The “Perks” of Being a Full-Stack Dev, Junior Devs’ Burnout, & JavaScript’s Temporal
🥐 How “full” is the “stack”?
Welcome to HackerPulse Dispatch! This edition covers the latest tech trends, from the industry's obsession with all things "full-stack" and how to outlast the hype, to the recurring cryptography mistakes that keep haunting devs. We also break down flaws in Okta’s authentication system, explore the long-awaited JavaScript Temporal API, and more.
Here’s what new:
🥀 Why Junior Developers Are Burning out Before They Bloom: Surviving Tech’s Obsession With “New”: AI and automation have made coding faster, but devs risk losing the deep problem-solving skills that separate true experts from copy-paste coders.
😵 The Full-Stack Lie: How Chasing “Everything” Made Developers Worse at Their Jobs: The tech industry’s obsession with full-stack devs spreads engineers too thin, but true career success comes from mastering deep, specialized skills.
😈 Hell Is Overconfident Developers Writing Encryption Code: Developers keep rolling their own cryptography—often while insisting they aren’t—which leads to the same security failures being repeated endlessly.
🧙🏼♂️ What Okta Bcrypt Incident Can Teach Us About Designing Better APIs: A flaw in Okta’s authentication system allowed users with long usernames to bypass password checks due to Bcrypt’s 72-character input limit, exposing a critical security oversight.
⏱️ JavaScript Temporal Is Coming: JavaScript's new Temporal object is starting to roll out in experimental browser releases, offering a modern, built-in solution for precise and reliable date and time management.
Why Junior Developers Are Burning out Before They Bloom: Surviving Tech’s Obsession With ‘New’(🔗 Read Paper)
Developers today have access to AI-powered tools that write code in seconds, but something has been lost along the way. The ability to deeply understand code, debug complex issues, and think independently is fading as automation takes over.
Instead of mastering the fundamentals, many developers are stuck in an endless loop of tutorials, frameworks, and updates. The result? More efficiency on the surface but less true problem-solving ability. The solution isn’t learning more—it’s understanding better.
Key Points
The tutorial treadmill: learning without progress: Junior devs are bombarded with new tools but rarely get the time to master any of them. They know four times as many frameworks as past generations but take three times longer to debug simple issues.
The dirty secret tech influencers won’t admit: The push to "stay relevant" hides an uncomfortable truth: depth beats novelty. A dev who truly understands linux process isolation is more valuable than one who has memorized kubernetes commands without knowing what they do.
The unfair advantage nobody talks about: The best devs don’t just build apps—they create tools, automation scripts, and reusable components. Instead of chasing trends, they refine foundational skills that stay relevant long after the latest framework fades.
The Full-Stack Lie: How Chasing “Everything’” Made Developers Worse at Their Jobs (🔗 Read Paper)
The tech industry’s obsession with full-stack devs has created a generation of engineers stretched too thin. Instead of fostering deep expertise, it rewards surface-level knowledge across dozens of tools and frameworks.
The result? Developers who can deploy a machine learning model, configure Kubernetes, and build a React frontend—just not very well. True mastery comes from depth, not from juggling endless technologies.
Key Points
The illusion of versatility: Full-stack development promises adaptability, but often leads to developers who are spread too thin to master anything. The more technologies you "kind of" know, the less effective you become at solving real problems.
Why companies push the full-stack myth: Businesses push for full-stack engineers to save money, not to build better products. The best developers in history—whether in databases, performance optimization, or security—earned their value through focus, not fragmentation.
The power of deep expertise: Specialization leads to leverage, higher salaries, and greater career stability. Instead of chasing every new trend, mastering fundamental skills like algorithms, system design, and performance tuning will keep you valuable no matter how the industry evolves.
Hell Is Overconfident Developers Writing Encryption Code (🔗 Read Paper)
Developers rolling their own cryptography is a longstanding security industry headache—one that predates the industry itself. While writing crypto code is a great way to learn, deploying homebrewed encryption schemes is where things go terribly wrong.
The latest example comes from a startup’s blog post on secret-sharing, where the author initially downplayed their DIY cryptography before later revising their approach. The discussion highlights a broader trend: many devs genuinely don’t realize when they’re rolling their own crypto, despite well-established warnings. And the biggest problem? This issue extends far beyond the mistakes we actually get to see.
Key Points
The startup that rolled its own crypto (and walked it back): A fully remote startup published a post detailing their secret-sharing approach, initially dismissing concerns about "rolling their own crypto." They encrypted keys directly with RSA—until they later realized their mistake and switched to AES-GCM.
The hidden epidemic of bad crypto: Examples range from devs hashing passwords with MD5 to storing encryption keys right next to encrypted data. Many of these flawed implementations are actively deployed in production without proper security oversight.
Why this keeps happening: Many devs assume that as long as they use trusted cryptographic libraries, they aren’t rolling their own crypto. But cryptography isn’t just about algorithms—it’s about securely implementing and managing them.
What Okta Bcrypt Incident Can Teach Us About Designing Better APIs (🔗 Read Paper)
Okta’s security incident earlier this month raised serious concerns about password hashing and authentication vulnerabilities. The issue stemmed from the way the Bcrypt algorithm was used to generate cache keys, allowing authentication bypass under certain conditions.
Specifically, usernames exceeding 52 characters could cause the password to be ignored, making it possible to log in with any password. While long usernames are rare, some companies use full names in email addresses—turns out, Albus Dumbledore would have been at risk. But why wasn’t this limit enforced at the library level? A closer look at different programming languages reveals surprising inconsistencies in handling Bcrypt’s 72-character input limit.
Key Points
Go gets it right: The official Go Bcrypt library enforces the 72-character limit, preventing passwords that exceed it from being processed. This safeguard eliminates the risk of unintended authentication bypass.
Java’s mixed results: While Spring Security's Bcrypt implementation fails to enforce the limit, Patrick Favre’s Bcrypt library correctly rejects long passwords, proving that validation isn’t universal across Java ecosystems.
Inconsistent enforcement elsewhere: JavaScript’s widely used bcryptjs and Python’s bcrypt library both allow passwords to exceed 72 characters without warning, leading to the same vulnerability Okta faced. Rust, however, demonstrates better safety practices with stricter handling.
JavaScript Temporal Is Coming (🔗 Read Paper)
Implementations of the new JavaScript Temporal object are beginning to ship in experimental browser releases, marking a major step forward for web developers. Temporal is set to replace the long-troubled Date object, offering built-in support for time zones, calendars, and precise time calculations.
While full cross-browser support is still a ways off, developers can start exploring how Temporal simplifies date and time management. With over 270 pages of documentation added to MDN this week, now is a great time to get up to speed on what’s changing and why it matters.
Key Points
Why Temporal replaces date: JavaScript’s Date object, inherited from Java’s flawed early implementation, has long been plagued by issues like unreliable parsing, limited time zone support, and mutation-related bugs. Temporal eliminates these problems with a modern API designed for precision and consistency.
Core features of temporal: The Temporal API introduces clear distinctions between absolute timestamps, local times, durations, and various calendar representations. Developers can now perform complex operations like handling Daylight Saving Time shifts, working with non-Gregorian calendars, and sorting durations natively.
How to start using it: While full browser support is still in progress, Firefox has an experimental implementation in Nightly, and other browsers are following suit. Devs can experiment with Temporal using the @js-temporal/polyfill library or the TC39 Temporal docs, making it easy to test the new API before it becomes a standard.
🎬 And that's a wrap! Catch you next week with more cutting-edge tech updates.