Tech • IA • Crypto
The Explore → Plan → Code → Commit workflow in Claude Code
TL;DR
A structured “explore, plan, code, commit” workflow is emerging as a best practice for AI-assisted development, reducing rework and improving reliability.
KEY POINTS
Four-step workflow gains traction
Developers are adopting a repeatable cycle—explore, plan, code, commit—to guide AI-assisted coding. The approach emphasizes understanding a codebase and defining success criteria before generating code, which reduces later corrections and speeds delivery.
Plan mode separates thinking from editing
In plan mode, the AI reads files and gathers context without modifying code. It can locate where features belong, assess dependencies, and propose an implementation strategy. This separation helps teams validate direction before any changes are made.
Use case: adding WebP to an image pipeline
For tasks like integrating WebP conversion into an upload pipeline, plan mode can identify insertion points, evaluate whether new libraries are required, and outline performance and compatibility considerations. Teams can refine the plan before execution, minimizing churn.
Early course correction reduces rework
Reviewing and iterating on the plan is the most efficient point to course-correct. Teams can request revisions or extensions to the plan, ensuring alignment with architectural constraints and product goals before code is written.
Controlled execution and approvals
Once approved, the AI can execute the plan’s tasks, with options to auto-accept edits or require per-change approval. The system attempts to troubleshoot issues during implementation, but developers can intervene with additional guidance as needed.
Context persistence improves outcomes
The planning phase creates a trace of decisions and assumptions. This context helps the AI make better follow-up choices during coding and debugging, increasing confidence in the final result.
Define success with tests and tools
Clear success criteria are essential. Teams are encouraged to maintain a reliable test suite that serves as a source of truth, and to equip the AI with tools—such as browser control for UI validation—to verify outcomes autonomously.
AI-assisted testing and validation
The AI can generate or extend tests to validate new features. Continuous test runs help prevent regressions and provide objective signals that the implementation meets requirements.
Knowledge capture reduces repeated errors
When recurring issues arise, saving resolutions to a project knowledge file (e.g., Claude.md) helps prevent repetition and accelerates future tasks by encoding learned fixes and conventions.
Pre-commit review and standardized messages
Before pushing changes, teams can run an AI code review agent to catch defects and enforce standards. The AI can also generate consistent commit messages, streamlining repository hygiene.
CONCLUSION
A disciplined workflow that separates exploration, planning, execution, and review is proving critical to making AI coding assistants effective, delivering faster results with fewer errors.
Full transcript
If you take one thing away from cloud code, let it be this workflow. Explore, plan, code, and commit. Without this, most people jump straight to asking Claude to write code, which means more course correcting later on. The fastest way to handle step one and two is with plan mode. With plan mode, Claude can't edit files. It just reads files to gather research on how to tackle its implementation. To enter plan mode, hit shift and tab until you see the plan mode under the text input. I need to add webp conversion to our image upload pipeline. Figure out where the pipeline should happen, whether we need new dependencies and how to approach it and claude will read relevant files, do some web searches, and give you a plan of action. Make sure you review it and determine if it meets your criteria. Otherwise, I can ask it to add on or revise some areas. Perfect. And this right here is the best place to course correct because it's before any code is written. You can also use explore without being in plan mode by just asking Claude to explore your codebase. Now, once the plan looks good, you can select approve to accept the plan and let Claude tackle all the list items it provided. You can determine if you want Claude to auto accept the file edits or ask every single time. Cloud will do its best to troubleshoot your codebase before considering the plan finished, but at times you'll need to course correct. This is the benefit of working with plan mode because after the plan is finished, we also have the context of how it got to the results to help it guide its next decision. In order for Claw to be confident in its results, it has to be clear on what it deems correct. When writing your plan, make this explicit. Adding tools that will help Claude complete its goals will remove a lot of back and forth. For example, if you're building web UIs, make sure you have the Claude and Chrome extension so that Claude code can control a tab and test out the UI before deeming it finished. In your project, include a test suite that Claude can continuously validate on. Claude can even write tests for you. Before passing this off to Claude, make sure that the tests are a source of truth for you and your team to avoid any false positives. Quick tip. If you find Claude keeps running into these same issues, ask Claude to save the solution to his Claude MD file. Now, once you have tested for yourself and are happy with the results, it's time to push your code. A tip before you commit, run a sub agent code reviewer to look at your code. Then you get Claude to generate a commit message for you in your style. Rinse and repeat. If you want to be effective with Cloud Code, follow the explore, plan, code, and commit workflow. Exploration will give the relevant context Claude needs for your project. Plan will create a plan of action that Claude will use to determine if they are successful. Code is the back and forth that you and Claude do before settling on the final outcomes of the plan. Commit helps you review and push your code so you can start on your next feature.