2024 DevOps Predictions - Part 5
December 11, 2023

Industry experts offer thoughtful, insightful, and often controversial predictions on how DevOps and related technologies will evolve and impact business in 2024. Part 5 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


In 2024, the rapid evolution of centralized platforms and integration of AI/ML in every stage of the software development lifecycle — from ideation and planning to production deployment management — will revolutionize software engineering. These will streamline and accelerate every aspect of an engineer's workflow — reducing cognitive overload, enabling creation of reusable code, simplifying code searches, faster troubleshooting, and even generating test code — so they can focus on the more creative aspects of software design and bring solutions to market faster. This new relationship between the engineer's platform and AI/ML will pave the way for an era of software development where intelligent automation and human creativity synergize to deliver exceptional products and services at unprecedented scale to customers and users worldwide.
Sandhya Sridharan
Head of Engineers' Platform and Experience, JPMorgan Chase

GenAI will change the nature of work for programmers and how future programmers learn. Writing source code will become easier and faster, but programming is less about grinding out lines of code than it is about solving problems. GenAI will allow programmers to spend more time understanding the problems they need to solve, managing complexity, and testing the results, resulting in better software — software that’s more reliable and easier to use.
Mike Loukides
VP of Emerging Tech Content, O'Reilly Media

For software, the most significant shift will be that most software will be developed with the aid of AI, and software will be built, released, and updated in what today would feel like incredibly short cycles. The AI models will learn from how the software is experienced and how well the expected outcome is achieved and modified based on this telemetry. It will fundamentally transform the current ways we make and maintain software today.
Russ Whitman
CEO, NodeSource


2024 will be the year that AI-assisted DevOps becomes a thing. There will be a proliferation of "DevOps copilots" which assist or even supplant your DevOps engineers for all sorts of tasks — from managing production, to debugging outages, to configuring services. The best DevOps teams will be the ones most able to integrate AI into their daily workflows; ones that don't will fall behind and risk wasted time and unnecessary outages.
Zach Lloyd
Founder and CEO, Warp

Co-pilots will take on an increasingly important role in helping product teams with conceptual problem-solving. Co-pilots will review and inspect user stories, design choices and code written to solve a problem. As it learns, the co-pilot will accumulate an extensive library of solutions shortening the agile lifecycle. It will become a best practice engine for the product and engineering team, helping guide them to a solution without wasting precious time and money exploring a multitude of avenues, as happens currently. This streamlining of the SDLC will accelerate the delivery of high-quality software and applications.
Rupert Colbourne
CTO, Orbus Software

Adoption of AI-Powered Software Development Tools Will Triple in 2024

With rapid advancements in the maturity of AI-powered software development tools, new entrants from all of the large cloud players, and an explosion of smaller, specialized offerings, we expect the usage of AI in the software development lifecycle will at least triple. One study by StackOverflow estimated that 70% of their audience are using or are planning to use AI tools, and with the demand for greater productivity amongst enterprise developers only growing, achieving that number (at least amongst enterprise developers) is highly likely. The productivity that these tools will deliver could not come at a better time, as we desperately need more developers. The U.S. government is projecting 25% job growth from 2022 to 2032 for software developers, quality assurance analysts, and testers. With a shortage of talent to fill these roles, AI-powered software tools will make the developers that organizations already have on staff dramatically more efficient and begin to close that talent gap.
Peter Guagenti
President, Tabnine


As engineers further integrate generative AI into their day-to-day tasks, I think more and more of the code produced will be the result of generative AI assistance. By the end of next year, it'll be interesting to see how much code is actually being written by hand versus being written through engineering prompts given to LLMs — and then tweaked by engineers to ensure it's up to their standards.
Camden Swita
Senior Product Manager, New Relic


In 2024, AI and ML will transcend their roles as mere tools and emerge as indispensable partners in reshaping cloud automation and optimization. Traditional development is time-consuming and requires significant expertise, but with AI and ML integration, manual coding and testing will become a thing of the past. These technologies excel at generating code and drastically reduce manual work. They also analyze data comprehensively, pinpoint inefficiencies, and recommend efficient resource management. This shift allows businesses to redirect human resources towards strategic goals, fostering innovation and growth. The outcome: enhanced efficiency, reduced costs, and seamless collaboration between human expertise and AI, delivering unprecedented value and agility in the digital era.
Mohan Atreya
SVP Product and Solutions, Rafay


Developers expect to be 30% more efficient using generative AI assistants. I asked my developer team to estimate how much of the code they're writing could be produced by a generative AI tool, and they consistently estimate 30%. While this has yet to be proven, that level of efficiency is a real game changer. Beyond that initial increase in productivity, there are also the benefits of reusability and sharing. The AI-generated piece of code that makes development 30% more efficient today could be reused to help transform the AI tool from an assistive technology to a semi-autonomous technology. By continually improving the AI tool, organizations could then get it to extend code generation and efficiency even further, and leverage it again on other projects — increasing the overall capabilities of future developments.
Sunny Bedi
CIO and CDO, Snowflake


Generative AI and AI coding assistants will move from what some people call "junior developer" level, with a 25-30% code acceptance rate status, to CTO status through embedded context. The ability to add more context, including runtime context, will exponentially increase the value and massively improve the acceptance rate (70% and better) of AI-generated code. Currently activities like deep debugging, multi-file changes, using large files as inputs is beyond the scope of most coding assistants.
Elizabeth Lawler
CEO, AppMap


Copilot is just the start. We'll see a new generation of AI-assisted programming tools. We are already seeing tools for managing prompts; we will soon have libraries of prompts designed to direct genAI to accomplish specific tasks. And, while Copilot is primarily useful for low-level coding, we will soon see generative AI tools for high-level tasks like software architecture and design.
Mike Loukides
VP of Emerging Tech Content, O'Reilly Media


Generative AI tools have already shown their potential in generating code snippets, helping developers with autocomplete suggestions, and even debugging code. In 2024, these capabilities will become more integrated into development environments (IDEs), reducing the time and effort needed for routine coding tasks.
David Pinett
Sr. Director of Product Management, Copado


We expect to see generative AI play a role in debugging, allowing engineers to use generative AI, and ask simple questions, like "Hey, I'm having an incident. Can you, assistant, go look at logs, errors, and/or deployments for that time range and deliver a summarized version of everything that happened around this incident?" The ability for an engineer to have this work for them in the background while they handle other aspects of the incident response will be a game-changer in the debugging process moving forward.
Camden Swita
Senior Product Manager, New Relic

In 2024, generative AI and automation tools will play a supportive role in amplifying developers' capabilities, hastening routine coding tasks and highlighting potential issues that often result in extensive debugging sessions. Such technological augmentations can result in boosted productivity and, on average, superior code quality.
Tiago Cardoso
Principal Product Manager, Hyland


The rallying mantra in the DevOps landscape to "do more with less" sees no sign of slowing down in 2024. It's what will propel automation to the forefront next year. Whether through integration, AI, or data — automation will redefine developer tasks as tool suggestions keep getting better and better. Double-clicking on AI and ML for a moment: it's been used for years by leading DevSecOps tools to help automate and make critical decisions in the name of speed and efficiency. In 2024, there will be a pivotal shift towards integrating automation in every aspect of software development to not only improve productivity but reshape how organizations operate.
Tyler Warden
SVP of Product, Sonatype


Generative AI will provide assistive automation of DevOps pipelines, much in the way copilots have provided assistive coding for engineers. AI will help generate pipelines, generate automated tests, create infrastructure, and find and surface problems during the release process. This will enable teams to deploy faster, with better quality than ever before.
Mike Salinger
VP of Engineering, TrustCloud

Automation is a key part of DevOps. In 2024, we can expect to see even more automation of DevOps tasks as teams look to improve their efficiency and reliability. Artificial intelligence (AI) and machine learning (ML) are being used to automate a variety of tasks in the software development lifecycle. In 2024, we can expect to see wider adoption of AI and ML in DevOps as teams look to further improve their efficiency and reliability.
Vishnu Vasudevan
Head of DevOps, Opsera


There will be increased exploration of generative AI, particularly focused on leveraging APIs to drive more automated workflows. APIs will act as the connective tissue between data and actions, aiming for improved automation outcomes. Experimentation will need to be the focus as there is much to define in this space and many teams will need to better design and define their APIs from a readiness perspective.
Sean Butler
Vice President of Product Management, SmartBear

I think we'll see a deepening trend toward AI-powered APIs in the developer tooling space — more intelligent code suggestions and auto-completions, with better understanding of context and requirements. Developers will have access to a wider range of AI-driven tools and services that simplify their work and improve the delivery and quality of their software.
April Dagonese
Senior Director of Product Growth, Foursquare

Go to: 2024 DevOps Predictions - Part 6, covering the impact of AI on DevOps and development.

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