Engineering Context — Page 2

Hidden infrastructure and staffing costs often dwarf the sticker price of code search tools.

Global teams must align code storage with shifting residency laws or face billion-dollar fines.

Model choice has become a compliance requirement, not just a feature preference.

AI agents need enterprise-wide code context to avoid costly mistakes across teams and repositories.

Self-hosted AI coding tools need Docker and structured code graphs to stay secure.

Regulators now demand source code stay inside company networks, forcing a reckoning.

Simplifying deployment to run code search anywhere without infrastructure overhead.

Three variables—compliance, cost, and operational capacity—determine which architecture fits.

How to size infrastructure for self-hosted code search without undersizing a critical layer.

Modern AI coding needs live organizational data, not just code in memory.

Agents hallucinate fixes and duplicate code when they can't see the entire system they're changing.