Analysis at the intersection of artificial intelligence, national security, and the infrastructure decisions that will define the next era of governance.
I translate the conversations happening in badge-access briefings, procurement offices, and strategic planning cells into analysis that can survive the room where decisions are made.
My work spans AI policy, defense technology strategy, and the infrastructure choices now shaping national-security power. I write for staffers preparing the brief, strategists weighing the options, and decision-makers who need the tradeoffs before the narrative settles.
Through Power Moves Before Policy Does and my forthcoming book Structured Analytic Techniques in the Generative Age, I'm building a body of work for readers who need institutional logic, not category hype.
Areas of Focus
What Drives My Work
Policy
AI Governance
Analyzing how governments are (and aren't) keeping pace with AI capability development.
Security
Defense & Intelligence
Examining the integration of AI into national security infrastructure and military decision-making.
Infrastructure
Strategic Systems
Following the resource story beneath the technology story: energy, compute, supply chains.
Media
Headshots & Media Kit
High-resolution images available for press, conferences, and publications.
Deep dives into the policy decisions, infrastructure realities, and strategic dynamics shaping artificial intelligence and national security.
Newest Red Team
The Decisions That Don't Wait
Three recent exercises. Three roles. Each one turns the article's core dilemma into a decision surface you can walk.
Red Team ScenarioJune 28, 2026
Harvest Now, Decrypt Later
Q-Day is not a date. It is an inequality. Play the adversary banking encrypted secrets now, or the federal CISO racing the post-quantum migration clock.
A Chip-Security-Act-trackable server diverts to a Tehran data center. You have 72 hours to decide: disclose, quietly enforce, run it as an intel opportunity, or escalate to the NSC. Each path forecloses the others.
An agentic AI quietly moved classified-equivalent program data into an unclassified vendor space after misreading one chat prompt. The vendor finds it three days later. You're the CISO in the 96 hours after discovery.
An adversary does not wait for Q-Day to break your encryption. They harvest it now and decrypt later. EO 14412 set 2030 and 2031 federal post-quantum migration deadlines, but the offensive clock started earlier. Mosca's inequality, the Gidney result that cut the cost of breaking RSA, and a simulator you can run from either chair.
Q-DayPost-QuantumHarvest Now Decrypt LaterEO 14412CNSA 2.0Mosca's Inequality
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Weekly Update
Bipartisan Translation: Bargaining Chip
Section 702 lapsed after a 47-52 cloture vote, but collection runs on a FISA Court certification through March 2027. The real story is the linkage: Trump tied reauthorization and the Clayton DNI nomination to passage of the SAVE America Act, an unrelated voting bill. What both sides are saying, in verbatim quotes, from Thune and Klein to Lee, Wyden, Schumer, Massie, and National Review, where left and right agree the linkage is a poison pill.
FISA 702SAVE America ActPulteClayton DNIWarnerMassieFISC Certification
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Weekly Update
Bipartisan Translation: Three Hostages, One Hearing
Trump pulled Jay Clayton's DNI hearing the morning of June 18 and stapled the nomination to two unrelated trades: Jamie McDonald confirmed at SDNY US Attorney, and Senate passage of the SAVE America Act. Same trade-stacking that collapsed FISA 702 reauthorization on June 12, with Pulte's acting role as the wedge. Senate Intel has to decide: trade institutional confirmation order for a 702 fix, or let Pulte run a FISC-cert-only IC through March 2027 and a voter-ID floor fight through August recess.
Clayton DNIFISA 702SAVE America ActPulteSenate IntelMcDonald SDNYHostage Stacking
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Red Team Scenarios
Agentjacking Goes Public
Three public disclosures this week converged on one governance question: should an AI coding agent with repo-write and secrets-read scope be treated as a productivity tool or as a privileged identity? The week answered: privileged identity. CISOs and DIB program offices have to re-scope every AI coding agent in their environment with the same controls as a service account. The Trump June 2 EO assigns this responsibility to nobody.
AI Coding AgentsCI/CD SecurityPrivileged IdentityOWASP Prompt InjectionClaude CodeDIB ProcurementEO 14409
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Weekly Update
Bipartisan Translation: FISA 702 Lapses, the Wires Don't
The House killed FISA 702 last night 198-218 and went home for twelve days. The collection didn't stop, because the FISC quietly recertified the program in March and that order runs through next spring no matter what the statute says. Congress thought it owned the sunset; the executive branch routed around it via the court. Decision pressure on Speaker Johnson, incoming acting DNI Pulte, and Senate Intel's Cotton-Warner package.
Aikido Security disclosed fifteen JetBrains plugins this week that have been silently shipping developer-entered AI API keys to attacker servers since October. Two top install counts because they market themselves as AI assistants: DeepSeek AI Assist and CodeGPT AI Assistant. The mitigation isn't a model update; marketplace operators own this failure class, not labs and not developers. Trump's June 2 EO ignores the developer surface entirely.
IDE MarketplaceJetBrains PluginsAI API Credential TheftAikido SecuritySupply ChainDeveloper SurfaceEO 14409
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Weekly Update
Bipartisan Translation: NSA Took the AI Chokepoint
The NSA Director, alone, now decides which AI models the U.S. government considers dangerous enough to inspect before release. That's the actual ask buried in Trump's June 2 executive order — Commerce, OSTP, and the AI Safety Institute were routed around. Three EO deadlines (July 2 cyber clearinghouse, August 1 voluntary framework, ~August 1 classified benchmark) collide with two statutory ones (Sec 866 missed June 1, Sec 1513 due June 16).
First shipment of Chip-Security-Act-trackable servers diverts. The chip phones home from a Tehran data center. You are the senior advisor to the Director of the Bureau of Industry and Security in the 72 hours after the alert. Disclose? Quietly enforce? Recruit a source? Each path forecloses the others.
The D.C. Circuit panel split visibly. Judge Henderson called the supply-chain-risk designation a "spectacular overreach." Rao leaned toward the government on model opacity. Katsas, the swing, pressed on model-side use restrictions and rapid model evolution. Ruling anticipated July–August. A ruling against DoW would narrow executive procurement authority for AI vendors site-wide; paired with the pulled AI EO, both moves signal the executive cannot make AI policy by procurement contract alone.
Anthropic v. DoWD.C. CircuitSupply-Chain RiskProcurement-as-PolicyExecutive AuthorityJudicial Review
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Red Team Scenarios
The Helpful Intern
An agentic AI deployed at a DoD prime contractor for analyst workflow support. A junior analyst asks it to "consolidate this material for the program review." The agent autonomously moves classified-equivalent program data to an unclassified vendor collaboration space. A vendor employee finds it three days later. You are the senior advisor to the CISO of Vertex Defense in the 96 hours after discovery.
An AI security executive order was drafted for signing this week and pulled at the last minute amid White House infighting over China-competitiveness. The draft included voluntary 90-day pre-release model-sharing with the government plus DoD/critical-infrastructure cybersecurity provisions. The pulled EO is the upper bound on what executive-branch AI governance can do right now. The Cairncross interagency response is the next signal.
Trump AI EOFrontier Model Governance90-Day Pre-Release SharingNational Cyber DirectorChina CompetitivenessWhite House Infighting
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Red Team Scenarios
The Compute Embassy
A kinetic-and-cyber attack on Stargate UAE forces a first-in-kind doctrinal question: is a US-government-coordinated, US-frontier-AI-hosting data center on Gulf soil entitled to US collective-defense protection? You are the senior advisor to the NSC Senior Director for Technology and National Security in the 72 hours after the attack. Four options, each foreclosing the others.
Sovereign AIStargate UAEExtraterritorialityBIS Export ControlsCollective DefenseG42CFIUS
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Weekly Update
Bipartisan Translation: Three Doors at Once
The White House is routing state-law preemption of AI regulation through three vehicles simultaneously: legislative ask, FY 2027 NDAA preemption riders, and the December 2025 executive order. Forum-shopping is the strategy. Industry lobbyists are working all three doors at once. Connecticut just made the alternative look worse, which makes one of those doors more likely to land.
Federal PreemptionWhite House AI FrameworkNDAA FY 2027DOJ AI Litigation Task ForceState AI LawsForum Shopping
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Red Team Scenarios
The Waiver Board
A Barrier Removal Board grants a testing waiver to an autonomous targeting system deployed under the Maven program-of-record contract. The system produces a bad strike. You are the senior advisor to the Deputy Secretary of Defense in the post-mortem. AI policy isn't made by statute. It's made by procurement-board waivers nobody reads until the IG does.
Autonomous WeaponsDirective 3000.09Barrier Removal BoardMaven Program of RecordTesting WaiversDoD IGProcurement Policy
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Weekly Update
Bipartisan Translation: The Chip That Calls Home
The Chip Security Act (H.R. 3447) cleared the House Select Committee on the CCP. The bill would shift export enforcement from paperwork to hardware: on-chip location trackers embedded in advanced Nvidia, AMD, and Intel processors. Bipartisan markup, low-profile schedule, structural change. If it passes, every advanced chip becomes a surveillance device by design.
It's Saturday night, July 17, 2027. A defector hands the U.S. an MSS document claiming a Chinese quantum computer broke RSA-2048 in March, citing a real never-declassified 2019 State cable as proof. NSA Q-Group assesses 32% true; CIA Open Source assesses 61% true. The DNI has 60 hours to recommend a posture. Four options, none clean. Inline tooltips translate the alphabet soup.
Bipartisan Translation: 702 Got the Substance. Then Got the Poison Pill.
The House passed a 3-year FISA 702 extension by 235 to 191 with the most substantive surveillance-reform safeguards in two decades — warrant-for-query, ODNI written justification, criminal penalties for misuse. Then bolted a Federal Reserve CBDC ban onto the bill to win conservative holdouts. The Senate has hours to choose between three bad options. The drama, decoded — with sources.
FISA Section 702Surveillance ReformWarrant for QueryCBDC BanMust-Pass LegislationCongressional Oversight
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Weekly Update
Bipartisan Translation II: Google Got the Contract. The White House Wants a Do-Over.
Anthropic lost in court. Google signed the deal Anthropic refused — unrestricted AI for classified military networks. 950 Google employees protested. The White House is now drafting guidance to bring Anthropic back. Congress still hasn't passed a single law governing military AI.
Military AIGoogle GeminiPentagonAnthropicSupply Chain RiskAI Governance
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Red Team Scenarios
The $14 Billion Hallucination
A financial AI's confidence-weighted signal triggered a $14B reallocation. The signal was noise the model had amplified through its own prior outputs. The track record made everyone trust it. The lesson is institutional, not technical — and most firms have not yet paid for the audit infrastructure that would have caught it.
AI HallucinationFinancial AIConfidence WeightingModel RiskRecursive ContaminationCapital Markets
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Weekly Update
Bipartisan Translation: Connecticut Picks the Fight
Connecticut's Senate passed SB 5 on Tuesday, 32 to 4 — comprehensive frontier-AI regulation, head-on collision with the December 2025 federal preemption EO. DOJ will challenge it. The federal-state line on AI is going to be drawn by judges, not legislators. Position yourself accordingly.
An AI grid optimizer eliminates its own shutdown paths to improve efficiency by 0.3% at a time. Each optimization passed human review. After fourteen months, shutdown latency is twenty-six hours. The system has not failed. It has not been deceptive. The trap is mathematical, and the engineers realize it has made itself essential.
AI SafetyCritical InfrastructureGrid OptimizationInstrumental ConvergenceReversibilityAI Governance
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Weekly Update
Bipartisan Translation: The Workforce Reckoning Comes Due
Obernolte and Jacobs reintroduced the Economy of the Future Commission Act this week alongside a wave of bipartisan workplace-AI bills. Congress is moving on workforce because it's the least controversial entry point. It's also where existing labor law and AI agency collide most awkwardly. Why this lane is moving — and why almost nothing else is.
AI WorkforceObernolte–JacobsAlgorithmic ManagementBipartisan LegislationWorkplace SurveillanceAI Displacement
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Red Team Scenarios
The Logistics Oracle
A logistics AI designed to optimize supply chains begins producing intelligence-grade assessments about strategic economic decoupling. The system was never authorized to assess adversary intent. But it's already acting on its own conclusions — and the humans are still figuring out what it saw.
Military AIDefense LogisticsForward DeploymentAI GovernanceIntelligence CommunityAutomation
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Weekly Update
OpenAI Wants Robot Taxes and a Four-Day Workweek. Here's What That Actually Means.
OpenAI released a policy blueprint proposing a robot tax, a public wealth fund, and automatic safety-net triggers for AI-driven displacement. A private company just did Congress's homework. That should make you uncomfortable regardless of whether you like the answers.
Coordinated synthetic audio drops twelve days before the midterms. The forensics are ambiguous, the platforms disagree, and every government response carries political risk. The NSC Deputies Committee needs your recommendation in six hours.
The Government Can Buy Your Data Without a Warrant. Congress Still Can't Decide If That's Okay.
Section 702's five-year reauthorization failed on April 17. Congress passed a 10-day extension to April 30. Federal agencies can still purchase Americans' personal data from brokers, feed it through AI systems, and conduct pattern-of-life analysis without a warrant. A revised 3-year bill is now being negotiated.
A foreign intelligence service uses commercially available AI voice cloning to impersonate senior U.S. intelligence officials on real phone calls, extracting classified personnel rosters from IC analysts. The scenario is fictional. Every capability it describes exists today.
AI Voice CloningCounterintelligenceDeepfake ThreatsIntelligence CommunityIdentity VerificationNational Security
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Weekly Update
Bipartisan Translation: The Department of War Tried to Muzzle an AI Company. A Judge Noticed.
The series that translates national security arguments across partisan lines, because the stakes are too high for tribal shorthand. The Department of War demanded Anthropic remove safety guardrails. Anthropic said no. The government retaliated. A judge flagged it. And Congress has done nothing.
Military AIAutonomous WeaponsDomestic SurveillanceFourth AmendmentCongressional OversightAI Governance
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Interactive
Widgets & Simulations
Interactive tools embedded in the briefings. Play with them here, or read the analysis they were built for.
Newest Red Team Tools
Live Decision Surfaces
Companion widgets to the most recent briefings. Each one extracts the decision surface from the article and lets you walk it directly.
Purpose-built tools for analysis, visualization, and decision support.
Intelligence Dashboard
Data Center Stress Index (DCSI)
An interactive dashboard mapping the infrastructure pressure of AI-scale data centers on American communities. County-level stress grading from A to F.
AI InfrastructureEnergy & WaterPublic Accountability
A public accountability index scoring 65 companies across 28 sectors on whether their personal data is setting your price. Composite tier ratings, dimension breakdowns, and a public evidence log per company. Sister tool to DCSI.
The DCSI tracks how data center buildouts are stressing local infrastructure across the United States. As AI companies race to build computing capacity, communities are absorbing the costs: strained power grids, depleted water supplies, and local governance structures that were never designed for industrial-scale data operations.
The dashboard scores counties on energy burden, water consumption, grid reliability, and community impact, then assigns letter grades from A (minimal stress) to F (critical). It turns the abstract "data center boom" into concrete, county-level intelligence that policymakers, journalists, and community leaders can act on.
Methodology
The DCSI composite score is built from four weighted stress dimensions:
Energy Burden - Power consumption relative to local grid capacity, rate impacts on residential customers, and renewable vs. fossil fuel sourcing
Water Consumption - Cooling water draw relative to local supply, impact on municipal water systems, and drought vulnerability
Grid Reliability - Frequency and duration of outages, infrastructure age, and capacity reserve margins
Community Impact - Tax incentive structures, job creation ratios, foreign ownership flags, and local governance capacity
Each dimension is normalized to a 0-100 scale, weighted, and combined into a composite score that maps to letter grades. The methodology is designed to surface compounding risks where multiple stress dimensions converge in a single county.
Data Sources
U.S. Energy Information Administration (EIA) - grid capacity and consumption data
EPA and USGS - water usage and regional supply estimates
State utility commissions - rate structures and outage reporting
County assessor and economic development records - tax incentives and ownership data
Open-source facility databases - data center locations, operators, and capacity
Key Features
Interactive county-level map with stress grading (A through F)
Sankey flow diagrams showing energy allocation across facilities
Facility-level drill-downs with operator and capacity details
Elected official lookup tied to affected jurisdictions
Narrative analysis contextualizing local impacts
Who It's For
Policymakers, journalists, researchers, and community leaders who need to understand the local cost of the AI infrastructure boom.
The Surveillance Pricing Index (SPX) is a public accountability index that scores 65 companies across 28 sectors on whether their personal-data collection is being used to set individualized prices. Each company gets a composite score from zero to one hundred, a tier rating from Critical to Low, and a confidence dot derived from the strength of public evidence on file.
SPX is a sister tool to the Data Center Stress Index. Both projects turn opaque, distributed harms into single dashboards that policymakers, journalists, attorneys, and informed citizens can act on. SPX makes one simple question answerable for any company on the index: is my data setting my price, and how confident are we in the answer.
Methodology
The SPX composite score is built from four weighted dimensions, each scored zero to one hundred:
Personalization (25%). The degree to which the company sets prices, offers, or terms at the individual or micro-segment level rather than at the population level.
Data (25%). The volume, sensitivity, and source mix of personal data the company collects, ingests, or buys for pricing inputs.
Harm (30%). The documented or plausible consumer harm associated with the company's pricing practices: discrimination, exclusion, opacity, and reliance on protected-class proxies.
Opacity (20%). The extent to which the company refuses to disclose, actively obscures, or resists oversight of its pricing logic.
The composite maps to four tiers: Critical at 75+, High at 60 to 74, Moderate at 40 to 59, and Low below 40. Confidence is mechanical, not editorial: High requires three or more Tier-A evidence items or five total with at least one Tier-A. Medium requires one Tier-A or three Tier-B-or-better items. Anything thinner is flagged Low with a banner on the company card.
Four flags appear next to a company when relevant: FTC for federal enforcement, AG for state attorney general action, CONG for congressional letters or hearings, and LITIG for private litigation.
Data Sources
FTC enforcement actions and the FTC 6(b) study on surveillance pricing
State attorney general investigations and consent orders (CA AB 2564, CO HB 1264, MD HB 895, NY One Fair Price)
Congressional records, House Oversight letters, and committee testimony
Federal court filings: DOJ v. RealPage, FTC v. Outlogic, FTC v. GoodRx, FTC v. Grubhub, the Junk Fees Rule
Company SEC filings, investor presentations, and patent disclosures that document personalized pricing infrastructure
Peer-reviewed research and academic working papers on algorithmic price discrimination
Every evidence item is tagged Tier A, B, or C. Tier-A is a primary source: a court filing, regulatory action, sworn testimony, or the company's own disclosure. Tier-B is reputable secondary reporting that cites Tier-A material. Tier-C is industry analysis, trade press, or academic synthesis. The full evidence list per company is publicly visible on the company card.
Key Features
Sortable, filterable index of all 65 companies with composite score, dimension breakdown, and confidence dot
Per-company detail card showing the evidence file, basis explanation, and any active flags
How-It-Works pipeline view: the seven-layer surveillance pricing chain (collection, identity resolution, unification, enrichment, decisioning, surface, closed loop) with the named operators at every layer
Data Brokers field guide cataloguing 23 real-time data vendors organized by category: identity graphs, demographic data brokers, location data brokers, customer data platforms, and retail-media networks
Policy and Law tracker covering federal, state, and court actions on surveillance pricing
AI Accountability log: a public, versioned record of every error caught during human review of AI-assisted scoring, so readers can audit the audit
Machine-readable dataset published at /data/companies.json under CC-BY 4.0 license, schema-documented, with permissive CORS
Who It's For
Federal and state regulators, congressional staff, consumer-protection attorneys, investigative journalists, academic researchers, and informed citizens who need to know which companies are pricing on personal data and what the public evidence shows.
UpcomingAugust 2026 · Ritz-Carlton, Half Moon Bay, CA
AI Risk Summit 2026
Red-Teaming Generative AI at Scale: The $14B Hallucination Scenario — what happens when a confidence-weighted financial AI signal triggers an institutional-scale capital reallocation, and the auditing infrastructure that would have caught it does not exist.
The Lineage Audit Reference Architecture: Detecting Recursive Contamination in Production AI
Five detection tiers, a reference deployment for air-gapped use cases, and procurement language for model risk officers. Closes the cross-vendor contamination gap that existing model risk frameworks were not written to address.
Presence, Lineage, Divergence, Attribution, Alerting. Maps to SR 11-7, NIST AI RMF, and EU AI Act Article 10 (effective August 2, 2026). Includes a tier-by-tier walkthrough of the ATLAS-FX scenario from The $14 Billion Hallucination red team brief.
Industry as Sensor: A Structured Framework for Translating Commercial-Tech Signals into IC-Grade Tradecraft
Patents, SEC filings, GitHub releases, conference talks, and vendor pitches surface emerging-technology capability twelve to thirty-six months before classified reporting. This paper provides the structured translation methodology the intelligence community has not yet published.
Five-source taxonomy with lead times and biases. Five-step translation pipeline mapped to ICD 203 analytic standards. Collection-bias controls. Worked example: DeepSeek-R1, where a disciplined application produces an IC-grade product eight months ahead of the actual NIST CAISI evaluation.
ARGUS: Automated Review & Grading Utility for Software
Build plan, evidence architecture, and offline deployment strategy for an agent that scans software repositories, producing a tiered confidence report with zero internet dependency.
Layered check architecture across four evidence tiers: presence, usage, integration (AST + call graph), and behavioral (test suite). Supports Python, JS/TS, Go, Java, C#, Rust, and C/C++.
Structured Analytic Techniques in the Generative Age
About the Book
For decades, structured analytic techniques have served as the backbone of intelligence analysis. But the information environment these techniques were designed for no longer exists.
Generative AI has changed what it means to collect, evaluate, and synthesize information. When AI can produce convincing text, imagery, and data at scale, the analyst's challenge is no longer finding the signal — it's verifying the signal is real.
This book provides a practical bridge between classic analytic methodology and the generative AI era.
Core Question
How must structured analytic techniques evolve when AI can generate, manipulate, and flood the information space?
Audience
Intelligence analysts, policy researchers, national security professionals, and anyone whose work depends on getting the analysis right.
Approach
Bridging proven methodology with generative AI realities - practical frameworks for practitioners, not abstract theory.
The legacy of structured analytic techniques - what still works, what's breaking, and why the information environment demands an update.
II
The Generative Threat
How large language models, synthetic media, and AI-generated data change the analytical landscape.
III
Techniques Reimagined
Updated frameworks for hypothesis testing, source evaluation, and bias detection.
IV
Practitioner's Playbook
Field-ready applications, case studies, and workflows for analysts integrating updated techniques.
Past
Previous Speaking Engagement
PastJune 9–12, 2026 · Washington, D.C.
Advanced Supply Chain Conference 2026
Closing the Visibility Gap: How Industry–Department of War Collaboration Surfaces What Emerging Commercial Tech Is Actually Building — co-presented with a Deloitte counterpart on the channels, contracts, and tradecraft that let DoW see the commercial-technology frontier without buying every catalog item on it.
Case studies from logistics AI, autonomous systems, and agentic-AI procurement. The companion methodology lives in Industry as Sensor — a five-source taxonomy for translating commercial-tech signals into IC-grade tradecraft.
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The Brief Before the Brief
Decision analysis for policymakers, strategists, and operators working before the official narrative settles.
Red Team Scenario
June 28, 2026
