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Rahul Agarwal
Founder | Agentic AI... • 2d
2025 is the year AI coding stopped being theory and became practice. But most teams are still figuring out how to use it. Cursor and Claude Code became everyday tools, while platforms like Lovable made software creation accessible to non-engineers. So what’s the right approach for different problems? Here’s a simple framework: 1/ Idea-First Coding Software creation without writing code line-by-line. You describe the outcome, the AI generates the implementation. Perfect for quick experiments before committing resources. Use when: • You need to validate features fast • Early-stage demos and mockups • Business teams testing concepts without engineering help Avoid for: Production environments or reliability-critical systems Examples: Lovable, Bolt, Replit 2/ Human-in-the-Loop Development Developers stay in charge while AI accelerates the work. Think: faster iteration, fewer repetitive tasks, better code quality. Use when: • Writing and refining daily code • Cleaning up boilerplate • Reviewing or improving existing code Examples: Cursor, Antigravity 3/ Agent-Driven Engineering AI handles multi-step execution: planning, writing, testing, revising. Claude Code set the benchmark for what this looks like in practice. Use when: • System migrations • Refactoring large codebases • Work that requires long reasoning chains Avoid for: Problems where goals aren’t well defined Examples: Claude Code, Gemini CLI, Codex But it’s important not to choose between these modes but to switch according to your specific use case and problem. Share this with others and follow for more such insights on AI.
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I finally understood the difference between Claude Code and Cursor. The answer is that Cursor will punish you for writing a bad prompt. if you write a good prompt it will give you good results, and if you write a bad one, you will get bad results.
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