A Structured Workflow for Using Claude Code: Research-Plan-Implement Methodology
By
vinhnx
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Summary
The article describes an author's unique workflow for using Claude Code, an AI coding assistant, emphasizing a structured approach where code is never written until a detailed written plan is reviewed and approved. The author contrasts this with typical AI coding workflows that often produce messy, non-maintainable results. The core methodology involves a research-plan-implement cycle where extensive research and planning precede any code generation, ensuring the AI understands the full context and requirements before implementation. The article provides practical examples and explains why this approach leads to more maintainable, well-structured code compared to typical prompt-and-fix patterns.
Key quotes
· 5 pulledThe workflow I'm going to describe has one core principle: never let Claude write code until you've reviewed and approved a written plan.
Most developers type a prompt, sometimes use plan mode, fix the errors, repeat. The more terminally online are stitching together ralph loops, mcps, gas towns (remember those?), etc. The results in both cases are a mess that completely falls apart for anything non-trivial.
The research-plan-implement workflow I use to build software with Claude Code, and why I never let it write code until I've approved a written plan.
This approach ensures that Claude understands the full context and requirements before writing any code, leading to more maintainable and well-structured results.
The key difference is that instead of jumping straight to code generation, you invest time upfront in research and planning, which pays off in cleaner, more reliable implementations.
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