Workday + TechWolf: Knowing the Work Behind the Work #workday #shorts #podcast #ai

Nowadays, if you believe Twitter and LinkedIn, every software engineer should be running for the hills because all their jobs are going to be done. Like it's going to be all agents because look at Claude's and Claude's code and whatever everybody can do. Um I can assure you, if your job is to maintain like mainframe codes at a legacy bank, the last thing you're going to do is load that entire repository into an AI coding tool and go mayhem on that code. That code has been like very carefully maintained and refactored for the last 60 years. Actually, like applying AI in the real job um is much more nuanced. Work is very context-specific. Even the same job or the same task at a different organization can be very different. To make AI land and stick out there in the real world, we have to understand the real world. Which means that we have to actually mine data information about what these tasks look like, how these tasks and decisions and processes build up into a job. And then once we fully understand that, then we can surgically assess and and figure out like how we can use AI to improve these workflows, um make these jobs more efficient.