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Tag: agent

  • Empirical Cumulative Distribution Function Clustering for LLM-based Agent System Analysis

    Empirical Cumulative Distribution Function Clustering for LLM-based Agent System Analysis arXiv:2602.16131v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as agents to solve complex tasks such as question answering (QA), scientific debate, and software development. A standard evaluation procedure aggregates multiple responses from LLM agents into a single final answer, often via…

  • Building a LangGraph Agent from Scratch

    Building a LangGraph Agent from Scratch Everything you need to know to get started The post Building a LangGraph Agent from Scratch appeared first on Towards Data Science. Vyacheslav Efimov Go to original source

  • Why Your Multi-Agent System is Failing: Escaping the 17x Error Trap of the “Bag of Agents”

    Why Your Multi-Agent System is Failing: Escaping the 17x Error Trap of the “Bag of Agents” Hard-won lessons on how to scale agentic systems without scaling the chaos, including a taxonomy of core agent types. The post Why Your Multi-Agent System is Failing: Escaping the 17x Error Trap of the “Bag of Agents” appeared first…

  • Microeconomic Foundations of Multi-Agent Learning

    Microeconomic Foundations of Multi-Agent Learning arXiv:2601.03451v1 Announce Type: new Abstract: Modern AI systems increasingly operate inside markets and institutions where data, behavior, and incentives are endogenous. This paper develops an economic foundation for multi-agent learning by studying a principal-agent interaction in a Markov decision process with strategic externalities, where both the principal and the agent…

  • Production-Ready LLMs Made Simple with the NeMo Agent Toolkit

    Production-Ready LLMs Made Simple with the NeMo Agent Toolkit From simple chat to multi-agent reasoning and real-time REST APIs The post Production-Ready LLMs Made Simple with the NeMo Agent Toolkit appeared first on Towards Data Science. Mariya Mansurova Go to original source

  • How Agent Handoffs Work in Multi-Agent Systems

    How Agent Handoffs Work in Multi-Agent Systems Understanding how LLM agents transfer control to each other in a multi-agent system with LangGraph The post How Agent Handoffs Work in Multi-Agent Systems appeared first on Towards Data Science. Kenneth Leung Go to original source

  • Multi-Agent Arena: Insights from London Great Agent Hack 2025

    Multi-Agent Arena: Insights from London Great Agent Hack 2025 What mattered: robust agents, glass-box reasoning, and red-team resilience The post Multi-Agent Arena: Insights from London Great Agent Hack 2025 appeared first on Towards Data Science. Erika G. Gonçalves Go to original source

  • Multi-Agent SQL Assistant, Part 2: Building a RAG Manager

    Multi-Agent SQL Assistant, Part 2: Building a RAG Manager A hands-on guide to comparing multiple RAG strategies — Keyword, FAISS, and Chroma The post Multi-Agent SQL Assistant, Part 2: Building a RAG Manager appeared first on Towards Data Science. Alle Sravani Go to original source

  • Deploy an OpenAI Agent Builder Chatbot to a Website

    Deploy an OpenAI Agent Builder Chatbot to a Website Using OpenAI’s Agent Builder ChatKit The post Deploy an OpenAI Agent Builder Chatbot to a Website appeared first on Towards Data Science. Thomas Reid Go to original source

  • How to Build An AI Agent with Function Calling and GPT-5

    How to Build An AI Agent with Function Calling and GPT-5 How an AI agent works: a step-by-step guide The post How to Build An AI Agent with Function Calling and GPT-5 appeared first on Towards Data Science. Ayoola Olafenwa Go to original source

  • LangGraph 201: Adding Human Oversight to Your Deep Research Agent

    LangGraph 201: Adding Human Oversight to Your Deep Research Agent Losing control of your AI agent in the middle of the workflow is a common pain point. If you have built your own agentic applications, you’ve most likely already seen this happen. While LLMs nowadays are incredibly capable, they’re still not quite there yet to…

  • Talk to my Agent 

    Talk to my Agent  The exciting new world of designing conversation driven APIs for LLMs. The post Talk to my Agent  appeared first on Towards Data Science. Roni Dover Go to original source

  • GraphRAG in Action: A Simple Agent for Know-Your-Customer Investigations

    GraphRAG in Action: A Simple Agent for Know-Your-Customer Investigations This blog post provides a hands-on guide for AI engineers and developers on how to build an initial KYC agent prototype with the OpenAI Agents SDK. We’ll explore how to equip our agent with a suite of tools (including MCP Server tools) to uncover and investigate potential…

  • Build Multi-Agent Apps with OpenAI’s Agent SDK

    Build Multi-Agent Apps with OpenAI’s Agent SDK Creating multi-agent apps is simple with this open-source SDK, and it can be used with any OpenAI-compatible LLM The post Build Multi-Agent Apps with OpenAI’s Agent SDK appeared first on Towards Data Science. Alan Jones Go to original source

  • Agentic AI 103: Building Multi-Agent Teams

    Agentic AI 103: Building Multi-Agent Teams Build multi-agent teams that can automate tasks and enhance productivity. The post Agentic AI 103: Building Multi-Agent Teams appeared first on Towards Data Science. Gustavo Santos Go to original source

  • GAIA: The LLM Agent Benchmark Everyone’s Talking About

    GAIA: The LLM Agent Benchmark Everyone’s Talking About What practitioners need to know about this LLM agent benchmark The post GAIA: The LLM Agent Benchmark Everyone’s Talking About appeared first on Towards Data Science. Shuai Guo Go to original source

  • Multi-Agent Communication with the A2A Python SDK

    Multi-Agent Communication with the A2A Python SDK The Agent Card helps discover agents, but how does communication between agents actually work in practice? The post Multi-Agent Communication with the A2A Python SDK appeared first on Towards Data Science. Deborah Mesquita Go to original source

  • How Not to Write an MCP Server

    How Not to Write an MCP Server I recently had the chance to create an MCP server for an observability application in order to provide the AI agent with dynamic code analysis capabilities. Because of its potential to transform applications, MCP is a technology I’m even more ecstatic about than I originally was about genAI…

  • AI Agents from Zero to Hero — Part 3

    AI Agents from Zero to Hero — Part 3 Intro In Part 1 of this tutorial series, we introduced AI Agents, autonomous programs that perform tasks, make decisions, and communicate with others.  In Part 2 of this tutorial series, we understood how to make the Agent try and retry until the task is completed through…

  • Google’s Data Science Agent: Can It Really Do Your Job?

    Google’s Data Science Agent: Can It Really Do Your Job? On March 3rd, Google officially rolled out its Data Science Agent to most Colab users for free. This is not something brand new — it was first announced in December last year, but it is now integrated into Colab and made widely accessible. Google says…

  • Probabilistic Shielding for Safe Reinforcement Learning

    Probabilistic Shielding for Safe Reinforcement Learning arXiv:2503.07671v1 Announce Type: new Abstract: In real-life scenarios, a Reinforcement Learning (RL) agent aiming to maximise their reward, must often also behave in a safe manner, including at training time. Thus, much attention in recent years has been given to Safe RL, where an agent aims to learn an…

  • Supercharge Your RAG with Multi-Agent Self-RAG

    Supercharge Your RAG with Multi-Agent Self-RAG Introduction Many of us might have tried to build a RAG application and noticed it falls significantly short of addressing real-life needs. Why is that? It’s because many real-world problems require multiple steps of information retrieval and reasoning. We need our agent to perform those as humans normally do,…

  • Improving Agent Systems & AI Reasoning

    Improving Agent Systems & AI Reasoning DeepSeek-R1, OpenAI o1 & o3, Test-Time Compute Scaling, Model Post-Training and the Transition to Reasoning Language Models (RLMs) Image by author and GPT-4o meant to represent DeepSeek and other competitive GenAI model providers Introduction Over the past year generative AI adoption and AI Agent development have skyrocketed. Reports from LangChain…

  • On a Time Crunch but Still Want to Learn to Develop Multi-Agent AI?

    On a Time Crunch but Still Want to Learn to Develop Multi-Agent AI? These 3 starter projects only take a weekend (and a few cups of coffee, maybe) Continue reading on Towards Data Science » Thuwarakesh Murallie Go to original source

  • How to Build an AI Agent for Data Analytics Without Writing SQL

    How to Build an AI Agent for Data Analytics Without Writing SQL Create a comprehensive AI agent from the ground up utilizing LangChain and DuckDB Continue reading on Towards Data Science » Chengzhi Zhao Go to original source

  • LangChain Meets Home Assistant: Unlock the Power of Generative AI in Your Smart Home

    LangChain Meets Home Assistant: Unlock the Power of Generative AI in Your Smart Home Learn how to create an agent that understands your home’s context, learns your preferences, and interacts with you and your home to accomplish activities you find valuable. Photo by Igor Omilaev on Unsplash Introduction This article describes the architecture and design of…

  • Creating a WhatsApp AI Agent with GPT-4o

    Creating a WhatsApp AI Agent with GPT-4o Created with DALL-E How to use the Meta API to build your own LLM-powered Whatsapp chatbot A game-changer in the field of AI and business management is the integration of AI agents with widely used communication tools. Think of having a familiar chat interface with real-time data requests, updates, and…

  • The Anatomy of an Autonomous Agent

    The Anatomy of an Autonomous Agent A blueprint for autonomous agents in an Agentic Mesh ecosystem. Continue reading on Towards Data Science » Eric Broda Go to original source

  • How to Build a General-Purpose LLM Agent

    How to Build a General-Purpose LLM Agent A Step-by-Step Guide High-level Overview of an LLM Agent. (Image by author) Why build a general-purpose agent? Because it’s an excellent tool to prototype your use cases and lays the groundwork for designing your own custom agentic architecture. Before we dive in, let’s quickly introduce LLM agents. Feel free…