Digital Services

Transforming software delivery with AI, responsibly: Department for Environment, Food & Rural Affairs GenAI offers organisations the promise of accelerated innovation and greater productivity. But delivering real, sustainable impact requires moving beyond hype cycles and embracing the complexity and uncertainty that come with transformative change. we partnered with the Department for Environment, Food and Rural Affairs (Defra) to explore how GenAI could responsibly enhance software delivery. This initiative aligns with the UK Government’s AI Playbook , demonstrating how AI can be leveraged safely, effectively, and responsibly. The engagement focused not just on technical gains, but on building the foundations for long-term, organisational transformation through disciplined engineering, structured workflows, and governance-first AI integration. As a result, and at the heart of this transformation, the Defra Playbook was created, a structured guide to integrating AI into software engineering workflows. About the Department for Environment, Food & Rural Affairs The Department for Environment, Food & Rural Affairs is responsible for improving and protecting the environment. They aim to grow a green economy and sustain thriving rural communities, and support the UK’s world-leading food, farming and fishing industries. Defra is a ministerial department, supported by 35 agencies and public bodies. Industry Government Organisation size 20,000+ Location UK Project length Ongoing Challenge Balancing the pressure to adopt AI with scalable and responsible engineering Organisations across industries are under increasing pressure to adopt GenAI coding tools to gain efficiency and competitive advantage. The promise of faster software development, automation, and reduced manual effort is compelling, but balancing speed with responsibility and scalability remains a major challenge. Key challenges faced by organisations include: Pressure to deliver faster – Leadership expects rapid AI-driven productivity gains, but without disciplined engineering and AI coding best practices, short-term speed can lead to far worse technical debt due to the AI not checking the code and solving the same problem in multiple ways, leading to an unmaintainable mess in a short space of time. Unstructured AI adoption – In the absence of a shared strategy, teams often experiment inconsistently with AI tools, creating uneven or risky implementations. AI-Generated code quality – While AI can generate code quickly, ensuring security, performance, and maintainability still requires a small pool of senior engineering experts who know what good looks like. Ethical & compliance risks – As AI models reflect biases in their training data, organisations face increasing pressure to address fairness, security, and IP concerns through clear governance. Integration with existing development workflows – For AI to add real value, it has to align with existing CI/CD pipelines and best practices Recognising these complexities, Defra sought a partnership that would enable them to innovate responsibly and lay the groundwork for scalable AI adoption. Through our phased approach, we helped Defra evolve from simply using GenAI tools to rethink how delivery happens, and how long-term value is created. This meant starting small and building confidence, with a clearer path towards broader, lasting transformation. Our approach Accelerating delivery with responsible GenAI At we, we approach AI adoption as a journey across three phases: Phase 1: Augmented expertise — Embedding GenAI tools within existing teams to enhance speed and start to consider the impact of AI effects on the organisation. Phase 2: Accelerated initiatives — Designing GenAI-driven workflows and small, nimble teams to unlock specific, strategic value. Phase 3: AI organisations — Reimagining operating models and structures to fully integrate AI across the enterprise. Structuring delivery around AI-driven workflows Rather than bolting GenAI tools onto traditional delivery processes, we partnered with Defra to design delivery around AI from the outset. This meant: Identifying opportunities where GenAI could potentially add value with experimentation on internal prototypes. We refined our ways of working and built a structured playbook. Structuring small, cross-functional delivery teams specifically optimised for AI-driven workflows, blending AI-augmented expertise with strong human oversight by senior engineering experts. Embedding GenAI into core activities, from code generation and testing to backlog refinement and technical analysis. With growing confidence in the approach, we are now piloting the rollout to other teams in a controlled environment — focusing on data privacy, appropriate tool use, and measured scaling. While many organisations find themselves stuck on early experimentation (Phase 1), our work with Defra was weighted towards Phase 2: Accelerated initiatives – designing real AI-enhanced delivery models that prove strategic value. While we also built foundational capabilities associated with Phase 1, the primary focus was on creating tangible outcomes that could enable Defra to responsibly plan for future, broader organisational change. Building safe, sustainable practices Recognising the risks that come with unstructured AI adoption, we applied rigorous engineering discipline to all initiatives: AI-driven productivity, validated : Engineers reported feeling up to 5x faster during early stages of prototyping and iteration. However, we stressed that perceived gains must be supported by structured workflows, prompt discipline, and human validation at every step. Engineering rigour to combat “vibe coding” : We broke down work into small, well-scoped tasks that kept AI outputs manageable and understandable, maintaining clear lines of accountability. Human-led quality assurance : AI-generated code was subjected to structured code reviews, manual refactoring cycles, and robust test automation practices. Governance-first AI integration : Ethical, compliance, and security checks were built into every step of the GenAI workflow, ensuring that Defra could move quickly without compromising on critical safeguards. Through this approach, Defra avoided the pitfalls of rushed, uncontrolled AI usage and laid the foundations for safe, scalable adoption. Creating a prompt-first delivery framework A key enabler for sustainable scaling was the development of a centralised prompt library. By treating prompts as first-class assets, we: Standardised prompting techniques, ensuring consistent, reliable AI outputs. Created reusable prompt patterns, enabling teams to leverage best practices rather than starting from scratch. Controlled AI variability, reducing the risk of non-deterministic outputs or inconsistent coding styles. Locked AI to structured methods, encouraging the application of known design patterns and structured problem solving. This “prompt-first” philosophy allowed Defra teams to manage GenAI behaviour predictably across different use cases, unlocking greater reliability and trust in AI-assisted work. The Defra AI SDLC Playbook A blueprint for AI in software development At the heart of our engagement was the creation of the Defra Playbook — a structured, evolving guide to integrating AI into software engineering workflows responsibly, without compromising quality and speed. The Playbook enables Defra to: Embedded rigorous engineering practices: Encouraged small, well-defined tasks, AI-assisted test automation, human-led refactoring, and disciplined version control. Developed a centralised prompt library: Standardised prompting techniques to produce consistent, high-quality AI outputs. Aligned AI usage with governance frameworks: Ensured that ethical, compliance, and security considerations were built into AI-driven workflows from the start. The Defra Playbook represents a critical first step towards a more AI-integrated operating model. As Defra builds on this foundation, the next phases of the journey will focus on: Structuring GenAI-driven delivery teams around high-value initiatives. Continuously evolving engineering practices to keep pace with rapidly advancing AI capabilities. Preparing for the longer-term organisational changes that full-scale AI adoption will demand. By moving carefully but purposefully, Defra is positioning itself to harness GenAI’s potential while safeguarding quality, security, and maintainability. The Playbook is a living document – it will continually evolve as new models emerge at a rapid pace. Our strategies and best practices remain adaptable as what works today may need re-evaluation tomorrow. It would have been easy to get swept up in the AI hype, but We helped us stay grounded, guiding us toward a responsible, long-lasting approach that actually delivers value. This is a transformation and we’re excited to see what’s possible as we move into phase two and scale this across more teams. — Tim Howard Deputy Director, Major Projects, Cross-Cutting Technical Services , Department for Environment, Food and Rural Affairs Results Unlocking value with AI through sustainable delivery Our work with Defra provided early proof that disciplined, structured AI adoption can drive meaningful impact — setting the stage for broader, scalable change. Perceived productivity gains : Engineers using AI tools reported feeling up to 5x faster in early prototyping and iteration cycles. Higher code quality : AI-generated test automation and structured human oversight improved reliability and reduced post-release defects. Greater consistency : The prompt library significantly increased consistency across AI-assisted outputs. Stronger governance : AI usage aligned with Defra’s broader compliance and security standards from the outset. A fivefold productivity boost isn’t just a technical win—it’s a public one. When engineering teams deliver more value, faster, we’re giving citizens better outcomes for the taxes they fund. This could be the foundation of a next-generation civil service—one that empowers teams, embraces innovation, and works smarter for everyone. — Tim Howard Deputy Director, Major Projects, Cross-Cutting Technical Services , Department for Environment, Food and Rural Affairs Conclusion Responsible AI delivery requires more than code At we, we believe the real promise of AI in software delivery lies not just in faster code generation, but in enabling sustainable, transformative change. By combining rigorous engineering discipline, structured workflows, and a phased, responsible approach to adoption, we help organisations like Defra move confidently from experimentation to wider adoption. By focusing on disciplined practices from the outset, our partnership with Defra produced measurable early benefits and laid a strong foundation for broader transformation. AI will make small businesses bigger and big businesses smaller. Enterprises have a choice: use AI to streamline operations and stay competitive, or risk losing revenue as faster, smarter challengers eat into their market. Ryan Sikorsky Co-Founder , we Video Watch the video case study Learn more about how this project provided Defra with early proof that disciplined, structured AI adoption can drive meaningful impact in our video case study. Recommended for you Previous Next Blog “My CEO keeps coming and asking me how we are using AI in the SDLC!” – AI Enabled Delivery According to 50+ Tech Leaders Blog AI in software delivery: Busting the 5 biggest myths before you get started Blog Are enterprises getting left behind in AI-powered SDLC? Get in touch Want to know more? Are you interested in this project? 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