Last month, our company hackathon became a vivid illustration of a broader shift in how software gets built. Across teams, from sales to support, product to engineering, domain experts huddled around laptops, experimenting with AI powered platforms such as V0, Lovable and Bolt. Within hours, they'd fashioned interactive prototypes complete with navigation flows and validation rules, all without writing a single line of traditional code.
Although these early demos relied on mock data, the fact that non-engineers could conjure usable software unaided was striking.
As a full-stack engineer accustomed to crafting CRUD apps from the ground up, I found myself asking a new question: How might we empower these citizen developers to build more often, more securely, and with live data? Their deep problem domain knowledge meant they moved swiftly, iterated boldly and learned faster than any handoff-laden process could permit.
An isometric illustration of a futuristic highway under construction, where software engineers in hard hats are laying down glowing code-shaped road segments.
Over my two decades in software, I've discovered my highest leverage isn't in writing every screen or endpoint myself, but in architecting robust APIs, infrastructure and tooling so that others can deliver user value. In this two-part series, I'll share how engineers can transition from gatekeeping code to enabling creation at scale. In this first instalment, we'll explore the mindset shifts and guiding principles. Part 2 will dive into concrete patterns and architectural strategies for secure, sustainable enablement.
Companies must be agile and respond quickly to changing customer needs in today's fast-paced and constantly evolving technology landscape. That's why DevOps practices that emphasise collaboration and communication between development and operations teams to deliver software rapidly, reliably, and at scale have become increasingly popular.
Shifting left, a core principle of DevOps can significantly benefit companies of all sizes. By empowering engineers to take on more operations responsibilities and promoting a culture of experimentation and innovation, companies can improve collaboration, increase reliability, and deliver high-quality software at scale.
In this post, I'll discuss how and why Cambridge University Press adopted a shift left culture.
Engineers are responsible for designing and building complex systems that are expected to perform optimally under different conditions. However, without a deep understanding of how these systems behave, they risk making assumptions that can result in inefficiencies or even system failures.
In this post, we'll discuss why understanding a system like a doctor helping a patient is essential for engineers and by taking a proactive and data-driven approach, engineers can ensure that their systems are performing optimally and can make informed decisions that result in improved performance and reliability.
As engineers, one of our primary responsibilities is to ensure that the systems we build are stable and reliable.
However, despite our best efforts, issues and issues will inevitably arise in production environments. When this happens, it can be tempting to try and patch the problem and move on quickly.
However, recreating production issues locally is a critical step in the debugging and resolution process.
In this post, I'll explain the benefits of reproducing production issues locally.
An isometric illustration of a futuristic highway under construction, where software engineers in hard hats are laying down glowing code-shaped road segments.
