AI Workflows: Hope-Flows and Hard Truths
According to Nic Palmer, head of customer architecture for international at Elastic, AI workflows are critical to modern enterprises.
However, they often focus too much on the model layer, and failures usually stem from weak plumbing rather than weak models.
A failure in AI workflow may be a consequence of a ‘hope-flow’.
If a workflow cannot be seen, controlled, or adapted from end-to-end, it cannot be expected to be resilient.
As Nic Palmer notes, when something breaks, you don't want to be stuck running on hope.
Elastic is a company known for its open source platform that powers search, observability, security, and wider functions.
Author's summary: AI workflows rely on robust plumbing.
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