Latest Learning Out Loud

Every week another Australian business decides it needs an "AI Lead." Far fewer know what that person should actually do, what to pay them, or how to tell a genuine operator from a confident talker. Get this hire right and you set the ceiling on your entire AI strategy. Get it wrong and you quietly burn six to twelve months you can't get back.

Something's changed in the briefs. Until recently, the default motion for AI hiring was contract. It made sense — the work was project-shaped, budgets were cautious, and nobody wanted to commit permanent headcount to a capability they were still figuring out. Bring someone in, ship the pilot, see what happens.

If you're recruiting for AI roles right now, you've probably noticed something frustrating: two companies can advertise the exact same job title and be looking for completely different people.

A client called me last month to tell me the candidate I'd backed for the role had missed out. And on paper, it made no sense. Fifteen years in the field,glowing references, the kind of CV you don't second-guess. I'd been sure they'd land it. Instead, the client went with the other candidate — someone with half the experience. When I asked why, the hiring manager didn't hesitate: "The other one could actually use the tools. We could feel the difference in the first interview."

A forward deployed engineer is a customer-facing software or AI engineer who embeds directly with a client to scope, build, customise, and ship production AI solutions inside the client's own environment and workflows.

Let's be honest. In most organisations right now, AI transformation in the workplace is being led by the CTO, the CDO, or an enthusiastic exec who just came back from a conference with a subscription to three new tools and a lot of energy.And HR? HR is in the back seat. Waiting to be told what's happening. Reacting to the fallout.That needs to change.