Retired Army Special Forces officer Mike Nelson criticized Hegseth's rhetoric, stating, 'That's a necessary end to achieve goals through military force - you have to kill people to achieve them. That's not the end. It's a weird obsession with death for the sake of it.'
The economics are hard to ignore. Shooting down a drone with AeroVironment's LOCUST laser system costs less than $10, using just two to five seconds of laser energy. Compare that to the interceptor missiles currently used against Iranian drone swarms, which cost orders of magnitude more and are in short supply across allied arsenals.
When civilian banks, logistics platforms, and payment processors share physical data center infrastructure with military AI systems, those facilities become legitimate military targets under international humanitarian law - and the civilian services housed inside lose their legal protection.
I have been working in Ukraine since 2019, first as an active Green Beret advising in an official capacity, then after leaving that service, directing special operations on the ground and more recently carrying hard-won lessons back to NATO before they are forgotten or overtaken by the next news cycle.
Number one is speed takes priority over perfection. We can iterate to get to operational capability. And the second is that early soldier feedback is critical in order to make sure we're getting the right technology for the future fight, and then we want to be able to prove the demand signal before we spend big dollars on programs.
Lead without authority. You may not have direct reports, yet you shape architecture, quality and the roadmap. Your leverage comes from artifacts, reviews and clear standards, not from title.I started by publishing a lightweight architecture template and a rollout checklist that the team could copy. That reduced ambiguity during design and cut review cycles by nearly 30 percent
According to the Secretary of Defense Pete Hegseth's memorandum on the Strategy, this AI-first status is to be achieved through four broad aims: Incentivizing internal DOD experimentation with AI models. Identifying and eliminating bureaucratic obstacles in the way of model integration. Focusing the U.S.'s military investment to shore up the U.S.'s "asymmetric advantages" in areas including AI computing, model innovation, entrepreneurial dynamism, capital markets, and operational data.
The US Army's biggest AI gamble may not be on autonomous weapons, but instead whether Silicon Valley software can tackle the service's most tedious and, more often than not, grueling administrative jobs. Think less uncrewed aircraft and more behind-the-scenes tasks like recruiting, equipment maintenance, and endless gear inventories. Through a mix of new tools, redesigned workflows, and data integration, logisticians