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Framework Helps Teams Decide Whether to Self-Host AI Coding Tools

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Engineering teams frequently jump from data privacy concerns to deployment decisions without fully accounting for the operational responsibilities that self-hosting entails, including identity management, incident response, and ongoing support. A structured decision scorecard has been proposed to bring rigor to this choice, using MonkeyCode — an AI coding tool with both hosted and private deployment options licensed under AGPL-3.0 — as a reference candidate. The framework first applies binary gate checks across criteria such as data boundary, execution isolation, legal obligations, and recovery procedures, where a single failure disqualifies an option. Surviving options are then scored on a weighted scale covering factors like developer onboarding time, workflow fit, governance, security, and total cost. The goal is not to produce an objective answer but to make disagreements between stakeholders inspectable and grounded in evidence.

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