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Reality Graph

Local-first & data protection

Verifying AI code without shipping source to another cloud: local-first architecture, data boundaries, secrets protection, and what 'local' really covers.

How to use this collection

Use local-first & data protection when you need a bounded answer rather than a generic promise about AI coding. The 6 articles separate observed evidence, working assumptions, product boundaries, and decisions that still belong to a human reviewer. Each guide is dated and keeps its source limitations visible.

Start with “Local AI Code Review” for the broadest entry point, then use “Air-Gapped AI Code Verification” when you need the collection's more specific edge. The cards below state what each article covers, so you can choose by task instead of reading a manufactured sequence. Related links inside each guide connect methods, risks, evidence, and next actions without treating one check as universal proof.

Check each article's publication date, cited source, and stated scope before applying it to a live repository. Examples explain a method; they do not replace your project rules, threat model, tests, or accountable reviewer. If two guides appear to conflict, compare their assumptions and evidence rather than selecting the more confident wording.

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