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Dolo Miah avatar

Dolo Miah

·7 min read
AI

AI adoption in business: real examples, risks and lessons from UK leaders

Person writing in a notebook with a pen on a wooden table, next to some paperwork.

AI: The good, the bad, and the ugly

Over the last six months, I have had the privilege of sitting down - virtually and in person - with leaders from across UK industries: energy, utilities, construction, law, manufacturing, media, education, and beyond. Not to sell anything. Not to run a workshop. Just to have an honest conversation about where they are with AI adoption and implementation.

What I heard was revealing. Not because everyone was doing extraordinary things with AI (some were, some weren't), but because the honesty in those conversations cut through the noise that dominates most AI discourse

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Elia Corkery avatar

Elia Corkery

·7 min read
Software

Technical debt in software development: What it is, why it matters, and how to manage it

A digital artwork depicting a futuristic scene with a staircase leading from a solid, crumbling dark cube on the left to a glowing, transparent structure of geometric glass shapes on the right. The scene is set in a dimly lit environment.

Every business wants software that moves fast, scales well, and supports innovation. But behind many digital products sits an invisible problem quietly slowing everything down: technical debt.

It is one of the most common reasons software projects become harder to maintain, more expensive to evolve, and increasingly frustrating for both users and development teams.

Technical debt is not always caused by bad development. In many cases, it is the natural result of moving quickly, prioritising short-term delivery, or building on systems that were never designed for today’s demands. The issue is not necessarily the existence of technical debt, it is

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