4 Criteria for Deciding When to Simplify Complex React Code (2025)

Honestly, even developers who have been using React for years sometimes catch themselves thinking: "Why did I make this so complicated?" Business logic piling up inside useEffect, useMemo and useCallback attached out of habit, a whole day gone just picking a state management library — I used to think this meant I "didn't know React well enough." Then at some point I realized: this isn't a skill problem. It's a standards problem.

In 2025, React holds an overwhelming lead as the number-one framework at 44.7% usage, yet a quiet fracture is forming within the community. Stories of an 8-year React veteran rewriting an entire startup frontend in Rails are circulating widely, and the call to return to "boring monoliths" is growing louder. This is React Complexity Fatigue — the cognitive exhaustion produced by the React ecosystem's relentless churn and excessive abstraction.

This article explores why this phenomenon occurs, and examines 4 criteria for judging when complexity is justified and when to simplify, illustrated with real code. If you use TypeScript and have some React experience, you can apply these right away.

Three Paths Through Which Complexity Accumulates

useEffect Hell

useEffect was originally a hook for synchronizing with external systems. Somewhere along the way it became a garbage bin for business logic, data fetching, and derived state management. If you've ever debugged a codebase plagued by infinite loops, stale closures, and memory leaks, you know this pain intimately.

The most common pattern is "managing a value that could be computed during rendering with useState + useEffect anyway." I did this myself early on — it's actually one of the biggest single sources of unnecessary complexity.

Over-splitting Components

When the practice of "everything into a component" is taken to extremes, you end up with an "Ultimate Component" festooned with dozens of optional props. That's where you get architectures too frightening to touch at the base component level, and an explosion of cross-file dependencies. When you open a file and can't tell where to start reading, over-splitting is already well underway.

Ecosystem Decision Fatigue

The flood of state management options — Redux → Context API → Zustand → Jotai → TanStack Query — creates a paradox where you must learn the third-party ecosystem before you can learn React itself, exhausting beginners and seniors alike. Honestly, starting every new project with "what should I use this time?" has become perfectly normal.

React Complexity Fatigue — A sub-concept of "Frontend Fatigue," referring to the state of cognitive and emotional exhaustion arising from the decision fatigue and tooling overload of the React ecosystem.

4 Criteria for Deciding When to Simplify

Having shared criteria within a team for when refactoring is needed makes code reviews significantly easier. Teams that have added these criteria to their PR checklist frequently report a noticeable drop in review time.

Changes React Is Making in 2025

The most notable change is the React Compiler, a separate opt-in tool usable with React 19. It automatically optimizes components and expressions, dramatically reducing the need for manual useMemo, useCallback, and React.memo. There are reports of large teams introducing React Compiler and deleting widespread memoization code from their codebases while maintaining identical performance.

The use() hook is also worth watching. It enables conditional handling of async resources, making the traditional useEffect + loading-state pattern considerably more concise.

The Signals paradigm is also influencing the React ecosystem in 2025. Even if you won't be using Signals in React right now, what this direction implies is clear.

Signals — A fine-grained reactivity primitive pioneered by SolidJS and Preact. Instead of re-rendering an entire component, only the changed DOM elements are updated, achieving reactivity without Virtual DOM overhead. This trend reaffirms that "reducing unnecessary re-renders" is a core challenge of frontend complexity — and React Compiler's approach of solving the same problem through automatic memoization is cut from the same cloth.

Three Patterns You Can Change Right Now

Example 1: Replacing useEffect with Derived Calculation

I used to manage derived state exclusively with useState + useEffect, and it's actually the most common yet most unnecessary source of complexity. The same principle applies from simple cases like fullName all the way to filtering only completed items from a list of selected items.

// Before: managing derived state with an unnecessary useEffect
const [firstName, setFirstName] = useState('');
const [lastName, setLastName] = useState('');
const [fullName, setFullName] = useState('');
 
useEffect(() => {
  setFullName(`${firstName} ${lastName}`);
}, [firstName, lastName]);
 
// After: compute directly during rendering
const [firstName, setFirstName] = useState('');
const [lastName, setLastName] = useState('');
const fullName = `${firstName} ${lastName}`; // no state needed

The React official docs page "You Might Not Need an Effect" covers this pattern well. Values that can be computed during rendering don't need to be stored as state. Of course, if a computation is genuinely expensive, using useMemo is the right call — in that case, confirm the actual bottleneck first with the React DevTools Profiler.

Example 2: Consolidating Related State with useReducer

When three or more data-fetching-related states are coupled together, managing each with useState makes synchronization bugs easy to introduce. This is a situation you encounter frequently in practice — treating it as a state machine with useReducer is far safer.

// Before: managing 3 related states separately → risk of sync bugs
const [isLoading, setIsLoading] = useState(false);
const [error, setError] = useState<Error | null>(null);
const [data, setData] = useState<User[] | null>(null);
 
// An impossible state where isLoading and error are both true can arise
 
// After: single state machine with useReducer
type State =
  | { status: 'idle' }
  | { status: 'loading' }
  | { status: 'success'; data: User[] }
  | { status: 'error'; error: Error };
 
type Action =
  | { type: 'FETCH_START' }
  | { type: 'FETCH_SUCCESS'; data: User[] }
  | { type: 'FETCH_ERROR'; error: Error };
 
function fetchReducer(state: State, action: Action): State {
  switch (action.type) {
    case 'FETCH_START': return { status: 'loading' };
    case 'FETCH_SUCCESS': return { status: 'success', data: action.data };
    case 'FETCH_ERROR': return { status: 'error', error: action.error };
    default: return state;
  }
}
 
const [state, dispatch] = useReducer(fetchReducer, { status: 'idle' });

Impossible state combinations (e.g., isLoading: true while error is set) are blocked at the type level. Because all state transition logic is in one place, debugging becomes much easier too. I still remember the first PR review I got after switching to this pattern: "Wow, this is so much easier to read."

That said, if the state is genuinely simple and there's no transition logic, useReducer can be overkill. Two independent booleans like isOpen and isDirty are more naturally handled with two separate useState calls.

Example 3: Replacing useEffect-based Data Fetching with TanStack Query

Managing server data-fetching logic directly with useEffect means you have to hand-write all the caching, retry, and loading state handling yourself. There's also a trap that's easy to miss: fetch does not automatically reject on 4xx/5xx responses. Code written like the Before example below has a hidden bug where a server 500 won't be caught.

// Before: useEffect + state management combo (watch out for fetch error handling)
function UserList() {
  const [users, setUsers] = useState<User[]>([]);
  const [isLoading, setIsLoading] = useState(false);
  const [error, setError] = useState<Error | null>(null);
 
  useEffect(() => {
    setIsLoading(true);
    fetch('/api/users')
      .then(res => {
        // fetch doesn't reject on 4xx/5xx, so an explicit check is required
        if (!res.ok) throw new Error(res.statusText);
        return res.json();
      })
      .then(data => {
        setUsers(data);
        setIsLoading(false);
      })
      .catch(err => {
        setError(err);
        setIsLoading(false);
      });
  }, []);
}
 
// After: server state separated with TanStack Query
function UserList() {
  const { data: users, isLoading, error } = useQuery({
    queryKey: ['users'],
    queryFn: async () => {
      const res = await fetch('/api/users');
      if (!res.ok) throw new Error(res.statusText);
      return res.json();
    },
  });
 
  // caching, background refresh, and retry logic are included automatically
}

Server State vs. Client State — Data fetched from the server (server state) and data managed through UI interactions (client state) are fundamentally different in nature. TanStack Query is a dedicated server state management tool that helps you keep the two from getting mixed together.

There are situations where TanStack Query isn't the right fit. For real-time WebSocket streams, or when you only have simple one-off requests, it can actually be overkill. If your team's server state patterns are straightforward, looking at React 19's use() hook first is also a perfectly good choice.

Pros and Cons Analysis

This section is also an honest accounting of "why React, still?" Viewed through the lens of complexity fatigue, React's strengths and weaknesses come into sharper relief.

Pros

Cons and Caveats

Hydration mismatch — An error that occurs when the HTML rendered on the server differs from the DOM React generates on the client. Especially difficult to debug in React Server Components environments.

The Most Common Mistakes in Practice

1. Storing derivable values as state — Managing a value that can be computed from existing state as a separate state variable brings synchronization errors and unnecessary re-renders along with it. Enabling the dependency array warnings from eslint-plugin-react-hooks helps catch these patterns early.

2. Attaching useMemo/useCallback out of habit without measuring performance — Memoization that hasn't been validated against actual bottlenecks with the React DevTools Profiler only makes the code more complex. Since React Compiler is moving toward handling this automatically, if you're attaching these out of habit right now, it's worth taking another look.

3. Choosing a state management library first and then fitting your architecture to it — The correct order is to define the problem first, then choose the right tool for it — not the other way around. It helps to think in terms of separation: TanStack Query for server state, Zustand for global client state, and useState/useReducer for component-local state.

Closing Thoughts

The solution to React Complexity Fatigue is not "choosing a better library" — it's establishing clear simplification criteria and sharing them across the entire team. Here are three things you can start doing right now.

1. You can search your current codebase for useEffect and check each one: "Is this actually an external synchronization?" If it's a derived value that can be computed during rendering, you can switch it immediately to a const declaration. It's also a good time to clean up any dependency array warnings from eslint-plugin-react-hooks along the way.

2. You can add the four simplification criteria from this article to your PR checklist. "Can this useEffect be replaced with a derived calculation?", "Are there 3 or more coupled useState calls?", "Are props being passed through 3 or more layers?" — when these questions come up repeatedly in code review, they naturally become the whole team's standard.

3. You can experiment with React Compiler first in a side project or development environment. Check out the official React Compiler introduction to enable it, and see for yourself how much your existing useMemo/useCallback code shrinks.

References

• Why I Decided to Stop Working with React.js in 2026 | Medium
• The Frontend Fatigue Is Real: Why 2025 Is the Year Developers Simplify | Medium
• The React Component Pyramid Scheme: An Over-Engineering Crisis | The New Stack
• You Might Not Need an Effect | React Official Docs
• React State Management in 2025: What You Actually Need | Developer Way
• React Compiler & React 19 - Forget About Memoization Soon? | Developer Way
• React Compiler Official Docs | React
• Framework Fatigue 2025: Why Developers Are Ditching React for Boring Monoliths | XYZBytes
• Optimizing JavaScript Delivery: Signals v React Compiler | RedMonk
• Frontend Developers Are Burned Out, Not Lazy | LogRocket Blog
• Managing State | React Official Docs