Insights on AI, human expertise, and how they work together.
Andrej Karpathy's 'LLM Wiki' pattern offers a compelling alternative to retrieval-augmented generation. Instead of re-deriving insights from scratch on every query, AI incrementally builds and maintains a persistent, structured knowledge base. The implications for organisational knowledge management are significant.
AI is widely used to process existing information. Its potential to capture expertise that was never documented in the first place is largely overlooked.
ReadMost AI is designed to optimise tasks. But when it's built without reference to the expertise behind those tasks, it doesn't just fail to capture that knowledge — it can actively erode it.
ReadAround 80% of AI projects fail to deliver business value. We break down the three root causes, including the tacit knowledge problem most teams miss.
ReadIn high-stakes domains, human-AI collaboration consistently outperforms full automation. Here’s why, and how to design for it.
ReadFive essential questions before any AI project, including how to account for the tacit knowledge your experienced people rely on.
ReadWe're happy to talk through how any of this applies to your organisation — no pitch, just a conversation.
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