2025 Wrapped

Introduction

2025 was a year of change, but not the energizing kind. It felt like operating in rough seas with shifting rules, thinning margins, and a work environment that became harder to recognize. The mandated return to office and the steady evaporation of telework options took a real toll. Four-hour daily commutes have been rough on my time, my truck, my wallet, and frankly, my patience. Watching a workplace turn toxic seemingly overnight, and seeing talented people walk away from civil service because of it, has been one of the most dispiriting parts of the year.

Layered on top of that, the broader political environment amplified the strain. The new administration’s posture, and the DOGE-style approach to “efficiency,” has felt less like constructive reform and more like disruption for disruption’s sake. From where I sit, it has been destructive to morale and corrosive to the sense of stability that public service depends on. At the same time, the affordability squeeze kept tightening: pay, housing, groceries, and the everyday costs that make planning harder even when you are doing everything “right.”

Still, there were pockets of positivity. If you work in technology, you either keep learning or you get left behind, and I chose to keep moving. This year I leaned hard into AI/ML, not because I buy the hype wholesale, but because the underlying capabilities are real and increasingly relevant to how we make decisions. I am skeptical of the bubble dynamics and the way this space is being oversold, but it is not blockchain or crypto. There are legitimate use cases, and when you cut through the noise, the work can be genuinely interesting again. Starting JPME Phase I added structure and perspective, and I also began building side consulting work to help non-DoD organizations move outcomes forward with pragmatic technology.

As I close out 2025, I am trying to hold two truths at once. I can stay optimistic and keep scanning for opportunities where they exist. But this year also forced more honest reflection about career, priorities, and what kind of life I want to build next. If 2024 was about expanding the horizon, 2025 was about reassessing the course.

By the Numbers

• Published 15 blog posts, including this one, and kept the cadence going across both professional development, technical writing, and sharing knowledge.
• Earned 4 certifications: CompTIA Security+, AWS Certified AI Practitioner, Microsoft Azure AI Fundamentals, and Google Cloud Generative AI Leader
• Pivoted from long-term JDISS Technical Director work on intelligence support to C2 applications to AI pilot missions: closed out 1 major role and started 2 AI pilot efforts—Manada Technology's AI@FlankSpeed pilot sponsored by PEO Digital and the Vannevar Labs ARCHER pilot—focused on transitioning OSINT C5ISRT capabilities toward operational adoption, with ARCHER moving from DIU to PMW-120 under N2/N6 sponsorship.
• Completed 3 Staff Assist Visits (SAVs) visiting 1 Bi-National Command: NORAD, and 3 Combatant Commands: USINDOPACOM, USNORTHCOM, and USSPACECOM.
• Visited 1 IC agency: ONI.
• Started JPME Phase I at the U.S. Naval War College in March, and will carry it into Spring of next year (Module FKC, 1, 2, and 3 in the books, more ahead).
• Received 1 graduate program acceptance: the Johns Hopkins University M.S. in Artificial Intelligence; agency funding is pending, so the start decision rolls into next year.
• Logged ~100 GitHub contributions.
• LinkedIn Content Performance: ~17,000 impressions, and grew follower count to 1,426 (+36.9% year-over-year).
• Started 1 side consulting gig with Respect Foods, Inc. (a food broker), helping a non-DoD organization modernize workflows and deliver outcomes using practical cloud, automation, and AI-enabled approaches.

Blog Post Highlights

JPME Phase I Series

A running set of write-ups from JPME Phase I, translating the coursework into practical takeaways on strategy, operational art, and the mechanics of how leaders think and decide in complex environments.

• JPME Phase I: Foundational Knowledge Course (FKC) (April)
  The on-ramp to the Naval War College journey—what the FKC covers, how it’s structured, and why it sets the tone for the rest of the program.
• JPME Phase I: Module 1 – Fundamentals of Strategy (June)
  A strategy-focused tour through foundational theorists and enduring problems, tying big ideas to real warfighting challenges across different eras and theaters.
• JPME Phase I: Module 2 – The Security Environment (August)
  A deep dive into how strategy gets made and executed—framed through systemic, national/organizational, and individual/leadership lenses, with a focus on decision-making under real constraints.
• JPME Phase I: Module 3 – Operational Art (September)
  Operational art as the bridge between policy aims and feasible campaigns—balancing time, space, and force, with center of gravity logic, joint functions, and theater geometry shaping the plan.

AI, ML & GenAI Demystified Series

A practical, plain-language series that moves from “what is AI” to “how it’s built, evaluated, governed, and deployed,” with an emphasis on avoiding hype and understanding tradeoffs—and it also captured the focused study push that helped me earn three AI certifications back-to-back: AWS Certified AI Practitioner, Microsoft Azure AI Fundamentals, and Google Cloud Generative AI Leader.

• AI, ML & GenAI Demystified Series: Foundations of Modern AI (July)
  A grounding post that traces how we got from early AI approaches to today’s generative models and why the fundamentals still matter.
• AI, ML & GenAI Demystified Series: Should AI Solve This? (July)
  A decision filter for when AI is the right tool (and when it isn’t), with clear framing around outcomes, constraints, and risk.
• AI, ML & GenAI Demystified Series: Good Data Beats Clever Models (July)
  Why data quality, structure, and stewardship usually decide success long before model selection does.
• AI, ML & GenAI Demystified Series: Training Day (July)
  A walkthrough of how models actually learn—from training paradigms to practical workflows like fine-tuning and prompt-centric approaches.
• AI, ML & GenAI Demystified Series: Judgement Day (July)
  The evaluation reality check: metrics, failure modes, robustness, fairness, drift, and what “good enough” really means in production.
• AI, ML & GenAI Demystified Series: Skynet Activation (July)
  From model to mission: the nuts and bolts of deployment—platform choices, security, guardrails, and the operational controls that keep systems reliable.
• AI, ML & GenAI Demystified Series: Cloud-Native Foundations (July)
  A cloud perspective on “AI-ready” claims—comparing how major providers position ML/GenAI capabilities and what that means for real adoption paths.

Staff Assist Visit Series

Field notes from staff assist visits—what the mission looks like up close, what’s working, what’s brittle, and what the acronyms are really doing to outcomes.

• Staff Assist Visit: USINDOPACOM (January)
  A mission-centered look at Indo-Pacific realities, paired with on-the-ground observations from time in Hawaii.
• Staff Assist Visit: NORAD, NORTHCOM, SPACECOM, and the MMC (May)
  A behind-the-curtain view of homeland defense and space missions—where process, tooling, and staffing friction meet real operational demands.

Certifications

• CompTIA Security+ Renewal (February)
  A practical recap of renewing Security+—what worked, what didn’t, and how to keep the certification current with minimal wasted motion.

Conclusion

2025 was a difficult year to live through, and an even harder one to romanticize in hindsight. The day-to-day realities of federal service became more exhausting: mandated return-to-office, telework flexibility evaporating, long commutes eroding time and energy, and a workplace climate that, in many cases, shifted toward instability and toxicity. Add a higher-cost economy to the mix and the margin for error, rest, or recovery got thinner than it has been in a long time. If 2024 felt like forward motion, 2025 often felt like endurance.

But endurance still counts. I kept learning, kept writing, and kept investing in skills that matter. I doubled down on AI/ML not because I am blind to the hype, but because the core capabilities are real and increasingly central to how we will build decision advantage. I continued JPME Phase I to develop the strategic lens that complements technical execution. And I started building a small consulting practice on the side, helping non-DoD organizations pursue outcomes with pragmatic technology and less ceremony.

Looking ahead, 2026 feels less like “more of the same” and more like an opportunity to reset. I intend to finish JPME Phase I at the Naval War College. If funding and administrative realities allow, I may start a master’s program and take the next step in formalizing the AI depth I have been building on my own. Professionally, I am energized by the prospect of new pilot work, including efforts centered on the Navy’s API platform and the practical mechanics of turning modern software patterns into operational capability. Personally, I am focused on protecting time, sustaining health, and keeping a growth mindset that is grounded in application, not just learning for learning’s sake.

Cheers and good riddance to 2025. Here’s to 2026—more clarity, more control over the variables that matter, and a sharper focus on work that is useful, honest, and worth doing.

See the associated LinkedIn post.