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Gemini Spark is Google's AI workflow assistant powered by Gemini 3.5 Flash, deeply integrated with Google Docs, Gmail, and Workspace apps for cross-app task orchestration and office automation.

Gemini Spark is Google's AI workflow assistant powered by Gemini 3.5 Flash, deeply integrated with Google Docs, Gmail, and other Workspace apps for cross-app task orchestration and boosted productivity.
Industry InsightsPractical strategies for AI product development: why not to train models from scratch, when to use APIs vs. fine-tuning, building product moats, and the full path from evaluation systems to commercialization.
TutorialsA complete methodology for open-source project customization based on real-world experience, detailing the Cursor+Codex dual-IDE workflow, seven-stage process, MVP validation, and AI source code reading techniques.
TutorialsBuild a full-stack blog in 50 minutes using Cursor IDE's multi-Agent mode with Next.js, Clerk auth, and Supabase. Learn the 4-phase AI Agent workflow and key integration pitfalls.
TutorialsCursor engineer Eric shares practical insights on building an AI software factory: automation levels, guardrail design, parallel Agent management, and scaling to 1000+ Agents for 24/7 development.
TutorialsIn-depth comparison of ReAct and CodeAct — two core Agent tool-calling architectures. From paper principles to code implementation, learn the trade-offs between reasoning+action and code execution.
TutorialsA deep dive into Agent Tuning principles and practices, covering why Agent training is needed, the evolution from Prompt to RAG to Agent, development workflows, and cost assessment for private deployment.
TutorialsA complete guide to building a financial analysis Agent system from scratch using Cursor AI and MCP protocol, covering three-layer architecture design, MCP Server development, and production deployment.
TutorialsDeep dive into Function Calling and MCP working principles through Cursor editor's system prompt analysis, comparing regular tools vs MCP tools and testing Agent capabilities across model sizes.
TutorialsRAG (Retrieval-Augmented Generation) is the core solution for LLM hallucination. Learn RAG concepts, how it works, three causes of hallucination, and the complete learning path from basics to Knowledge Graph RAG.
Product ReviewsHands-on comparison of Qoder vs Cursor AI IDEs: Agent autonomy, human interaction count, and architecture decisions. Qoder needed only 2 interactions vs Cursor's 8.
Tech FrontiersGitHub Universe unveils Agent HQ platform for unified coding agent management, Copilot upgrades with multi-model support. OpenAI completes restructuring, Anthropic tests new model, NVIDIA open-sources AI models.
TutorialsComplete guide to deploying Hermes Agent locally, covering WSL2 installation, Git setup, and DeepSeek model integration on Windows to build a self-learning open-source AI Agent.
TutorialsComplete guide to deploying Hermes Agent locally on Windows, covering WSL2 setup, Git configuration, and DeepSeek model integration for a self-learning AI Agent.
TutorialsDeep dive into how AI coding Skills work: from Function Call to MCP to Skills as sub-agents with on-demand loading, implemented via Spring AI Alibaba.
TutorialsDeep dive into how AI coding Skills work technically, from Function Call to MCP to Skills as sub-agents with on-demand loading, implemented via Spring AI Alibaba.
Product ReviewsDeep analysis of Cursor's Cloud Agent demo showing how cloud VMs, automated test artifacts, and a full-chain control plane systematically eliminate human bottlenecks across the software development lifecycle.
Product ReviewsCursor 3.0 evolves from an AI coding assistant into an Agent fleet command center. Explore multi-agent parallelism, Design Mode, and Best-of-N model comparison.
Product ReviewsCursor 3.0 evolves from an AI coding assistant into an Agent fleet command center. Deep dive into multi-agent parallelism, Design Mode, and Best-of-N model comparison.