Gartner Identifies Top Strategic Technology Trends In Software Engineering

Developer experience, artificial intelligence-augmented software engineering teams, platform engineering, and digital immune system are some of the strategic technology trends in software engineering for 2023 and beyond, according to a report by research and consulting firm Gartner.

These trends represent a set of approaches and technologies that software engineering leaders must leverage over the next 2-3 years to stay ahead of the curve, innovate, and thrive in an environment of constant disruption, Gartner said.

“Software engineering leaders are under continuous pressure to adopt modern architectures and technologies. To do this well, they need to know which trends have the greatest potential impact for their digital business efforts within an actionable planning horizon,” said Joachim Herschmann, VP analyst at Gartner.

Below are the technology trends that Gartner has identified in software engineering:

InnerSource

InnerSource is a software development strategy that applies open source practices to proprietary code. Enterprises can narrow gaps and break down silos by embracing an open source approach to software development, creating a stronger and more efficient software development lifecycle.

“Ultimately, InnerSource helps teams build software faster and work better together—resulting in higher-quality development and better documentation,” said Herschmann.

Developer Experience

Developer experience refers to all aspects of interactions between developers and the tools, platforms, processes, and people they work with to develop and deliver software products and services. Improving developer experience is important for succeeding with digital initiatives and building high-performing teams.

Gartner suggests that developer experience extends beyond developer tools and technologies. “The tools used in day-to-day work certainly play a role in improving the quality of developer workflows. However, developer experience also depends on non-technology factors. These include having dedicated time for deep, creative, meaningful work, as well as personal freedom to try new things without the fear of failure,” said Herschmann.

AI-Augmented Software Engineering Teams

AI-augmented software engineering leverages AI technologies to help software engineering teams create and deliver applications faster. With the use of AI, teams can quickly produce various artifacts such as design components, application code, or test cases, which they can then modify and reuse to speed up the overall process.

"AI-augmented software engineering calls for making software engineering teams more efficient in their work by relieving them of tedious work, rather than letting the technology replace them," said Herschmann.

AI-Empowered Applications

Data-enhanced applications that improve business decisions can be produced by integrating available enterprise data, advanced model-building capabilities, and generative AI services. AI-empowered applications can automate operations, help build risk assessment models, recommend best actions, and improve information available in enterprises and applications.

For success when using AI, software engineering leaders should treat AI model development differently from application development, and coordinate activities between development and model-building teams, Gartner said.

Platform Engineering

Platform engineering is the discipline of building and operating self-service internal developer platforms for software delivery and lifecycle management. It helps developers discover, operate, secure, improve, and build upon complex, distributed IT systems, especially when they are not technical experts in the underlying systems.

Platforms improve overall developer experience with a curated set of tools and services. They also improve the consistency and quality of IT solutions, and reduce redundant tools and processes, consolidate parallel efforts by multiple teams, enforce security and compliance standards, and include pervasive automation.

Digital Immune System

Digital immunity integrates practices from the areas of observability, software testing, chaos engineering, software development, site reliability engineering, and software supply chain security to improve resiliency and quality of applications.

“Many software engineering organisations are already using some of these strategies, but none of these practices by themselves will be sufficient to achieve the goal of building highly resilient systems,” said Herschmann. “Together, these practices constitute a powerful continuous quality approach to ensure that complex digital systems keep running even if the ‘house is on fire'.”