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Migration Guide

How to Continue a Replit Project in Feature1

You exported to GitHub. Now move from prototype iteration to production delivery.

Prerequisite

First export your Replit project to GitHub: Export Replit project to GitHub .

Step 1: Connect Repo in Feature1

  • Sign in to Feature1 and select your project.
  • Connect GitHub and choose the exported repository.
  • Feature1 analyses your codebase — indexing module dependencies, architectural patterns, and conventions already in your code.
  • A Domain Spec is generated automatically — a living knowledge graph of your codebase that powers every downstream AI decision.

Step 2: Plan the First Production Feature

Describe the feature you want to build in plain language — no special syntax needed. Feature1 runs a multi-stage analysis pipeline that produces:

  • Decomposition: Breaks your feature into concrete sub-tasks aligned with your codebase structure.
  • Feasibility and impact assessment: Evaluates technical feasibility, identifies risks, and estimates downstream effects.
  • Implementation study: Maps the changes needed across your codebase — files, modules, and dependencies.
  • Open questions: Surfaces ambiguities that need your input before implementation begins.
  • PRD generation: Produces a complete product requirements document with scope, acceptance criteria, and user stories.

The output is a set of user stories, each with independently testable acceptance criteria — ready for implementation.

Step 3: Implement with Autopilot or Copilot

Choose the mode that matches your level of control:

  • Autopilot: AI implements each acceptance criterion autonomously — creating branches, committing code, and opening PRs. You review at approval gates and confirm or request changes.
  • Copilot: You drive implementation through your preferred MCP client (Claude Code, Cursor, Windsurf, or Codex CLI). Feature1 provides the workflow context, codebase grounding, and orchestration while you make the design decisions.

In both modes, the AI writes code consistent with the patterns and conventions already in your repository — the codebase you exported from Replit.

Step 4: Ship with Traceability

  • Review the PR on GitHub — each change is linked to the acceptance criterion that drove it.
  • Merge through your normal process. Feature1 integrates with your existing CI/CD pipeline.
  • Release notes are generated automatically, tracing every change back to the feature and user story that produced it.

What Changes vs Staying on Replit

  • Every change is traceable: Each code change maps to an acceptance criterion, which maps to a user story, which maps to a feature.
  • Code review is built in: PRs are opened on GitHub with full context — no more deploying untested changes directly.
  • Planning is structured: Features go through analysis before implementation, catching issues early instead of after deploy.
  • Your existing stack stays: Feature1 works with your code as-is. No framework changes, no rewrite required.

Frequently asked questions

What do I need before continuing a Replit project in Feature1?

Export the Replit project to GitHub first. Then sign in to Feature1, select your project, connect GitHub and choose the exported repository. Feature1 analyses the codebase and generates a Domain Spec, a living knowledge graph of your code that powers every later AI decision.

Do I have to change my stack or rewrite code to use Feature1?

No. Feature1 works with your code as it is. There are no framework changes and no rewrite. In both Autopilot and Copilot mode, the AI writes code that follows the patterns and conventions already in the repository you exported from Replit. You merge through your normal process, and Feature1 integrates with your existing CI/CD pipeline.

What changes compared with staying on Replit?

Every code change maps to an acceptance criterion, then a user story, then a feature. PRs open on GitHub with full context, so you stop deploying untested changes directly. Features go through analysis before implementation, which catches issues early instead of after deploy. Release notes are generated automatically from the work.

Recommended Reading

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Two and a half minutes on what changes between a working prototype and a product people pay for, and what to check before you call it launched.

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