Ben Gaddy

The big unlock for me was to learn to see work as systems. Once you start breaking messy, bespoke tasks into components, you realize a huge chunk of knowledge work can be programmable. Not in the "build an app" traditional sense. More so in the sense that reading research, extracting a writing style, replicating the logic of a spreadsheet layout... these all have structure or patterns you can translate into code. Most people never saw it as that because code always felt like some esoteric tech thing that only software engineers touched. That's the big paradigm shift. I.e., you stop thinking about code as a technical skill and start thinking about it as a way of seeing work. Every workflow you now launch at work becomes a question of inputs, logic, data, and outputs. Every repeatable task becomes a candidate for automation. And... once you're in that mode, you can't turn it off. You find leverage everywhere - probably some foolish & unproductive endeavors, but you only learn by doing. That's also why I think people still underestimate the potential upside on demand. Most companies sit on massive backlogs of work that never got automated. Engineering was too scarce or too expensive or the ROI looked wasn't worth it or the problem touched too much unstructured data or systems to solve cleanly. Pick whatever excuse. AI changes the calculus on all of those simultaneously. The people who can see work this way will translate it into systems. As the cost of building and intelligence keeps falling, more of these projects clear the hurdle (aka the ROIC math gets better). This expands cumulative technical demand in the long run vs. compressing it. Now you start to see the blue sky thinking emerge...