# PKM-to-AI Readiness A readiness assessment for whether your [[Personal Knowledge Management (PKM)]] system is ready to be used as AI context. Most knowledge bases are not AI-ready. They were built for human browsing, not machine consumption. This creates a gap between "I have notes" and "my AI can use my notes." Seven dimensions, each with levels from "not ready" to "fully AI-ready": 1. **Structure**: Is it organized into consistent folders and categories? Flat dumps of files are hard for AI to navigate. A clear hierarchy ([[Knowledge Management (KM)]]) makes context selection possible. 2. **Metadata**: Are notes tagged, dated, and typed? Frontmatter properties enable filtering. Without metadata, you cannot selectively load relevant context. 3. **Linking**: Are notes wikilinked and cross-referenced? Links create a traversable graph. AI can follow connections to gather related context automatically. 4. **Currency**: Is it up to date? Stale notes produce stale AI output. [[Context Hygiene]] requires active maintenance. 5. **Completeness**: Are gaps identified? Knowing what is missing is as important as knowing what is present. Gaps in knowledge become blind spots in AI output. 6. **Format**: Is it AI-readable markdown? Clean markdown with consistent formatting is easier to parse than PDFs, images, or proprietary formats. 7. **Atomicity**: One idea per note? Atomic notes can be composed into precisely targeted context. Monolithic documents force loading irrelevant content, wasting the [[Context Budget]]. Each dimension compounds. A well-structured, well-tagged, well-linked, current, complete, clean, atomic vault is exponentially more useful to AI than one that scores well on only a few dimensions. [[Personal Context Management (PCM)]] is the practice of maintaining readiness. [[Context Engineering]] is the skill of loading it effectively. [[Levels of AI Context Management]] describes the maturity curve. ## References ## Related - [[Personal Knowledge Management (PKM)]] - [[Personal Context Management (PCM)]] - [[Context Engineering]] - [[Levels of AI Context Management]] - [[Context Hygiene]] - [[Knowledge Management (KM)]]