◉GEMINI LABJP
●NANOLITE — Nano Banana 2 Lite is here: Google's fastest and most cost-efficient Gemini Image model, made for running lightweight image generation cheaply●OMNIFLASH — Gemini Omni Flash is in public preview, a natively multimodal model that lets enterprises and developers build custom, dynamic video workflows●AGENTS — Managed Agents expand with background: true for async server-side runs and polling, remote MCP server integration, and refreshing credentials across interactions●MEMORY — The Memory Bank IngestEvents API is generally available, decoupling event ingestion from memory generation so you can stream content continuously●THROUGHPUT — Provisioned Throughput now lets you submit up to seven pending orders for the same model and region●DEPRECATE — Image generation models shut down on August 17, and the Grok 4.1 family on the Gemini Enterprise Agent Platform on August 20●NANOLITE — Nano Banana 2 Lite is here: Google's fastest and most cost-efficient Gemini Image model, made for running lightweight image generation cheaply●OMNIFLASH — Gemini Omni Flash is in public preview, a natively multimodal model that lets enterprises and developers build custom, dynamic video workflows●AGENTS — Managed Agents expand with background: true for async server-side runs and polling, remote MCP server integration, and refreshing credentials across interactions●MEMORY — The Memory Bank IngestEvents API is generally available, decoupling event ingestion from memory generation so you can stream content continuously●THROUGHPUT — Provisioned Throughput now lets you submit up to seven pending orders for the same model and region●DEPRECATE — Image generation models shut down on August 17, and the Grok 4.1 family on the Gemini Enterprise Agent Platform on August 20
TAG

agent-design

3 articles
← Back to all tags
Related:
gemini-api3managed-agents3production3automation2regression-testing1staged-rollout1cost-management1quality-gate1
◈ Gemini API/2026-07-06Advanced

Measure a Managed Agent's Behavior Against Fixed Scenarios Before It Reaches Production

The public-preview Managed Agents run autonomously inside an isolated sandbox, so a small prompt or config change can quietly shift their behavior. Diffing the output once, the way you would for a single prompt, is not enough. Here is how to build a regression harness that runs fixed scenarios repeatedly and judges on pass rate, plus a shadow to canary to full promotion with automatic rollback, all with runnable Python.

◈ Gemini API/2026-06-19Advanced

Your Managed Agents Bill Has a Second Axis: Drawing a Budget Boundary Around Sandbox Runtime

Managed Agents in public preview bills for tokens and for how long its Google-hosted sandbox stays alive. A single hung run quietly drains your budget on that second axis. Here is a working Python design for wall-clock caps, idle teardown, and a concurrency ceiling.

◈ Gemini API/2026-06-16Advanced

Before You Let a Managed Agent Ship: Designing Your Own Acceptance Gate

Let the public-preview Managed Agents generate files and broken artifacts will flow straight into production. Here is how to build a verification gate that artifacts must pass before you accept them, with runnable Python and a rejection-feedback loop.