very clever and effective workflow that everyone listening can copy. To make that copying even easier, at the top of the show notes of this episode, you can download all of the prompt and slash commands and start doing all of this yourself. Zevi shows you how to work with Cursor to quickly add your ideas to linear, to explore your idea with AI, how to develop your plan, how to then build a thing, and then have different LLMs review your code and update your documentation, and then use all of this as a learning opportunity to develop your own sense of how things work. I haven't stopped thinking about this conversation since we had it, and everyone needs to pay attention to what AI is unlocking for nontechnical people. A huge thank you to Tal Ravi for encouraging me to meet Zevi. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It helps tremendously. And if you become an annual subscriber of my newsletter, you get 19 premium products for …

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Books, tools, and gear mentioned in this episode

SignalCast may earn commission on purchases via these links.

Tools

  • ClaudeRecommended
    Run code reviews using Claude, GPT Codex, and Gemini simultaneously, then use peer-review slash command to have Claude evaluate feedback from other models.
  • CursorRecommended
    demonstrates his complete workflow for building production apps using Cursor and Claude Code, including custom slash commands for planning, execution, and multi-model code review.
  • GPT CodexRecommended
    Run code reviews using Claude, GPT Codex, and Gemini simultaneously, then use peer-review slash command to have Claude evaluate feedback from other models.
  • LovableRecommended
    graduate to Bolt or Lovable for contained features, then move to Cursor in light mode before attempting full development.
  • SPONSORS: DX
  • ChatGPTRecommended
    Start with ChatGPT projects as a CTO copilot, graduate to Bolt or Lovable for contained features, then move to Cursor in light mode.
  • GeminiRecommended
    Run code reviews using Claude, GPT Codex, and Gemini simultaneously, then use peer-review slash command to have Claude evaluate feedback from other models.
  • LinearRecommended
    Create reusable prompts in Cursor for each development phase: create-issue captures ideas to Linear mid-development.

company

  • SPONSORS: 10Web

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