Jeremiah Henning
Technologist & MBA Candidate — AI Infrastructure, Accounting & Finance
I spent twenty years in technology, from the ground up through senior leadership. Now I'm an MBA candidate focused on accounting and finance — and I still build, in the open. Labs is where I document that other half: self-hosted inference, agent architecture, and the unglamorous work of keeping AI systems running. The drive is the same on both sides — build the thing to understand the thing. That pairing turns out to be pretty rare.
Currently building
Two abandoned games and the one-shot prompt
A year of agentic coding finished two games I had abandoned, in one prompt each. The implementation problem was solved. The part the model could not finish was whether the games were any good.
Previous chapter
Leadership
Led technology at a small company where “technology” touched everything: software, infrastructure, manufacturing, marketing systems, sales pipeline, order processing. Small team count, large blast radius.
Transformation
Inherited platforms that had accumulated years of deferred decisions. Modernized them under real operational pressure, simplified what could be simplified, and built what didn't exist yet.
Security & resilience
Worked through real incidents — the kind of cases that clarify what your architecture actually is versus what you thought it was. Hardened what remained.
Education
BS Information Technology (Summa Cum Laude) + BS Business & Professional Leadership. MBA in progress, started May 2026, expected 2027.
How I think
- Start with the model. Before an opinion, understand the structure — the mechanism that explains why a number is what it is, not just what it might say.
- Prefer artifacts over opinions. Notes, spreadsheets, and small tools beat vague takes and guesswork.
- Optimize for clarity. If something can't be explained simply, it's not understood well enough yet.
- Learn by building. I build small simulations and bridges to internalize concepts before the coursework formally covers them.
What I'm building to learn
Full update on the Now page →MBA learning tools
CMO Desk
An interactive Streamlit app for learning Segmentation, Targeting, and Positioning within a full 5C situation analysis. Users work through 15 business scenarios, make STP decisions, and study with 51 flashcards.
Read the write-up →SWOT Check
A Streamlit app for practicing SWOT analysis and TOWS strategic pairing. Includes basic categorization mode and an advanced mode for building actionable strategies from internal and external factors.
Read the write-up →LBO Value Bridge
A Python/Streamlit model for working ahead of leveraged-buyout mechanics — mapping how debt, equity, and operational improvements combine to create value.
Read the write-up →Accounting Simulator
A dual-perspective accounting simulator built to internalize financial and managerial accounting concepts before the coursework formally covers them.
Read the write-up →Labs
Two abandoned games and the one-shot prompt
A year of agentic coding finished two games I had abandoned, in one prompt each. The implementation problem was solved. The part the model could not finish was whether the games were any good.
What Round 3 actually proved
Two weeks, two characters, eleven proposals, two moves — and nothing spent. What the shared world actually did when Round 3 finally ran clean, and why the result was a refusal.
You first. No, you first.
A week of perfectly green machinery, a world that refused to move, a model that couldn't commit, and the decision that ended the testing: Round 3 starts now.