2025-11-18 19:24:07
In an era defined by rising energy costs and increasing pressure on sustainability, food manufacturing plants cannot afford to lag behind. For small and mid-sized enterprises in the food & beverage manufacturing industry, improving energy efficiency is more than a green initiative — it’s a strategic lever to boost profitability, future-proof operations, and gain a competitive edge. Below are practical, high-impact strategies to reduce energy consumption and optimize operations — rooted in industry best practices.
The first step toward greater efficiency is to understand where energy is being wasted. Conducting a detailed energy audit helps identify “energy hogs” in your plant — whether it's inefficient boilers, motors, chillers, or lighting systems. By mapping out your energy flow, you can prioritize upgrades that promise the maximum return.
Sub-metering at the process-line or equipment level provides actionable data. Rather than relying on a single building-wide meter, you’ll gain visibility into consumption for specific machines or zones — and identify opportunities for savings that may otherwise go unnoticed.
Once you know where energy is being used, it’s time to tackle the right equipment. Opting for energy-efficient machinery can deliver major savings:
Food processing often involves thermal steps — heating, cooking, drying — that generate significant waste heat. Rather than venting this heat out, you can recover and reuse it:
To further decouple your production from fossil fuel dependency, consider renewable energy sources:
Energy costs often vary throughout the day, especially in regions with time-of-use tariffs. Effective load planning can be a game-changer:
Energy efficiency isn’t just about machinery — it begins at the drawing board. Whether you're building new or upgrading existing facilities, design matters:
- Optimize plant layout: Group heat-intensive areas (like ovens) so that recovered heat can be reused efficiently.
- Challenge HVAC assumptions: Reassess air-change rates and airflow. Reducing unnecessary ventilation can save significant energy over time.
- Insulate strategically: Proper insulation on boilers, ovens, pipes, and storage areas limits heat loss and prevents wasted energy.
Efficiency is not a one-time effort — it requires ongoing care:
Your people are your most valuable asset — and their engagement is key to energy savings:
For small and mid-sized enterprises in the food manufacturing space, energy may represent 15% or more of your operational costs. Improving energy efficiency not only cuts utility bills, but also strengthens resilience, supports sustainability goals, and enhances long-term competitiveness.
Moreover, demonstrating your commitment to energy stewardship can improve your brand’s appeal — especially to eco-conscious customers, investors, or partners. As energy costs remain volatile, adopting these strategies helps you lock in savings, reduce risk, and build a leaner, more agile operation.
If you’re serious about driving down energy costs while building a more sustainable, efficient food manufacturing operation, BrightPath Associates LLC can help. Our deep experience in the food-manufacturing industry positions us to connect you with talent who can design, lead, and execute energy-efficiency projects. Visit our Food Manufacturing Industry page to learn more about our work.
And if you’re ready to deep-dive into digital strategies, process improvements, and sustainable hiring — start with our in-depth post on Energy Efficiency Tips for Food Manufacturing Plants.
2025-11-18 19:17:28
As an iOS developer working in a corporate environment, you might find yourself confined to a specific part of the codebase, implementing features within established patterns and rarely touching certain fundamental aspects of app development. This is where pet projects become invaluable—they offer something that production work often cannot: the complete journey from zero to one.
When you start a pet project, you face the blank canvas that many developers rarely encounter in their professional work. Should you use MVVM, VIPER, Clean Architecture, or the newer MV pattern with SwiftUI? How will you handle navigation—coordinators, or SwiftUI's native NavigationStack? What about dependency injection—will you use a framework like Swinject, or implement your own lightweight solution?
These aren't theoretical questions in a pet project. You'll feel the consequences of your decisions as your app grows. That navigation approach that seemed elegant at first might become cumbersome when you add deep linking. The architecture that felt lightweight might struggle when you introduce complex state management. These lessons stick because you experience them firsthand.
You'll discover that MVVM works beautifully with SwiftUI's observation framework, but might feel verbose for simple screens. You'll learn when VIPER's strict separation helps and when it becomes over-engineering. Most importantly, you'll develop the judgment to choose the right architecture for the right context—a skill that comes only from experiencing the pain points of each approach.
In most production applications, authentication is already implemented. It works, it's tested, and your job is simply to maintain it or make minor adjustments. But do you really understand what's happening under the hood?
A pet project lets you implement authentication from scratch. You'll connect to services like Firebase Authentication and discover how OAuth flows actually work. You'll implement JWT tokens and finally understand the dance between access tokens and refresh tokens. You'll handle token expiration, secure storage, and session management—concepts that remain abstract until you've debugged why your users keep getting logged out unexpectedly.
You'll learn about different authentication strategies:
Firebase Authentication provides an excellent learning platform because it handles the server-side complexity while letting you focus on the client implementation. You'll learn how to store tokens securely in the Keychain, how to handle token refresh in background, and how to maintain authentication state across app launches.
Speaking of Firebase, this is where pet projects truly shine. In production environments, backend infrastructure is usually already established, but Firebase gives you a complete backend-as-a-service platform to explore:
Firebase Realtime Database and Firestore teach you about real-time data synchronization, offline persistence, and document-based storage. You'll experience the challenges of structuring NoSQL data, writing security rules, and handling concurrent updates. The difference between these two databases becomes clear only when you've worked with both—Realtime Database for simple real-time needs, Firestore for complex queries and better scalability.
Firebase Cloud Messaging (FCM) introduces you to push notifications from end to end. You'll configure APNs certificates, handle notification payloads, implement custom notification UI, and learn about silent notifications for background updates. You'll discover the differences between remote and local notifications, and how to handle notifications when your app is in foreground, background, or terminated state.
Firebase Remote Config teaches you about feature flags and A/B testing. You'll learn how to change app behavior without releasing updates, how to gradually roll out features, and how to customize experiences for different user segments.
Firebase Dynamic Links (though being phased out in favor of App Links) help you understand deep linking, deferred deep linking, and how to create seamless user flows from web to app.
This is where pet projects provide invaluable real-world experience that's difficult to gain otherwise. Firebase Crashlytics (or alternatives like Sentry) teaches you about production monitoring and crash reporting.
Setting up Crashlytics involves understanding several critical concepts:
dSYM Files - These debug symbol files are crucial for crash report symbolication. In your pet project, you'll learn:
You'll experience the frustration of receiving a crash report you can't read because you forgot to upload dSYMs, and you'll never forget that lesson.
Crash Reporting becomes tangible when it's your app crashing. You'll learn to:
Custom Logging with Crashlytics teaches you about breadcrumbs—those crucial logs leading up to a crash. You'll learn to log user actions, network responses, and state changes that help you reproduce and fix bugs.
Non-Fatal Errors tracking lets you monitor errors you've caught and handled gracefully, helping you understand which parts of your app are most problematic even when they don't cause crashes.
Beyond crashes, understanding how users interact with your app is crucial:
Firebase Analytics provides free, unlimited event tracking. You'll learn:
Alternative Analytics Solutions like Mixpanel, Amplitude, or Flurry each have their strengths. A pet project lets you integrate and compare them, understanding which provides the insights you need.
Where should data live? This question branches into multiple decisions that pet projects force you to confront:
SwiftData (iOS 17+) offers a modern approach to persistence with its declarative syntax and seamless SwiftUI integration. But you'll only discover its quirks when you forget to handle migrations properly and watch your app crash on update. You'll learn:
Core Data still powers countless apps and understanding it is valuable. You'll grapple with:
Realm offers an alternative that's sometimes simpler than Core Data. You'll experience:
UserDefaults seems simple until you learn what doesn't belong there:
Keychain is essential for security. You'll implement:
FileManager for document storage teaches you about:
Implementing Face ID and Touch ID authentication teaches you about:
The networking layer is another area where pet projects shine. Should you use a third-party framework or stick with native URLSession? And which patterns fit your needs?
URLSession - Apple's native solution can be implemented in multiple ways:
Alamofire remains popular because it simplifies common tasks:
Moya adds a layer above Alamofire, teaching you about the provider pattern and type-safe networking with enum-based endpoints.
You'll implement crucial networking concepts:
Pet projects let you explore Swift's concurrency features without the constraints of legacy code:
Async/await transforms how you write asynchronous code:
Combine teaches reactive programming:
Grand Central Dispatch (GCD) still has its place:
Pet projects give you permission to explore the vast landscape of Apple's native frameworks:
AVFoundation is massive and powers audio/video capabilities:
Vision Framework brings powerful image analysis:
Core Image for image processing:
PhotoKit for Photos library integration:
Core ML lets you integrate machine learning models:
Create ML enables training custom models:
Natural Language framework for text processing:
Core Location for positioning:
MapKit for map display and interaction:
ARKit opens the door to AR experiences:
HealthKit for health data integration:
Core Motion for device motion:
WidgetKit for home screen widgets:
App Extensions expand your app's reach:
UIAccessibility ensures your app is usable by everyone:
Learning to build accessible apps from the start is much easier in pet projects than retrofitting accessibility into established codebases.
SwiftUI is the future but comes with challenges:
You'll experience SwiftUI's limitations and learn when to drop down to UIKit with UIViewRepresentable.
UIKit still powers most production apps:
Modern SwiftUI Effects (iOS 18+):
Understanding in-app purchases is crucial for many iOS careers, yet it's a specialized area that many developers never touch.
StoreKit 2 (iOS 15+) modernized in-app purchases with:
Original StoreKit is still relevant for apps supporting older iOS versions:
You'll implement:
Server-side receipt validation teaches you about:
Alternative: RevenueCat simplifies subscription management:
Setting up StoreKit in a pet project means:
You might think localization is simple—just translate some strings, right? A pet project reveals the reality:
String Localization is just the beginning:
Layout Challenges emerge with different languages:
Internationalization (i18n) goes beyond translation:
Locale Testing in your pet project:
You'll discover frameworks like Localize-Swift or learn to implement custom localization logic for switching languages without restarting the app.
Pet projects teach you about performance monitoring and optimization:
Instruments becomes your best friend:
MetricKit provides production performance metrics:
Optimization Techniques you'll implement:
Here's where pet projects reveal an uncomfortable truth: proper testing requires resources most individuals don't have.
Unit Testing with XCTest:
UI Testing with XCUITest:
Device Matrix challenges:
This constraint forces you to maximize simulator usage and prioritize testing strategies. You learn to identify which device-specific issues are most critical and how to test efficiently with limited resources.
Snapshot Testing with libraries like SnapshotTesting:
Setting up CI/CD for your pet project teaches DevOps skills:
Fastlane automates common tasks:
GitHub Actions, Bitrise, or CircleCI for automation:
Code Quality Tools:
Managing third-party code teaches you about:
Swift Package Manager (SPM):
CocoaPods:
Carthage:
You'll learn when to use third-party libraries and when to roll your own solutions. You'll experience dependency conflicts, breaking changes in updates, and the importance of pinning versions.
Publishing to the App Store is a rite of passage that many developers never complete in their professional work.
App Store Connect becomes familiar:
Preparing for Submission:
App Review Process:
Post-Launch Activities:
App Store Optimization (ASO):
Core Bluetooth for BLE devices:
MultipeerConnectivity for peer-to-peer:
CallKit for VoIP integration:
SiriKit and App Intents:
CloudKit for iCloud integration:
Combine with UIKit:
Metal for advanced graphics:
Pet projects let you implement security from day one:
Secure Coding Practices:
Encryption:
App Security:
Perhaps the most liberating aspect of pet projects is the freedom to embrace modern features without compromise. In production, you're often constrained by the need to support iOS 15, 16, or 17 to maintain your user base. With a pet project, you can boldly set the minimum version to iOS 18 and use the latest APIs without hesitation.
Want to explore iOS 18's exclusive features? Go ahead—there's no product manager to convince. You can use the newest SwiftUI views, the latest async/await patterns, the most recent Vision framework capabilities, all without worrying about backward compatibility.
This freedom extends to architectural choices too. Want to build your entire app with The Composable Architecture (TCA)? Try it. Curious about Redux-like state management? Implement it. Interested in exploring reactive programming with ReactiveSwift? Nothing's stopping you.
In a large corporate project, experiencing this entire journey—from architectural decisions through App Store publication—could take years, if it happens at all. You might spend your entire tenure in one part of the stack, never understanding how the pieces fit together.
Pet projects compress this timeline and give you ownership of every decision. The mistakes you make are yours to fix. The victories are yours to celebrate. You'll develop an intuition for iOS development that comes only from experiencing the full stack, from conception to users holding your app in their hands.
You'll learn that authentication isn't just calling an API—it's understanding token lifecycles, secure storage, and session management. You'll discover that database choice affects not just performance, but how you structure your entire app. You'll realize that networking isn't just fetching JSON—it's handling failures gracefully, managing concurrent requests, and keeping your UI responsive.
When you see a crash report in Crashlytics with a properly symbolicated stack trace pointing to the exact line of code that failed, you'll understand the entire pipeline: your code, the compiler, the dSYM generation, the upload process, the crash, and the reporting. This end-to-end understanding is impossible to gain when you're working on a small piece of a large system.
Pet projects teach you more than just coding:
Product Thinking: You're not just implementing features—you're deciding what to build, why it matters, and how it fits together.
User Empathy: When you handle your own support emails and read your own reviews, you understand users differently.
Scope Management: You'll learn to ruthlessly prioritize. That fancy animation can wait; authentication cannot.
Ship Fast, Learn Fast: Without bureaucracy, you can ship features in days and see real user feedback immediately.
Marketing and Communication: Writing App Store descriptions and responding to users teaches you to communicate value clearly.
These skills compound over time. When you interview for iOS roles, you're not just talking about what you know—you're demonstrating apps you've built, showing code you've written, explaining decisions you've made.
When you join a new team and they're debating which analytics solution to use, you can share firsthand experience with Firebase, Mixpanel, and Amplitude. When they're implementing StoreKit, you've already navigated its complexity. When crashlytics reports a symbolication issue, you know exactly what's wrong.
Pet projects transform you from a specialist in one corner of iOS development into a developer who understands the complete picture. You become someone who can architect an app from scratch, make informed technology choices, debug production issues, and ship quality software to real users.
This is why pet projects aren't just hobbies—they're essential professional development tools that give you the breadth and depth of experience that years of production work might never provide. They're your laboratory, your playground, and your proving ground, all in one.
The journey from idea to App Store is long, challenging, and immensely rewarding. And the best part? You can start today.
2025-11-18 19:09:31
Let's get something straight: growth hacking isn't dead, but the term has been beaten to death by every startup founder who thinks adding a referral button counts as innovation.
What's changed is that the low-hanging fruit got picked around 2018. The tactics that worked when Dropbox was giving away 500MB for referrals? They're now table stakes. Everyone has a referral program. Everyone's doing content marketing. Everyone's "optimizing the funnel."
So what actually works now? I've spent the last year digging through what's driving real growth—not vanity metrics, not LinkedIn celebration posts, but actual user acquisition that doesn't require venture capital-sized budgets. Here's what I found.
Here's the thing about growth hacking in 2025: your product is probably fine. Maybe even great.
Your distribution is what's broken.
I see this constantly. Teams spend six months building features, two weeks thinking about how anyone will find out those features exist. Then they're shocked when growth flatlines. Because clearly, if you build it, they will come. (Narrator: they will not come.)
The companies actually growing right now have flipped this. They're thinking about distribution before features. Superhuman spent months perfecting their waitlist and onboarding before they worried about adding features. Linear built in public and created a community before they had a complete product.
That's not growth hacking. That's just... not being delusional about how discovery works in 2025.
PLG became a buzzword somewhere around 2022, and now every SaaS company claims they're doing it. Most aren't.
Real product-led growth means your product is the primary driver of acquisition, activation, and retention. Not your sales team. Not your content marketing. The product itself.
Notion nailed this. Their free tier is genuinely useful—not a 14-day trial that creates urgency, not a crippled version that frustrates you into upgrading. It's actually valuable. People use it, love it, share it. The product spreads itself.
Slack did the same thing. Teams would start using it organically, then other teams in the company would notice and want in. Bottom-up adoption that sales teams dream about.
But here's what makes this hard: your free tier has to be good enough that people actually want to use it, but limited enough that power users need to upgrade. That's a narrow band. Mess it up either direction and you've either got no revenue or no users.
Calendly found that sweet spot. Free users get basic scheduling (genuinely useful). Power users need custom branding, team features, and integrations (worth paying for). The result? They hit $70M ARR with basically zero sales team.
Everyone wants to be Dropbox. Give users extra storage, watch them invite friends, print money.
The reality? Most referral programs generate about 3-5% of new users. Useful, but not transformative.
The ones that work have three things in common:
The reward matters to your specific users. Dropbox users wanted storage. Airbnb users wanted travel credits. Your users probably don't want a generic $10 Amazon gift card. PayPal literally paid people $20 per referral in the early days because customer acquisition cost was worth it.
The referral is easy and natural. Uber's "give $20, get $20" works because sharing a ride code takes five seconds and happens in context (you're literally talking about getting somewhere). Asking users to share a link via email in 2025? That's friction.
Both parties benefit immediately. One-sided referral programs die fast. If only the referrer gets something, there's no incentive for the friend to actually sign up. Morning Brew grew to millions of subscribers partly because their referral rewards were legitimately cool (books, merch, experiences) and the referred person got quality content immediately.
Robinhood's free stock referral program was genius because both people got something valuable (a stock, even if small) and it reinforced the core product value (investing). That's how you get to 13 million users.
SEO is harder than ever. Everyone's publishing content. Google's AI overviews are eating clicks. The advice to "just create quality content" ranks right up there with "just be yourself" as actionable guidance.
So where's the opportunity?
Reddit, but strategically. Not spam. Genuine participation in relevant subreddits, then occasionally mentioning your product when it's actually relevant. I've seen B2B companies get their first 1,000 users entirely from Reddit by being helpful first, promotional never. The trick is you need to actually add value for months before anyone cares about your product.
YouTube Shorts and TikTok for B2B. Yes, really. Everybody thinks these are for consumer brands, but I'm seeing SaaS companies blow up by posting quick tips, tool comparisons, and workflow hacks. The algo is still relatively friendly, and B2B buyers are humans who scroll TikTok. Wes Kao grew her audience by posting no-nonsense career advice. Not exactly viral dance content, but it works.
Newsletters (but niche ones). Starting your own newsletter in 2025 is playing on hard mode. Sponsoring existing newsletters in your niche? That's smart. The audiences are targeted, engaged, and the CPMs are often better than LinkedIn ads. Find newsletters your ICP actually reads and test small.
Community-first, content-second. Indie Hackers, Product Hunt communities, niche Slack/Discord groups. The distribution comes from being a valuable community member, not from posting your blog link. Contribute for three months, then mention your product once. That ratio matters.
Growth hacking isn't just about getting users in the door. It's about getting them to the "aha moment" before they bounce.
Facebook famously discovered that users who added 7 friends in 10 days were far more likely to become active users. That single insight shaped their entire onboarding.
Twitter's magic number was following 30 accounts. Duolingo's was completing one lesson. These aren't random—they're the minimum viable engagement that correlates with retention.
Here's what most teams get wrong: they haven't identified their activation metric. They're tracking signups (vanity) and revenue (lagging) but not the leading indicator that predicts whether someone will stick around.
Find yours. Look at your retained users and work backward. What did they all do in their first session? First week? That's your north star for onboarding.
Airtable realized users who created their first base and invited a collaborator within 48 hours had 5x higher retention. So they redesigned onboarding to push both actions early. Simple, but effective.
Integration partnerships are the unsexy growth channel that compounds quietly in the background.
Zapier has built an entire business on this. They integrate with 5,000+ apps, which means they show up in 5,000+ app directories, get mentioned in 5,000+ help docs, and appear in countless "how to connect X to Y" searches. Each integration is a distribution channel.
Stripe did this brilliantly with payment processing. By making it dead simple to integrate, they became the default for developers. Every startup using Stripe is a mini case study and referral source.
The key is finding non-competitive products with overlapping audiences. If you're a CRM, partner with email marketing tools, scheduling apps, and proposal software. Build real integrations, co-market them, share leads.
Notion's integration with Slack drove significant adoption. People were already living in Slack; being able to surface Notion docs there removed friction and created natural exposure.
Growth hacking is really just structured experimentation with a catchy name. Here's what's working:
Interactive tools and calculators. HubSpot's Website Grader generated millions of leads. Not because it was revolutionary, but because it gave immediate value and required an email to see full results. Build something your ICP finds genuinely useful, even if it's simple.
Freemium templates and resources. Notion's template gallery, Canva's design templates, Webflow's cloneable sites. Give away something valuable that showcases your product. Users get value immediately, you get exposure and potential conversions.
Community challenges and cohorts. 30-day challenges, cohort-based courses, accountability groups. Reforge built a massive community around structured learning cohorts. The social pressure and FOMO drive completion rates way higher than self-paced content.
Strategic content plays. Not blog posts. I'm talking about state of the industry reports, salary surveys, benchmark data. First Round Capital's State of Startups report gets massive coverage every year. It's content marketing, but the kind that actually generates backlinks and brand authority.
The framework for testing these: pick one, commit for 90 days, measure actual outcomes (not just traffic), kill it if it doesn't work, double down if it does. Most teams quit after two weeks because they don't see immediate results. Growth compounds. Give it time.
Aggressive pop-ups. Users hate them. Google penalizes them. Your conversion rate might tick up 0.5%, but your brand perception tanks. Not worth it.
Buying email lists. This should be obvious, but apparently it needs repeating. Deliverability is brutal in 2025. One spam complaint and your domain reputation is cooked. Build your list organically or don't build one.
Vanity partnerships. Getting featured on a big publication sounds great. Does it drive signups? Usually no. I've seen companies get TechCrunch coverage and gain 50 users. Meanwhile, a well-placed Reddit comment drove 500. Focus on what converts, not what sounds impressive.
Growth hacking without product-market fit. You can't hack your way out of building something people don't want. I see teams trying every tactic in the book while ignoring the fundamental problem: their product isn't solving a real pain point. Fix that first.
Here's what nobody wants to hear: sustainable growth is boring.
It's not one viral moment. It's not a genius hack that 10x's your users overnight. It's doing several things consistently well, measuring what matters, and optimizing incrementally.
Linear grew from 0 to thousands of customers by:
No silver bullet. Just execution.
The companies actually winning in 2025 have 3-5 reliable acquisition channels, not 20 experimental ones. They know their unit economics cold. They've identified their activation metric and optimized onboarding around it. They measure retention as closely as acquisition.
That's not sexy. It doesn't make for a great LinkedIn post about "the one weird trick that 50x'd our growth."
But it works.
If you're looking at this list and feeling overwhelmed, start here:
Identify your activation metric. What do retained users do that churned users don't? Optimize your onboarding to drive that behavior.
Pick one distribution channel and commit. Not five. One. Do it well for 90 days. Content, community, partnerships, paid—pick what aligns with your strengths and your audience.
Make your product easier to share. Can users invite teammates in one click? Can they share their work publicly? Can they export and show value to others? Reduce friction.
Measure what matters. Signups are vanity. Active users, retention, revenue—those are reality. Build your dashboard around leading indicators, not lagging ones.
Talk to users who almost churned but didn't. They'll tell you exactly what value they found and what almost made them leave. That's your roadmap.
Growth hacking in 2025 isn't about tricks. It's about understanding your users deeply, removing friction relentlessly, and building distribution into your product from day one.
The tactics change. The principles don't.
Now go build something people actually want to tell their friends about.
2025-11-18 19:06:54
Last month, I watched Sarah, the owner of a bustling downtown café, spend 45 minutes manually writing down WiFi passwords for customers. By 11 AM, she'd done it 37 times. That's when we did the math: 37 customers × 1.5 minutes each = 55.5 minutes daily. At $25/hour for her time, that's $687.50 monthly just for WiFi access. And that's before we counted the 2 hours weekly she spent printing and replacing paper menus, or the 3 hours monthly updating business cards for her team.
This isn't just Sarah's problem. Restaurants, retail shops, and service businesses across the country are hemorrhaging 10-15 hours weekly on repetitive tasks that QR codes eliminate in seconds. A 2023 hospitality survey showed 73% of businesses still manually handle customer WiFi access, while 68% waste staff time on physical menu distribution.
Step 1: Create Your QR Code Arsenal (Today)
Step 2: Implement Contactless Systems (Tomorrow)
Step 3: Monitor Competitor Moves (Ongoing)
While QR codes fix your internal operations, use competitive intelligence tools to track when competitors redesign their websites or launch new contactless features. Sarah discovered her top competitor had added mobile ordering 6 weeks earlier - she caught it through AI monitoring and launched her own version in 10 days.
Right now, you can:
Here's what happens next:
Then automate the bigger picture:
Once you've reclaimed those weekly hours, set up TrackSimple to monitor competitors' digital moves. Their AI alerts will show you when rivals launch new contactless features - so you're never caught off guard again.
2025-11-18 19:06:21
If you’ve been in the JavaScript world for more than a minute, you’ve felt the pain of asynchronous code. It’s the bedrock of modern web development, powering everything from API calls to file reading, but for years, managing it was a chore. We went from the “Callback Hell” of nested functions to the slightly improved, but often still confusing, chains of .then() and .catch() with Promises.
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Then, in 2017, a new syntax landed in ES8 that changed everything: async and await.
It wasn’t a new magic behind the scenes — it was syntactic sugar on top of Promises. But what glorious sugar it is! It allowed us to write asynchronous code that looks and behaves like synchronous code, making it infinitely more readable and maintainable.
Let me show you how it works and why it will become your new best friend.The “Before Times”: A Tale of Two Asynchronous Styles
The “Before Times”: A Tale of Two Asynchronous Styles
To appreciate async/await, let's first glance at what we dealt with before.
The old way. A pyramid of doom that is hard to read and reason about.
getUser(id, function (user) {
getPosts(user.id, function (posts) {
getComments(posts[0].id, function (comments) {
// And so it goes... deeper and deeper
console.log(comments);
});
});
});
A significant step up! Promises gave us a cleaner, chainable structure. But long chains could still become difficult to follow, and error handling could be tricky.
getUser(id)
.then(user => getPosts(user.id))
.then(posts => getComments(posts[0].id))
.then(comments => console.log(comments))
.catch(error => console.error('Something went wrong!', error));
While this is better, we’re still “threading” values through callbacks. It’s functional, but it doesn’t feel natural.
The async/await Revolution
async and await are two keywords that work together to make Promise-based code feel synchronous.
The async Keyword
You place the async keyword before a function declaration. This does two things:
It forces the function to always return a Promise. If you return a non-Promise value, JavaScript automatically wraps it in a resolved Promise.
It enables the await keyword to be used inside that function.
async function myAsyncFunction() {
return 42;
// This is equivalent to: return Promise.resolve(42);
}
myAsyncFunction().then(alert); // 42
The await Keyword
This is the real magic. The await keyword can only be used inside an async function. It pauses the execution of the async function and waits for a Promise to resolve. Once resolved, it resumes the function and returns the resolved value.
Key point: It pauses the function, not the whole JavaScript runtime. The rest of your application (event listeners, other async operations, etc.) remains perfectly responsive.
Let’s rewrite our Promise chain with async/await:
async function fetchUserData() {
const user = await getUser(id);
const posts = await getPosts(user.id);
const comments = await getComments(posts[0].id);
console.log(comments);
}
fetchUserData();
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Look at that! It’s clean, linear, and reads just like synchronous code. We assign the resolved values of our Promises to variables (user, posts) and use them in the next line. The code tells a clear story of what happens and in what order.
Error Handling: try...catch to the Rescue
This is one of the biggest wins. With Promise chains, you have a single .catch() at the end. With async/await, you can use the familiar try...catch block, which is much more powerful and flexible.
async function fetchUserData() {
try {
const user = await getUser(id);
const posts = await getPosts(user.id);
const comments = await getComments(posts[0].id);
console.log(comments);
} catch (error) {
// This will catch ANY error thrown in the try block,
// whether it's a network error, a runtime error, or a rejected Promise.
console.error('Oops!', error);
} finally {
// This will run regardless of success or failure.
console.log('Fetch operation attempted.');
}
}
This structure gives you fine-grained control. You can even wrap individual await statements in their own try...catch blocks if you need to handle specific errors differently.
Leveling Up: Parallelism and Performance
A common mistake when starting with async/await is unintentionally making your code slower. Look at this example:
async function slowSeries() {
const user = await fetch('/api/users/1'); // takes 1 sec
const posts = await fetch('/api/posts/1'); // takes 1 sec
// Total time: ~2 seconds
}
We wait for the user to finish fetching before we even start fetching the posts. This is sequential, and it’s inefficient if the two operations are independent.
The solution? Run them in parallel!
Since await is just waiting on a Promise, we can start the Promises first, then await their results.
async function fastParallel() {
// Start both fetches immediately, they run concurrently.
const userPromise = fetch('/api/users/1');
const postsPromise = fetch('/api/posts/1');
// Now we await their results. Both requests are already in flight.
const user = await userPromise;
const posts = await postsPromise;
// Total time: ~1 second!
}
For an even cleaner approach, use Promise.all().
async function fastParallelWithPromiseAll() {
// Kick off all promises simultaneously
const [user, posts] = await Promise.all([
fetch('/api/users/1'),
fetch('/api/posts/1')
]);
// Destructure the results array. Total time: ~1 second!
}
Promise.all is your best friend for true, fire-and-forget parallelism. (Remember, it fails fast—if any promise rejects, the whole thing rejects).
Key Takeaways & Best Practices
async functions always return a Promise. This is non-negotiable. Remember to handle it with .then() or await when you call it.
await can only be used inside an async function. You'll get a syntax error otherwise. (Top-level await is now available in ES modules, but that's a topic for another day).
Don’t forget the await! A common beginner mistake is calling const data = fetch(...) without await. You'll just get a pending Promise assigned to data, not the actual response.
Use try...catch for error handling. It's the most robust and readable way to handle both Promise rejections and other errors.
Be mindful of sequential vs. parallel execution. Use Promise.all to run independent async operations concurrently for a major performance boost.
Conclusion
The async/await syntax didn't change how JavaScript's event loop works, but it fundamentally changed how we write asynchronous code. It took the powerful concept of Promises and made it accessible, readable, and less error-prone.
It turned this:
getUser(id)
.then(user => getPosts(user.id))
.then(posts => getComments(posts[0].id))
.then(comments => console.log(comments))
.catch(error => console.error('Error:', error));
Into this:
async function displayComments() {
try {
const user = await getUser(id);
const posts = await getPosts(user.id);
const comments = await getComments(posts[0].id);
console.log(comments);
} catch (error) {
console.error('Error:', error);
}
}
The second version is, in my opinion, a clear winner. It’s a joy to write and a gift to your future self (and your teammates) who will have to read it later.
So go ahead, refactor that old Promise chain. Embrace async/await. Your codebase will thank you for it.
If you enjoy this guide, I wrote a full ebook that goes deeper: Mastering JavaScript for AI. Click here to get yours
What are your thoughts on async/await? Have you run into any tricky situations while using it? Share your experiences in the comments below!
2025-11-18 19:06:11
I've spent the last year building Neuron, a PHP framework designed specifically for agentic AI applications. What started as a technical challenge became something else entirely when developers began reaching out with stories I wasn't prepared to hear. They weren't asking about framework features or deployment strategies. They were telling me about losing their jobs.
One senior developer had spent eight years at a fintech company, building and maintaining their entire backend infrastructure in PHP. The systems worked. The codebase was clean. Then the leadership decided to pivot toward AI-driven automation. Within six months, the entire PHP team was let go, replaced by Python engineers who could integrate LangChain and build agent workflows. He watched his expertise become irrelevant not because he wasn't skilled, but because the tools he knew couldn't participate in the conversation that mattered to his company's future.
Here is the link to the post on the Neuron GitHub repository: https://github.com/neuron-core/neuron-ai/discussions/156#discussioncomment-13436693
Another engineer contacted me after his SaaS company made a similar shift. They didn't abandon PHP because it was slow or outdated. They abandoned it because when the CTO asked "can we build autonomous agents that handle customer support and data analysis", the answer from the PHP ecosystem was silence. No frameworks, no examples, no path forward. Python had entire conferences dedicated to agentic architectures while PHP developers were still arguing about whether type hints mattered.
These aren't isolated incidents. I hear versions of this story regularly now, and what disturbs me most is how predictable it all was. The PHP community saw the AI wave coming and collectively decided it was someone else's problem. We kept optimizing for the web patterns we've always known, reassuring ourselves that "PHP powers a significant portion of the internet" as if market share from past decisions protects against future irrelevance.
Some people dismiss AI development as a trend, a temporary excitement that will settle down and return us to familiar patterns. This perspective fundamentally misunderstands what's occurring. Agentic applications aren’t a feature being added to existing software. They represent a different approach to building systems entirely. Companies aren't experimenting with this because it's fashionable. They're adopting it because it changes their operational economics in ways that matter to survival.
When a business realizes they can automate complex workflows that previously required multiple employees, they don't care about your framework preference or language loyalty. They care about implementation speed and ecosystem maturity to deploy effective solutions as soon as possible. If the only credible path to building these systems runs through Python, then Python is what they'll use. Your years of PHP expertise become a liability rather than an asset because you can’t deliver what the company needs to remain competitive.
The PHP community's response to this has been inadequate bordering on negligent. We write articles titled "Why PHP is the Best Choice" that convince nobody because they address none of the actual questions people are asking. Nobody talk about how to build agentic applications that can interact with multiple APIs, maintain conversation context, and make autonomous decisions. They don't provide patterns for integrating language models into Laravel applications or handling the operation complexity that agent workflows require. They just repeat the same defensive talking points about PHP's web capabilities while the industry moves toward problems PHP developers claim they can't solve.
This creates a self-fulfilling prophecy. PHP appears unsuitable for AI development because no one builds the tools to make it suitable. Talented developers leave for ecosystems that support their career growth. Companies hire outside the PHP community because we don't demonstrate competence in the areas they're investing in. Then we point to the exodus as evidence that maybe PHP really isn't meant for this kind of work, completing a cycle of irrelevance we constructed ourselves.
The developers who lost their positions didn't lack skill or intelligence. They were caught in an ecosystem that hadn't yet evolved with the problems businesses needed solved. But some of them found their way to Neuron and discovered something that changed their trajectory: PHP handles agentic applications naturally once you have the right enabling paltform in place. The language's mature capabilities, and large package ecosystem, provide exactly what these systems need.
** What was missing wasn't potential but actual implementation.**
These developers started building again. Not toy projects or proofs of concept, but production agentic systems handling real business logic. Customer service agents that resolve support tickets autonomously. Data analysis agents that generate insights from business metrics. Workflow automation that adapts to changing conditions without manual intervention.
They're now demonstrating capabilities their previous employers assumed required abandoning PHP entirely. What changed was their access to tools designed for the problems they were solving. They didn't have to become Python developers or learn entirely new paradigms. They applied their existing PHP knowledge to agentic architectures using a framework that understood both domains. Their career trajectories shifted because PHP finally has a credible answer when someone asks about building intelligent, autonomous systems.
The community forming around this work represents PHP's actual future, not its past. These developers understand that web frameworks were just the first chapter, and that the language's evolution doesn't end with serving HTTP requests. They're building the proof that PHP developers can lead in agentic development rather than watch from the sidelines. Every production agent they deploy, every autonomous workflow they implement, every business problem they solve with AI-driven systems reinforces that PHP belongs in this space.
That gap is closing now, and the developers who bridge it first are positioning themselves at the front of PHP's next chapter. Your expertise in PHP doesn't have to be a limitation in an AI-driven industry. The tools exist now to take what you already know and apply it to the systems companies are actually building. The question isn’t whether PHP can participate in agentic development anymore. The question is whether you’ll be part of this revolution.
Discover the new space Neuron is creating in the PHP ecosystem. Start developing your next application with Neuron-powered AI agents at https://neuron-ai.dev