Software Development Trends and Predictions 2024 From Industry Insiders

Earlier this month, ITPro Today shared five trends — including fewer developer jobs but more software security problems — that should impact software development in 2024.

Do IT leaders and industry insiders feel the same way about where software development is headed this year? They have already made their predictions about security, AI, cloud computing, open source, IT careers, data analytics and management, and more in 2024:

Now it's their turn to share what they are expecting in the software development realm in 2024. Check them out below:

What the Tech Industry Expects Will Happen in Software Development in 2024

Bun Will Replace Node.js

In 2024, Bun will shake up the JavaScript runtime scene and take the lead away from Node.js. Bun's rapid adoption can be attributed to its ability to significantly enhance the software development process, making it faster, more agile, and less frustrating. The beauty of Bun lies in its seamless integration — libraries and frameworks remain fully functional without the need to abandon familiar software development conventions. But speed is where Bun truly shines with a startup time up to four times faster than Node.js. — Ratnesh Singh Parihar, Principal Architect, Talentica Software

Related:One Year In: How Has ChatGPT Impacted Software Development?

2024 Will Produce Significant Challenges to AI-Assisted Code Development

We will reach a threshold where we've tampered and experimented enough with AI across the SDLC that there will be an incident that will force enterprises to pay attention to end-to-end governance and the consequences of not having AI policies in place. DevOps teams need guidance on what they are/aren't allowed to do with the tools they're using, and team leaders need full visibility into how those tools are being used. — Wing To, General Manager, Intelligent DevOps, Digital.ai

AI-Generated Code Will Create the Need for Digital Immune Systems

In 2024, more organizations will experience major digital service outages due to poor quality and insufficiently supervised software code. Developers will increasingly use generative AI-powered autonomous agents to write code for them, exposing their organizations to increased risks of unexpected problems that affect customer and user experiences. This is because the challenge of maintaining autonomous agent-generated code is similar to preserving code created by developers who have left an organization. None of the remaining team members fully understand the code. Therefore, no one can quickly resolve problems in the code when they arise. Also, those who attempt to use generative AI to review and resolve issues in the code created by autonomous agents will find themselves with a recursive problem, as they will still lack the fundamental knowledge and understanding needed to manage it effectively. — Bernd Greifeneder, Chief Technology Officer and founder, Dynatrace

Related:AI-Assisted Coding: What Software Developers Need to Know

With the Combination of GenAI and Low-Code, App Development Will Finally Become Democratized

We will see developers leverage generative AI to write code, allowing them to quickly customize their app portfolio and grow their product portfolio. When combined with generative AI, low-code technology will help organizations expand the pool of developer resources, putting innovation into the hands of every employee, so professional developers can focus on more complex projects while allowing other employees to create apps quickly, securely, and with fewer resources. — Jithin Bhasker, GM and VP for the App Engine business, ServiceNow

The Move Beyond Traditional Docker Containers

As the serverless landscape evolves, there will be a substantial move in 2024 to go beyond traditional Docker containers. By compiling to WebAssembly, a new era of more efficient, lightweight, and universally deployable containers will emerge. Not only does this approach streamline the deployment process, but it also improves security, given WebAssembly's roots in browser execution. Companies will also be able to transcend cloud boundaries and CPU specifications through a seamless "develop once and deploy anywhere" paradigm." — Pankaj Mendki, Head of Emerging Technology, Talentica Software

Attributes of Cloud Data Cost 'Winners'

Cloud data cost "winners" will be data leaders who are proactively thinking about (and addressing) their data cost ROI. This means implementing the proper guardrails to identify and correct bad code in the development stage before it makes it into production. It makes more sense to buy a fire extinguisher for your house when you're building your house rather than when the house is on fire. — Kunal Agarwal, CEO and co-founder, Unravel Data

CIOs Will Treat App Dev as a Critical Business Function

In 2024, businesses will recognize the significant impact of application development on revenue generation through changes brought about by the AI revolution. It will require a more strategic approach to the software development and delivery lifecycle for executives to predict risks, costs, and efficiency gains of every change in process, ultimately allowing businesses to release and deploy at scale while meeting competitive pressures and revenue expectations. — Jeff Moloughney, CMO, Digital.ai

New Governance Models Like IT-Provided Governance Templates and Sandboxes for Citizen Developers Will Emerge

The rapid advancement of citizen developers in businesses promises to unleash a wave of innovation through new applications but also poses risks around governance. Over the next three years, we will see the rise of new governance models tailored to properly guide these citizen developer initiatives. Sandbox environments will allow citizen developers to safely test new ideas before deploying to production. — Jithin Bhasker, GM and VP for the App Engine business, ServiceNow

Low-Code Governance Will Become More Proactive

The governance of low-code platforms will evolve from reactive to proactive risk management. Rather than just responding to issues, leading governance solutions will take pre-emptive measures to identify and mitigate threats. This shift will be fueled by the need to protect businesses from escalating cyber-attacks, data breaches, and compliance audits. Low-code can introduce new attack surfaces and vulnerabilities that traditional security tools miss. AI-powered governance platforms will scan for risks and anomalies in real time before they become incidents. — Jithin Bhasker, GM and VP for the App Engine business, ServiceNow   

Modular Monoliths Are the Next Stage in the Evolution of Software Architecture

More people are talking about a return from microservices to monoliths. I don't see this as a change per se; leaders on microservices have always believed that monoliths have their place, and that you shouldn't start developing microservices until you've outgrown your monolith and need the flexibility that microservices provide. But it's interesting and important to see companies like Thoughtworks talking about modular monoliths. This looks like the next stage in the evolution of enterprise software architecture. — Mike Loukides, Vice President of Emerging Tech Content, O'Reilly Media

Growth of Platform Engineering

The need for training about platform engineering has come out of nowhere and quickly become one of the top 500 search terms on O'Reilly's platform. (To put that in perspective: We have over a million unique search terms per month.) We've also had several well-attended online events that discussed platform engineering. What's driving the growth of platform engineering? Software developers have always built tools to improve their work environment. As software has become more complex, with distributed systems running in the cloud becoming the norm, deploying software has also increased in complexity. Platform engineering is about automating the whole process of delivering software, from check-in and testing through to deployment into production. It has become a necessity. — Mike Loukides, Vice President of Emerging Tech Content, O'Reilly Media

Using AI to Find Inefficient Code

To accelerate the speed to value and minimize the cost of AI, data teams need to understand the impact inefficient code has on AI pipeline performance and costs in the cloud. Data engineering teams are going to need AI to find the inefficient code that is not performant or too costly. It's not humanly possible to go through all the lines of code in a given day. As a result, data engineering teams are going to need to rely on AI to go through the code to find the inefficient code, recommend how to fix it, and automate that process. — Kunal Agarwal, CEO and co-founder, Unravel Data

For more 2024 trends stories, check out the list below: