AI Agent Success Depends on Context Layer, Not Just Models
Pavan_Belagatti · x · 2026-08-18
Most engineering organizations are approaching AI agents incorrectly by focusing on the agent itself rather than the differentiating context layer behind it. Using the example of deploying a service to production, the post argues that an agent's effectiveness stems from accessing organizational context—such as service ownership, infrastructure topology, policies, historical telemetry, and governance rules—rather than just the model capabilities. The future of software delivery will be defined by who has the most complete context, not who has the most agents.
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