At a Glance
AI isn’t making roles redundant, it’s changing how work gets done. As tools compress the distance between idea and execution, traditional layers of coordination are being removed. This blog argues that the real shift in product management is toward judgement, quality, and accountability. The people who will thrive are not those who rely on process or tools, but those who stay close to the work, apply critical thinking, and take ownership of outcomes. In this new environment, value comes from being able to assess what’s right, not just produce more.
‘Everyone’s role is being disrupted. And it’s not about any role being redundant — it’s about a fundamentally new way of working.’
This is the frame we should all be holding. But it requires being honest about what that disruption actually looks like, because the honest version is both more confronting and more interesting than the LinkedIn hot takes suggest.
What’s actually changing
The tools that used to sit between a skilled professional and their output are being compressed or removed. A designer, engineer, and product person can now sit in a room, talk about a product, and have AI agents translate that conversation into a task breakdown and start building. The specification document that used to live in Confluence or JIRA is becoming a conversation that gets recorded, parsed, and acted on.
This doesn’t mean there’s no work. It means the nature of the work is changing. And it’s changing faster in some contexts than others, more mature, higher-autonomy, AI-enabled organisations are living this now. Most Australian enterprises are still figuring out where to start.
The uncomfortable truth about middle management
Management layers are being reduced. Not necessarily because AI has replaced the function, in many cases, it’s still over-hiring corrections and bad strategic decisions coming home to roost. But the direction of travel is clear: organisations want senior people who are close to the work, hands-on, high judgment, able to assess quality and make strategic calls. Not layers of people whose primary function is coordination.
At the same time, very senior people are also getting cut. No role is immune. What survives is value that is demonstrably hard to replicate, and that value is overwhelmingly about judgment, context, and the ability to make things actually happen.
You need to be the quality adjudicator
Here’s what the practitioners who are thriving have in common: they’re excellent at their core discipline, they use AI as a force multiplier, and they take personal responsibility for the quality of what comes out the other end.
This isn’t just reviewing outputs against a checklist. It’s the harder, more human kind of QA: is this realistic? Does this reflect our context? Can we actually execute it? Would I stake my professional reputation on this being right?
That’s not a prompt engineering skill. It’s a craft and judgment skill that comes from doing the work well for a long time.
What you should actually focus on
Get closer to the work, not further from it. Build genuine depth in your domain, not just familiarity with AI tools. Develop your critical and systems thinking. And resist the pressure to optimise your career around being seen to use AI, versus actually using it to produce work that matters.
The people who will be most valuable in three years aren’t the ones who can name the most tools. They’re the ones who used those tools to become undeniably good at something real.
