AI

We’re living through the awkward teenage years of AI in hiring. Post-Covid layoffs, productivity hype and LinkedIn’s algorithm soup have collided—creating a noisy, trustless, demoralising mess. Everyone’s optimising, no one’s connecting. And the system’s broken for all involved.

An embedding is a way of representing text (or any data) as a numerical vector in multi-dimensional space. Essentially, it captures meaning and context—so that words, phrases, or even entire conversations that have similar themes end up closer together.

There is a lot of noise about AI. The pace of progress is jaw-dropping. Tools are launching weekly, models are growing more capable, and entire industries are being reimagined. But amid all the hype, something important is missing. The technology is moving fast. The value is not always following.