Systems thinking, applied to engineering in the age of AI and autonomy
- What I would tell a systems engineer five years into their career
The career advice nobody gave me, written for the engineer I was at 28 and now sometimes see across the table.
- Why autonomous vehicles have a harder verification problem than spacecraft
A satellite operates in a bounded environment. An autonomous vehicle operates in an open-ended one. The difference reshapes everything about how you build confidence in the system.
- Executable models close the verification gap that descriptive models never could
A system model that can drive simulation is a different category of artifact than a system model that can only be reviewed.
- Doing systems engineering at startup cadence
The methods that work at Lockheed do not survive contact with a weekly release schedule. The methods that survive are the ones worth keeping anyway.
- The curse of the sheep
Reflections on context, mastery, and systems engineering from INCOSE IS 2026, and why the discipline exists to preserve understanding across time.
- Requirements traceability is a survival skill, not a compliance checkbox
What aerospace gets right about traceability, what autonomous vehicle development is still figuring out, and why the answer changes depending on who is asking the question.
- Your system model belongs in CI, not your document repository
SysML v2 helps, but the harder shift is how systems engineers work when AI handles the typing and git owns the truth.
- Reading Donella Meadows from inside an autonomy company
A book about ecosystems and global resource flows is the most useful thing I have read for autonomy engineering. Why Meadows's leverage points matter more for AV development than additional simulation miles ever will.
- What satellite systems engineering taught me about building autonomous vehicles
Two domains that look nothing alike on the surface, and the MBSE discipline that translates between them.