Enterprise AI & Software Delivery
48 essaysHow AI changes engineering workflows, developer experience, governance, and the SDLC — without the hype.
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The bottleneck is never the stack. It was not the stack when we moved to cloud, and it is not the stack now that we have agents. I write about what actually constrains software delivery: clarity, judgment, and the humans doing the work.
Vice President of Engineering at a Fortune 100 company, leading Cloud, Platform & DevOps. Thirty-plus years across financial services, insurance, manufacturing, and education, and a 95%+ team retention rate, keep me grounded in what actually ships.

years building
30+
financial services · insurance · manufacturing
VP Engineering
F100
cloud, platform & DevOps
team retention
95%+
across multiple orgs and reorgs
essays published
60
and counting · weekly
explore by intent
understand how I think
The operating thesis behind the essays and decisions.
see what I am tracking
Current bets across engineering, AI, leadership, and narratives.
see what I still ship
Side projects, open source, and proof that the craft stays close.
evaluating me?
The bio, the track record, and the ten essays to judge the thesis by.
Trust the Gate, Not the Actor
agentic-sdlc · engineering-leadership · ai-strategy
The Kill Switch Was Always There
★ai-strategy · engineering-leadership · agentic-sdlc
The Agent Era Gets an Invoice
★engineering-leadership · ai-strategy · ai-economics
The AI Operating Ledger
★engineering-leadership · ai-strategy · agentic-sdlc
Your First AI Reorg Should Be the Work, Not the People
engineering-leadership · ai-strategy · agentic-sdlc
the shortlist
If you only read six posts, start here. These will give you a quick sense of how I think about leadership, platforms, and AI-assisted software delivery.
The thesis behind everything here: the constraint on software delivery has never been the technology. Start with this one.
Where AI-assisted development is actually heading, the orchestration problem most teams miss, and the Context Spine that holds it together.
The operating model in three words: write the spec, hold the standards, deploy the specialists.
Why the spec, not the code, is the durable artifact of AI-assisted development.
The thesis, evolved: once agents can do the work, the quality of the frame you hand them becomes the constraint.
Enterprise AI is entering its accounting phase. Measure verified outcomes, not tokens or generated output.
what i write about
How AI changes engineering workflows, developer experience, governance, and the SDLC — without the hype.
How leaders create clarity, trust, accountability, and teams that actually stay together.
How large organizations build internal platforms, reduce cognitive load, and improve delivery speed.
Lessons from shipping real apps, running frontier models locally, and learning by doing.
// new here?
Whether you lead, build, or just want to understand how I think — there's a way in.