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Caskey Engineering2026 – Present · Founder & Full-Stack Builder

A Fork-Your-Own Life OS an AI Agent Reasons Over, Without Owning Your Data

Designed, built, and shipped a fork-your-own life operating system: principles, vision, goals, areas, and projects as plain markdown an AI agent reasons over, under one rule the agent can read and question every file but never writes the record. A public MIT template plus a static launch site and privacy-by-construction adoption tracking, with the author's own corpus never leaving the machine.

About this artifact

case-studyproductionmaintained

method · automation · since 2026

The Problem

AI agents are good at organizing and connecting information, but handing one your whole life raises a trust problem most "AI life coach" products ignore: the moment something other than you authors your principles, goals, or journal, the record stops being yours.

The core gap is not capability; agents can already read files and ask good questions. It is a missing structure and a missing boundary, a durable, portable, self-owned place to keep the layers of a life with one hard rule about who may write them. A hosted app answers this by taking custody of the most private data a person has; a chatbot answers it by generating plausible insights nobody actually decided. Both give up ownership.

And it had to be shareable without being invasive: a scaffold others could fork and run with their own agent, while the author's content, and every forker's, never left their own machine.

The Approach

Modeled a whole life as a spec'd system: principles, vision, goals, areas, projects, and daily/weekly/monthly journal and review folders, all plain markdown in the user's own git repository, no backend and no account. The structure is committed; the content lives under your-life/, gitignored by default, so the scaffold is corpus-free by construction and forks without carrying anyone's data.

Wrote the operating contract as an agent-neutral AGENTS.md with one non-negotiable rule: the human decides and commits, the agent organizes, connects, surfaces, and challenges, but never silently authors the record. This is the same pattern that runs the finance engine (the math decides, the AI narrates) and the marathon coach (a rules engine owns the call, the LLM explains it), drawn in a third domain.

Layered Claude-Code-native acceleration on top without forking the contract: nine persona subagents (Intake, Journalist, Coach, Skeptic, Therapist, Stoic, Future-Self, Biographer, Forensic-Auditor) that read their lens file at runtime and stay read-only over your-life/, five cadence slash commands (/capture, /daily, /weekly, /review, /coherence-check), and a SessionStart hook that nudges overdue reviews.

Shipped the front door as a static site on S3 + CloudFront + ACM, one landing page and a quick-start, with no third-party scripts and no client analytics.

Made adoption measurable without surveilling anyone: a counted-redirect Lambda behind /r/starter 302-redirects to the template's "Use this template" page and increments a day-bucketed counter with no PII, and a scheduled GitHub-poll Lambda reads forks, stars, and clones from a read-only token.

Gated the publish itself: before the repo went public, an allowlist check confirmed only structure files were tracked (never corpus), a secret scan and a relative-link-escape check ran clean, the internal extraction runbook was stripped, and a sensitive-content audit signed off. The repo was created private and flipped public only after the gate passed.

The Impact

  • A public, MIT-licensed GitHub template (CaskeyCoding/specself-starter), template-enabled, forkable in one click and runnable with any capable agent
  • One operating rule enforced by design: the agent reads and questions every file but authors none of the record, the same decide/narrate boundary that runs the finance and coaching engines
  • Corpus-free by construction: the life content lives in a gitignored your-life/ tree, so the method is fully shareable while a user's substance never leaves their machine and is never seen by the author
  • A live front door at specself.ai (static, no third-party scripts) with privacy-by-construction adoption tracking: a no-PII counted redirect verified end to end, plus a GitHub-native forks/stars/clones poll
  • A Claude-Code-native bundle layered on the agent-neutral contract: nine persona subagents that read their lens at runtime and stay read-only, five cadence commands, and an overdue-review nudge
  • Shown working, not asserted: the author runs it on his own life (foundation complete, principles and journal accumulating, weekly cadence held), shown only in aggregate so the proof never exposes the corpus

Evidence

AI/MLSpec-Driven DevelopmentProductFull-StackAWS

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