Most conversations about developer skills focus on what’s hot. The fastest-growing languages, frameworks, and platforms. But the flip side, the skills that are losing momentum, is just as revealing. 

When growth slows or declines, it doesn’t mean a skill has no value. But it can hint at bigger shifts in technology preferences, toolchain evolution, automation, or how AI is reshaping the software development lifecycle. 

Understanding which skills are slipping helps you prepare for the future, whether you’re a developer keeping your skillset sharp, or an employer mapping how your hiring priorities may need to evolve. 

To see how skill demand is evolving, we looked at two key metrics from the HackerRank platform:

• Test Invites: How many candidates were invited to complete an assessment involving a given skill-a direct signal of hiring activity.
• Active Tests: The number of unique tests that included at least one invite for that skill during the year. This helps us spot broad demand, regardless of volume.

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Overall skills demand

First, some quick context: this chart shows where developer skills land in terms of 2024 invite volume and growth, percentile-ranked to keep everything digestible.

You can read this like any other quadrant chart. High-growth, high-volume skills sit in the upper right quadrant, and low-growth, low-volume skills cluster in the lower left. In the bottom right, you’ll find skills with high invite volumes, but below average growth. It’s worth noting that doesn’t mean declining-the median growth rate for test invites in 2024 was about 23%. Declining skills can be found beneath the 20th percentile. 

All this context matters. Some fading skills still have enormous footprint, while some rising ones are just gaining traction. What’s changing is often just as important as what’s popular.

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Flatliners: still relevant, but stalling out

Some skills remain in heavy use, but are no longer surging in popularity. These flatliners show stable usage, but slower-than-average growth. They might be maturing, getting abstracted away, or facing new competition.

 

JavaScript

• Still everywhere, but slowing down. 
• JavaScript remains a pillar of web development, but its versatility is both its strength and its curse. Much of its core usage is increasingly abstracted by frameworks or handled by AI.
• As AI takes over repetitive scripting tasks, assessments are shifting toward higher-leverage or more specialized skills. 

Node.js

• From fast riser to slow burner.
• Node still powers many production back ends, but demand is softening.
• Its slowdown may reflect emerging alternatives, edge-first platforms, or architectural shifts.

HTML/CSS/JavaScript

• Still foundational but fading from the front line.
• These skills remain essential, but active testing is down as modern tooling and component libraries reduce the need for deep hands-on expertise.
• No-code and low-code platforms are further abstracting traditional markup work.

REST API

• The glue of modern systems, but less of a focus.
• As REST becomes more standardized and automation tools evolve, developers are expected to know it-but not necessarily be tested on it.
• The growth of GraphQL and backend-as-a-service solutions may also be playing a role.

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Descenders: clearly on the way down

These skills are shrinking in both usage and demand. Some are being replaced. Others are being automated. A few are just aging out. They tend to fall into one of three buckets:

• Legacy hang-ons: PL/SQL, Hadoop, Java
• AI-displaced: Django, Ruby, TensorFlow, PyTorch
• Platform-specific fadeouts: Android, R

 

Java

• Still everywhere, but slowly slipping.
• One of the most-used skills by volume, but its growth has trended downward for years.
• Modern JVM alternatives like Kotlin and Scala, along with cloud-native development trends, may be pulling attention away from it.

TensorFlow and PyTorch

• Once essential, now increasingly sidelined
• Both frameworks show steep declines in active tests, meaning fewer companies are assessing for them.
• One explanation: as companies move from DIY ML models to foundation models and hosted AI services, deep expertise in these frameworks may be less crucial.

Django

• A Python classic that’s losing its edge.
• Django had a strong run, especially during the early rise of Python-but demand is tapering off.
• Its opinionated structure and batteries-included approach may feel heavyweight in a microservice-dominated world, and modern teams are increasingly opting for lighter, more modular stacks.
• While ASTRA shows AI handles Django tasks well, its decline likely reflects broader architectural and ecosystem shifts, not just automation.

Ruby / Ruby on Rails

• From darling to declining.
• Ruby’s elegance made it a startup favorite for building web apps, but usage has cratered.
• Performance ceilings, dated conventions, and minimal ecosystem growth are driving it out.

PL/SQL and Hadoop

• Anchors from another era.
• These tools served enterprise systems well, but modern demands are pulling away.
• Cloud-native, distributed alternatives are winning the scalability game.

Android

• The bottom fell out of native mobile demand.
• Android development saw the sharpest drop in invites of any skill-down over 60%.
• Native mobile (apps built specifically for iOS or Android) is losing ground to cross-platform frameworks like Flutter and React Native, which allow teams to build once and deploy everywhere.
• This shift may be reducing the need for dedicated Android specialists on hiring teams.

R

• Data science’s former go-to, losing ground fast.
• Once favored for statistical analysis and academic research, R is being steadily eclipsed by Python’s more versatile and developer-friendly ecosystem.
• Python’s dominance in machine learning, broader community support, and integration with production environments make it the clear choice for most new projects.
• As a result, R is increasingly confined to legacy systems and niche use cases.

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Where to focus instead

If you’re working in-or hiring for-any of the descending skills above, here are stronger, future-facing bets worth considering:

• From Java → Kotlin, Scala, or Go: More modern, cloud-native-friendly languages that work well with containers and microservices.

• From TensorFlow/PyTorch → Foundation models and AI ops: Focus on prompt engineering, model evaluation, and ML integration, not low-level framework work.

• From Django → FastAPI or Flask: Lighter Python frameworks that align better with microservices and modern DevOps practices.

• From Ruby → Node.js or TypeScript: More scalable, actively supported, and widely adopted for web and backend development.

• From PL/SQL and Hadoop → Snowflake, BigQuery, or dbt: Cloud-first data platforms that scale more easily and integrate with modern analytics pipelines.

• From Android → Flutter or React Native: Cross-platform frameworks that offer faster delivery and broader reach.

• From R → Python: Broader ecosystem, more ML/AI integrations, and stronger traction in both enterprise and research environments.

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The ASTRA effect: an indicator worth watching

Our ASTRA benchmark measures how well AI handles real-world, multi-file coding challenges. The dataset is still growing, but early patterns are worth watching.

Some skills, like Django, Ruby, and REST API, show both strong AI performance and declining human demand. That could be a sign of things to come.

Skill	ASTRA benchmark average	Active test growth	Invite growth
.NET	0.000	21.6%	14.7%
Java	0.320	-7.7%	-4.8%
Selenium	0.470	7.8%	41.6%
Spring Boot	0.470	14.6%	74.8%
Ruby	0.700	-33.3%	-59.3%
AngularJS	0.715	22.8%	55.2%
Node.js	0.842	7.5%	-8.6%
React	0.870	9.3%	22.5%
Django	0.870	-2.9%	-25.8%
REST API	0.937	-9.7%	8.7%

 

Meanwhile, other skills with high ASTRA scores, like React and AngularJS, haven’t seen the same drop-off. As AI tools grow more capable in these areas, it’s worth watching whether demand for these skills starts to shift in 2025. And if the trends we’re seeing with Django, Ruby, and REST API begin to extend further.

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Why does any of this matter?

For developers: Skills fade for many reasons: automation, ecosystem shifts, or changing business needs. Stay curious. Focus on learning concepts, not just tools. And invest in areas where human intuition, design, and collaboration still shine.

For employers: Watch for signs of stagnation in your tech stack. Are you hiring for skills that are trending down? Consider investing in training or refreshing your assessment criteria to stay aligned with the future.

Knowing what’s fading doesn’t mean abandoning those skills entirely. But it does mean you can plan ahead, before the ground shifts beneath your feet.