Replit Agent plan mode: agree the work before building
Use Replit’s Plan control to discuss a change before Agent builds it. Review the scope, open questions, and checks, then keep the accepted requirements beyond the chat.
Updated 5 min read
Replit Agent plan mode lets you discuss a change before building: select Plan at the bottom of the input in the Project Editor. Replit’s editor documentation (opens in a new tab) describes reviewing and refining the proposed tasks before approving work. Keep the requirements you accept in fenbs, so a later session can start with the agreement instead of interpreting an old conversation.
How do you start a planning conversation?
- Open the app in the Project Editor and select Plan at the bottom of the input.
- Describe the user outcome you want. Include what already works and what should stay unchanged.
- Ask Agent to explain its proposed approach, list the work in order, and identify questions that need your answer.
- Review the proposal and refine it until the scope and completion checks are clear.
- Approve the agreed plan when you are ready for building. Keep a short copy of the accepted requirements and remaining questions.
Keep the first discussion small. For an appointment app, plan the change that lets a customer reschedule an existing appointment. Save unrelated ideas about reminders, reporting, or a new design for later work. A review is much easier when you can name the user action it is meant to improve.
Replit documents planning as a way to ask questions and explore ideas before changes. Its AI billing page (opens in a new tab) is the source for current access and usage terms; paid planning can involve billable reasoning without code edits. Check those terms before assuming planning is available or has no usage cost.
What information makes a plan useful?
Give the proposed work a clear destination and useful boundaries. Replit’s prompting guidance (opens in a new tab) recommends specific requirements and building in small increments. You can apply that advice without choosing the implementation yourself.
- Outcome: the person using the app can reschedule one existing appointment.
- Current behavior: the app already creates and displays appointments.
- Scope: add rescheduling to the appointment details screen.
- Preserve: keep the existing appointment information and current display wording.
- Check: after rescheduling and refreshing, exactly one appointment shows the new time.
- Open question: who may reschedule, and how close to the appointment?
The final question is a product decision. Ask the owner to answer it instead of letting a proposed implementation quietly establish the policy. Include the answer and its reason in the accepted requirements, so the next review has something definite to compare against.
How do you review the proposed approach?
Read the plan as a description of behavior you should be able to inspect. Every major step should connect to the requested outcome. If a step introduces a new service, replaces a working part of the app, or changes stored information, ask why that is necessary.
| Part of the plan | Ask this | A useful answer gives you |
|---|---|---|
| Scope | Which user action will work differently? | One observable outcome. |
| Affected parts | Which screens, files, or stored data are involved? | A bounded area to review. |
| Assumptions | What have you assumed that I have not agreed? | Questions for a person to settle. |
| Checks | How will we know the change works? | Repeatable steps and expected results. |
| Failure | What should we do if the check fails? | A stopping point and a next investigation. |
You do not need to approve technical language you cannot evaluate. Ask for the practical effect: what becomes simpler, what could break, and how you will notice. Save the chosen answer in fenbs so later assistants can distinguish your decision from an earlier suggestion.
How small should the first build be?
Choose a first piece that can be checked on its own. In the appointment example, that could be changing the time of one existing test appointment, then reading it again. Once that works, consider additional cases such as invalid times or permission differences.
Avoid bundling the new behavior with a visual redesign unless both are needed for the same outcome. When several unrelated things change, a failing check tells you less about the cause. Smaller steps give you clearer evidence for the next decision.
Write the expected result before building, then keep it stable while checking the first attempt. If the requirement itself changes, record that choice rather than quietly rewriting the check to match what appeared. The Replit testing guide develops the verification side of this workflow.
What should stay after you accept the plan?
Keep the accepted outcome, boundaries, decisions, and completion checks. A transcript may contain several possible approaches, so add a short final agreement that says which one was chosen. Mark unresolved questions as unresolved rather than burying them below the accepted steps.
Replit also documents replit.md (opens in a new tab), a root-level file Agent reads for persistent instructions. Use it for concise conventions that continue to apply, rather than making it a long diary of one planning discussion. Its instructions do not automatically apply to other AI tools.
The Replit Agent overview covers the broader development workflow. If you later consider moving the app to another tool, Claude Code vs Replit covers that separate choice; preserving the agreement helps whichever workflow you use.
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How to keep accepted plans with fenbs
Keep the agreement where you can find it again, then carry on from exactly where you left off, on any device and in any other AI. Save what you chose and the checks still to do. You do not need to keep every discarded wording of the plan.
- Create a free account.
- Add a task for the change. Write what should work for the person using the app.
- Save the plan you accepted and the choices you made. Say which questions still need an answer.
- Connect Replit to fenbs. Ask the assistant to read the agreement before building.
- After checking the work, save what passed, what failed, and where to continue next.
Replit supports custom MCP connections (opens in a new tab), a standard way for an assistant to use an outside tool. fenbs keeps the work and decisions; it does not enforce a planning mode inside Replit or verify generated code. For a throwaway experiment, a short checklist may be all you need.
When is the plan ready to approve?
Approve when you can explain the outcome, name the boundaries, and show how you will check success. If a key question still changes who can do what or what happens to stored data, settle it before the first build.
The AI at work collection has more ways to keep the useful part of an AI session. For this workflow, the useful part is simple: the agreement a person made and the evidence needed to call the change complete.