Google Gemini is a multimodal AI model used for code generation, SQL synthesis, and analytical tasks. Posts cover Gemini-powered BigQuery SQL generation, model integration patterns, and the practical considerations of using Gemini in production FinOps tooling.
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We built a small Go + Python service that parses a project's INFORMATION_SCHEMA, asks Gemini to classify each top-spending query against a catalog of anti-patterns, and recommends a rewrite. It is not a magic box; it is a pipeline that cuts the human review time per query from 20 minutes to 90 seconds.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.