Introduction

Now, with the rise of AI and LLMs, we’re at an inflection point. The reality is that AI initiatives will struggle — or fail — without the solid architecture, engineering, and standards that modernisation provides.

Where Modernisation and AI Converge

Where modernisation and AI converge, we can industrialise the SDLC:

• Built-in governance: Architecture standards, engineering standards, fitness functions, and quality gates — enforced by AI.
• Quality everywhere: Embedding automated quality measures across the SDLC ensures quality is built into the product and issues are caught early and continuously, not late in the cycle.
• More time in the problem space: Engineers spend less time battling compliance, and more time planning early, iterating rapidly, and solving meaningful business problems.
• Context engineering: High-quality requirements, data, and standardised practices give AI the knowledge it needs to reason safely about complex systems.

The Future of Enterprise Delivery

The next evolution of enterprise delivery is AI-augmented modernisation and the industrialised SDLC.

I’ll be sharing patterns and lessons as I explore this frontier — bridging architecture, engineering, quality, and AI to create sustainable, scalable delivery.