Enterprise AI works better when it stays compact and domain-specific
DavidLinthicum · x · 2026-07-20
The author argues that enterprises often over-engineer AI. Instead of deploying huge general-purpose LLMs everywhere, companies should use compact models tailored to each domain and trained on their own data.
The analogy is simple: using a full LLM for every task is like hitting a thumbtack with a sledgehammer. The point is not that large models are useless, but that many business workflows are better served by smaller, specialized systems that are cheaper, more focused, and easier to fit to internal data.
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