Refactoring prototypes into modules with minimal risk

Why prototypes become risky to change

A prototype feels fast because everything sits close together. A route hits the database, shapes the response, and the UI renders it. That speed is real, but it hides a cost: once more features land, the first “quick path” becomes the path everything depends on.

What breaks first usually isn’t the new code. It’s the old assumptions.

A small change to a route can quietly change the response shape and break two screens. A “temporary” query copied into three places starts returning slightly different data, and nobody knows which one is correct.

That’s also why big rewrites fail even with good intent. They change structure and behavior at the same time. When bugs show up, you can’t tell if the cause is a new design choice or a basic mistake. Trust drops, scope grows, and the rewrite drags.

Low-risk refactoring means keeping changes small and reversible. You should be able to stop after any step and still have a working app. The practical rules are simple:

• One clear goal per change (move code, don’t change what it does)
• Short cycles where you can re-test the same user flow each time
• A boring rollback plan you can execute quickly
• New code living next to old code until it proves itself

Routes, services, database access, and UI tangle when each layer starts doing the others’ jobs. Untangling isn’t about chasing “perfect architecture.” It’s about moving one thread at a time.

Set rules before you touch the code

Treat refactoring like a move, not a remodel. Keep behavior the same, and make the structure easier to change later. If you also “improve” features while reorganizing, you’ll lose track of what broke and why.

Write down what will not change yet. Common “not yet” items: new features, UI redesign, database schema changes, and performance work. This boundary is what keeps the work low-risk.

Pick one “golden path” user flow and protect it. Choose something people do daily, like:

sign in -> create item -> view list -> edit item -> save

You’ll re-run this flow after every small step. If it behaves the same, you can keep moving.

Agree on rollback before the first commit. Rollback should be boring: a git revert, a short-lived feature flag, or a platform snapshot you can restore. If you’re building in Koder.ai, snapshots and rollback can be a useful safety net while you reorganize.

Keep a small definition of done per stage. You don’t need a big checklist, just enough to prevent “move + change” from sneaking in:

• Same inputs produce the same outputs (including errors and empty states)
• Golden path passes a quick manual test (or a small automated check)
• Changes stay inside the stage’s scope (routes only, or services only)
• Rollback is verified at least once (you actually try it)
• A short note explains what moved and where it lives now

If the prototype has one file that handles routes, database queries, and UI formatting, don’t split everything at once. First, move only route handlers into a folder and keep the logic as-is, even if it’s copy-pasted. Once that’s stable, extract services and database access in later stages.

Quick inventory: routes, screens, and data paths

Before you start, map what exists today. This isn’t a redesign. It’s a safety step so you can make small, reversible moves.

List every route or endpoint and write one plain sentence about what it does. Include UI routes (pages) and API routes (handlers). If you used a chat-driven generator and exported code, treat it the same way: the inventory should match what users see to what the code actually touches.

A lightweight inventory that stays useful:

• Route/endpoint + purpose (example: "/checkout" shows the payment form)
• UI screen/component that triggers it
• Business rules involved (pricing, validation, permissions)
• Database tables touched and the type of access (read/write/transaction)
• Copies and repeats (the same validation copied into three files)

For each route, write a quick “data path” note:

UI event -> handler -> logic -> DB query -> response -> UI update

As you go, tag the risky areas so you don’t accidentally change them while cleaning up nearby code:

• Payments and billing
• Auth, sessions, roles
• Database migrations and seed scripts
• Background jobs and scheduled tasks
• Anything that runs in a transaction

Finally, sketch a simple target module map. Keep it shallow. You’re choosing destinations, not building a new system:

routes/handlers, services, db (queries/repositories), ui (screens/components)

If you can’t explain where a piece of code should live, that area is a good candidate to refactor later, after you’ve built more confidence.

Stage 1: Stabilize routes without changing logic

Start by treating routes (or controllers) as a boundary, not a place to improve code. The goal is to keep every request behaving the same while putting endpoints in predictable places.

Create a thin module per feature area, like users, orders, or billing. Avoid “cleaning up while moving.” If you rename things, reorganize files, and rewrite logic in the same commit, it’s hard to spot what broke.

A safe sequence:

• Group existing route handlers by feature, even if the internals are messy.
• Move only wiring code first: read params, basic validation, call the same existing functions you already trust.
• Keep responses identical: status codes, error messages, and payload shapes.
• Add one tiny check for the golden path per route (a happy-path call that must keep working).

Concrete example: if you have a single file with POST /orders that parses JSON, checks fields, calculates totals, writes to the database, and returns the new order, don’t rewrite it. Extract the handler into orders/routes and call the old logic, like createOrderLegacy(req). The new route module becomes the front door; the legacy logic stays untouched for now.

If you’re working with generated code (for example, a Go backend produced in Koder.ai), the mindset doesn’t change. Put each endpoint in a predictable place, wrap legacy logic, and prove the common request still succeeds.

Stage 2: Pull business logic into services

Routes aren’t a good home for business rules. They grow fast, mix concerns, and every change feels risky because you touch everything at once.

Define one service function per user-facing action. A route should collect inputs, call a service, and return a response. Keep database calls, pricing rules, and permission checks out of routes.

Service functions stay easier to reason about when they have one job, clear inputs, and a clear output. If you keep adding “and also…”, split it.

A naming pattern that usually works:

• CreateOrder(input) -> order
• CancelOrder(orderId, actor) -> result
• GetOrderSummary(orderId) -> summary

Keep rules inside services, not in the UI. For example: instead of the UI disabling a button based on “premium users can create 10 orders,” enforce that rule in the service. The UI can still show a friendly message, but the rule lives in one place.

Before moving on, add just enough tests to make changes reversible:

• One happy-path test that creates/updates correctly
• One error-path test (missing required field, permission denied)

If you use a vibe-coding tool like Koder.ai to generate or iterate quickly, services become your anchor. Routes and UI can evolve, but the rules stay stable and testable.

Stage 3: Isolate database access safely

Once routes are stable and services exist, stop letting the database be “everywhere.” Hide raw queries behind a small, boring data access layer.

Create a tiny module (repository/store/queries) that exposes a handful of functions with clear names, like GetUserByEmail, ListInvoicesForAccount, or SaveOrder. Don’t chase elegance here. Aim for one obvious home for each SQL string or ORM call.

Keep this stage strictly about structure. Avoid schema changes, index tweaks, or “while we’re here” migrations. Those deserve their own planned change and rollback.

Put transactions in one place

A common prototype smell is scattered transactions: one function starts a transaction, another silently opens its own, and error handling varies by file.

Instead, create one entry point that runs a callback inside a transaction, and let repositories accept a transaction context.

Keep moves small:

• Move one query at a time into the repository, keeping the same inputs/outputs.
• Have services call the new repository function directly (no extra logic).
• Centralize transaction begin/commit/rollback in one helper.
• Standardize error mapping (for example, “not found” vs “unexpected error”).

For example, if “Create Project” inserts a project and then inserts default settings, wrap both calls in one transaction helper. If something fails halfway, you don’t end up with a project that exists without its settings.

Once services depend on an interface instead of a concrete DB client, you can test most behavior without a real database. That reduces fear, which is the point of this stage.

Stage 4: Clean up UI components without redesigning

UI cleanup isn’t about making things pretty. It’s about making screens predictable and reducing surprise side effects.

Group UI code by feature, not by technical type. A feature folder can hold its screen, smaller components, and local helpers. When you see repeated markup (the same button row, card, or form field), extract it, but keep the markup and styling the same.

Keep props boring. Pass only what the component needs (strings, ids, booleans, callbacks). If you’re passing a giant object “just in case,” define a smaller shape.

Move API calls out of UI components. Even with a service layer, UI code often contains fetch logic, retries, and mapping. Create a small client module per feature (or per API area) that returns ready-to-use data for the screen.

Then make loading and error handling consistent across screens. Pick one pattern and reuse it: a predictable loading state, a consistent error message with one retry action, and empty states that explain the next step.

After each extraction, do a quick visual check of the screen you touched. Click the main actions, refresh the page, and trigger one error case. Small steps beat big UI rewrites.

A realistic example: refactor one feature end to end

Imagine a small prototype with three screens: sign in, list items, edit item. It works, but each route mixes auth checks, business rules, SQL, and UI state. The goal is to turn just this feature into a clean module with changes you can roll back.

Before and after: what moves where

Before, “items” logic might be scattered:

server/
  main.go
  routes.go
  handlers.go          # sign in + items + random helpers
  db.go                # raw SQL helpers used everywhere
web/
  pages/
    SignIn.tsx
    Items.tsx          # fetch + state + form markup mixed

After, behavior stays the same, but boundaries are clearer:

server/
  routes/
    items_routes.go
  handlers/
    items_handler.go
  services/
    items_service.go
  repositories/
    items_repo.go
web/
  pages/
    Items.tsx
  components/
    ItemForm.tsx

One end to end pass (small, reversible)

Start by moving code without changing logic. Keep function names and return shapes the same, so a rollback is mostly file moves.

Refactor one route first. The handler should only deal with HTTP, not rules or SQL:

// handlers/items_handler.go
func (h *ItemsHandler) UpdateItem(w http.ResponseWriter, r *http.Request) {
  userID := h.auth.UserIDFromRequest(r) // same auth logic as before
  itemID := mux.Vars(r)["id"]

  var in UpdateItemInput
  json.NewDecoder(r.Body).Decode(&in)

  item, err := h.itemsService.UpdateItem(r.Context(), userID, itemID, in)
  if err != nil { writeError(w, err); return }
  writeJSON(w, item)
}

Next, move business rules into a service. This is where you put checks like “user can only edit their own items” or “name cannot be empty.” The service calls a repository for DB work:

// services/items_service.go
func (s *ItemsService) UpdateItem(ctx context.Context, userID, itemID string, in UpdateItemInput) (Item, error) {
  if strings.TrimSpace(in.Name) == "" { return Item{}, ErrInvalidName }
  return s.repo.UpdateItem(ctx, userID, itemID, in)
}

Then isolate DB access in a repository function:

// repositories/items_repo.go
func (r *ItemsRepo) UpdateItem(ctx context.Context, userID, itemID string, in UpdateItemInput) (Item, error) {
  row := r.db.QueryRowContext(ctx,
    `UPDATE items SET name=$1 WHERE id=$2 AND user_id=$3 RETURNING id, name`,
    in.Name, itemID, userID,
  )
  var it Item
  err := row.Scan(&it.ID, &it.Name)
  return it, err
}

On the UI side, keep the page layout, but extract repeated form markup into a shared component used by both “new” and “edit” flows:

• pages/Items.tsx keeps fetching and navigation
• components/ItemForm.tsx owns input fields, validation messages, and the submit button

If you’re using Koder.ai (koder.ai), its source code export can be handy before deeper refactors, and snapshots/rollback can help you recover quickly when a move goes wrong.

Common traps that increase risk

The biggest risk is mixing “move” work with “change” work. When you relocate files and rewrite logic in the same commit, bugs hide in noisy diffs. Keep moves boring: same functions, same inputs, same outputs, new home.

Another trap is cleanup that changes behavior. Renaming variables is fine; renaming concepts is not. If status switches from strings to numbers, you’ve changed the product, not just the code. Do that later with clear tests and a deliberate release.

Patterns that quietly create trouble

Early on, it’s tempting to build a big folder tree and multiple layers “for the future.” That often slows you down and makes it harder to see where the work really is. Start with the smallest useful boundaries, then grow them when the next feature forces it.

Also watch for shortcuts where the UI reaches into the database directly (or calls raw queries through a helper). It feels fast, but it makes every screen responsible for permissions, data rules, and error handling.

Risk multipliers to avoid:

• Big refactor commits that touch many files and also change logic
• Shared return shapes changing without updating every caller
• New layers added without a clear reason
• Error handling getting flattened (everything becomes null or a generic message)

A small example: if a screen expects { ok: true, data } but the new service returns { data } and throws on errors, half the app can stop showing friendly messages. Keep the old shape at the boundary first, then migrate callers one by one.

Quick checks before you move to the next stage

Before the next step, prove you didn’t break the main experience. Run the same golden path every time (sign in, create an item, view it, edit it, delete it). Consistency helps you spot small regressions.

Use a simple go/no-go gate after each stage:

• The golden path still works end to end, including common error cases.
• Routes/controllers are thin: read input, call one service, return a response.
• Services are portable: callable from routes, background jobs, or UI actions without knowing about HTTP.
• Database access is centralized with one transaction pattern and consistent error handling.
• Rollback is fast and proven.

If one fails, stop and fix it before building on top of it. Small cracks become big ones later.

A quick “can we undo this?” drill

Right after you merge, spend five minutes verifying you can back out:

• Revert the last commit on a local branch and confirm the app boots and the golden path runs.
• Toggle off the new code path (feature flag, config switch, or conditional) and confirm the old behavior still exists.
• Check logs and DB writes for the golden path once to confirm storage behavior didn’t change.

Next steps: keep it modular as the product grows

The win isn’t the first cleanup. The win is keeping the shape as you add features. You’re not chasing perfect architecture. You’re making future changes predictable, small, and easy to undo.

Pick the next module based on impact and risk, not what feels annoying. Good targets are parts users touch often, where behavior is already understood. Leave unclear or fragile areas until you have better tests or better product answers.

Keep a simple cadence: small PRs that move one thing, short review cycles, frequent releases, and a stop-line rule (if scope grows, split it and ship the smaller piece).

Before each stage, set a rollback point: a git tag, a release branch, or a deployable build you know works. If you’re building in Koder.ai, Planning Mode can help you stage changes so you don’t accidentally refactor three layers at once.

A practical rule for modular app architecture: every new feature follows the same boundaries. Routes stay thin, services own business rules, database code lives in one place, and UI components focus on display. When a new feature breaks those rules, refactor early while the change is still small.