#Google multi-agent platform
387 related articles
·3 min
Practical Guide to Agent Development: The Complete Path from Zero to Commercial Deployment
A systematic guide to AI Agent development from beginner to deployment, covering task planning, tool calling, memory management, learning paths, and realistic commercial monetization considerations.
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·5 min
Learn AI Agent Development from Scratch: A 3-Step Practical Path to Get Started Quickly
How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.
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·3 min
How to Choose an AI Agent Platform for Your Team: 5 Evaluation Dimensions and a Decision Framework
Choose the right AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to help technical leaders avoid vendor lock-in.
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·3 min
How to Choose an AI Agent Platform for Your Team: 5 Evaluation Dimensions & Decision Framework
Choose an AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to avoid vendor lock-in.
Read more →
·3 min
From Frontend to Agent Development: A Complete 6-Week Systematic Learning Path
A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.
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·2 min
Claude as Music Partner: The AGI Moment of AI Paired Creation
A developer added a DAW to their agentic dev environment with Claude, then paired with AI to finish music — experiencing a true AGI moment in creative collaboration.
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·5 min
Will Chinese Open-Source Models Burst the US AI Bubble? A Deep Dive into the Transmission Chain
Chinese open-source models like Kimi K3 and DeepSeek approach US closed-source performance at a fraction of the cost. This deep dive analyzes the transmission chain from price competition to valuation reassessment.
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·4 min
The More Complex the AI Agent, the More It Hallucinates? The Hidden Cost of Architectural Complexity
Why do AI Agents hallucinate more as they grow more complex? This article analyzes the causes from error accumulation, context noise, and model completion nature, with 5 practical production strategies.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·2 min
After Getting Burned by AI Coding for Three Months, I Built WishGraph
After three months of costly AI coding mistakes, a developer built WishGraph: separating discussion and execution into dual windows with parallel multi-agent collaboration to make complex projects manageable again.
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·3 min
The AI Coding Landscape: Model Tiers, Tool Camps, and a Deep Dive into MCP/Skills/CLI
A systematic map of today's AI coding landscape: the evolution from ChatGPT to Claude Code, LLM capability tiers, tool camps like Cursor/Copilot, and the three key weapons of the Agent era — MCP, Skills, and CLI.
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·2 min
Can One Skill Transform All Skills? The Boundary Debate Between Dify Workflows and Agents
A recursive technical proposition: Can we build a "meta-Skill" that auto-transforms any Skill into a Dify workflow? This article dissects the boundary between deterministic orchestration and autonomous Agent decisions.
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·3 min
Pinterest Medic: Engineering an AI Agent for Automated Spark Failure Diagnosis
How Pinterest engineers built Medic for Apache Spark — a multi-agent auto-diagnosis tool — covering the evolution from a single ReAct agent, observability, log denoising, and end-to-end testing.
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·3 min
The Rise of General AI: Breakthroughs in Mathematical Reasoning and Competitive Programming
Frontier AI is going general: costs are dropping, general models are beating specialized ones in math and competitive programming, and multi-agent workflows are maturing fast.
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·4 min
Beyond Vibe Coding: A Complete Guide to Enterprise-Grade AI Engineering
Hit the Vibe Coding ceiling? This guide covers the three-stage AI coding progression path, Claude Code vs. Codex, SuperPower SDD, and how to go from vibe coding to enterprise-grade AI engineering.
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·3 min
Vibe Coding for Beginners: Build Your First Project with AI from Scratch
What is Vibe Coding? Learn this new AI programming paradigm from scratch — no CS degree needed. Use Claude Code, Cursor, and more to build real projects by describing your ideas.
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·8 min
LangChain Crash Course: A Complete Roadmap from Zero to Agent Development
A systematic roadmap from LangChain and LangGraph to multi-agent development, covering RAG, Tool Calling, MCP, and more, helping developers break into AI app development.
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·3 min
Qwen3.8 Deep Dive: How Does a 2.4 Trillion Parameter MoE Model Claim Second Place?
Alibaba's Qwen3.8 challenges larger models with a 2.4T-parameter MoE architecture, claiming second only to Gemini. A deep dive into MoE mechanics, continuous updates, two-speed release strategy, and real local deployment requirements.
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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Topics in the Agent Domain
A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.
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