AI Agents

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How to Design Self-Reflective Dual-Agent Governance Systems with Constitutional AI for Secure and Compliant Financial Operations

In this tutorial, we implement a dual-agent governance system that applies Constitutional AI principles to financial operations. We demonstrate how we separate execution and oversight by pairing a Worker Agent that performs financial actions with an Auditor Agent that enforces policy, safety, and compliance. By encoding governance rules directly into a formal constitution and combining […]

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Users flock to open source Moltbot for always-on AI, despite major risks

An open source AI assistant called Moltbot (formerly “Clawdbot”) recently crossed 69,000 stars on GitHub after a month, making it one of the fastest-growing AI projects of 2026. Created by Austrian developer Peter Steinberger, the tool lets users run a personal AI assistant and control it through messaging apps they already use. While some say

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Moonshot AI Releases Kimi K2.5: An Open Source Visual Agentic Intelligence Model with Native Swarm Execution

Moonshot AI has released Kimi K2.5 as an open source visual agentic intelligence model. It combines a large Mixture of Experts language backbone, a native vision encoder, and a parallel multi agent system called Agent Swarm. The model targets coding, multimodal reasoning, and deep web research with strong benchmark results on agentic, vision, and coding

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DSGym Offers a Reusable Container Based Substrate for Building and Benchmarking Data Science Agents

Data science agents should inspect datasets, design workflows, run code, and return verifiable answers, not just autocomplete Pandas code. DSGym, introduced by researchers from Stanford University, Together AI, Duke University, and Harvard University, is a framework that evaluates and trains such agents across more than 1,000 data science challenges with expert curated ground truth and

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How a Haystack-Powered Multi-Agent System Detects Incidents, Investigates Metrics and Logs, and Produces Production-Grade Incident Reviews End-to-End

In this tutorial, we design this implementation to demonstrate how Haystack enables building advanced, agentic AI systems that go far beyond toy examples while remaining fully runnable. We focus on a cohesive, end-to-end setup that highlights orchestration, stateful decision-making, tool execution, and structured control flow, demonstrating how complex agent behavior can be cleanly expressed. We

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

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

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

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

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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