The company that forgets

Organizations store enormous amounts of information and still struggle to answer a basic question: why did we decide this? Episode 8 separates search from memory and documents from knowledge. Berk Bayri argues that some of the most valuable organizational context is reasoning — the thesis, evidence, dissent, confidence and constraints behind a decision — and that AI becomes far more useful when it can inspect how a company has thought, not merely retrieve what it has stored. Featuring a Ray Dalio excerpt on converting historical patterns into indicators and explicit decision rules.

References

Anne S. R. Marx, Ricardo M. Avelino, Torbjørn Netland and Mennatallah El-Assady, Do We Have the Knowledge We Need? Rethinking Human-AI Decision-Making in Corporations (2026 position paper). Describes organizational knowledge as fragmented across software systems, tacit expertise and manual documents, and explores how knowledge availability should affect human/AI agency.

Bhada Yun et al., Generative AI in Knowledge Work: Design Implications for Data Navigation and Decision-Making (2025). Study involving knowledge workers and product managers; highlights adaptable user control, transparent collaboration and integration of background knowledge with external information, while noting risks including overreliance and missing context.

NIST, AI Risk Management Framework. Background for provenance, traceability, accountability, lifecycle risk and the need to distinguish authoritative information from model-generated output.