There's a version of the AI story that goes like this: the machine does the work, the human checks it. Faster output, lower effort, less thinking required.
At Optimation, it's going differently.
Philippa McQuillan, our Customer Success Manager, says the biggest change has been clarity. AI helps her collect scattered thoughts, shape them into something sharper, and cut through the repetitive work that used to eat into the time she actually needs for clients.
Jeshua Hertzke, our Engineering Team Lead, puts it this way: his thinking time hasn't decreased since AI entered his workflow, It's moved. The heavy lifting now goes into precisely defining what needs to be built and why. AI executes well on clear direction, but it can't supply the domain knowledge and judgment that make the direction right in the first place.
"The real challenge," Jeshua says, "is directing AI with enough domain knowledge and governance to get correct outcomes, not just fast ones."
AI feels a lot like the internet did in the early 2000s, fundamental shift in how knowledge is accessed and understood, arriving fast and changing everything around it.
What made the internet transformative wasn't that it replaced human thinking. It amplified the reach of it. The people who adapted weren't the ones who found the internet easiest to use. They were the ones who understood their field well enough to know what to do with it.
AI is playing out in a similar way. The advantage doesn't go to whoever has access, it goes to whoever knows enough to direct it well.
What both Philippa and Jeshua describe is a recalibration, not a replacement. The parts of the job that require clear thinking, sound judgment, and genuine expertise still require those things.
AI has removed some of the friction between having an idea and getting it into the world, but it hasn't removed the need to have good ideas in the first place.
Philippa's ideas aren't generic: they come from years of understanding her clients and what good work actually looks like in their context. Jeshua's ability to precisely define what needs to be built draws on knowing what goes wrong when that definition is vague. That's the kind of experience AI can't replicate. It can only amplify it.
This matters because there's a tempting shortcut in the AI conversation that goes: learn the tools, get the productivity gains. That's true as far as it goes. But the deeper advantage, compounding over time, comes from pairing those tools with genuine domain knowledge. AI amplifies what you bring to it. Which means the more you know, the more useful it becomes.
It means the answer to "how do I get more out of AI?" isn't just to use it more. It's to keep developing the expertise that makes your direction of it worth following. The thinking was always the hard part. AI doesn't change that. It just makes the thinking matter more.
We've been thinking about this a lot at Optimation. If your team is working through the same questions, Get in touch.
Philippa McQuillan | Customer Success Manager
Jeshua Hertzke | Engineering Team Lead