2024 DevOps Predictions - Part 7
December 13, 2023

Industry experts offer thoughtful, insightful, and often controversial predictions on how DevOps and related technologies will evolve and impact business in 2024. Part 7 covers AI's impact on DevOps and development.

Start with: 2024 DevOps Predictions - Part 1

Start with: 2024 DevOps Predictions - Part 2

Start with: 2024 DevOps Predictions - Part 3

Start with: 2024 DevOps Predictions - Part 4

Start with: 2024 DevOps Predictions - Part 5

Start with: 2024 DevOps Predictions - Part 6


AI will give individual engineers far more leverage and shrink the optimal size of development teams. Products like coding co-pilots and code generation tools have gained popularity, but I predict they will become even more entrenched into the software development process in the coming year. Small development teams of engineers with AI co-pilots and AI-integrated devtools contributing what in the past would've taken dozens of engineers will become the norm.
Avthar Sewrathan
GM for AI and Vector, Timescale

AI Will Not Replace Developers

AI is moving to the forefront of software development, with IT leaders using AI to speed time to market and alleviate the developer shortage. While generative AI-based tools can speed up many common developer tasks, complex tasks remain in the domain of developers for now. AI technology will be used to augment developers rather than replace them as some tasks continue to demand skilled developer expertise.
Jason Beres
SVP Developer Tools, Infragistics

Much has been written about the AI takeover, and for the better part of a year, we have been subject to a plethora of clickbait headlines that spell doom and destruction for just about every white-collar profession out there, and developers were not spared.
After months of speculation and experimentation with LLMs in a coding context, we remain entirely unconvinced that development jobs are at collective risk.
Matias Madou
Co-Founder and CTO, Secure Code Warrior


Frontend developers are under a unique pressure to redefine their role in the app dev space and reconsider how the tools they use adapt to the AI-powered landscape. As AI gets better at delivering code for app development, frontend developers will need to find new ways to stand out, bringing in creativity, problem-solving, or a unique expertise — or else we're going to see fewer frontend dev roles, and likely a lot of AI generated websites that start to look alike.
Rita Kozlov
Senior Product Director, Cloudflare


AI-assisted programming is going to reward software developers who focus on higher level skills. Software architecture, understanding users' requirements, and thinking about how to solve problems, and of course, testing. But I don't think there will be any new job titles. There will be a shift in the skills needed — away from low-level coding and towards higher level thinking.
Mike Loukides
VP of Emerging Tech Content, O'Reilly Media

As AI matures in 2024, developers will find their roles shifting. They will need to put up with fewer repetitive tasks, but in return, will be expected to accomplish more in less time. Strategies like relying on AI to generate code or using design-to-code conversion programs will no longer be considered convenient time savers, but rather the baseline level of efficiency required to be a productive employee. It's hard to predict what functions AI will expand to cover next, so developers will need to keep up with the latest trends. Otherwise, by the time their companies expect them to be fully proficient with AI tools, it will be difficult to catch up.
Alessandro Cauduro
Chief Developer Experience Officer, Azion

AI will force organizations to rethink how they train and develop their junior engineers / prepare their career paths. AI will force engineering leaders to redefine the role of junior engineers as AI automates the basic tasks they perform. A few months ago, proficient developers wrote perfect code, and now AI does. Therefore, developers must become experts in areas like prompt engineering, testing and training large language models, and knowing how to deal with non-deterministic outcomes — a skill even more experienced engineers wouldn't have had to touch just last year. The industry must prepare for this upcoming crunch by investing in educational initiatives, upskilling programs, and fostering an environment that nurtures talent and promotes continuous learning.
Jim Rose
CEO, CircleCI


Organizations are starting to ramp up their expectations of new hires, especially in the technology and developer space. According to Gartner, by 2025, more than half of all software engineering leader role descriptions will explicitly require oversight of generative AI. However, this spotlight does not need to be a cause for concern. For engineers, developers, IT practitioners, and other technologists, it also creates opportunities to close existing skills gaps. In 2024, we can expect to see technologists make even more moves toward prioritizing AI skills, especially through enhancing code generation and modernization.
Kyle Charlet
IBM Fellow and CTO, IBM Z Software

Generative AI is rapidly changing the way we work, and the DevOps space will benefit greatly by applying GenAI tools in existing processes. The skills related to the understanding of GenAI and LLM technologies, along with prompt design, prompt engineering, and model tuning, will be in high demand.
Ed Lopez
Senior Strategic and Solution Architect, Terazo


In 2024, the technological landscape will witness a significant increase in the accessibility to generative AI tools which will fundamentally democratize the software development landscape. It will lower the barriers and prerequisites for software development, enabling a far more diverse talent pool. Those with self-directed learning experiences will be able to construct their proofs of concept or preliminary versions of inventive products or services.
Tiago Cardoso
Principal Product Manager, Hyland

AI-Assisted CODING SUPPORTED BY low-code/no-code

Everybody's talking about generative AI and large language models (LLMs) and for good reason. However, there are still many unanswered questions with regulation, privacy, security, intellectual property and more. Developers' natural response to these challenges often mirror a curious and entrepreneurship-like approach — with many developers taking the "I'm going to build my own thing to solve this problem" route. But as developers' interests grow around a particular area, the general level of knowledge rises, tooling improves and abstractions move up so that it becomes easier to tackle a particular problem. If we look at the most optimal way to fine tune models, it's often well-suited to a chain of tasks, and this can be easily represented graphically with low-/no-code tooling. As such, we can expect low-/no-code and generative AI to work hand in hand in facilitating everyone's productivity.
Laurent Doguin
Director of Developer Relations and Strategy, Couchbase


I believe AI will continue to be a transformative force in the developer workflow, igniting both enthusiasm and apprehension. It will also revolutionize how developer teams function within their organizations and how they collaborate with different departments. For example, executives can use AI to convert business jargon into more technical language when they interact with product managers, engineers, and DevOps teams, accelerating the efficiency of those technical teams as a result. I expect an increasing number of teams to turn to AI to foster better collaboration and teamwork across functions.
Christian Ward
EVP & Chief Data Officer, Yext

AI tooling will change how teams work together. Machines help decide things, making teamwork better. Smart methods and adaptability are key for DevOps teams in the evolving tech world. Basic communication and coordination frameworks will have to evolve to take advantage of these new interactions. Humans now will have to play a different and more valuable role.
Martin Borthiry
SVP of Engineering, Copado

There's a lot of media buzz surrounding how AI could codify the coding process (yes, pun intended). But we should also focus on AI's potential to amplify our capacity for collaboration. Large language models (LLMs) and GenAI at large can greatly impact how we interact with one another. For example, we've recently seen developers of different languages leverage LLMs to translate their comments and interact with one another at a previously impossible level. That's a huge improvement to workflow that should be highlighted more, especially in a diverse industry like development.
Adam Frank
SVP Product and Marketing, Armory.io

Go to: 2024 DevOps Predictions - Part 8, covering the impact of AI on DevOps and development.

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