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

Jan 18, 2026 1h 15m 22 insights Episode Page ↗
Zevi Arnowitz, a non-technical PM at Meta, shares his unique AI-powered workflow for building real products from scratch. He details how he uses tools like Cursor and Claude code, along with custom slash commands, to manage the entire product development lifecycle.
Actionable Insights

1. Adopt a Structured AI Workflow

Implement a systematic workflow for building with AI, encompassing issue creation, exploration, plan development, execution, multi-model review, and documentation updates, to ensure comprehensive and efficient product development.

2. Create an AI ‘CTO’

For non-technical users, establish an AI project (e.g., in GPT or Cursor) with a custom prompt to act as a CTO. This AI should own technical implementation, challenge your ideas, and avoid being a ‘people pleaser’ to ensure robust technical decisions.

3. Implement Multi-Model Peer Review

After AI generates code, have multiple AI models (e.g., Claude, Codex/GPT, Composer) independently review the code. Then, use a ‘peer review’ command to present these findings to your primary AI agent, prompting it to justify or fix identified issues, which significantly improves code quality.

4. Continuously Update AI Tooling

When AI makes mistakes or fails to execute correctly, ask it to reflect on the root cause within its system prompt or tooling. Use this insight to update documentation and tools, preventing recurrence and continuously improving AI performance.

5. Leverage AI for Learning

When encountering difficult technical concepts, use an AI ’learning opportunity’ command to have the AI explain the concept using the 80-20 rule. This approach, tailored for a ’technical PM in the making,’ helps build engineering knowledge efficiently.

6. Start AI Building Gradually

If code is intimidating, begin your AI building journey slowly with a simple chatbot UI (like a GPT project), then progress to low-code platforms (like Bolt or Lovable), and finally transition to more advanced environments like Cursor in light mode, gradually easing into full development.

7. Use Slash Commands for Efficiency

Save frequently used prompts as reusable slash commands within your AI development environment (e.g., Cursor/Claude) to quickly invoke specific actions like creating issues, exploring ideas, or generating plans, streamlining your workflow.

8. Capture Issues with AI

When an idea or bug arises mid-development, use an AI slash command (e.g., /create issue) to quickly capture it and create a Linear issue. This allows you to maintain focus on your current task while ensuring new ideas are recorded.

9. Explore Ideas with AI

After an issue is captured, use an ’exploration phase’ AI command to have the AI analyze the problem, understand the existing codebase, and ask clarifying questions. This ensures a deep understanding of the problem and guides the best technical implementation.

10. Create Detailed Plans with AI

Utilize an AI command (e.g., /create plan) to generate a structured markdown file plan, including a TLDR, critical decisions, and broken-down tasks. This plan serves as a clear roadmap for execution and can be used by different AI models.

11. Specialize AI Model Usage

Allocate tasks to different AI models based on their strengths (e.g., Cursor’s Composer for speed, Gemini for UI/design, Claude for communicative technical leadership, GPT’s model for complex bug fixing). This optimizes efficiency and output quality.

12. Guide AI for Quality Output

To minimize ‘AI slop’ and ensure high-quality results, provide AI with clear guidelines and extensive context about your writing style, problem-solving approach, and specific requirements. This helps the AI produce more relevant and useful outputs.

13. Own All AI Outputs

Take full personal responsibility for any content or code generated by AI that you present or release. Blaming AI for mistakes is unacceptable; you are accountable for the quality and accuracy of your final deliverables.

14. Compartmentalize AI Contexts

Use AI ‘projects’ or similar features to separate different areas of your life or work (e.g., running, product management, personal projects). This prevents the AI’s memory from mixing up irrelevant information and ensures context-specific responses.

15. Be a ‘10x Learner’

Especially for junior professionals, prioritize being an exceptional learner over being a ‘10x doer’ or having all the answers. Actively seek out mentors, assess their strengths, and consult them for specific areas of expertise to accelerate your growth.

16. Embrace an ‘AI-First’ Mindset

When faced with any new challenge or problem, immediately consider how AI can assist in solving it. This proactive approach leverages AI’s capabilities for preparation, building, or learning, making it a default problem-solving tool.

17. PMs Can Code (Cautiously)

As a PM, you can use AI to build contained UI projects or create pull requests with AI-generated code for developers to finalize. This is particularly feasible in codebases with robust documentation for AI agents, but avoid complex database migrations.

18. Prioritize Human Mock Interviews

While AI can aid in interview preparation (e.g., mock interviews, question analysis), conducting human mock interviews is crucial, especially for competitive roles. This provides invaluable real-world practice and feedback that AI alone cannot fully replicate.

19. Use AI for Interview Feedback

Record your human interviews and feed them to an AI coach (e.g., a Claude project) to receive objective feedback on your performance. This helps identify areas for improvement, such as missed points or better phrasing, addressing the common lack of detailed human feedback.

20. Learn from AI’s ‘Perfect’ Answers

For interview preparation, ask AI to role-play as the ideal candidate and provide exemplary answers to questions. Studying these ‘perfect’ responses can offer valuable insights and improve your own articulation and content.

21. Build Your Own Startup

Recognize that the current AI era makes it the ‘best time to be a junior’ because individuals can now build and launch their own startups with minimal technical background and resources. This encourages entrepreneurship and independent creation.

22. Cultivate Key Traits

Develop curiosity, optimism, and a strong work ethic. These qualities, when combined with effective AI utilization, provide an ‘unfair advantage’ and enable individuals to deliver significant value, often surpassing those with more traditional experience.