After building and deploying AI systems for defense and intelligence organizations — and serving as an Army Special Operations Officer in high-consequence environments — I turned my attention to a different problem, but inextricably linked: the erosion of human depth. In a world engineered for passive consumption, notification-driven urgency, and algorithmic influence, the scarcest resource is no longer information. It is attention. It is judgment. It is the capacity for deliberate thought.
Enterprise AI executive turned builder. TS/SCI clearance. Production systems for defense and intelligence. I'm not theorizing about AI — I'm building it and telling you what I see.
Air Force and Army Special Operations. Leadership forged in environments where focus isn't optional and distraction has real consequences — whether that's a combat zone or above 18,000 feet.
2 of 7 continental summits. John Muir Trail 2026. Mountaineering is the embodiment of choosing discomfort, presence, and earned experience over digital consumption.
Where AI transformation, attention management, leadership, and mountain philosophy converge.
The attention economy treats your focus as a commodity. The actualization economy treats it as a resource for becoming who you're meant to be. Here's why the shift matters — and how to lead it.
Inside the design philosophy of Watchfire AI: hard stops over guardrails, adversarial review over blind trust, and why "I don't know" is the most valuable thing an AI system can say.
At altitude, your margin for error is zero and your attention is everything. The same principles apply to leading organizations through AI transformation — but the consequences are less visible.
Most CIB detection systems need to read messages. BLOODHOUND doesn't. This working paper presents a multi-layer detection system that finds coordinated influence operations using only behavioral metadata — posting entropy, distributional fingerprints, coordination graphs, and information flow. It catches 94% of the IRA's active accounts without touching content, identifies exactly where behavioral analysis hits its ceiling, and doesn't pretend the ceiling isn't there. The full paper includes methodology, code-level architecture, negative results, and every assumption that could break it.
A small experiment in attention.
Most digital systems are engineered around a simple loop: Stimulus → Response → Reward → Repeat. Cassius is a deliberately small demonstration of that mechanism.
Talks that bridge enterprise AI expertise, military leadership, and the human performance imperative.
For leaders navigating AI transformation who sense that the real risk isn't falling behind on technology — it's losing the human capacity to use it well.
Lessons from building production AI systems for the Intelligence Community — and why hard stops, adversarial review, and "I don't know" are the most important features you can ship.
A hands-on workshop combining military leadership frameworks, attention science, and practical tools for teams drowning in digital noise. Participants leave with a personal operating system for intentional technology use.
The summit demands everything the screen consumes: presence, discomfort tolerance, earned experience. A talk about what high-altitude mountaineering reveals about our relationship with the digital world.
For leaders and organizations navigating AI transformation with intention.
Strategic guidance on responsible AI adoption. Use case identification, change management, workforce readiness, and implementation that doesn't sacrifice the humans it's supposed to serve.
For senior leaders who want to reclaim their cognitive capacity, lead with presence, and model the intentional technology use their organizations need to see.
Half-day and full-day sessions for teams on digital discipline, attention management, and building healthy AI adoption practices. Practical, not preachy.
Strategic advisory for defense contractors navigating AI market opportunities. Capture strategy, competitive intelligence, and proposal development — augmented by production AI tools.
Production tools that enforce oversight, prevent fabrication, and keep humans in command. This is what responsible AI looks like when you actually build it.
Problem: Research briefs take days to assemble and still get challenged on sourcing.
System: A 7-stage analytical pipeline that produces cited, adversarially reviewed deliverables — so the output holds up under scrutiny.
In-ProductionProblem: Proposal teams lose pursuits to process failure — missed compliance, weak positioning, and generic AI-generated content that regurgitates requirements without a technical basis.
System: A structured analytical pipeline producing exceptionally high-quality, compliant response packages with adversarial verification and human decision gates at strategy and submission.
In-ProductionProblem: Critical decisions made on gut feel and unstructured analysis — with no framework to surface what's uncertain or quantify what's at stake.
System: Structured probabilistic forecasting with calibrated confidence intervals and human approval gates at every critical juncture.
In-ProductionProblem: Competitive landscapes shift faster than teams can monitor manually, and signals get buried across fragmented sources.
System: Serverless signal ingestion, pattern detection, synthesis, and dashboard delivery for business development teams.
In-ProductionProblem: Strategic decisions ship without structured challenge — confirmation bias compounds unchecked through the approval chain.
System: Six-module decision analysis with cognitive isolation and built-in controls to stress-test decisions before they're final.
In-ProductionProblem: Entry requirements vary by passport, destination, and travel mode — and travelers piece together guidance from outdated forums and generic government pages.
System: Personalized entry guidance synthesizing visa requirements, documentation, timelines, safety, and real-time environmental data into a structured pre-departure brief.
In-ProductionProblem: Coordinated inauthentic behavior campaigns manipulate public discourse at scale, and platform-level detection remains opaque and inaccessible to independent researchers.
System: A multi-layer behavioral detection pipeline that identifies CIB through temporal entropy, network coordination, and content propagation analysis — detecting how accounts behave, not what they say.
In-ProductionProblem: Training platforms treat learning as content delivery — present material, test recall, move on. Retention collapses within weeks and credentials don't produce competence.
System: An adaptive learning engine built on cognitive science — spaced repetition, calibrated confidence assessment, and desirable difficulty to produce durable knowledge that transfers to application.
In-ProductionProblem: LLMs confirm their own outputs. Single-model pipelines share blind spots, and hallucinations are syntactically indistinguishable from accurate text.
System: A 6-stage claim verification pipeline grounded in Popperian falsificationism — adversarial disconfirmation under epistemic isolation using a separate model family, retrieval-backed citation verification, and tiered evidence quality.
In-Production