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A Brave New (Generative) World – The future of generative software engineering

Keith Glendon
26 Mar 2024

Disclaimer: This blog article explores potential futures in software engineering based on current advancements in generative AI. While the content presents a plausible vision, it cannot predict the future. Our purpose is to inspire software engineers, software companies and enterprises who are embracing the next generation of ‘product-centric’ business models driven by software to anticipate and embrace the transformative potential of generative AI with bold and forward-looking actions and strategies.

The AI evolution: Transforming software engineering

In the past year, the landscape of tech has seen unprecedented upheaval. Generative AI (GenAI) has catapulted data science, machine learning, and AI into the limelight, sparking conversations and at all levels of business and democratizing access to the power of AI.  From the boardroom to dining room tables around the world, there’s no question that the GenAI evolution will profoundly reshape humanity’s relationship with technology.

Among the many impacts of GenAI, one of the greatest transformations underway is that of Software & Platform Engineering.  As a core capability for every product-centric enterprise in a world that runs on software, this critical domain is being reshaped before our eyes and the impact will be profound.  Every industry is experiencing disruption and reinvention. From software itself to AI-powered products and services, this paradigm shift will be felt.

GenAI is taking these advancements to the next level with a new era of “Generative Software & Platform Engineering.” This concept elevates software to new heights, with visions of enabling it to adapt, scale, and evolve autonomously in response to a dynamic environment.

Just as object-oriented languages and cloud concepts revolutionized software development, GenAI promises to unlock unprecedented possibilities for resilient systems that drive progress in the digital age. To survive, compete and thrive in this context, enterprises must not only adopt Generative AI – but must quickly evolve and mature their core Software & Platform Engineering capabilities.

Unlocking the potential of generative software engineering: Lessons from the past, projections for the future

The transformative journey of software engineering, from procedural development to object-oriented programming, to cloud and microservices, revolutionized how we build and maintain software. Generative Software Engineering is poised to drive an even greater leap forward. Fueling this evolution is Generative AI, a game-changer that empowers software entities to autonomously generate, test, deploy and maintain code.

Inspired by the adaptability of living organisms, these entities will transcend the constraints of a traditional development lifecycle. Guided by human-defined principles, they will orchestrate their capabilities to evolve and optimize in real-time.

The evolution of microservices architecture lays the foundation for Generative Software Engineering. By leveraging Generative AI, we can create Generative Microservices. Eventually, these autonomous entities will seamlessly rewrite themselves to meet fluctuating demands, enhance performance, and integrate with other services. This will lead to the emergence of perpetually optimized software systems that require minimal human intervention.

Generative AI will act as a catalyst, propelling MACH (Microservices, API-first, Cloud-native, Headless) principles to new heights. It will enable the development of self-evolving, API-first software that can autonomously generate new APIs based on user behavior. Cloud-native systems will be empowered to seamlessly migrate across providers to optimize for both cost and performance.

Generative AI will pave the way for “sense and respond” enterprises, where software platforms are inherently dynamic and responsive. This will empower businesses to create new business models that continuously adapt and thrive in the ever-evolving digital landscape.

The human element – adopting and evolving alongside AI

To meet the potential of this vision, realize its value and create a positive future for humans involved in software engineering will require a planned, considered transformation for the human beings involved in software engineering.  To effectively manage this road ahead, organizations need to have a vision and roadmap for adoption, acceleration and elevation of human skills, roles and value.

Generative AI in its present form has the power to take on the role of ‘co-developer’ as the proliferation of coding assistants, generative SDLC tools and Gen AI powered utilities rapidly become integrated into IDEs and traditional software engineering toolchains.  These will quickly lead to increasingly autonomous agents that will essentially become ‘digital developers’ on human-AI development teams.  This first phase – already well underway – is focused on adoption for productivity, efficiency, and quality gains throughout the software development lifecycle.  As the technology evolves, tools mature, and adoption reaches a state of near ubiquity, we expect many organizations will struggle to cross the chasm between experimentation and maturity at scale. 

On the other side of that chasm lies the realization of the vision and value of the Generative Software Engineering Era.  In this future, those organizations who have successfully made the transformative leap will see humans working in more creative, high-value roles that increasingly focus on the orchestration of Generative AI agents who do the heavy lifting of software engineering under the conceptual and value-oriented direction of human experience engineers.

Traditional roles in the software engineering lifecycle will become more strategic and focused on faster iteration of product engineering lifecycles, accelerated value growth and oversight of product and platform quality.  Increasingly, platform engineering teams will focus on the supervision of adaptive product roadmaps that quickly respond to new user preferences, market opportunities and emergent business models. While much of the short-term focus is currently on the productivity and efficiency aspect of Generative AI’s potential – the far more powerful and exciting future lies in the new value it can unlock and the promise it holds to vastly expand the scope and impact that human beings have through building software in this new paradigm.

Dynamic software co-creation

Generative Software Engineering heralds a future wherein human ingenuity, human innovation and human goals and opportunities are the driving force behind dynamic creation of software products, platforms and services.  Future software products will take direction and orchestration from sophisticated software product orchestrators, highly-skilled in collaborative software creation in concert with autonomous software engineering agents. Guided by high-level objectives and constraints, these agents will autonomously generate code, perform testing, and deploy updates, much like a highly skilled developer.

Not only will they respond to direct human instructions but in this new era, software products and platforms will evolve in real-time, driven by sophisticated analysis of user data, preferences,  interactions and market insights. Generative AI will enable software to self-optimize, self-configure, and even self-expand its features and capabilities in response to this analysis. This will lead to the co-creation of highly personalized user experiences, with software automatically adjusting such aspects as its interface, performance, and functionality to suit individual and organizational user needs and preferences.

Foundations for success

These prospects for the Brave New World of Generative Software Engineering are both incredibly inspiring and significantly daunting.  The rapid pace of change is driving an ever-widening gap between the future value and current realities for the great majority of enterprises.  At Capgemini, our experience suggests that every organization in the business of building software or adopting a platform & product-centric mindset as a strategic growth imperative must act now with commitment and bold vision to prepare for success in the age of Generative Software Engineering.  While the foundational building blocks are also evolving, our work with clients and in our own internal GenAI transformation has given us insight to some key domains of focus to jumpstart the transformation while bringing immediate value.  We highlight in the next section a set of critical success factors we believe will underpin a bright horizon of possibilities for Generative Software & Platform driven enterprises.

Have a roadmap – Seldom do we wind up anywhere meaningful without plotting a course.  Plotting a wayfinding course implies a destination both sufficiently valuable and sufficiently defined to get there.  Perhaps nowhere is this concept more crucial than in the realm of Generative Software Engineering.  Our Point of View is that those enterprises who define an inspiring and powerful “North Star” for their unique Generative Software future and a considered roadmap to guide them ever in that direction will attain much greater success than those (the majority at present) who fail to drive their iterative experiments, ideation and use cases without a vision and dynamic roadmap to value.

Employ Framework thinking – from innovation frameworks adapted to the world of Generative AI to Software Engineering methodology frameworks that guide increasing maturity, skillsets and roles, to technical frameworks for the industrialization of GenAI software product engineering at scale.  In the Generative AI world, things will become far more complex and possibly chaotic.  In light of such realities, a grounding in frameworks will be essential to scaling and accelerating value realization in building software.  This is why we highlight the importance of maturity in development and engineering practices.  Many enterprises remain in fractured states of evolution when it comes to software engineering.  Success in the Generative Era requires a product-centric, platform engineering rigor that will bring every organization value in itself and will position any enterprise for greater success with Generative Software Engineering.

Transform end-to-end – a future-ready, Generative Software Engineering enterprise needs to think and act end-to-end, not in silos and pockets of process transformation and tool adoption.  At Capgemini, our own journey has a focus on prioritizing and realizing cohesive end-to-end Software Product Engineering capabilities over lots of shorter term PoC’s and use case experiments.  In short – we’re focusing on “quality over quantity” with ideation, innovation and uptake experiments, so we continue to lead the market in “quantity with quality” in software innovations for our clients who are serious about leading their industries with the aid of Generative Software Engineering.

Hit the Human Element “Head On” – Traditional software engineering roles will be radically transformed in the coming years.  This will come with great challenges from organizational change dynamics to individual human anxieties to significant HR complexities. Alongside the challenges, it’s crucial to stay informed about the evolving regulatory landscape surrounding Generative AI and ensure compliance with relevant legal frameworks.

The successful leaders of the Generative Era will forge clear paths to support their valuable human resources in evolving alongside AI, engaging them in creating the future, elevating their value through enablement, empowerment and training in everything from innovation skills to data engineering, from prompt engineering to creative experience engineering and orchestration of Generative Autonomous Agents.  Rather than asking ‘what are the productivity gains’ and seeking to translate those metrics into incremental efficiencies or profits, visionary enterprises should ask ‘what is our North Star vision and roadmap for human value development in the Generative Engineering Era’.  Then, make bold investments in people as opposed to reducing their numbers.

Collaborate wisely – With a clear “North Star” vision and an enterprise-specific roadmap in mind, organizations should seek to build strong partnerships with technology and services providers who can bring thought leadership, proven assets and accelerators, skills leadership and flexible options for shared value.   The need for collaboration will only intensify as the landscape of Generative AI technologies continues to grow and evolve.  Partnerships will need to move past ‘where have you done it before and what’s your price’ and into a space of ‘who are the best partners to help me adapt and evolve through the volatility of this paradigm shift’ based on capabilities, depth of understanding and creativity in collaborative value creation.

Conclusion: A future of co-creation and autonomy

Generative Software Engineering is here, and every day we’re building an exciting – if daunting – future of unprecedented acceleration in the development of robust, scalable, and user-centric software products and platforms. Just as object-oriented languages and cloud architectures opened new horizons for software development, Generative AI will pave the way for a future where software not only serves but anticipates and evolves with human needs. In this future, the role of the software engineer evolves from creator to orchestrator, guiding intelligent systems that can generate, adapt, and innovate, marking a new chapter in the symbiotic relationship between humans and their technological creations.  At Capgemini, in collaborative partnership with visionary industry partners like Google and its enterprise GenAI stack powered by groundbreaking models like Gemini and dynamic Google Cloud services, we’re committed to unleashing human potential through technology for an inclusive and sustainable future.  We look forward to working with you to help you build yours.

Capgemini at Google Cloud Next 2024

Google Cloud Next brings together a diverse mix of developers, decision makers, and cloud enthusiasts with a shared vision for a better business future through technology. As a Luminary Sponsor, Capgemini is committed to elevating the event experience with opportunities to boost learning and engagement and get fresh insight into today’s riveting topics – including generative AI.

Whether the aim is empowering businesses or their people to unlock the power of generative AI, Capgemini is at the forefront of this evolution. Our continuous work in this growing domain means we are equipped to help our partners capitalize on this unique technology and engineer use cases for enhanced and unprecedented customer experiences.

Come by our booth #840 and let’s explore the possibilities of generative AI with live demos showcasing its potential for Cloud, Data/AI, and Software Engineering. Or reach out to us – we would love to hear your perspective on how we can get ready for what comes next.


Keith Glendon

Senior Solution Director – Software Product Innovation – Capgemini Engineering R&D
Experienced technologist, entrepreneur, and strategist, with a proven track record of driving and supporting innovation and software-led transformation in a range of industries over the past 25+ years. A business and technology leader, powerful visionary storyteller and deeply-experienced executive consultant. Demonstrated results in global multinational enterprises as well as bleeding-edge high-tech startups through creative disruption and expert application of the entrepreneurial mindset. Grounded in an ethical framework that honors a ‘give first’ philosophy and the power of collaboration. Passionately committed to the ideals of sustainability, inclusivity and regenerative practices as keys to disrupting the status quo and driving meaningful change in the world.