By:
Mark Johnson
Mark is a Senior Infrastructure Engineer at Caylex
Photography:
Jason Liu
2025-09-21T16:24:32.404Z
Updated: 2025-09-21T16:24:27.905Z
By:
Mark Johnson
Mark is a Senior Infrastructure Engineer at Caylex
Photography:
Jason Liu
2025-09-21T16:24:32.404Z
Updated: 2025-09-21T16:24:27.905Z
Why Context Sharing Matters in AI
Most AI pipelines lose vital context between steps — degrading performance. We explain how shared context infrastructure can dramatically improve system coherence and output quality.
Context is the lifeblood of effective AI systems. Without access to relevant context, even the most sophisticated models produce generic, irrelevant, or contradictory outputs.
Many AI implementations suffer from context fragmentation — where vital information is lost between processing steps. This article explores why context sharing matters and how to implement effective context management in production AI systems.
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