Career · Leadership · The field
Leadership that has done the job, not just described it
Twenty-five years in technology and leadership, holding every role that exists and a few that do not — engineer, architect, manager, director, VP, CIO, CTO, founder, mentor, partner. Full-time and interim, across startups finding their first customers and $xB corporations defending their last ones. The writing here is what the work actually taught, including the parts that went badly.
The hardest technology problems are almost never technology problems — they are ownership, sequencing, and what the number actually was.
Every role in this field looks different from inside it. The engineer sees a system; the director sees a quarter; the board sees a line item and a risk. Having sat in each of those chairs makes one thing obvious: most failures are not caused by a bad decision, they are caused by a decision nobody could see being made. The work below is about closing that gap — naming the owner, showing the cost, and making the evidence available before somebody has to ask for it.
The frame
Four surfaces of technology leadership
Read the cost study →Direction
Is there one stated bet, and does the roadmap spend against it? A strategy nobody can repeat back is a preference, not a direction.
Delivery
Does the work ship on a cadence the business can plan around, with the scaffolding — tests, gates, reviews — that makes the pace survivable rather than borrowed against.
Cost
What does this actually cost, measured rather than estimated — licences, run-rate, the rework nobody books, and the hours spent proving it worked.
People
Who owns what, who is being grown into the next role, and what the evaluation says when it is written down instead of felt.
Flagships
What the decisions cost, and who should make them
What AI First Actually Costs
The bill nobody itemises: licences and tokens are the visible part, and the rest is review time, rework, evaluation, and the capability you stop building while you integrate. Written for the person who has to defend the number, not the person who chose it.
The Case for an AI Resident
A role that did not exist until the work demanded it: someone who lives inside the system, keeps its memory, and is accountable for what it does. An argument about org design first and tooling second — which is the order these decisions actually arrive in.
Why it fits
Every seat in the room, from both sides of the table
Every role, including the invented ones
Engineer through CTO, plus the roles that had no title yet — the person who owns the integration, the one who owns the evidence, the one who owns the thing nobody wanted to own.
Startup and enterprise, not one or the other
Series A–C companies where the next customer decides the year, and a $3.1B multi-brand enterprise where the audit does. The instincts that work in one are frequently wrong in the other, and knowing which is the job.
Interim, fractional, and alongside
Full-time leadership, interim cover through a gap or a transition, and partner-and-mentor work beside a leader who is growing into the seat — with the handover treated as the deliverable.
Built for growth companies
Working with and for companies in the stretch between traction and scale, where process arrives late, cost arrives early, and the wrong hire sets a year back.
Field notes
Career & leadership writing
See all leadership writing →- NIST and Trustworthy AI: The Lab That Never Fines AnyoneAI Governance & Standards
- FedRAMP and GovRAMP: Evidence as a CommandGovernment Cloud Authorization
- Identity Data in Marketing and Fraud: The Web of IdentityIdentity Data & Fraud
- Pareto in Practice: Eighty Percent from ThreeTesting & Build Engineering
- Email and Text Campaigns: Two Sides of the Same SendMarketing Data & Campaigns
- Engineering Team Turnarounds: Nobody Gets to Blame HistoryEngineering Leadership
- Virtual Cell Models: The Bottleneck Is the DataHealthcare AI & Biology Data
- Reading Healthcare-AI Evidence: One Arm Is Not EvidenceHealthcare AI Evidence
- Wearable Health Labels: Cleared, Certified or WellnessWearable Health Regulation
- AI and Healthcare Payment: The $942 Million Nobody CheckedHealthcare AI & Payment
- Local-First Medicine: The Box in the ClinicLocal-First Clinical AI
- AI Voice Agents in Medical Practices: The 81% ProblemHealthcare Voice AI
- AI Agent Liability: Who Goes to Prison When the Agent Breaks In?AI Agent Liability
- MARA Demo Update: Earned Authority and a Person on CallHealthcare AI Design
- Agile and Iterative Development: A Slice Through Every LayerSoftware Delivery & Engineering Practice
- MARA, the Medical Agentic Resident Assistant: Four Generations, One LineHealthcare AI Design
- What Building With AI Really Costs: The Whole BillAI Toolchain Costs & CI
- Self-Hosted CI Runners: The Job That Waited for a Sleeping PCCI/CD & Runner Infrastructure
- MARA: A Medical Agentic Resident Assistant That Learns From Every Encounter and Never Makes the DecisionHealthcare AI Design
- Root Cause Analysis: The Check Name GitHub Never RenderedRoot Cause Analysis
- Epic Migration Planning: Twelve Thousand Questions, One DateHealthcare IT Program Planning
- EHR Migration Economics: The Cash Trough Nobody BudgetedHealthcare IT Economics
- An Engineering Organization Run by AI AgentsAgentic AI
- Hosted Code Review: The YAML Parsed and Nothing Read ItAI Code Review
- CapEx, OpEx, and EBITDA: The Same Dollar, Two Different StoriesTechnology Finance & Capital Strategy
- Reading the Financials: The Primer for Everyone Who Never Had To CareTechnology Finance & Capital Strategy
- Capitalize or Expense: Your Jira Board Is Now Audit EvidenceSoftware Capitalization & Audit
- Depreciation and Useful Life: The Chip Outlives Its EconomicsInfrastructure Depreciation & Useful Life
- Placement Economics: The Right Answer, Applied EverywhereCloud, Colocation & Placement Economics
- Lift-and-Shift or Re-Architect: The Two That Modernized LaterCloud Migration Economics
- Vendor Economics: The Email in NovemberVendor Economics & Renewals
- AI Spend: Three Budgets Pretending to Be OneAI Cost & Procurement
- AI and Headcount: Somebody on the Board Did the ArithmeticAI, Productivity & Headcount
- Outsourcing After Section 174A: Eleven Months to Relearn ItSourcing, Outsourcing & §174A
- Domain-Driven Design: The Word the Code Got WrongArchitecture & Domain Modelling
- The Scaffolding Comes FirstCI/CD & Delivery Pipelines
- What AI First Actually CostsAI Cost & Procurement
- The Flat LineAI Writing & Detection
- False GreenAI Code Review
- When NOT to Use an AI Agent: A Practitioners Decision FrameworkConcepts
- The 2026 AI Engineer Is NOT What You ThinkCareer & Leadership
- Claude Code vs Codex CLI vs Gemini CLI: The Agentic CLI WarsTools
- Your AI Strategy Has a Single Point of Failure: Your DataStrategy
- Dashboard BI vs Agentic Analytics: The Next Wave of Business IntelligenceTools & Ecosystem
- The Zero Dollar AI Stack: Building a Full AI App Without Paying a CentTools
- The Open-Source AI War Just Exploded: April 2026 ScorecardAI Landscape
- Repository Intelligence: The Skill Replacing Prompt Engineering in 2026Developer Skills
- The AI Code Review Problem: Why the Same AI That Writes Your Code Cant Review ItTools
Engage
Need the seat filled, or the person in it grown?
Interim and fractional leadership, a partner beside the leader you already have, or a second opinion on the decision in front of you — architecture, cost, an evaluation, or the org chart underneath it.
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