As AI technology becomes more advanced, it’s changing how we build software. The traditional Software Development Lifecycle (SDLC) is a process used to plan, create, test, and maintain software. But with AI’s growing capabilities, we have an opportunity for a new, better way of doing things. In our recently published white paper, we proposed a new approach, called the “V-Bounce,” that integrates AI into every stage of software development, from the initial planning to the final deployment.
This overview simplifies some of the concepts from that paper. To gain a more comprehensive understanding of the complexities of the AI-Native SDLC, and an in-depth exploration of this new methodology, we invite you to read the full white paper.
When we say something is “AI-Native,” we mean that AI is not just an add-on duct-taped to the process, but is designed to be part of every part of the process from the beginning. For software development, this means using AI to enhance efficiency, accuracy, and innovation in every phase.
AI has the potential to revolutionize every step of the software development process, having impact across engineers, designers, project managers, finance teams, architecture teams, and business stakeholders:
By integrating AI into all these phases, the SDLC becomes a more continuous, efficient, and high-quality process.
Here at Crowdbotics we saw early on that being able to effectively turn ideas into requirements and that requirements into context, we create immense value at the start of any software project. Our PRD AI tool is able to turn natural language into full Product Requirements Docs that not only helps set projects up for success at the start but also acts as a springboard for other AI models to integrate farther down the chain in the SDLC.
One great example of how our tool is being used today is using the context model created from our tool to integrate and enhance code generation tools. This means that code generation models become aware of the larger business context and thus increase in accuracy and performance.
Traditional methods like Agile and Waterfall have been effective in software development since the 1990s, but their 2-week sprint structure doesn’t fully capitalize on AI’s potential. The V-Bounce Model is a newer approach that adapts the traditional V-Model to integrate AI throughout the entire development process.
In this model, AI reduces the time spent on coding and increases the focus on planning, design, and continuous testing. By leveraging large-language models (LLMs), high-quality code generation becomes near-instantaneous and cost-effective. Natural language becomes the primary programming interface, and humans’ roles shift from creators to verifiers and strategic decision-makers.
The V-Bounce model — which can be used in agile development — represents a new way of thinking about software creation. By fully integrating AI, we can make the process faster, more efficient, and more reliable. While the V-Bounce model is still a theoretical framework, it opens up many opportunities for future research and practical applications.
Curious about how to leverage the V-Bounce model to accelerate your development process? Reach out to our team at Crowdbotics to learn how V-Bounce and CodeOps can help you create a faster, better development lifecycle and tap into the future of software development.
