
What we saw across 500 AI tools in one enterprise
Watching the AI layer showed that tool count was only the surface problem. The larger issue was not knowing which work deserved to become a company default.
Field Note 01 · July 11, 2026
Observed patterns and lessons from enterprise AI adoption in practice.
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Watching the AI layer showed that tool count was only the surface problem. The larger issue was not knowing which work deserved to become a company default.
Field Note 01 · July 11, 2026

Seven teams had independently built versions of the same research workflow. Visibility turned that duplication into a reusable company asset.
Field Note 02 · July 11, 2026

Compression produced meaningful savings on repeated, context-heavy requests. It mattered less when prompts were already short or the model output dominated cost.
Field Note 03 · July 11, 2026