The Agile Manifesto was written in 2001 by some of the biggest names in software development. Since then, the Agile community has worked to spread and support the best-known, as well as emerging, practices under the umbrella of Agile methodologies.
With nearly a quarter of a century passed, a legitimate question has recently surfaced online: is Agile still relevant today, after all these years?
With the evolution of technologies, practices, methodologies, new programming languages, cloud computing, AI, and all the innovations in the past two decades, is it still important to talk about Agile?
What is Agile?
To reflect on how relevant Agile is in 2025, it’s important to quickly recap its values and principles, as well as clarify its correlation with other methodologies. I’m sure everyone has heard of Agile in some form, but many common implementations have led to some misconceptions.
The name “Agile” was coined in 2001 with the drafting and signing of the Manifesto, which includes a declaration of intent and the 12 Agile principles. Some of the most well-known Agile methodologies include Scrum and Kanban, with Scrum having become a major topic of discussion in recent years due to numerous interpretations, often aimed at making it more digestible for corporate environments.
Anyone who has had the opportunity—or perseverance—to truly encounter Agile in any form will immediately recognize that many of the best practices that have gained popularity in recent years stem from its roots—and vice versa, in some cases.
Some examples? Here they are!
The similarities between eXtreme Programming (XP) and Agile are obvious and almost trivial. For example, the author of XP is one of the Manifesto signatories, and including XP means also including other practices easily traceable to it, such as TDD, OKRs (quarter cycle), or planning (weekly cycle), which are very similar to Scrum’s sprints. Likewise, Lean is undoubtedly related to many shared principles, and consequently, the DevOps approach inspired by it, which emphasizes close collaboration between roles traditionally seen as separate (Development and Ops, but also Testers, Product Management, etc.), is a great example of “individuals and interactions over processes and tools.”
If we think about practices, Continuous Delivery is explicitly mentioned in the Manifesto, and consequently, we can also count Continuous Integration and Trunk-Based Development. It’s also clear that cross-functional teams are the main implementation that makes teams “self-organized.”
And the list could go on for a while! I believe the practices within this group are all part of a positive feedback loop, empowering and enabling each other.
So, Is Agile Still Worth Talking About in 2025?
Short answer? Yes. Of course, yes! In fact, time has only helped spread these concepts, and new technologies have only enhanced the relevance of Agile.
Consider this: today, computers are incredibly fast, programming languages are much more “dev-friendly,” and practically everyone has a smartphone. Technology has become truly ubiquitous. Given this, we can reflect on how, a few years ago, long development cycles were considered reasonable because long times due to poor practices in software development were somewhat masked by equally long times required to simply compile and test code.
Today, when we talk about Continuous Delivery, we can realistically aim for at least one release per day without any issues. The technology to achieve this is within reach of any development team, especially using the cloud, without needing to set everything up in-house unless there’s a specific reason to do so.
A clear example of how relevant it is to talk about Agile, Lean, and XP comes from the book Accelerate (2018). Based on research, it demonstrates year after year how Agile practices and methodologies have a massively positive impact not only on development teams but also—crucially—on business success. The research is updated every year with the State of DevOps report, diving deeper into the subject.
It’s also crucial to continue discussing and spreading the values, principles, and technical practices that enable teams to become high-performing. We’ll revisit this in future articles, but it’s essential to understand that an organization cannot be Agile if its development team doesn’t implement Agile practices and methodologies. In this sense, technology can enable a company to achieve greater success and respond more effectively to market and customer needs.
But Now AI is Here
Another important element to consider, which could generate some confusion, is the rise of Artificial Intelligence (AI) and Low/No-Code tools.
None of us can know for sure where they will take us, although I have my own opinion. The greatest potential I see in software development is an AI capable of writing, maintaining, and refactoring an entire project’s codebase on command. Some might think this would eliminate the need for automated tests, since we write them mainly to ensure we don’t break existing code with future changes. But I disagree.
Instead, I imagine doing “TDD with AI”—writing tests and letting the AI update the codebase to satisfy the new test as well as existing ones. Something similar can already be done on a single class, and I’m sure it will be possible on an entire codebase in the future.
This example illustrates my point: there are aspects of programming, even quite complex ones, that are difficult not because it’s hard to write the first version of software, but because maintaining it over time while keeping the cost of change under control is challenging. If AI can manage the codebase, we might forget about Clean Code principles and Design Patterns—what matters is that the code does what the business needs. The design will no longer need to be optimized for readability and maintainability but only, when necessary, for better performance. That’s why I still want to write the tests—to maintain that level of control that ensures “the code does what it needs to.”
It’s a small example to demonstrate how I think Agile practices will remain fundamental. If TDD gives us control over code behavior, maintaining only the tests will become our focus, with the same benefits we currently see in pair/mob programming, such as knowledge sharing and real-time review. Being able to do CI will remain essential for quickly releasing an MVP of our feature and understanding whether it works—just with less time required since many more elements will be automated.
In Conclusion
The answer seems clear: yes, Agile, the Manifesto, Lean, XP—these intertwined methodologies will continue to hold value. Paradoxically, their value may increase because they will impact the parts of work where AI will have less influence, as context, business objectives, domain knowledge, and case specifics are crucial. In a world where purely technical aspects will flatten a bit due to automation, it will be these working practices and methodologies where we can make the most impact and truly differentiate ourselves.
