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How to Design a Production-Grade Multi-Agent Communication System Using LangGraph Structured Message Bus, ACP Logging, and Persistent Shared State Architecture

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In this tutorial, we build an advanced multi-agent communication system using a structured message bus architecture powered by LangGraph and Pydantic. We define a strict ACP-style message schema that allows agents to communicate via a shared state rather than calling each other directly, enabling modularity, traceability, and production-grade orchestration. We implement three specialized agents, a […]

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Alibaba Team Open-Sources CoPaw: A High-Performance Personal Agent Workstation for Developers to Scale Multi-Channel AI Workflows and Memory

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As the industry moves from simple Large Language Model (LLM) inference toward autonomous agentic systems, the challenge for devs have shifted. It is no longer just about the model; it is about the environment in which that model operates. A team of researchers from Alibaba released CoPaw, an open-source framework designed to address this by

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A Coding Implementation to Build a Hierarchical Planner AI Agent Using Open-Source LLMs with Tool Execution and Structured Multi-Agent Reasoning

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In this tutorial, we build a hierarchical planner agent using an open-source instruct model. We design a structured multi-agent architecture comprising a planner agent, an executor agent, and an aggregator agent, where each component plays a specialized role in solving complex tasks. We use the planner agent to decompose high-level goals into actionable steps, the

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Sakana AI Introduces Doc-to-LoRA and Text-to-LoRA: Hypernetworks that Instantly Internalize Long Contexts and Adapt LLMs via Zero-Shot Natural Language

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Customizing Large Language Models (LLMs) currently presents a significant engineering trade-off between the flexibility of In-Context Learning (ICL) and the efficiency of Context Distillation (CD) or Supervised Fine-Tuning (SFT). Tokyo-based Sakana AI has proposed a new approach to bypass these constraints through cost amortization. In two of their recent papers, they introduced Text-to-LoRA (T2L) and

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Upgrading agentic AI for finance workflows

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Improving trust in agentic AI for finance workflows remains a major priority for technology leaders today. Over the past two years, enterprises have rushed to put automated agents into real workflows, spanning customer support and back-office operations. These tools excel at retrieving information, yet they often struggle to provide consistent and explainable reasoning during multi-step

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Goldman Sachs and Deutsche Bank test agentic AI for trade surveillance

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Banks are testing a new type of artificial intelligence, like agentic AI, that does more than scan for keywords or follow preset rules. Instead of relying only on static alerts, some trading desks are beginning to use systems designed to reason through patterns in real time and flag conduct that may need human review. Bloomberg

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Perplexity Just Released pplx-embed: New SOTA Qwen3 Bidirectional Embedding Models for Web-Scale Retrieval Tasks

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Perplexity has released pplx-embed, a collection of multilingual embedding models optimized for large-scale retrieval tasks. These models are designed to handle the noise and complexity of web-scale data, providing a production-ready alternative to proprietary embedding APIs. Architectural Innovations: Bidirectional Attention and Diffusion Most Large Language Models (LLMs) utilize causal, decoder-only architectures. However, for embedding tasks,

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Microsoft Research Introduces CORPGEN To Manage Multi Horizon Tasks For Autonomous AI Agents Using Hierarchical Planning and Memory

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Microsoft researchers have introduced CORPGEN, an architecture-agnostic framework designed to manage the complexities of realistic organizational work through autonomous digital employees. While existing benchmarks evaluate AI agents on isolated, single tasks, real-world corporate environments require managing dozens of concurrent, interleaved tasks with complex dependencies. The research team identifies this distinct problem class as Multi-Horizon Task

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