Most engineers default to cloud AI without questioning the cost, the privacy trade-offs, or the dependency it creates — and the token bill grows with usage. How one freelancer moved an AI-assisted development workflow from 100% cloud to 90% local: the hardware, the models that actually perform, the honest downsides, and where cloud still wins.
Everyone uses AI to improve their organization, but without care you drain your budget, increase energy usage, or create risks you never intended. Do you keep a leash on your AI? Practical governance and sustainability for your AI landscape with Azure API Management and Azure AI Foundry: content filtering, token-aware throttling, and caching.
