Build Wide, Ship Narrow
adapt.com
August 12, 2026
10 min read
🔥🔥🔥🔥🔥
48/100
Summary
Effective engineering involves planning before coding, typically through writing a Request for Comments (RFC) to outline features and breaking them into smaller, manageable issues. This method helps maintain manageable code reviews and prevents complications from large merges, though it requires making critical structural decisions early in the process.
Key Takeaways
- AI assistants can significantly reduce the time needed to turn a clear problem into working code, sometimes achieving this in hours or minutes.
- The process of decomposing a finished branch into smaller pull requests (PRs) has become easier, allowing for more efficient code review and iteration.
- Product validation remains a slow process, but having a fully functional feature early enables feedback before code is reviewed.
- Engineers should focus on building wide and iterating based on revealed code boundaries rather than pre-defining boundaries before coding.
Community Sentiment
Positives
- The idea of using AI agents to clean up git histories is intriguing; it could streamline the messy process of iterative coding and make deployments cleaner.
- There’s a lot of good advice here for shipping substantial changes while maintaining code quality, which is crucial for mature codebases.
Concerns
- Many commenters find the AI-generated article hard to understand and believe it lacks clarity, which undermines its value.
- The examples of AI agents making changes are largely criticized as being terrible, with many users noting they're filled with unrelated adjustments that don't focus on quality.
