Familiarity is the enemy: On why Enterprise systems have failed for 60 years
felixbarbalet.com
April 24, 2026
33 min read
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Summary
Enterprise knowledge systems have struggled for sixty years due to issues related to familiarity. A senior executive at a global enterprise indicated that this familiarity was a key reason for not adopting a new AI product.
Key Takeaways
- Enterprise knowledge management systems have failed for over sixty years due to buyers prioritizing familiarity over innovation.
- A senior executive stated that purchasing from a small innovative company is perceived as risky compared to established firms, which are viewed as an "insurance policy."
- The enterprise software industry has incurred over a quarter of a trillion dollars in write-offs and productivity losses due to ineffective knowledge management solutions.
- The technology used to transform information assets is crucial to realizing their value, yet buyers continue to select solutions based on familiarity rather than effectiveness.
Community Sentiment
Positives
- The discussion highlights that LLMs can effectively work with various programming languages, emphasizing the importance of token efficiency and structural regularity over mere familiarity.
- The emphasis on stability and clarity in libraries suggests that well-defined programming environments can significantly enhance AI model performance and reduce token wastage during training.
Concerns
- Concerns are raised about the lack of reliable enterprise software solutions over the past sixty years, indicating a persistent gap in effective AI applications in this domain.
- The sentiment that enterprises prefer established companies for support rather than innovative solutions suggests a stagnation in the adoption of potentially superior AI technologies.
