The Future Is Now: TuringBots Will Collapse the Software Development Lifecycle Silos

Thanks to TuringBots (AI and generative AI for software development), software development is on the cusp of a transformative change, one that promises to redefine the way development teams collaborate, create, and deploy applications. Picture this: a room full of product owners, subject matter experts, testers, and developers, all working in harmony with the aid of advanced technology including voice and audio integration, digital boards, and, perhaps most intriguingly, holograms. This is not a scene from a sci-fi movie; it's the imminent future of the software development lifecycle (SDLC), projected to unfold by 2028. And it doesn't have to happen in a meeting room; it can all be happening while you are sitting at your desk.

The Invisible and Real-Time SDLC: A New Era Begins

Gone are the days of siloed development processes and delayed feedback loops. The future SDLC is seamlessly integrated and invisible, operating in real time. Teams will no longer face the barriers of traditional software development; instead, they will engage in dynamic collaboration with TuringBots — AI and generative AI entities capable of understanding spoken conversations, natural language text, and low-code and code in many programming languages, and furthermore even able to interpret sketches or ideas jotted down on a board.

Related:Watch Out for TuringBots: A New Generation of Software Development

TuringBots are at the heart of this revolutionary shift, enabling teams to generate graphics and code through integrated development environments that support the SDLC as we know it today. Imagine sharing ideas and information instantaneously on boards that not only display flows and diagrams but can also project low-code/high-code or even, a bit further out than 2030, holographic visualizations in the middle of the meeting table.

Real-Time Reviews and Autonomous Evolution

The process of executing and reviewing development work will be dramatically expedited. Teams will be able to review their creations on the fly, conduct code checks, perform security reviews, and grant approvals in real time. Meanwhile, TuringBots will work in the background, autonomously evolving applications to meet emerging needs and fixing issues before they become problems. This paradigm shift is not merely about speeding up the development process; it's about enhancing creativity, improving accuracy, and ensuring security in ways we've only begun to imagine. By enabling all collaboration and asset generation to occur instantaneously, tested and checked by an ever-vigilant, combined team of humans and TuringBots, the development of new applications will reach speeds previously thought impossible.

The Unimaginable Speed of App Development

As we look toward this future, it's clear that the role of developers and IT professionals will evolve. The focus will shift from manual coding to strategic oversight and from problem-solving to creative innovation. TuringBots, with their ability to operate behind the scenes with other TuringBots and collaborate with humans, will become an indispensable ally, ensuring that the SDLC can keep pace with the rapid rate of technological change and the ever-growing demands of consumers and businesses alike.

Collaboration, Communication, and Speed Will Increase as TuringBots Enter the Loop

Read Forrester's Architect's Guide to Help You Make It Happen

TuringBots exist for each stakeholder, although the most mature and familiar ones are coder TuringBots such as GitHub Copilot, AWS CodeWhisperer, Tabnine, or Codeium, to mention a few. For tester TuringBots, firms like Applitools, Tricentis (Testim.io), or Appvance offering AI testing platforms come up. There are also TuringBots supporting analysis/planning, design, and delivery. There are still concerns, however, about hallucination, custom software development and architecture enterprise requirements, and the need to adapt to the changing landscape. To harness the power of TuringBots, teams must prioritize prompt engineering and learn to leverage new technologies such as vector embedding and retrieval augmented generation. Teams have to incorporate architecture and architects into generative AI and enforce security by design through Zero Trust principles, enhanced testing and security policies, and minimum-viable security. Download the Forrester report, The Architect's Guide To TuringBots, to read the details.

Wrapping It All Up

The vision of an invisible and real-time SDLC facilitated by TuringBots is not a distant dream but an impending reality. By 2028, software development as we know it today will undergo a radical transformation, enabling teams to build new applications at previously unimaginable speeds. This future promises not only to enhance the efficiency and effectiveness of the development process but also to open up new possibilities for innovation and creativity in software creation. As TuringBots get better and we, together with them, learn better ways to collaborate, control, and manage them, as my colleague John Bratincevic and I wrote our blog, The Rise Of Application Generation Platforms, we'll assist in building a future going from code and software asset generation to increasingly larger blocks of finished application generation.

Forrester clients can reach out to [email protected] for guidance sessions and inquiries if they want to set their own roadmap aimed at the future of software development.

— Diego Lo Giudice, VP, Principal Analyst

This article originally appeared on Forrester's Featured Blogs.