Notes, working papers, experiment reports, and validation write-ups from the Answer North research program.
Every public numerical claim will be tied to a reproducible report before it ships — which is why the first
entries below are staged, not yet published.
ASTRA-Q · VALIDATION
RESEARCH NOTE 001
Research that argues with itself
Building a quantitative research system designed to preserve the evidence that proves it wrong: preregistered experiments, frozen evaluators, evidence custody, fail-closed authority — and the cycle where the system withdrew its own recommendation to protect a sealed measurement.
PUBLISHED · AUGUST 2026 · ~14 MIN
TLTLL · SYSTEMS
WORKING PAPER
Useful intelligence per token as an optimization target
Token counts are a cost metric, not a value metric. This paper proposes optimizing the ratio of task-relevant reasoning to total compute spent, and describes the compress–route–verify architecture TLTLL uses to pursue it without silent quality loss.
FORTHCOMING — IN PREPARATION
ANSWER NORTH · COMPANY
ESSAY
Why consequential AI requires infrastructure beyond the model
Fluency is not accountability. The case for evidence custody, deterministic execution, verification layers, and governance gates as the missing infrastructure between capable models and consequential decisions.
FORTHCOMING — IN PREPARATION