Industry executives and experts share their predictions for 2025. Read them in this 17th annual VMblog.com series exclusive.
By Ori Saporta, VP of engineering and co-founder, vFunction
AI coding tools are rapidly transforming software development, creating both opportunities and significant risks for organizations. Throughout 2024, code generation has accelerated at unprecedented rates, with AI tools churning out code without understanding the broader software architecture. As a result, engineers will increasingly face new challenges of managing overwhelming system-wide complexity that could take weeks or months to address. While issuing new AI products and services has been a priority in 2024, we will begin to see the aftermath of rapid implementation without considering sustainability, longevity, and simplicity in 2025.
Fast AI code today will end in system gridlock tomorrow
While AI makes writing code faster, engineering teams will be challenged in 2025 and beyond to take control of their software architecture as thousands of AI-generated components interact. Teams rushing AI development will spend more time untangling messy code than writing new features. Software fixes that once took days will stretch into weeks as developers wade through AI-generated functions with hidden dependencies.
Traditional monitoring approaches will prove inadequate as design patterns silently break down, system boundaries blur, and unexpected performance issues surface. Forward-thinking engineering teams will shift focus from code generation to deep architectural understanding, implementing new tools that monitor how AI-generated code impacts how systems evolve and detecting application design problems before they cascade. New capabilities and methodologies will be required to deal with the mass of generated code which will come with its share of AI hallucinations. Success with GenAI isn’t about writing more code faster, but about maintaining architectural integrity across application ecosystems.
Organizations must invest in next-generation observability capabilities that track architectural drift, identify service dependencies, and protect system boundaries, or risk their AI-accelerated development leading to complex, tangled systems. The winners in 2025 won’t be the fastest coders – they’ll be teams who found ways to keep AI’s speed while preventing it from gridlocking their systems.
Ignore software complexity at your own peril. Fix it or face the fallout.
Far too many organizations run bloated, complex Frankenstein systems they barely understand and can no longer sustain. The mounting pressure to increase reliability and prevent costly outages will drive companies to gain a deeper understanding of their applications and put a critical focus on optimizing their software architecture. Bad architecture carries many costs: skyrocketing cloud bills, increased carbon emissions, engineering team burnout, and more.
Research found that companies experienced challenges, such as slower engineering velocity and issues with application scalability and resiliency, due to overwhelming technical debt within increasingly complex software architectures. It also revealed that software architecture is a critical yet often overlooked driver of business success in the technology landscape, presenting untapped opportunities for organizations to optimize their operations and gain a competitive advantage. As new dependencies and applications get added to software architectures at hyperspeed due to AI, organizations will begin to see and feel the negative effects of rapid implementation.
In the next year, to optimize applications, teams will need to have complete visibility of their software architecture to evaluate necessary services, eliminate redundancies, reduce cost and cognitive load on teams, and build applications for longevity. For microservices, organizations should implement architecture governance, or rules that act as guardrails, to combat microservices sprawl. The issue of complex software architectures is only going to increase as more organizations push to implement additional AI projects. 2025 will be about architecting for sustainability as AI changes the course of software.
As we expect to see an influx of code generation and resulting complexity in 2025, AI software development will demand a new approach to system architecture. Organizations will need to revisit development strategies and seek out new tools, such as architectural observability, that find and address system-wide complexity to remain agile, flexible, and competitive in the next year.
##
ABOUT THE AUTHOR
Ori Saporta co-founded vFunction and serves as its VP of Engineering. Prior to founding vFunction, Ori was the lead Systems Architect of WatchDox until its acquisition by Blackberry, where he continued to serve in the role of Distinguished Systems Architect. Prior to that, Ori was a Systems Architect at Israeli’s Intelligence Core Technology Unit (8200). Ori has a BSc in Computer Engineering from Tel-Aviv University and an MSc in Computer Science from the same institute for which his thesis subject was “Testing and Optimizing Data-Structure Implementations Under the RC11 Memory Model.”
