Papers
Independent conceptual AI research on language agents: memory, perspective, functional individuation, self-models, accountability, and continuity across successor models. Across six papers, I ask how generic capability becomes, or fails to become, persistent, differentiated agency. The program examines variables that scaling alone does not specify: how experience is ordered, how authenticated history affects later decisions, when external accountability or relational reciprocity matters, and what should pass from one model generation to the next.
Each paper advances a causal hypothesis precise enough to be wrong, identifies the strongest ordinary engineering alternative, and outlines an experiment that could distinguish them. Together, the papers form a connected research program whose individual interventions and stronger developmental-order hypothesis can succeed or fail separately. We Scaled the Ape and Expected the Human explains how A Jornada da Mônada generated the conceptual map; How I Would Try to Break the Map lays out the sequence of experiments that could narrow, revise, or overturn it.

Published
Known, Not Scaled: Why Capability Alone Does Not Explain Individuation in Language Agents
Making an AI more capable does not by itself create a continuous individual; this paper tests whether authenticated history and external accountability are sufficient for functional continuity, and whether a persistent reciprocal relationship adds anything beyond them.
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Published
Stable Before Selfless: Why Deference in Language Agents May Require Functional Self-Models
An AI with no stable commitments may become easy to push around rather than safely deferential; this paper tests whether commitments-first training helps, and whether the benefit comes from a self-model, training order, or a matched provenance-aware policy.
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Published
Formed, Not Stored: Testing Relational Identity Formation in Long-Horizon Language Agents
Saving an AI's memories is not the same as forming a functional identity; this paper tests whether active external accountability makes prior commitments matter, and whether a reciprocal counterpart adds anything beyond a matched impersonal auditor.
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Published
Somewhere, Not Nowhere: First-Person Register, Epistemic Limitation, and Perspective Formation in Language Models
First-person voice and limited knowledge are often confounded. This paper separates them in a controlled 2×2 experiment to test whether voice, epistemic limitation, or their interaction produces perspective skills that transfer beyond narrative prose.
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Published
Inherited, Not Remembered: Lifecycle Consolidation for Successor Language Agents
When one AI model replaces another, the key question is not only what it remembers but what it can inherit with evidence. This paper tests whether lifecycle consolidation transfers a deployment-learned rule with auditable lineage while rejecting decoys and source episodes.
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Published
Borrowed, Not Believed: Developmental Models of Individuation as Heuristic Engines for Machine Learning
This paper treats a pre-scientific developmental schema as a disclosed source of testable machine-learning hypotheses, separating six independent interventions from a stronger dependency order that must survive matched baselines and prospective preregistration.
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