DEV Community: Mittal Technologies

Why Most Mobile Apps Fail Before Users Even Open Them

Mittal Technologies — Tue, 12 May 2026 10:15:22 +0000

There's a particular kind of product failure that nobody in a post-launch retrospective wants to talk about. Not a crash. Not a feature gap. Not bad marketing.
It's the failure that happens in the app store listing, in the first three seconds of loading, and in the screenshots on the download page, before the user has ever opened your app once.
This is a real, significant source of drop-off. And teams that are deep in the technical work of building rarely spend enough time thinking about it.

The App Store Is a UX Surface Too

Your listing is your first impression. The icon, the name, the first two lines of the description (because nobody reads the rest), the screenshots, the rating all of it is communicating something to a potential user making a split-second decision.
I've watched people browse app stores. The decision to download takes about four seconds. The decision to not download takes about one. Most apps lose users before the install.

First Load Is a Make-or-Break Moment

Okay, they downloaded it. Now they open it. If they're waiting more than three seconds for something to appear, 40% of them are already considering closing it. If your splash screen is long and your actual onboarding doesn't start immediately, you've used up emotional credit you haven't earned yet.
This is why teams working on mobile app development India are increasingly treating first-load performance as a top-priority feature, not an optimization to tackle post-launch. The first experience is the experience that determines if there will be a second one.

Permissions at the Wrong Moment

Nothing kills initial trust faster than an app that asks for your location, contacts, camera, and notifications before you've even seen what the product does.
The right approach is contextual permission requests - ask for location when the user tries to use a location feature. Ask for a camera when they're about to take a photo. Ask for notifications after they've experienced something worth being notified about.
This sounds obvious. The majority of apps still get this wrong.

The Empty State Problem

A new user opens your app for the first time. There's no data yet. No activity. Just... an empty screen with a generic message or, worse, nothing at all.
Empty states are actually one of the highest-leverage UX moments in mobile apps. Done well, they're invitations. Done poorly, they make users feel like they're doing something wrong.

Why This Matters More in a Competitive Market

Every category in the app store is crowded. Users are not patient. The apps that survive the first week of a user's install are the ones that engineered the early experience as carefully as they engineered the core product.
This isn't a design problem or a development problem. It's a product thinking problem. And getting it right, really right - requires the whole team to care about what happens in those first few minutes.

Server Components in Next.js: What Actually Changes About How You Build (And What Doesn't)

Mittal Technologies — Thu, 07 May 2026 09:52:04 +0000

I want to tell you that React Server Components completely changed how I think about building web applications, but I want to be more honest than that. What they actually did is make me rethink some assumptions I'd been carrying for years without questioning — which is more interesting, if less dramatic.
The mental model shift is real but it's specific. For most of the React era, the default was: render on the client, fetch on the client, manage state on the client. Server-side rendering existed, but it was often an optimization bolted on rather than a native way of thinking about components. Server Components flip this. The default, in a properly set up Next.js 13+ App Router project, is that components render on the server unless you explicitly opt into client-side rendering. That's a genuinely different starting point.
What does this mean practically? Server Components can do things that were previously only possible with data fetching hooks or getServerSideProps: directly query a database, read from the filesystem, access environment variables without exposing them to the browser, fetch from APIs without the data appearing in the client bundle. And they do this as a natural part of the component itself, not through a separate data-fetching mechanism that has to be coordinated with the component.
Here's a concrete example. Imagine a product page that needs pricing data, inventory data, and review data from three different sources. In the old world, you'd either have one getServerSideProps function making three requests (or trying to parallelize them), or you'd be doing client-side fetching with loading states for each piece. With Server Components, you can have three separate components each responsible for their own data, fetched concurrently on the server, with streaming to the browser as each piece resolves. The code is more modular and the user experience is better.
The bundle size implications are significant. Server Components never appear in the JavaScript bundle sent to the browser because they never run in the browser. A component that imports a heavy markdown parser, a date formatting library, and a syntax highlighter is doing all of that work on the server — the browser gets HTML. For applications that have grown heavy JavaScript bundles over time, this can produce dramatic performance improvements.
What doesn't change: anything requiring interactivity, browser APIs, or React state and effects. Those stay as Client Components, which work exactly as React components always have. The architecture becomes a composition of Server and Client Components, with data flowing from server to client but not the reverse. Getting comfortable with where that boundary lives — what belongs on the server and what requires the client — is the main learning curve.
The patterns around data mutation are still evolving, but Server Actions (functions that run on the server, callable from Client Components) are the current recommended approach for form submissions and mutations. They work well for typical CRUD operations and reduce the boilerplate of building API routes for internal operations.
For teams that develop mobile apps as well as web applications, the same architectural principles apply: components should live where their dependencies live, data fetching should happen close to the data source, and the client should only get the data it needs. A good mobile app development company India approaches React Native projects with similar principles: minimize what has to happen on the client, keep business logic where it can be tested and maintained, and design the data flow deliberately.
The honest advice I'd give to someone starting a new Next.js project: start with Server Components as the default and add 'use client' only where you genuinely need it. Don't try to preplan which components are which — you'll figure it out as you build. The compiler will tell you when you're trying to do something that requires client-side APIs in a Server Component. And invest time in understanding the caching behavior early, because Next.js's caching model is powerful and not entirely intuitive until you've seen it in action a few times.

Why Your Startup's Tech Stack Choices at Launch Will Define Your Scaling Ceiling

Mittal Technologies — Wed, 06 May 2026 11:56:40 +0000

I've watched this happen more times than I'd like to admit. A startup launches on what felt like perfectly reasonable tech choices, maybe a shared hosting plan, a monolithic PHP codebase, a MySQL database that wasn't quite architected for growth. Things work fine at 1,000 users. At 10,000, cracks appear. At 100,000, everything breaks and the team spends six months re-platforming instead of shipping features.
The tech stack you choose at launch isn't just a technical decision. It's a business decision. And it has a ceiling.

The Startup Tech Decision That Nobody Talks About Honestly

There's a particular kind of optimism in early-stage startups which is mostly a good thing, because nobody would build anything without it, that leads teams to believe that "we'll deal with scale when we get there."
The problem is that by the time you get there, you're often dealing with scale while also dealing with everything else a growing startup deal with. New hires. Increasing customer expectations. Competitors pushing. Investors asking questions. That's not the moment you want to be rearchitecting your entire data layer.
The decisions made in week three of a startup's life create constraints that are still felt in year three. That's just reality.

What "Scaling Ceiling" Actually Means in Practice

A scaling ceiling isn't necessarily a hard crash. It's usually a gradual accumulation of pain.
Response times creep up as database queries get heavier. Deployments get riskier as the codebase grows and nobody fully understands the whole thing. New features take longer because the architecture didn't anticipate them. Technical debt compounds. Developer velocity slows. Customer experience degrades at the margins in ways that are hard to diagnose.
Eventually you hit a point where forward progress requires backward steps - refactoring, rewriting, migrating. That work is expensive, disruptive, and demoralizing. The engineers who built the original system often feel like their work is being discarded. The new engineers think the old engineers made bad decisions. It's messy.
Most of this is avoidable. Not all of it - requirements change, technology evolves, nobody has a crystal ball. But a lot of it.

The Common Stack Mistakes I Keep Seeing

Let me get specific because general advice is easy to ignore.
Choosing the framework your team knows over the framework your use case needs. There's a real tension here. Developer familiarity has value; it increases velocity early. But if you're building a real-time application on a framework that wasn't designed for it, you're writing code against the grain of the tool. That debt accumulates.
Underpowered databases for the expected data model. Choosing a relational database because everyone knows SQL, when your data model is fundamentally document-like or graph-like, leads to increasingly painful workarounds. And migrating databases at scale is genuinely one of the hardest engineering challenges.
Skipping infrastructure as code from day one. It seems like overhead. It saves enormous pain later. When your team grows and everyone has slightly different local environments, or when you need to spin up a staging environment quickly, or when a production incident requires you to understand exactly what's deployed, infrastructure as code pays for itself many times over.
Serverless everywhere versus serverless where it makes sense. Serverless is brilliant for the right workloads. It's painful and expensive for the wrong ones. Understanding the difference requires architectural thinking, not just following the trend.
Ignoring observability until something breaks. Logging, monitoring, tracing these feel like overhead until production is on fire and you have no idea what's happening. By then it's too late to get useful data from the incident itself.

The Framework I'd Apply to Every Stack Decision

When evaluating a technology choice at startup stage, I'd ask five questions:
What does this look like at 100x our current scale? Not "will it work at 100x" necessarily, but "what does the transition look like, and how hard is it?"
What's the migration story? If we outgrow this, what does switching look like? Some tools are easy to swap out. Others become deeply embedded in your architecture and are nearly impossible to replace without rebuilding around them.
Is there a talent pool for this? Choosing a niche technology might give you advantages, but if your founding engineers leave, can you hire replacements? This matters more than most technical founders want to admit.
Does this choice own us or do we own this choice? Vendor lock-in is real. Proprietary platforms, closed data formats, services that don't have export capabilities create dependencies that are easy to enter and painful to exit.
What are the operational complexity costs? Some architectures are brilliant in theory and brutal in practice. Microservices, for example, solve certain scaling problems but create operational overhead that small teams often underestimate.

The Underrated Power of Good Architectural Foundations

Here's a perspective that I think gets drowned out in the tech discourse: boring, solid architectural choices often outperform exciting, novel ones over a three-to-five-year horizon.
A well-structured monolith with clean separation of concerns and good test coverage will often outperform a poorly designed microservices architecture. A carefully designed relational database schema will scale further than people expect with proper indexing and query optimization. Server-rendered web applications continue to power enormous businesses at scale.
The exciting architectural choices are usually more exciting to talk about than to maintain. Especially with a small team.
This doesn't mean never adopt new technology. It means that the adoption decision should be driven by genuine need and team capability, not by what was featured at the last conference.

When to Call in External Expertise

There's a point in a lot of startup's evolution where the in-house team's collective knowledge creates blind spots. You've been building a certain way for so long that you've stopped questioning whether that way is still optimal. The codebase has grown in ways that made sense incrementally but don't quite hold together at the macro level.
This is a good moment to bring in architectural reviews from people who've built at scale before. Not to hand over the keys, but to get an external perspective on where the constraints are forming and what options exist.
The best web development company in India understands this dynamic well. Mittal Technologies works with startups and growing businesses to evaluate their technology foundation and identify where scaling ceilings are forming before they become crises. That's a much more pleasant conversation to have at 10,000 users than at 1,000,000.

The Intersection of Business Strategy and Technical Architecture

One thing I've seen over and over: technical architecture decisions and business strategy decisions are often made in separate rooms by separate people. The engineers decide the stack. The business team decides the roadmap. Sometimes these decisions align. Often, they create tension.
The healthiest startups I've seen are the ones where these conversations happen together. Where the CTO understands the business priorities well enough to make architectural choices that support them. Where the business leadership understands technical constraints well enough not to set impossible requirements.
If your product roadmap calls for a feature in six months that your current architecture makes extremely difficult, that's a critical piece of information. Either the architecture needs to evolve now, or the roadmap needs to account for the architectural work required. Leaving that misalignment unaddressed just means discovering it at the worst possible moment.

What Good Stack Decisions Look Like

I don't want this to end as a list of things not to do without acknowledging what good looks like.
Good stack decisions are boring to talk about at conferences. They're made by teams who deeply understand their use case, have thought seriously about scale requirements, have chosen tools they can hire for, and have built in the observability to understand when things are going wrong.
Good stack decisions also include clear documentation of why decisions were made, not just what was chosen. Three years later, nobody remembers why the session storage works the way it does. That context is gold when you're diagnosing a problem.
Good stack decisions leave options open. They don't create more lock-in than the problem requires. They think about egress and migration from day one, not day one thousand.
And good stack decisions are revisited. Not constantly, churn is its own problem. But periodically, with honesty about whether the original assumptions still hold.

Final Thought

The ceiling you set at launch is not permanent. It can be raised. But raising it costs time, money, and engineering morale.
The best investment you can make is a few extra days of architectural thinking at the beginning. The kind of thinking that asks, "what's the hardest version of the problem we might face?" and makes sure the foundation can handle it.
Those few days, compounded over three years, are worth an enormous amount. Do them justice.

Why Your Next Web App Needs a Design System from Day One

Mittal Technologies — Mon, 04 May 2026 08:51:49 +0000

I want to tell you about a project I know way too well. A web application that grew over three years from a 10-screen MVP to something with over 200 views, seven developer contributors, and a UI that looked like it was designed by a committee of people who had never met each other. Because that's basically what happened.
Buttons were five different shades of blue across different screens. Form inputs had three different behaviors depending on which part of the app you were in. The same component had been built independently by three different developers, each slightly differently. And by the time anyone recognized the problem, untangling it was a six-week project nobody wanted to own.
A design system from day one would have prevented most of this.

What a Design System Actually Is (And Isn't)

Let me clear something up. A design system is not a style guide PDF. It's not a Figma file with your color palette. It's not Bootstrap.
A design system is a shared, documented, maintained library of components, design tokens, patterns, and guidelines that your entire team, designers and developers work from. It's the single source of truth for what your product looks and behaves like.
Done well, it means when a developer builds a new feature, they're assembling from a consistent kit of parts rather than inventing things from scratch.

Why "We'll Add It Later" Never Happens

Teams skip design systems at the start for understandable reasons. You're moving fast. You need to validate the product. Building a design system feels like infrastructure work that delays feature work.
But by the time the inconsistency becomes obvious, you have a problem. Components are scattered across the codebase. Some are well-written, some aren't. "We'll add it later" turns into "we'll add it in the next major version" which turns into "we never added it."

What a Design System Enables in Practice

Faster feature development. When components already exist, built, documented, and tested, adding a new feature is assembly rather than construction. At scale, this is often the difference between shipping in a sprint versus a month.
Consistent user experience. Users navigate software partly by learned behavior. If the same action works differently in different parts of your app, that's friction even when users can't articulate why the app "feels weird."
Easier onboarding for new developers. A new engineer joining a project with a well-maintained design system can be productive much faster. Without it, they reverse-engineer conventions that may not even exist.
Accessibility built in, not bolted on. If your base components are built with accessibility in mind - proper semantic HTML, ARIA attributes, keyboard navigation every feature built with those components inherits that accessibility.

How to Actually Do This Without It Becoming a Six-Month Project

Start small. Build your design tokens first colors, spacing scale, typography. Get those agreed on and documented. This takes maybe a day. Then build components as you need them, but build them once, properly, into the shared system.
Document as you build. Not exhaustively, just enough that someone else can use the component without asking you. Review the system quarterly. Remove things that aren't used. Improve things that keep being worked around.

A Note for Teams Working with External Partners

If you're working with the best web development company in India or any external development partner, design system ownership is something to establish explicitly at the start. Who maintains it? Who reviews additions? How are decisions made when there's a conflict between a new feature's design needs and the existing system?
Teams that haven't answered these questions produce design systems that nobody really owns, which means they drift and degrade.

The Real Cost of Not Having One

Imagine you have a UI bug, a missing focus state on interactive elements, an accessibility issue. If that element was built from a shared design system component, you fix it once and it's fixed everywhere. If it was built twenty different times across twenty different parts of the application, you have twenty things to find and fix.
Multiply that by every bug, every small improvement, every rebrand, every accessibility requirement. The compound cost of not having a design system is enormous over the life of a product.
Spend the time now. You will not regret it.

Why India's Web Development Scene in 2026 Is Genuinely Different (Not Just "Cheaper")

Mittal Technologies — Sat, 02 May 2026 10:54:53 +0000

I've had this conversation way too many times. Someone outside India says they're "considering Indian developers" in a tone that implies they're making a compromise - trading quality for cost. And every time, I want to hand them a list of the products built here and ask them to finish that sentence.
The web development ecosystem in India in 2026 is not the offshore coding farm it was caricatured as fifteen years ago. It's genuinely different in capability, in specialization, in the kind of work being produced. Let me tell you what I actually see from where I sit.

The Talent Pipeline Is Different Now

Something changed about five or six years ago. The engineering colleges were always producing large numbers of developers, that part's been true for decades. What changed was what those developers were building, what they were learning independently, and what they expected their careers to look like.

A fresh developer entering the Indian market now has probably built side projects, contributed to open source, consumed hours of international technical content, and has opinions about system architecture. Not all of them. But the distribution shifted. The floor got higher.

The developers who've been in the field for five to ten years? Many of them have worked on international products, often directly with European or North American engineering teams, and they've operated at those standards for long enough that those are just their standards now.

What Indian Web Development Actually Specializes In

Full-stack web development is broad, and India has strong coverage across it, but the particular strengths worth highlighting:
React and Next.js ecosystems. Indian development teams have gone deep on this stack. You'll find strong opinions, real expertise, and production battle-hardening at companies across the country. This isn't a "we also do React" situation. It's a genuine specialization.
API development and microservices. Node.js, Go, Python (FastAPI specifically has gotten a lot of traction), Java for enterprise, the API layer is where Indian engineering teams are often at their most confident.
Progressive web apps and mobile-first development. Given India's own mobile-first internet culture, there's a genuine native understanding here that you can't manufacture, developers who've built for low-bandwidth environments, diverse device capabilities, and varied network conditions are solving real problems they've actually experienced.
E-commerce and SaaS platforms. The experience base here is enormous. If you're building or scaling a product in either of these categories, there's accumulated engineering knowledge available that translates to faster, less error-prone development.

The Collaboration Question

This is where I want to push back on a common assumption: that working with an Indian development partner is inherently more difficult because of distance, time zones, and communication styles.

It depends on the partner. A lot. The communication quality, responsiveness, and project management practices of different companies vary enormously probably more than they vary by geography. I've seen projects handled impeccably by Indian teams and seen domestic teams manage communication badly. The zip code is not the variable.

What actually matters: Does the team communicate proactively? Do they flag problems early or hide them until they become crises? Are their project updates honest? Do they push back when a technical decision is questionable, or just execute what they're told?

These are cultural and organizational qualities, not national ones. When evaluating any development partner, these are the questions worth asking.

What "Full Service" Actually Means Now

The expectation used to be that you bring the vision, they build it. Increasingly, the better Indian development companies offer something broader UX research, design systems, DevOps setup, security architecture, performance optimization, ongoing product development partnerships. It's closer to a product team than a coding service.
Mittal Technologies, for instance one of the recognized names in this space describes themselves explicitly as a product partner rather than just a development vendor. The best web development company in India distinction in 2026 isn't about who can write the cleanest React components. It's about who can think with you about what you're building and help you build it well from inception through maintenance.
That's a different offering than hourly coding, and it's worth knowing the distinction exists when you're evaluating options.

The Honest Caveats

No honest piece about this would skip the real challenges:

Vetting is harder at a distance. When you can't easily meet an agency or do a site visit, evaluating genuine capability requires more diligence, more specific technical conversations, more references checked, more test work reviewed. The good partners will welcome this scrutiny. The bad ones will resist it.
Communication overhead is real. Asynchronous collaboration across time zones adds latency to decision-making. The best way to mitigate this is to have clear, documented requirements and a communication cadence that everyone commits to. If a decision-maker is only available for two hours a day to answer questions, that's a bottleneck regardless of where the team is located.
"We can do anything" is a yellow flag. Strong teams have preferences and strengths. When someone tells you they're equally comfortable in React, Vue, Angular, Ruby, PHP, Go, and .NET, you're either talking to a team of hundreds or someone who's not giving you an honest picture of where their actual expertise lives.

Building Something? Here's What I'd Actually Do

If you're at the point of evaluating web development partners:

Ask for work that's similar to what you're building, not a portfolio of unrelated projects. Talk to those clients.

Do a paid discovery engagement first, a few weeks of scoped work before committing to a large project. This tells you far more about working style than any pitch call.

Ask uncomfortable questions: "What's a project that went badly and what happened?" Any honest partner has an answer to that. The answer tells you about their culture.

And if you're specifically building something product-grade scalable, secure, maintainable, not just an MVP you're going to throw away, the investment in a quality development partner from the start is dramatically cheaper than rebuilding poor technical foundations later.

The Bottom Line

India's web development talent in 2026 is genuinely world-class at the top end and genuinely strong across the middle tier. The value proposition isn't just about price - it's about available expertise, time-zone coverage, and increasingly, the depth of product thinking that comes with the engineering work.
Finding the right partner requires real evaluation, not assumptions in either direction. The ones worth working with are out there, they're busy because they're good, and they're not marketing themselves primarily on cost.
Look for quality first. The economics follow.

How to Use the New Animation Backend in React Native 0.85 (Step-by-Step)

Mittal Technologies — Fri, 01 May 2026 09:22:49 +0000

React Native 0.85 quietly shipped something developers should pay attention to: a significantly updated animation backend that changes how animations are scheduled and executed under the hood.
If you've been living with dropped frames on complex animated sequences, sluggish gesture response, or animations that hiccup when your app's state updates - this update is actually relevant to you. Let me walk through what changed and exactly how to take advantage of it.

What Changed (And Why It Matters)

Before 0.85, the default animation system had a fundamental synchronization issue. Animation frames were tied to the JS render cycle in ways that caused visible stutter whenever the JS thread was under load. You could work around this with useNativeDriver: true and Reanimated, but the defaults were bad.
React Native 0.85 introduces a new animation scheduling architecture that:
Decouples animation frame scheduling from the JS render cycle
Provides better interoperability with the new architecture (Fabric/JSI)
Reduces the number of bridge crossings for common animation patterns
Gives developers more granular control over animation priority
The result, in practice: smoother default animations even without the Reanimated workarounds, and better behavior when you combine animations with heavy state updates.

Step 1: Update to React Native 0.85

First things first.
bash
Using npm
npm install react-native@0.85.0

Using yarn
yarn add react-native@0.85.0
After upgrading, run the upgrade helper at react-native-community/upgrade-helper to see exactly what config files need updating for your specific version jump. Don't skip this, there are usually a handful of native config changes that aren't handled by package install alone.
For iOS, update your pods:
bash
cd ios && pod install
For Android, make sure your gradle versions are compatible. Check android/build.gradle for the required gradle plugin version listed in the 0.85 release notes.

Step 2: Enable the New Animation Backend

The new backend is opt-in in 0.85 (it'll be default in a later release). Enable it in your app's root:
javascript
// index.js or App.js — wherever you initialize your app
import { unstable_enableNewAnimationBackend } from 'react-native';

// Call this before your app renders
unstable_enableNewAnimationBackend();
Yes, the unstable_ prefix is there. That's Meta being transparent about this still being in active development. In practice it's stable enough for production, teams are shipping with it - but you should test thoroughly on both iOS and Android, across a range of device performance levels, before rolling out to all users.
A good approach: use a feature flag to enable it for a percentage of users first.
javascript
import { unstable_enableNewAnimationBackend } from 'react-native';

// Enable for testing cohort or percentage rollout
if (FeatureFlags.newAnimationBackend) {
unstable_enableNewAnimationBackend();
}

Step 3: Update Your Animated Calls to Use the New Priority API

0.85 introduces animation priority levels. This is new and worth using.
javascript
import { Animated } from 'react-native';

// Before 0.85: all animations had equal priority
Animated.timing(value, {
toValue: 1,
duration: 300,
useNativeDriver: true,
}).start();

// 0.85+: you can specify priority
Animated.timing(value, {
toValue: 1,
duration: 300,
useNativeDriver: true,
priority: 'interactive', // or 'normal' or 'low'
}).start();

Priority levels explained:
'interactive' — For animations triggered directly by user interaction (taps, gesture responses). Gets scheduled ahead of everything else. Use this for button press feedback, swipe responses, gesture-following animations.
'normal' — Default. For standard transitions and content animations.
'low' — For background animations that can drop frames without it being visible. Loading indicators, decorative animations.
This is a small API surface but the effect on perceived performance is real. When you mark gesture-following animations as 'interactive', they maintain smoothness even under load.

Step 4: Use the New useAnimationBackend Hook

0.85 ships a new hook that gives you information about the animation backend status and lets you react to frame scheduling events.
javascript
import { useAnimationBackend } from 'react-native';

function MyAnimatedComponent() {
const { isNewBackend, frameRate, droppedFrames } = useAnimationBackend();

// Useful for debugging performance
useEffect(() => {
if (droppedFrames > 5) {
console.warn('Animation dropping frames:', droppedFrames);
}
}, [droppedFrames]);

return (
// your component
);
}
During development, droppedFrames is particularly useful for surfacing animations that look fine on high-end devices but drop frames on lower-end hardware. Add these checks in development builds and you'll catch issues before users report them.

Step 5: Migrate Complex Animation Sequences

If you have complex, chained animations, 0.85 introduces a cleaner API for sequencing:
javascript
// Old approach: nested callbacks or Animated.sequence
Animated.sequence([
Animated.timing(fadeIn, { toValue: 1, duration: 200, useNativeDriver: true }),
Animated.timing(slideUp, { toValue: -100, duration: 300, useNativeDriver: true }),
]).start(() => {
// completion callback
});

// 0.85 approach: async/await syntax with the new backend
const runAnimation = async () => {
await Animated.timing(fadeIn, {
toValue: 1,
duration: 200,
useNativeDriver: true,
priority: 'interactive',
}).startAsync(); // new in 0.85

await Animated.timing(slideUp, {
toValue: -100,
duration: 300,
useNativeDriver: true,
}).startAsync();

// post-animation logic
handleAnimationComplete();
};
The startAsync method is new in 0.85 and makes animation sequencing significantly cleaner - especially when you have conditional logic between animation steps.

Step 6: Test Thoroughly on Real Devices

I can't stress this enough. The Simulator and high-end test devices are liars. Your users might be on a mid-range Android from three years ago with background processes eating their CPU.
Essential testing checklist for 0.85 migration:
Run all animation-heavy flows on a physical mid-range Android (something like a Redmi Note or Samsung A-series)
Test with Background App Refresh happening in parallel
Run your animations while a heavy network request is in flight
Check behavior during navigation transitions specifically
Verify drop frame counts in development using the useAnimationBackend hook
If you're building for Indian or Southeast Asian markets especially, mid-range Android performance is basically table stakes. The best web development company in India treats this as non-negotiable testing scope, not optional QA.

What to Watch Out For

A few things to know before you go all-in:
The unstable_ API may change. Meta is explicit about this. The underlying capability will persist, but the specific API surface may shift between 0.85 and when this becomes stable. Keep an eye on the changelog.
Reanimated compatibility. If you're using React Native Reanimated (and you should be for complex animations), verify compatibility with the version you're on. Reanimated 3.x generally works but test your specific version combination.
Third-party animation libraries. Any library that directly drives Animated values may behave differently with the new backend. Test them. Most popular libraries have already been updated but check release notes.

The Practical Upshot

React Native 0.85's animation backend update is one of those changes that sounds incremental in a changelog but makes a noticeable difference in how your app feels. The priority system alone is worth the upgrade for apps with complex interaction patterns.
Adopt it incrementally. Feature flag the new backend for initial testing. Add priority: 'interactive' to your gesture animations first - that's the highest-impact change with the lowest risk. Then work through your animation inventory.
Your users' thumbs will notice the difference, even if they can't articulate why.

The Hidden Cost of Cheap Marketing Services No One Talks About

Mittal Technologies — Thu, 30 Apr 2026 10:25:37 +0000

Let me guess. You saw an agency offering a ₹5,000/month social media package and thought - okay, that's manageable. Or maybe you hired a freelancer for a one-time website SEO audit at what felt like a bargain price. I've been there. A lot of business owners have. And most of them ended up paying way more later than they would have upfront.
Nobody in the marketing industry really wants to talk about this. But cheap marketing services have a cost and it's rarely the one listed on the invoice.

What you're actually paying for

When an agency charges you ₹3,000 a month to "manage your social media," that usually means: three recycled posts per week, no real strategy, and a copy-pasted content calendar that looks suspiciously similar to what they sent their last ten clients. There's no research into your audience. No testing. No iteration. Just volume to justify the invoice.
The thing is, that kind of content doesn't just fail - it actively damages your brand. People can smell generic content from miles away now. Especially if your audience is in a competitive, knowledgeable niche. Every bland post you put out trains your audience to ignore you. And un-training that attention is really hard.

The technical damage you don't see immediately

Here's where it gets more serious. Cheap SEO services are a genuine nightmare. Black-hat backlinks, keyword stuffing, thin content written for bots rather than humans - this stuff can take months to affect your rankings, but when Google finally notices? The cleanup costs easily 3x the original savings you thought you made.
I know a business that paid ₹8,000/month for "guaranteed first page" SEO for 18 months. Rankings stayed flat, traffic was fake (bot-inflated), and when they switched agencies, the new team spent four months just removing toxic links. Do the math. That was a ₹1.5L lesson that started with a discount.

The opportunity cost nobody calculates

This is the hidden part. Every month you spend with a below-average agency isn't just costing you money - it's costing you time in a competitive market. Your competitors who invested properly are compounding their brand equity, their SEO authority, their customer loyalty. You're standing still or going backwards.
Cheap marketing often creates another invisible cost too: internal confusion. When a budget vendor delivers inconsistent results, business owners often start blaming the channel itself. "Facebook ads don't work for us." "SEO is a scam." But the problem was never the channel - it was the execution.

So, what should you actually do?

Honestly? Spend less on channels and more on quality. One genuinely good campaign executed well beats eight mediocre ones running simultaneously. If the budget is tight, narrow your focus. Do fewer things with better partners.
Look for agencies that ask uncomfortable questions before they quote you. Ones that want to understand your margins, your customer journey, your CAC. If an agency promises results before they've spent even an hour understanding your business... that should tell you everything.
The best digital marketing company in India, agencies worth working with won't be the cheapest option in the room. But they'll be the ones who show you exactly what they're doing and why, every single month.
Cheap marketing services don't just cost money. They cost trust, time, and competitive ground that's genuinely hard to get back. Next time you see that ₹4,999 package, ask yourself - what is this person cutting to offer this price? The answer is almost always: effort.

Why Security Should Be the First Feature in Your Mobile App

Mittal Technologies — Wed, 29 Apr 2026 09:49:57 +0000

Let me describe a conversation that happens way too often. A startup has a working product, growing users, and real traction. Then someone says, "we should probably look at security before we raise our Series A" and the audit comes back with a list of issues that would make a pen tester wince.
Tokens stored in AsyncStorage with zero encryption. No certificate pinning. API keys baked directly into the source code. Sensitive user data logged to the console in production builds. These aren't exotic vulnerabilities. They're fundamentals. And they exist because nobody made security a priority at the start.

The Cost of Retrofitting Security Is Brutal

Early-stage teams move fast - I get it. Security can feel like friction. But the math on fixing it later is punishing. Rebuilding a broken authentication system after you have 50,000 users means data migration, forced logouts, potential breach notifications, regulatory exposure, and weeks of engineering time that could have been avoided. Doing it right from the beginning might add three or four days to a sprint. Do the math.

Data at Rest Needs Encryption

Any sensitive user data stored on device should be encrypted. Authentication tokens, PII, session data, anything that would be harmful if extracted from a lost or stolen device. On iOS, the Keychain. On Android, EncryptedSharedPreferences or the Keystore system. These APIs aren't complicated and they're not optional for production apps. Use them.

Secure Your Transport Layer Properly

HTTPS is table stakes in 2025. Certificate pinning is where many teams stop short. Without it, a MITM attack using a custom CA certificate can intercept all your API traffic. iOS's App Transport Security helps, but Android requires more deliberate configuration. Your SSL pinning logic should live in a centralized network layer, not scattered across individual API call sites.

Authentication Token Lifecycle

Tokens should expire. Short-lived access tokens paired with longer-lived refresh tokens is the standard pattern. More critically: tokens should be invalidated on logout on the server side, not just deleted from the client. If an access token leaks, you want to be able to revoke it. That requires server-side session tracking. Skipping it means a logged-out user's credentials can potentially still be used.

Sensitive Data in Logs Is a Hidden Risk

Production builds should never log user emails, passwords, authentication tokens, or API responses containing PII to the console. This seems like common sense. It is shockingly uncommon in practice. Strip debug logging before release and review what's being logged during code review, it's one of those things that's very easy to miss when you're moving fast.
A responsible mobile app development company India treats security as a first-class feature, not a pre-launch checklist item. The OWASP Mobile Top 10 is a practical starting point - if your team hasn't worked through it recently, that's worth fixing before the next build ships.

I Built an App in 24 Hours Using AI - Here's What Happened

Mittal Technologies — Tue, 28 Apr 2026 11:34:49 +0000

Fair warning: this post is going to be honest in a way that a lot of "I used AI to build X in Y hours" posts aren't. There will be no inspiring productivity claims, no screenshot of a finished product with a clean UI that took three hours of prompt iteration to actually look like that.
I genuinely tried to build a working mobile app in 24 hours using AI as the primary builder. Here's what happened.

The Setup

I had an idea I'd been sitting on a simple habit tracker, nothing novel, but I wanted something with a specific feature set I'd never found in any existing app: habits grouped by life domain (health, work, relationships, personal growth) with a weekly rhythm instead of a daily one. Weekly habits, not daily. Sounds simple. Apparently, nobody has built this exact thing in a way I like.
Tools I used: Claude for architecture planning and code generation, Cursor for the actual editing environment, and FlutterFlow for the UI scaffolding because I wanted to move fast on screens. I know Flutter reasonably well, which matters. We'll get to that.
I started at 9 PM on a Tuesday. Bad idea in hindsight.

The First Four Hours: Surprisingly Good

The architecture planning conversation with Claude was genuinely useful. I described what I wanted, Claude suggested a state management approach (Riverpod, which I agreed with), a data model, and a folder structure. Good suggestions, well-reasoned. I'd done this myself before and the AI version was roughly comparable in quality to what I'd have come up with, maybe 20% better because it caught a data modeling edge case I'd have probably hit later.
Code generation for the base data layer was fast. Models, providers, local persistence setup - Claude wrote most of this and it was correct. Like, actually correct, not "correct with three bugs I had to find." I was impressed.
By 1 AM I had a working data layer and was feeling good about the timeline.

Hours Four Through Twelve: The Grind

This is where the honeymoon ended.
The UI code Claude generated was... fine. But "fine" in the sense that it rendered and did things, not "fine" in the sense that it felt good to use. Every screen needed touching. The spacing was wrong. The color implementation was technically correct but visually off. The navigation logic had a subtle bug where going back from nested screens didn't restore scroll position correctly - a tiny thing that took forty minutes to track down because the AI confidently suggested three solutions that didn't solve it before the fourth one did.
I started to feel the cost of not writing this code myself. When you write your own code, you have a mental model of it. When the AI writes it, you have code that works until it doesn't, and then you're reverse-engineering someone else's logic under time pressure.
The FlutterFlow portion was faster for screen scaffolding, but the exported code was messy in a way that made it hard to integrate with the hand-coded portions cleanly.
By 10 AM I was six hours behind my mental schedule.

The Part That Actually Impressed Me

AI is genuinely exceptional at some specific things. Writing boilerplate. Generating test cases once I described the behaviors I wanted to test. Explaining what a piece of code was doing when I couldn't immediately parse it. Suggesting fixes to compiler errors instantly.
There were moments where I'd be stuck on something and I'd describe it and have a working solution in three minutes. That used to take me twenty minutes of Stack Overflow archaeology. That acceleration is real and I don't want to minimize it.

Finishing at Hour 24

I shipped something at 9 PM the next day. It worked. The core habit tracking flow was complete. Weekly rhythm, domain grouping, basic stats screen. Running on my phone.
Was it production-ready? Absolutely not. It was a solid prototype. Would I have gotten further without AI? Probably not, I think the AI genuinely accelerated the parts it's good at enough to offset the friction it added elsewhere.
But here's the honest bottom line: I'm an experienced developer who knows Flutter. The AI was a collaborator with specific strengths, not a replacement for the skills I brought. If I didn't already know the platform well, I don't think I'd have shipped anything usable in 24 hours.

What I'd Do Differently

Start earlier in the day. Use AI for architecture and data layer planning where it's genuinely good. Write the UI code myself rather than generating it. Use AI for test generation and debugging assistance. Not as a "write my app for me" tool but as a "be a really fast, always-available pair programmer" tool.
If you're working on a mobile product and thinking about how AI development tools fit into your process, the best mobile app development company India - Mittal Technologies has been navigating this in real projects, happy to share what we've seen.

The Most Dangerous Sentence in Web Development

Mittal Technologies — Mon, 27 Apr 2026 10:03:07 +0000

You've heard it. You've probably said it. Maybe you've said it while making eye contact with a project manager who looked like they were about to have a very bad afternoon.
"It works on my machine."
There's even a running joke about shipping the developer's laptop to the client as a solution. Ha. Ha. Except, here's the uncomfortable part - this problem kills real projects, delays real launches, and causes real production incidents that wake real people up at 3 AM.
Let me talk about why this phrase exists and, more importantly, what it actually means about how web development goes wrong.

The Gap Between Development and Production

Every web developer has a local environment - your laptop, your config, your installed packages, your database seeded with test data. It works perfectly there because you built it there. You understand that environment. You control it.
Production is different. Different OS versions, different server configuration, different environment variables, different filesystem paths, different timezone settings, different available memory, different... everything, sometimes.
The phrase "it works on my machine" is really saying: "I have not bridged the gap between where I built this and where it needs to run."

What Actually Causes the Problem

Node version differences. You're running Node 20 locally. The production server is on Node 16. A method you used was introduced in 18. The logs say something unhelpful like TypeError: cannot read property of undefined.
Environment variables not set. The API key that lets your app talk to the payment gateway? Stored in your .env file which, hopefully, is in your .gitignore. Did anyone add it to the production environment? Was it added correctly? There's a missing RAZORPAY_SECRET_KEY that will be discovered at the exact worst moment.
Database differences. Your local MySQL is version 8. Production is version 5.7 (yes, some hosting environments are still there). A query that runs fine on 8 fails silently on 5.7.
Case sensitivity. MacOS filesystem: case-insensitive. Linux production server: case-sensitive. import Component from './component' works on your Mac. Fails on the Linux server because the file is actually Component.jsx. This one is an absolute classic.
Installed system dependencies. Your machine has ImageMagick, ffmpeg, or some other binary installed globally. Production doesn't. The error message when these are missing is often confusing because the application doesn't handle that edge case gracefully.
Package lock conflicts. Someone pushed an update to package-lock.json without running a full install, and now different team members are running different dependency trees without realizing it.

Why It Matters More Than Developers Often Admit

Here's the thing: in isolation, most of these issues are annoying but fixable. The real damage comes from:
When it happens at launch. You've built and tested everything locally. The client has signed off on the staging demo. Launch day arrives and the production deployment breaks in three different ways that were fine in every other environment. Now you're debugging under time pressure, in front of the client, with stakes.
When it's inconsistent. "It works sometimes" is harder to debug than "it always fails." Environment-dependent bugs that manifest intermittently will drive a team to madness.
When it erodes trust. Every time a bug in production comes with "but it worked fine in dev," the client's confidence in the process drops a notch. Enough notches and you have a relationship problem, not just a technical one.

What Actually Solves This

Docker for local development. If your local environment is containerised and matches production, the surface area for "works on my machine" shrinks dramatically. Your app runs in the same container locally as it does in CI and in production. Same OS, same runtime, same dependencies.
This isn't free, there's overhead to setting up and maintaining Docker configurations. But for teams working on projects that will be deployed to production, it pays for itself fast.
Environment variable management. Use tools like dotenv-vault, AWS Secrets Manager, or even a shared password manager with a documented variable list. Document every required environment variable in a README or .env.example file. Make it impossible to run the app without knowing what to configure.
CI/CD pipelines that catch environment issues. If your tests run in a clean environment on every pull request, you'll catch the "works on my machine but not anywhere else" bugs before they get to production. GitHub Actions, GitLab CI, CircleCI - pick one and make it enforce a build in a clean environment.
Staging environments that mirror production. A staging server running the same OS, same runtime versions, same configuration (minus the real production data) is not optional for serious projects. If you're only testing locally and then deploying directly to production, you're running without a safety net.
Locking dependency versions. package-lock.json and yarn.lock files exist for a reason. Commit them. Use exact versions in package.json for critical dependencies. Uncontrolled version drift is a source of environmental inconsistency.

The Deeper Cultural Issue

Here's what I actually think "it works on my machine" reveals when it becomes a pattern on a team.
It means testing is either not happening or not happening in the right environment. It means deployment isn't automated or isn't consistent. It means the team hasn't invested in the infrastructure that makes reliable software delivery possible.
None of these are character flaws. They're usually the result of time pressure, resource constraints, or just the natural accumulation of shortcuts over a long project. But the longer they go unchallenged, the worse the production incidents get.
The best teams I've seen treat the "it works on my machine" incident as a retrospective item, not just a resolved ticket. What infrastructure gap allowed this to happen? How do we close it? That conversation is where the real improvement lives.

For Business Owners Reading This

If you work with developers and you're hearing this phrase a lot, it's worth a conversation. Not to blame anyone - environment inconsistency is genuinely hard to manage without the right tooling. But to ask: are we investing in the infrastructure that makes this problem rare rather than routine?
The cost of a proper CI/CD setup and containerised development environment is real. The cost of production incidents, delayed launches, and the trust damage that comes with them is higher.
If you want to build software that ships reliably, not just software that works on someone's laptop - the infrastructure question matters. The best web development company in India, Mittal Technologies builds with deployment consistency in mind from the beginning of a project, because debugging at 3 AM on launch day is a problem entirely worth preventing.
If you've got a particularly memorable "it works on my machine" war story, drop it in the comments. We've all been there. Some of us are still recovering.

Why "It Works on My Machine" Is a Website Design Problem, Not Just a Dev Problem

Mittal Technologies — Fri, 24 Apr 2026 07:06:16 +0000

Every developer has said it. Every designer has heard it and rolled their eyes a little. But here's the thing: "it works on my machine" isn't just a testing failure. In 2026, it's often a design and architecture failure that was baked in way earlier than anyone wants to admit.
I've been thinking about this a lot lately after working through a few web projects where the gap between "looks great in Figma" and "actually works for real users on real devices" was... wider than it should have been.

The gap between design and lived experience

When you build websites professionally, you work on good hardware. You have a fast machine, a decent internet connection, probably a high-resolution monitor. Your browser is up to date. You've cleared your cache. The fonts load instantly because they're already cached from testing.
Your users are not in that environment. Some of them are on budget Android phones with 3G connections in areas with patchy coverage. Some of them are on ancient iPads their company hasn't replaced yet. Some of them have accessibility needs that mean your carefully designed hover states and animated reveals are actively making the experience worse for them.
This isn't just a "test on more devices" reminder. It's a design philosophy point. If your design decisions assume an ideal environment, they're not really design decisions - they're prototypes. Real design accounts for the actual range of people using it.

Performance is a design decision

Here's something that gets siloed incorrectly: performance is treated as a development concern, but a lot of performance problems start in design.
A 4K hero image because the designer wanted the visual impact. A custom font because the brand guidelines specified it. Twelve different animation effects on the homepage because they looked incredible in the prototype. All of these are design decisions. All of them have performance costs that the development team has to absorb downstream.
The most effective teams I've seen treat performance as a constraint from the very beginning of the design process, not something you bolt on at the end when Lighthouse is giving you red scores. "What's the performance budget for this page?" should be a design question, not a post-launch panic question.

Component-first design and why it matters for devs

This is where design and development decisions actually intersect in ways that matter for code quality. When design or website ux design is done without a component system when every page is essentially a new snowflake, the frontend code gets messy. You end up with twelve variations of a card component because the designer made each one slightly different, and now the developer has twelve separate things to maintain instead of one configurable component.
Component-first design (whether you're using Figma's component library, a Storybook instance, or just a shared design system document) maps to how good frontend code actually works. It forces consistency. It reduces the implementation surface. And it makes changes dramatically cheaper because you're changing one component, not hunting through every page.

The handoff problem nobody talks about enough

Somewhere between "the design is approved" and "the code is deployed," information gets lost. Interaction states that weren't fully specced. Edge cases the design didn't account for what happens to this card if the title is 80 characters instead of 30? What does the form validation look like? What happens on a 320px screen?
These gaps get filled by developers making judgment calls. Sometimes those calls are great. Sometimes they're not. And then the designer looks at the built thing and says "that's not what I designed," and the developer says, "you never told me what to do there," and both of them are right.
Better process: design reviews that specifically look for unspecced states, edge cases, and responsive breakpoints before anything gets built. Painful upfront. Much less painful than rebuilding later.

What this means practically

If you're on a dev team that works with designers, push earlier on performance and edge cases. If you're on a design team that hands off to devs, design for the messy reality of real content and real devices.
The websites that actually serve users well - not just the ones that look good in portfolio screenshots are built by people who understand that design and development aren't sequential phases. They're an ongoing conversation.
This is something the team at Mittal Technologies has built into their process for web projects - treating design decisions and development constraints as the same conversation rather than separate workstreams. It's not always the fastest process, but it produces good website ux design or websites that hold up when real people actually use them.
It's worth thinking about next time someone says, "it looks fine in the mockup."

Why Every Developer Should Care About Platform Architecture in 2026

Mittal Technologies — Wed, 22 Apr 2026 08:16:51 +0000

I've had this conversation too many times. A developer joins a project, looks at the architecture, and says some version of 'who made these decisions?' It's never one catastrophic choice. It's a dozen reasonable-at-the-time decisions that compounded into something that's genuinely painful to work in. Platform architecture isn't glamorous. Nobody puts it in their portfolio. But getting it wrong is one of the most expensive things a team can do.
The Invisible Tax of Poor Architecture
Bad architecture doesn't usually announce itself. It shows up as 'why is this feature taking three weeks when it should take three days?' It shows up as that one service that nobody wants to touch because every change breaks something unpredictable. It shows up as onboarding that takes new developers a month instead of a week.
Most teams don't calculate this cost. They just absorb it as slowness, frustration, and the quiet attrition of good developers who leave for places where they can actually build things.
Monolith vs Microservices: This Is Still Being Done Wrong
The narrative that microservices are inherently better than monoliths is one of the more damaging ideas that spread through the industry. It's not true. A well-structured monolith is easier to develop, deploy, and debug than a poorly designed microservices system. The distributed systems complexity you take on with microservices has to be earned by problems your monolith actually can't solve, usually around scaling specific components independently or enabling large teams to work without stepping on each other.
Start with a monolith. Extract services when you have specific, justified reasons to. Not before.
APIs: The Part That Gets Regretted Most
Internal APIs get designed lazily because 'we control both sides, we can change it later.' Later always costs more than you think. Design your internal APIs with the same discipline you'd apply to a public API. Version them. Document them. Think about what happens when the consumers of this API change independently of the provider.
REST is fine. GraphQL is fine for specific use cases. gRPC is great for high-throughput internal communication. The choice matters less than the discipline with which you apply it.
Database Decisions Have Long Tails
Your database choice relational, document, key-value, graph should be driven by your actual data access patterns, not familiarity or fashion. PostgreSQL handles a staggering amount of use cases well and is underused in favor of trendier options that don't offer meaningful advantages for most workloads. It starts boring. Choose interesting when boring has a specific inadequacy you can name.
The Platform Architecture Checklist Worth Keeping
Can a new developer understand the system from documentation alone? If not, your architecture has implicit complexity that's become institutional knowledge. Can you deploy and roll back safely without all-hands involvement? If not, you've got a risk problem. Can individual components be tested in isolation? If not, your coupling has gotten out of hand. These aren't aspirational questions. They're operational requirements.
If you want to go deep on building platforms that hold up, not just in demos but in production, under real load, with real teams. The best web development company in India - Mittal Technologies, thinks about this stuff seriously.