How I use Claude Code: Separation of planning and execution

boristane.com
February 22, 2026
12 min read
74/100
Summary
Claude Code has been used as a primary development tool for approximately nine months, focusing on a workflow that differs significantly from traditional methods. This alternative workflow aims to improve outcomes for complex coding tasks, avoiding the pitfalls of common practices that lead to messy results.
Key Takeaways
- The author uses Claude Code as a primary development tool, emphasizing a workflow that separates planning from execution to improve results and control over architecture decisions.
- The research phase involves asking Claude to deeply understand the codebase and document findings in a markdown file, which serves as a review surface to ensure comprehension before planning.
- The planning phase requires a detailed implementation plan in a markdown file, including code snippets and considerations, which the author prefers over Claude Code's built-in plan mode for better control.
- The author highlights that failures in AI-assisted coding often stem from incorrect implementations that work in isolation but disrupt the overall system, making thorough research essential.
Coverage & discussions
Hacker News · boristane.com
Community discussions
Historical count: 5 · 5 saved in sample · Historical sample
Analysis ready
Community Sentiment
Positives
- Using Claude Code for lecture preparation allows for a structured approach, transforming detailed notes into visually appealing slides, which enhances the quality of presentations.
- The practice of separating planning and execution in coding workflows is simple and effective, ensuring better control and quality in the output.
- Utilizing LLMs for planning sessions can streamline project specifications, making it easier to manage complex codebases and maintain clarity.
Concerns
- The reliance on detailed prompts and orchestration in Claude Code can be seen as cumbersome for experienced developers, potentially reducing overall productivity.
- The need for specific conditions, like a clear validation loop and AI-enabled tooling, limits the practicality of unsupervised agent workflows for most users.
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