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knowledge-management
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Pattern Context rot As AI-generated content feeds back into the organisation's context — documents, transcripts, summaries — today's hallucinations become tomorrow's training data, and the quality of the context degrades over time unless the cycle is actively broken. Heuristic Declining AI engineering commits you to content discipline The argument for deferring a custom AI build — pipeline, integration, evaluation harness — because content quality is the real leverage point only holds while someone is actively doing the content work; declining the engineering is a commitment to the discipline, not a free deferral. Pattern Defensibility lives in what AI can't access What survives AI disruption sits in three categories AI cannot access without human participation — privileged client knowledge, trust, and institutional memory. Heuristic A document store is not a knowledge management system Shelving documents in a repository is storage, not knowledge management; the presence of the repository often produces false confidence that the problem is solved. Heuristic Users assume AI has access to information it does not have Users routinely overestimate the information AI has access to, treating it as if it were working from a complete picture; this overestimate compounds with AI fluency to produce misplaced trust. Pattern Knowledge management becomes an M&A and partnership signal As AI pervades professional services, acquirers and partners are likely to treat the target's knowledge management as a due-diligence signal because poor KM implies unreliable AI-assisted work product downstream. Heuristic Start with knowledge management, not tools Audit and structure what the organisation knows before selecting AI tools; the limits of AI output are set by the limits of its input context. Heuristic Make tacit knowledge explicit, or AI cannot use it AI cannot interpret the unwritten assumptions that shape how an organisation actually works; operational self-description is precondition, not polish. Heuristic Structure documents for AI consumption, not just human reading Human-formatted documents obstruct AI consumption; plain-text formats such as Markdown let AI work with the underlying knowledge efficiently. Pattern Surveillance-chilled collaboration degrades knowledge work The collaborative behaviours that produce good knowledge work — thinking aloud, proposing imperfect ideas, showing uncertainty, offering dissent — depend on low-observation conditions that AI-enabled monitoring degrades. Case study A tools-first AI rollout that plateaued An abstracted composite showing what happens when a mid-tier firm buys AI tools without putting its information in order first. Heuristic Useful AI is a context problem The difference between useful AI and dangerous AI is almost entirely about the context it has; output quality is bounded above by input quality.