Library

A DMM-inspired relationship analysis app for turning conflict material into structured relational hypotheses.

A training operating system for planning, logging, and reviewing physical development with less noise.

A nutrition logging app for practical food awareness, lightweight planning, and personal pattern review.

A local design system playground that stores UI principles, component grammar, and product translation rules.

A personal agent dashboard concept for coordinating goals, AI workflows, tasks, and decision context.

A critique of turning nervous system language into a simplified moral story.

On the difference between symptoms, context, adaptation, and ordinary pain.

How adult-sounding therapeutic language can sometimes hide immature relational moves.

A grounded argument against treating boundaries as optimized distance.

A Social Baseline Theory influenced note on dependence, effort, and shared regulation.

Product notes on making a psychology-informed relationship analysis app.

A practical note on using agents while keeping direction, judgment, and ownership.

A developmental attachment model focused on self-protective strategies, danger, information processing, and adaptation.

A theory of human regulation that treats social proximity and shared load as baseline conditions rather than optional extras.

A nervous-system framework worth handling carefully, especially when translating it into public psychology language.

Patterns of self-protection and connection that can be understood as adaptive responses to developmental and relational context.

The ongoing interpersonal regulation of emotion, attention, effort, and safety through embodied and relational cues.

A product and personal operating concept: fewer unresolved loops, cleaner criteria, and visible next moves.

A practical lens for how environments, people, and interfaces reduce or increase perceived threat and effort.

A product stance where the app is useful immediately, private by default, and only later enhanced by sync or accounts.

A working practice for using AI to increase throughput while preserving product taste, verification, and ownership.

Started shaping the relationship analysis product surface and the underlying DMM-inspired reasoning direction.

Clarified the need for structured hypotheses, evidence handling, risk language, and careful uncertainty.

Created the direction for a training operating system focused on planning, logging, and review.

Built a nutrition logging product direction around simple capture and non-punitive review.

Defined a calm local-first interface language for future personal products.

Began consolidating a personal development plan across software, business thinking, mathematics, and AI workflows.