The news that Doge is reportedly using AI to create a ‘delete list’ of federal regulations has been rattling around in my head for days now. It’s one of those stories that perfectly captures the bizarre intersection of cutting-edge technology and political ideology that seems to define our current moment.

On the surface, there’s something seductive about the idea. Anyone who’s worked in tech knows the frustration of bureaucratic bloat - those endless forms, redundant processes, and regulations that seem to exist purely to justify someone’s job. The promise of AI cutting through decades of accumulated red tape sounds almost utopian. Just feed the machine learning algorithm thousands of regulations, let it identify the redundant ones, and voilà - streamlined government.

Reading about DOGE’s latest venture into developing software for automating government worker terminations sent a chill down my spine. Not just because of the cold efficiency it represents, but because it feels like we’re watching a particularly dark episode of Black Mirror unfold in real time.

The concept itself is disturbing enough, but what really gets under my skin is the cavalier approach to human employment. Picture receiving a termination notice generated by an AI system, probably with all the warmth and understanding of a parking ticket. My years in tech have taught me that even the most sophisticated systems can’t fully grasp the nuances of human employment situations.

The recent hack of the US Treasury Department has sparked quite a discussion in tech circles, and it’s hitting close to home for those of us who’ve spent time in government IT. Reading through the online commentary, there’s a clear pattern emerging about why these incidents keep happening, and it’s not just about technical vulnerabilities.

Working in tech, I’ve witnessed firsthand how government departments often struggle with the same fundamental issues: inadequate funding, rigid hiring practices, and an institutional resistance to change. The Treasury hack isn’t just a technical failure; it’s a symptom of a broader systemic problem.