I Planned Military Ops. AI Just Made It My Most Valuable Skill | Opinion

I never imagined military experience would become my most valuable asset in the world of artificial intelligence until I witnessed AI's struggles with a task deemed straightforward. During an enterprise AI project, a skilled developer instructed the system to merge multiple software functions into one platform. Though the AI produced results swiftly, they were inaccurate, records were misplaced, and business rules diverged from actual operations.

After several attempts, it became clear that the technology was not yet ready. This incident prompted a crucial question: Had we adequately considered the problem before entrusting AI to solve it? This realization altered my perspective on artificial intelligence and my career. Reflecting on my seven years as an infantry officer, I recognized that the disciplined thinking process I had internalized—often referred to as constraint-first thinking—had become a rare skill in the AI landscape.

Training included defining the mission, understanding its constraints, questioning assumptions, and only then executing. AI amplifies this same discipline. When people discuss military service, attention usually focuses on leadership, discipline, or resilience. However, the skill that has proven most valuable to me is the ability to navigate uncertainty before taking action.

Much of my military career involved planning complex amphibious operations. Each mission required coordinating personnel, equipment, logistics, communication, and timing while anticipating that conditions would change post-execution. We anticipated friction, so we dedicated more time to testing assumptions than celebrating them.

Every contingency had to be explored before any action was taken. In my subsequent career as an enterprise technology consultant, I discovered that AI thrives on the same tenacity. Enterprise systems harbor numerous business rules, security requirements, and interconnected platforms. AI can generate vast amounts of work rapidly, but success hinges on an equally critical quality: defining boundaries before execution begins.

My initial AI project underscored this point. Rather than dismissing AI, I paused, analyzed the target platform, mapped its business rules and data model, and identified critical constraints. Only after establishing these guardrails did I instruct AI to construct. The outcome was immediate. The technology ceased to improvise, as it comprehended the environment in which it was expected to operate.

While discussions surrounding AI often revolve around superior models and faster tools, my experience suggests a simpler truth: AI operates based on the instructions provided. The quality of those instructions depends on human judgment, experience, and the capacity to think through a problem before seeking a solution. This insight is evident in every project I undertake.

Whether I am developing AI systems for my own businesses or assisting enterprise organizations in redesigning complex technology environments, the fundamental challenge remains the same: the quality of the initial thinking. Every successful project begins with questions I learned in the Marines. What are we striving to achieve? Where could this endeavor fail?

Which assumptions warrant further examination? Which decisions should remain under human control? These questions have been the foundation of my career long before artificial intelligence emerged. Consequently, AI has merely amplified their importance. As I continue to work with AI, I increasingly appreciate the value of this mindset beyond my professional life.

Veterans often question whether they must become software engineers to remain relevant. Students ponder which AI certification will hold the most significance in the coming years. I comprehend the uncertainty, given the ever-evolving nature of technology. However, my advice remains consistent: immerse yourself in AI enough to alleviate intimidation.

Construct a small project. Ask questions. Experiment. Once you witness AI solving a genuine problem, curiosity will replace fear. Subsequently, invest your time in gaining deep expertise in a field of interest. AI tools will continue to evolve. Expertise compounds. Every profession harbors knowledge that transcends manuals. Firefighters comprehend how emergencies unfold.

Nurses discern subtle changes in patients. Construction supervisors identify issues that drawings overlook. These instincts stem from experience, and they form the constraints that enable AI to generate meaningful work. Constraint-first thinking is not exclusive to the military. It flourishes wherever individuals dedicate years to mastering a craft, learning where things fail and understanding the boundaries between a satisfactory outcome and a costly error.

This is why I believe the future of AI builders will span all professions, not solely technology. Their advantage will not stem from mastering a programming language first. Instead, it will arise from possessing profound expertise in their domain, enabling the articulation of what constitutes excellent work. The greatest opportunity lies ahead.

Today's AI is revolutionizing digital work, but tomorrow's breakthroughs will increasingly permeate the physical world through robotics and humanoid systems. These technologies will require individuals who understand construction sites, hospitals, factories, farms, warehouses, and emergency response from personal experience. Their expertise will become the operating principles that render these systems effective.

This realization has transformed my perspective on military service. Veterans inherently possess extensive training in uncertainty, questioning assumptions, planning for contingencies, and making decisions prior to execution. While the technical skills necessary to work with AI can be acquired, the habit of thoughtful thinking typically takes longer to develop.

Similarly, leadership potential may not reside in those who are familiar with the latest tools. Rather, it may lie with individuals who engage in thorough problem analysis, define boundaries, and anticipate potential failures before commencing construction.