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AgentScope AI: A Complete Guide to Building Scalable Multi-Agent Systems with LLMs 

ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Intermediate, LLMs

Modern AI applications rely on intelligent agents that think, cooperate, and execute complex workflows, while single-agent systems struggle with scalability, coordination, and long-term context. AgentScope AI addresses this by offering a modular, extensible framework for building structured multi-agent systems, enabling role assignment, memory control, tool integration, and efficient communication without unnecessary complexity for developers and […]

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What is Clawdbot? How a Local First Agent Stack Turns Chats into Real Automations

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, New Releases, Open Source, Staff, Tech News, Technology

Clawdbot is an open source personal AI assistant that you run on your own hardware. It connects large language models from providers such as Anthropic and OpenAI to real tools such as messaging apps, files, shell, browser and smart home devices, while keeping the orchestration layer under your control. The interesting part is not that

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StepFun AI Introduce Step-DeepResearch: A Cost-Effective Deep Research Agent Model Built Around Atomic Capabilities

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Staff, Tech News, Technology

StepFun has introduced Step-DeepResearch, a 32B parameter end to end deep research agent that aims to turn web search into actual research workflows with long horizon reasoning, tool use and structured reporting. The model is built on Qwen2.5 32B-Base and is trained to act as a single agent that plans, explores sources, verifies evidence and

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How UX Research Methods Reveal Hidden AI Orchestration Failures in Enterprise Collaboration Agents

Advanced, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Clustering, Generative AI Application

I have spent the last several years watching enterprise collaboration tools get smarter. Join a video call today, and there’s a good chance five or six AI agents are running simultaneously: transcription, speaker identification, captions, summarization, task extraction. On the product side of it, each agent gets evaluated in isolation. Separate dashboards, separate metrics. Transcription

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GitHub Releases Copilot-SDK to Embed Its Agentic Runtime in Any App

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, New Releases, Software engineering, Staff

GitHub has opened up the internal agent runtime that powers GitHub Copilot CLI and exposed it as a programmable SDK. The GitHub Copilot-SDK, now in technical preview, lets you embed the same agentic execution loop into any application so the agent can plan, invoke tools, edit files, and run commands as part of your own

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How an AI Agent Chooses What to Do Under Tokens, Latency, and Tool-Call Budget Constraints?

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, Artificial Intelligence, Editors Pick, Technology, Tutorials

In this tutorial, we build a cost-aware planning agent that deliberately balances output quality against real-world constraints such as token usage, latency, and tool-call budgets. We design the agent to generate multiple candidate actions, estimate their expected costs and benefits, and then select an execution plan that maximizes value while staying within strict budgets. With

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Microsoft Releases VibeVoice-ASR: A Unified Speech-to-Text Model Designed to Handle 60-Minute Long-Form Audio in a Single Pass

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Audio Language Model, Editors Pick, Language Model, New Releases, Sound, Staff, Technology, Voice AI

Microsoft has released VibeVoice-ASR as part of the VibeVoice family of open source frontier voice AI models. VibeVoice-ASR is described as a unified speech-to-text model that can handle 60-minute long-form audio in a single pass and output structured transcriptions that encode Who, When, and What, with support for Customized Hotwords. VibeVoice sits in a single

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eBay bans illicit automated shopping amid rapid rise of AI agents

agentic ai, Agentic Commerce, ai, AI (Artificial Intelligence), AI Agents, AI shopping, Amazon, anthropic, Arbitration, Artificial Intelligence, Biz & IT, ChatGPT, eBay, eCommerce, Etsy, Google, Large Language Models, Machine Learning, OpenAI, Perplexity, shopify, user agreements, web scraping

On Tuesday, eBay updated its User Agreement to explicitly ban third-party “buy for me” agents and AI chatbots from interacting with its platform without permission, first spotted by Value Added Resource. On its face, a one-line terms of service update doesn’t seem like major news, but what it implies is more significant: The change reflects

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FlashLabs Researchers Release Chroma 1.0: A 4B Real Time Speech Dialogue Model With Personalized Voice Cloning

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Audio Language Model, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Open Source, Software engineering, Sound, Staff, Tech News, Technology

Chroma 1.0 is a real time speech to speech dialogue model that takes audio as input and returns audio as output while preserving the speaker identity across multi turn conversations. It is presented as the first open source end to end spoken dialogue system that combines low latency interaction with high fidelity personalized voice cloning

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A Coding Guide to Anemoi-Style Semi-Centralized Agentic Systems Using Peer-to-Peer Critic Loops in LangGraph

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we demonstrate how a semi-centralized Anemoi-style multi-agent system works by letting two peer agents negotiate directly without a manager or supervisor. We show how a Drafter and a Critic iteratively refine an output through peer-to-peer feedback, reducing coordination overhead while preserving quality. We implement this pattern end-to-end in Colab using LangGraph, focusing

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