Most AI memory systems are designed as conveniences inside a product. The Personal Context Repository starts from a different question: what would durable AI context look like if the person, rather than the model provider, owned and governed the record?
A private Markdown and Git repository organized around a short agent boot path, provenance, freshness, privacy tiers, and compiled lookup surfaces. The public artifact is the replicable architecture, not Josiah's personal files.
The aim. Give AI agents durable context while keeping the underlying knowledge inspectable, correctable, and private by design.
01The problem behind the project
General assistants repeatedly lose preferences, project history, and corrected facts. A durable record makes collaboration cumulative while leaving the human able to inspect every important claim.
The answer is a small knowledge infrastructure built from ordinary files. Human-readable Markdown keeps claims inspectable; Git makes changes reviewable; provenance and freshness distinguish remembered facts from stale or uncertain ones; and privacy tiers prevent convenience from becoming indiscriminate exposure.
People who work repeatedly with AI agents may benefit. The subject of the context is also the person most at risk, so privacy, consent, and correction must remain first-class.
02How it took shape
Human-readable Markdown, version history, an llms.txt entry map, explicit privacy boundaries, source and freshness metadata, generated lookup surfaces, and agent instructions for asking corrective questions.
Agents enter through a compact llms.txt map and load information progressively instead of ingesting the repository wholesale. Compiled lookup surfaces accelerate routine work, while bidirectional question-asking gives an agent a way to notice gaps and ask the human to correct drift.
Josiah developed the architecture through sustained personal use, including the idea that downstream utility encourages honest input and that agents should ask questions to repair context drift.
The private system is used as working infrastructure across projects. This Compendium's paired human and /llm routes are one public application of the same architecture.
03What the project means now
Its effectiveness comes from a feedback loop. Because stored context will influence future help, the human has a reason to keep it accurate, and because the files remain visible, corrections can become durable rather than disappearing inside a conversation. The public article describes that pattern without exposing the private record that proved it.
The private repository, personal examples, psychological context, credentials, and third-party information are never publication material. Public examples must be synthetic.
Context is most valuable when it is a maintained knowledge system, not an indiscriminate transcript archive.
Publish a complete, synthetic replication guide that another person can safely point an agent at and adapt.