A Software Development Revolution That Won’t Happen
Forget everything you know about the software development life cycle (SDLC), application design and the role software developers play within organizations. A new paradigm, called AppGen, has made all these things irrelevant.
At least, that’s what some analysts would have you believe. They contend that AppGen — a software development strategy that centers totally around AI — is radically reshaping the way businesses design, build, and deploy software.
Personally, I’m skeptical on this front. I don’t think AppGen, or AI in general, is poised to revolutionize software development in a fundamental way. To me, AppGen is just the latest in a long string of overhyped tech buzzwords that will fade in time.
Here’s why.
What Is AppGen?
AppGen — short for application generation — is an approach to software delivery that is completely driven by AI. (AppGen also happens to be the name of an AI-powered development platform offered by Symph.ai, but in this article, we’re referring to AppGen as an idea and practice, not a specific tool.)
The AppGen concept has been promoted most prominently by Forrester analysts. In a June 2025 blog, they write that AppGen “will collapse the software development lifecycle, democratize development, and redefine what it means to ‘build software.'”
(Disclosure: I work on a part-time basis as an adjunct research advisor for IDC, a Forrester competitor; however, IDC played no role in the development of this article, and the views I express herein do not necessarily represent those of IDC.)
This will happen, Forrester says, because AI will make it possible for anyone — both professional developers and non-technical “citizen developers” who don’t actually know much, if anything, about coding — to tell AI tools what they want their applications to do. The AI will then, in theory, handle all aspects of application design, implementation, and deployment — hence how AppGen will supposedly “collapse” the traditional SDLC by making it unnecessary for humans to work through the traditional stages of application development one-by-one.
Why AppGen Won’t Change the World
There’s no denying that AI dramatically changes the way coders work. Generative AI tools can substantially speed up the process of writing code. Agentic AI can help automate aspects of the SDLC, like integrating and deploying code.
But for my money, it’s hyperbole to expect that AI-powered AppGen platforms will render the SDLC as we’ve known it for decades totally obsolete. Even with the assistance of AI, there remains value in treating application design, implementation, and deployment as distinct processes.
For example, the ability to sit down and think about what an app needs to do is important for producing an app that meets business goals. Skipping design as a deliberate step is likely to result in AI-generated apps that lack the capabilities and features an organization actually requires.
It’s equally implausible to me that AI will allow people with no technical skills whatsoever to create complex applications. Even when AI generates and manages code, an understanding of concepts like the differences between programming languages or how to mitigate software security risks is likely to spell the difference between the ability to create apps that actually work well and those that are disasters from a performance, security, and maintainability standpoint.
Old Hype, New Technology
The hype surrounding AppGen reminds me of the buzz spawned by the introduction of the “NoOps” idea nearly 15 years ago.
NoOps — short for “no IT operations” — theoretically heralded a world in which IT automation solutions were becoming so advanced that there would soon no longer be a need for traditional IT operations at all.
Incidentally, NoOps, like AppGen, was first promoted by a Forrester analyst. He predicted that, “using cloud infrastructure-as-a-service and platform-as-a-service to get the resources they need when they need them,” developers would be able to automate infrastructure provisioning and management so completely that traditional IT operations would disappear.
That never happened, of course. Automation technology has certainly streamlined IT operations and infrastructure management in many ways. But it has hardly rendered IT operations teams unnecessary. Even in the age of generative AI — a technology that has opened the door to all manner of new IT automations that no one could foresee in 2011 — Ops remains critical for most organizations.
AppGen, I suspect, will end up in retrospect looking just as over-hyped as NoOps does today.
AppGen: A New Take on No-Code/Low-Code?
I’d note as well that many of the premises behind AppGen sound pretty similar to those pushed by advocates of low-code/no-code platforms during much of the past decade. These solutions, too, were poised to turn everyone into a citizen developer and streamline the software development process — or so we were told.
In actuality, while low-code/no-code certainly did make it easier for some non-coders to build simple apps, it most definitely did not replace the need for traditional software development tools or personnel at most organizations.
To be sure, AI can do many things that traditional no-code/low-code solutions can’t. But is it good enough to make conventional software development practices and tools completely obsolete, a feat that forerunners like low-code/no-code platforms failed to achieve? I doubt it.
Conclusion: Why AppGen Won’t Change Software Development
I’d bet a lot of money that software development processes and tooling will evolve in major ways over the next several years, in response to AI-powered innovations. Indeed, this is already happening as developers integrate generative AI and agentic AI capabilities into tools like IDEs.
But I don’t think we’re headed for a future where everyone on the planet can build sophisticated, high-performing apps by spending a few minutes prompting AI models with short descriptions of what they want. Nor can I envision a world in which the SDLC no longer governs software development. AppGen may drive evolution in software development, but it won’t generate a full-on revolution.
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