●PRO35 — Gemini 3.5 Pro is reported to target July 17, though the date, context window, and pricing all remain unconfirmed by Google●REBUILD — The model is said to be a ground-up rebuild after the 2.5 Pro architecture was scrapped over structural failures in recursive tool-calling and SVG generation●FLASH35 — Gemini 3.5 Flash is the newest broadly available release, tuned for faster, lower-cost coding, agents, multimodal, and long-document work●SAATHI — ATL Saathi, built on Gemini 3.5 Flash, begins piloting in 100 Indian schools as a 24/7 planning and training assistant for Tinkering Lab educators●SEA — In Southeast Asia, nearly 70% of prompts arrive in native languages — Vietnam 89%, Thailand 87%, Indonesia 84% — and 3 in 4 requests come from mobile●SHEETS — From July 15, AI Expanded Access licenses raise the usage limits for Fill with Gemini and the AI function in Sheets●PRO35 — Gemini 3.5 Pro is reported to target July 17, though the date, context window, and pricing all remain unconfirmed by Google●REBUILD — The model is said to be a ground-up rebuild after the 2.5 Pro architecture was scrapped over structural failures in recursive tool-calling and SVG generation●FLASH35 — Gemini 3.5 Flash is the newest broadly available release, tuned for faster, lower-cost coding, agents, multimodal, and long-document work●SAATHI — ATL Saathi, built on Gemini 3.5 Flash, begins piloting in 100 Indian schools as a 24/7 planning and training assistant for Tinkering Lab educators●SEA — In Southeast Asia, nearly 70% of prompts arrive in native languages — Vietnam 89%, Thailand 87%, Indonesia 84% — and 3 in 4 requests come from mobile●SHEETS — From July 15, AI Expanded Access licenses raise the usage limits for Fill with Gemini and the AI function in Sheets

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Firestore

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Gemini API¹ Logging¹ Data Retention¹ Operations¹ gemini-api¹ vector-search¹ rag¹ embeddings¹ reembedding¹ production¹

⟐ Gemini Dev/2026-07-16Advanced

I stopped storing every generation log — three retention tiers and a prompt fingerprint that keeps traceability

I was storing every Gemini API request and response body for debugging. Here is how I moved to three retention tiers plus a prompt fingerprint, and kept the ability to diagnose issues without keeping the text.

⟐ Gemini Dev/2026-06-15Advanced

When Your Firestore × Gemini Embeddings RAG Quietly Degrades — Designing for Re-Embedding

A RAG built on Firestore native vector search and Gemini Embeddings drifts when the embedding model changes generations, and retrieval quality drops with no errors. Here is how to detect the drift, re-embed without downtime, and keep retrieval cost in check.