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Google ADK 2.0 workflows tutorial: Building reliable multi-agent systems
This tutorial introduces Google ADK 2.0 workflows for building reliable multi-agent systems, emphasizing a shift from traditional system prompts to intelligent routing mechanisms. The content focuses on practical techniques for orchestrating multiple AI agents effectively, reducing reliance on prompt engineering alone, and implementing structured workflows that ensure consistent agent behavior.
- Move beyond system prompts: Use routing logic instead of relying solely on prompt engineering for agent behavior control
- Implement intelligent routing: Direct tasks to appropriate agents based on context and requirements rather than hoping prompts work
- Multi-agent orchestration: Structure workflows to coordinate multiple specialized agents for complex tasks
- +5 more key points...
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Agent Teams
LangGraph vs CrewAI vs AutoGen: which agent framework, and when
This video compares three major AI agent frameworks—LangGraph, CrewAI, and AutoGen—examining their different architectural philosophies and design decisions for agent runtimes. Each framework makes distinct bets about what an agent system should prioritize, from low-level control to high-level abstractions. The comparison helps developers choose the right framework based on their specific use case, complexity requirements, and team expertise.
GyaanStack
Four Ways to Build an AI Agent: Beginner to Full Control
This guide presents four progressive approaches to building AI agents, ranging from simple bot implementations to complex multi-agent systems. Each method offers different levels of control, customization, and complexity, allowing developers to choose based on their needs and expertise. The progression moves from minimal setup requirements to full architectural control over agent behavior and coordination.
WhatAI
Google Home now lets AI agents control your house
Google has opened Home MCP (Model Context Protocol) in early access, enabling external AI agents such as Claude, Antigravity, Hermes, and OpenClaw to read and control smart home devices. This integration allows AI agents to interact with Google Home ecosystems, expanding automation capabilities beyond Google's native AI. The move represents a significant step toward interoperable AI agent control of IoT devices.
Fragmasoft Solutions
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