Join us

ContentUpdates and recent posts about Gemini 3..
 Activity
@codechaintech started using tool Atlassian Bitbucket , 2 weeks, 6 days ago.
Link
@simme shared a link, 3 weeks ago
Senior Engineering Manager, @canonical

Boring code is an organizational tell

Boring code is an organizational symptom, not an aesthetic failure. Co-change patterns in version control reveal team boundaries before any retrospective does; ownership concentration predicts defects better than code complexity metrics. With agents removing the friction that contained clever code accumulation, the incentive structures that produce boring code have never mattered more.

gradients
 Activity
@simme started using tool Ubuntu , 3 weeks ago.
 Activity
@simme started using tool TypeScript , 3 weeks ago.
 Activity
@simme started using tool Python , 3 weeks ago.
 Activity
@simme started using tool PostgreSQL , 3 weeks ago.
 Activity
@simme started using tool lxd , 3 weeks ago.
 Activity
@simme started using tool Kubernetes , 3 weeks ago.
 Activity
@simme started using tool K6 , 3 weeks ago.
 Activity
@simme started using tool Juju , 3 weeks ago.
Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.