TL;DR — Governability via explicit identity, authority, and traceability. ICE is the proof surface.
Proof — If a system acts, I can reconstruct the why through declared authority + durable state (no inference, no guesswork).
Most architectural failures today are not caused by missing features, but by unclear responsibility: implicit decisions, opaque transitions, and no reliable way to explain why something happened.
I work by making those boundaries explicit.
Systems are defined from observable behavior backward: what happens is visible first; what is allowed to happen is constrained next. Everything else is implementation detail.
I favor execution paths that are boring, inspectable, and reconstructible. If a system acts, I expect to trace that action through declared authority and durable state — without inference or guesswork.
Python is the medium I use to express this discipline: explicit control flow, lifecycle phases, and state transitions. I avoid agent frameworks and implicit schedulers; they trade convenience for opacity.
Tip
Models suggest. Code authorizes. State changes only by rule.
Persistence is treated as part of system semantics. SQLite / SQL and DuckDB anchor execution in durable state and make post-hoc reasoning possible.
Semantic indexing (sentence-transformers + FAISS / Chroma) may inform decisions, but never drive control flow.
LLMs are constrained strictly to inference. They produce proposals — never actions.
Important
ICE is where this approach is exercised — against real code, real state, and real failure modes.
This work is long-term, structural, and research-driven.
Support sustains continuity, not direction.
