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Reviewed by Muthu · Essay · Last verified Oct 18, 2026 · Drafted Oct 17, 2026 by seed-import/1.0 · Re-check by Oct 17, 2027 · 1 source
Overview
Enterprises budget for compute, models and licenses, but almost none budget for the context those models depend on. Unmanaged context is the largest cost nobody tracks, and every new AI agent adds to it.1
What it covers
- The cost we already pay
- Why AI multiplies it
- Four hidden line items
- A familiar night
- Why this is a leadership problem
- What stays yours when the models change
- What managed context looks like
- Start by measuring it
Bottom line
Context is the asset AI runs on, and most enterprises leave it unmanaged. Build it once, govern it once, and let every model you adopt reuse it. The rest of this series covers how.
Sources
- The cost of unmanaged context · published Jun 2, 2026
See also
- Context fragmentation: why your agents keep starting from zero - The knowledge an agent needs is scattered across code, tickets, chat, wikis, incident tools and people’s heads. Each fragment is accurate and useless alone. Fragmentation, more than model quality, is what makes enterprise agents brittle.
- Capture the why: the knowledge layer enterprise agents are missing - Most enterprise AI pilots hit the same wall: systems record what happened, but the reasoning behind decisions evaporates. Durable, governed context about the why is the real foundation for useful agents.
- Self-describing knowledge: why the Open Knowledge Format matters, and what enterprises must add - In June, Google Cloud published the Open Knowledge Format, and July’s v0.2 added provenance, verification and freshness. It is the right foundation. Regulated enterprises still need to add ownership, classification and a policy for how much trust an agent needs before it acts.
Footnotes
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The cost of unmanaged context, muthub.org, 2026-06-02. ↩