Insights

Prompt engineering has undergone a significant transformation in the rapidly evolving landscape of artificial intelligence. What began as simple text inputs to generate specific outputs has evolved into sophisticated instruction sets that guide autonomous AI agents through complex, multi-step processes with minimal human intervention.

In today's digital landscape, where security breaches can cost organisations millions and erode customer trust, building high-performing DevSecOps teams isn't just an operational choice - it's a strategic imperative.

This article explains the role of a data engineer as a specialist software engineer who builds and maintains the systems that manage and prepare data.

On the UK's Renters Reform programme, we scoped 170+ features using Agile T-shirt sizing. In collaborative workshops, teams from tech, design, and policy aligned on effort (S, M, L, XL). This built a shared understanding of complexity, surfaced hidden risks, and enabled realistic MVP planning and delivery forecasting across the entire project.

This series is aimed to help you take a step back and ground yourself on the core principles that every data team must understand. We will focus on the data engineering process, which is the art of preparing the most valuable ingredient your company has at its disposal: your data.

In this final article, we turn our attention to the technological foundations that underpin modern government services and consider how these foundations must evolve to meet emerging opportunities and challenges.