Counterintuitively, a model optimized for writing (GPT 5.1 High) excels at the planning stage in Cursor's "plan mode" due to its strength in logical thinking and step-by-step reasoning. For the actual code execution, switch to a coding-specific model like Sonnet.

LLMs often get stuck or pursue incorrect paths on complex tasks. "Plan mode" forces Claude Code to present its step-by-step checklist for your approval before it starts editing files. This allows you to correct its logic and assumptions upfront, ensuring the final output aligns with your intent and saving time.

Users often develop multi-product workarounds for issues they don't even recognize as solvable problems. Identifying these subconscious behaviors reveals significant innovation opportunities that users themselves cannot articulate.

Instead of writing Python or TypeScript to prototype an AI agent, PM Dennis Yang writes a "super MVP" using plain English instructions directly in Cursor. He leverages Cursor's built-in agentic capabilities, model switching, and tool-calling to test the agent's logic and flow without writing a single line of code.

Instead of prompting for code line-by-line, "Plan Mode" has the AI agent generate a detailed plan in a markdown file first. The user reviews and modifies this plan like a spec document, elevating their role from coder to architect before the AI executes the build.

While starting with a focused editor, Cursor's CEO sees a larger opportunity to become the single AI coding provider for its customers. This involves a deliberate multi-product strategy to build a "bundle" of tools that addresses the entire software development lifecycle, from individual coding to team collaboration, creating a powerful ecosystem.

Open-ended prompts overwhelm new users who don't know what's possible. A better approach is to productize AI into specific features. Use familiar UI like sliders and dropdowns to gather user intent, which then constructs a complex prompt behind the scenes, making powerful AI accessible without requiring prompt engineering skills.

In the early AI coding wars, many startups pursued ambitious, "science fiction" goals like creating autonomous agents. Cursor's success came from a deliberately narrow focus: building a dramatically better user experience within the existing VS Code ecosystem, a market already matured by GitHub Copilot. This pragmatic approach gained them immediate traction.

Unlike tools that immediately generate code from a prompt, Replit first engages in a planning phase. It collaborates with the user to define the structure and goals before execution. This structured, plan-first approach makes it a far stronger and more useful tool for product managers.