Ai

Gemini Spark is Google's always-on AI agent that runs in the cloud, takes actions across Workspace apps, executes multi-step workflows, and uses permission-based controls.

Explore how Gemini 3.5 Flash enables personalized learning paths and scalable assessments using long context, multimodal inputs, and agentic workflows.

Learn serverless patterns to deploy Gemini 2.5 Flash apps on Google Cloud using Cloud Run and Cloud Functions, plus security, streaming, and cost controls.

Learn how to evaluate Gemini 3.5 Flash outputs using automated tests, grounding, tool validation, and runtime guardrails to reduce hallucinations in production.

Learn how to build a crypto market news summarizer using Gemini 2.5 Flash, with clustering, guardrails, and SSE or WebSocket streaming for real-time updates.

Learn how to build secure AI integrations with Gemini 3.5 Flash by protecting API keys, minimizing data exposure, and safeguarding PII across prompts, tools, and outputs.

Learn cost optimization with Gemini 2.5 Flash using token budgeting, context caching, and latency tiering to reduce output spend and control production costs.

Learn when to use prompting, tools, RAG, or supervised fine-tuning with Gemini 3.5 Flash, plus a decision framework to optimize quality, cost, and consistency.

Learn how to build multimodal apps with Gemini 3.5 Flash using text, images, and PDFs end-to-end, with long context, tools, structured output, and agentic workflows.

Learn how to build agentic workflows with Gemini 3.5 Flash using multi-tool, multi-agent patterns for Web3 monitoring, smart contracts, CI/CD, and incident response.

Learn how to build real-time RAG with Gemini 2.5 Flash, from architecture and vector database choices to chunking strategies, citations, and evaluation metrics.

Learn prompt engineering for Gemini 3.5 Flash with practical patterns for speed, accuracy, structured output, thinking levels, and long-context reliability.