Insights

Old core standing in the way of new customers? It doesn't have to be that way. Once upon a time rebuilding a legacy core meant locking your best people down on a hard job with uncertain outcomes. Not anymore. Answer five questions, put AI on the grind, and that launch date becomes a solid commitment instead of forlorn hope. This is how we do it.

The entire production diff was about 15,000 lines — roughly thirty lines per engineer per day. AI's real contribution wasn't writing them. It was comprehension, not codegen.

Most production systems should use AI at the edges and deterministic code in the core. As per-token pricing turns honest, a lot of what's on AI roadmaps today won't survive the look.

If you take AI transformation advice at face value, the work looks done once the tools are bought — and the business still moves like it did a year ago. The Playground is the pattern that turns the tools into a business that moves differently.

Going AI Native means one thing: your customers get superhuman speed and superhuman quality no competitor can humanly match. A Head of AI and a Centre of Excellence won't get you there — Parnas, Conway, and Jevons explain why.

The "SaaS is dead" debate is fixated on pricing. The real shift is deeper: AI is converting one class of software after another from a scarce asset into cheap, replicable inventory — and below that line, there is no product.

We tried to fix our timesheets and accidentally built a context graph. Here's what we learned about why operational discipline matters more than architecture.

35% of companies are already using agentic AI, with another 44% planning deployment soon. But few have restructured how they deliver projects. That gap is where implementation timelines extend and where fixed-price engagements turn into scope management problems.