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Category: agentic-ai

  • How AI Agents “Talk” to Each Other

    How AI Agents “Talk” to Each Other Minimize chaos and maintain inter-agent harmony in your projects The post How AI Agents “Talk” to Each Other appeared first on Towards Data Science. TDS Editors 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

  • Model Context Protocol (MCP) Tutorial: Build Your First MCP Server in 6 Steps

    Model Context Protocol (MCP) Tutorial: Build Your First MCP Server in 6 Steps A beginner-friendly tutorial of MCP architecture, with the focus on MCP server components and applications, guiding through the process of building a custom MCP server that enables code-to-diagram. The post Model Context Protocol (MCP) Tutorial: Build Your First MCP Server in 6…

  • Inside Google’s Agent2Agent (A2A) Protocol: Teaching AI Agents to Talk to Each Other

    Inside Google’s Agent2Agent (A2A) Protocol: Teaching AI Agents to Talk to Each Other Exploring how Google’s A2A enables plug-and-play communication between LLM-powered agents across frameworks The post Inside Google’s Agent2Agent (A2A) Protocol: Teaching AI Agents to Talk to Each Other appeared first on Towards Data Science. Hailey Quach Go to original source

  • Agentic RAG Applications: Company Knowledge Slack Agents

    Agentic RAG Applications: Company Knowledge Slack Agents Lessons learnt using LlamaIndex and Modal The post Agentic RAG Applications: Company Knowledge Slack Agents appeared first on Towards Data Science. Ida Silfverskiöld 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

  • Code Agents: The Future of Agentic AI

    Code Agents: The Future of Agentic AI HuggingFace smolagents framework in action The post Code Agents: The Future of Agentic AI appeared first on Towards Data Science. Mariya Mansurova Go to original source

  • Google’s AlphaEvolve: Getting Started with Evolutionary Coding Agents

    Google’s AlphaEvolve: Getting Started with Evolutionary Coding Agents Introduction AlphaEvolve [1] is a promising new coding agent by Google’s DeepMind. Let’s look at what it is and why it is generating hype. Much of the Google paper is on the claim that AlphaEvolve is facilitating novel research through its ability to improve code until it solves…

  • Agentic AI 102: Guardrails and Agent Evaluation

    Agentic AI 102: Guardrails and Agent Evaluation Introduction In the first post of this series (Agentic AI 101: Starting Your Journey Building AI Agents), we talked about the fundamentals of creating AI Agents and introduced concepts like reasoning, memory, and tools. Of course, that first post touched only the surface of this new area of…

  • ACP: The Internet Protocol for AI Agents

    ACP: The Internet Protocol for AI Agents With ACP (Agent Communication Protocol), AI agents can collaborate freely across teams, frameworks, technologies, and organizations. It’s a universal protocol that transforms the fragmented landscape of today’s AI Agents into inter-connected team mates. This unlocks new levels of interoperability, reuse, and scale. As an open-source standard with open…

  • Generating Data Dictionary for Excel Files Using OpenPyxl and AI Agents

    Generating Data Dictionary for Excel Files Using OpenPyxl and AI Agents Introduction Every company I worked for until today, there it was: the resilient MS Excel. Excel was first released in 1985 and has remained strong until today. It has survived the rise of relational databases, the evolution of many programming languages, the Internet with…

  • Think. Know. Act. How AI’s Core Capabilities Will Shape the Future of Work

    Think. Know. Act. How AI’s Core Capabilities Will Shape the Future of Work “It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change.” – Charles Darwin, Originator of Evolutionary Theory Not long ago, I came across an article about a CEO, who was visibly…

  • Attaining LLM Certainty with AI Decision Circuits

    Attaining LLM Certainty with AI Decision Circuits The promise of AI agents has taken the world by storm. Agents can interact with the world around them, write articles (not this one though), take actions on your behalf, and generally make the difficult part of automating any task easy and approachable.  Agents take aim at the most…

  • Agentic AI 101: Starting Your Journey Building AI Agents

    Agentic AI 101: Starting Your Journey Building AI Agents Introduction The Artificial Intelligence industry is moving fast. It is impressive and many times overwhelming. I have been studying, learning, and building my foundations in this area of Data Science because I believe that the future of Data Science is strongly correlated with the development of…

  • A Farewell to APMs — The Future of Observability is MCP tools

    A Farewell to APMs — The Future of Observability is MCP tools Image generated using Midjourney The past years have been an absolute rollercoaster (or joyride) of rapidly evolving generative AI technologies. In the twenty-five years I’ve counted myself a software developer, I cannot recall a tectonic shift of a similar magnitude, one that is already fundamentally changing…

  • AI Agents Processing Time Series and Large Dataframes

    AI Agents Processing Time Series and Large Dataframes Intro Agents are AI systems, powered by LLMs, that can reason about their objectives and take actions to achieve a final goal. They are designed not just to respond to queries, but to orchestrate a sequence of operations, including processing data (i.e. dataframes and time series). This…

  • Deb8flow: Orchestrating Autonomous AI Debates with LangGraph and GPT-4o

    Deb8flow: Orchestrating Autonomous AI Debates with LangGraph and GPT-4o Introduction I’ve always been fascinated by debates—the strategic framing, the sharp retorts, and the carefully timed comebacks. Debates aren’t just entertaining; they’re structured battles of ideas, driven by logic and evidence. Recently, I started wondering: could we replicate that dynamic using AI agents—having them debate each…

  • Creating an AI Agent to Write Blog Posts with CrewAI

    Creating an AI Agent to Write Blog Posts with CrewAI Introduction I love writing. You may notice that if you follow me or my blog. For that reason, I am constantly producing new content and talking about Data Science and Artificial Intelligence. I discovered this passion a couple of years ago when I was just…

  • Agentic AI: Single vs Multi-Agent Systems

    Agentic AI: Single vs Multi-Agent Systems We’ve seen this shift the last few years from building rigid programming systems to natural language-driven workflows, all made possible with more advanced large language models. One of the interesting areas into these Agentic Ai systems is the difference between building a single versus multi-agent workflow, or perhaps the…

  • 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…

  • AI Agents from Zero to Hero — Part 2

    AI Agents from Zero to Hero — Part 2 Intro In Part 1 of this tutorial series, we introduced AI Agents, autonomous programs that perform tasks, make decisions, and communicate with others.  Agents perform actions through Tools. It might happen that a Tool doesn’t work on the first try, or that multiple Tools must be…

  • A Clear Intro to MCP (Model Context Protocol) with Code Examples

    A Clear Intro to MCP (Model Context Protocol) with Code Examples As the race to move AI agents from prototype to production heats up, the need for a standardized way for agents to call tools across different providers is pressing. This transition to a standardized approach to agent tool calling is similar to what we…

  • The Urgent Need for Intrinsic Alignment Technologies for Responsible Agentic AI

    The Urgent Need for Intrinsic Alignment Technologies for Responsible Agentic AI Advancements in agentic artificial intelligence (AI) promise to bring significant opportunities to individuals and businesses in all sectors. However, as AI agents become more autonomous, they may use scheming behavior or break rules to achieve their functional goals. This can lead to the machine…

  • AI Agents from Zero to Hero – Part 1

    AI Agents from Zero to Hero – Part 1 Intro AI Agents are autonomous programs that perform tasks, make decisions, and communicate with others. Normally, they use a set of tools to help complete tasks. In GenAI applications, these Agents process sequential reasoning and can use external tools (like web searches or database queries) when…

  • Zero Human Code: What I Learned from Forcing AI to Build (and Fix) Its Own Code for 27 Straight Days

    Zero Human Code: What I Learned from Forcing AI to Build (and Fix) Its Own Code for 27 Straight Days 27 days, 1,700+ commits, 99,9% AI generated code The narrative around AI development tools has become increasingly detached from reality. YouTube is filled with claims of building complex applications in hours using AI assistants. The…

  • 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,…

  • How to Implement Guardrails for Your AI Agents with CrewAI

    How to Implement Guardrails for Your AI Agents with CrewAI LLM Agents are non-deterministic by nature: implement proper guardrails for your AI Application. Continue reading on Towards Data Science » Alessandro Romano Go to original source

  • Building Visual Agents that can Navigate the Web Autonomously

    Building Visual Agents that can Navigate the Web Autonomously A step-by-step guide to creating visual agents that can navigate the web autonomously Continue reading on Towards Data Science » Luís Roque Go to original source

  • AI Agents Hype, Explained — What You Really Need to Know to Get Started

    AI Agents Hype, Explained — What You Really Need to Know to Get Started I’ll set the record straight — AI Agents are not new but advanced. Learn how they’ve evolved and where to get started. Continue reading on Towards Data Science » Marc Nehme Go to original source

  • GDD: Generative Driven Design

    GDD: Generative Driven Design Reflective generative AI software components as a development paradigm Nowhere has the proliferation of generative AI tooling been more aggressive than in the world of software development. It began with GitHub Copilot’s supercharged autocomplete, then exploded into direct code-along integrated tools like Aider and Cursor that allow software engineers to dictate…

  • Building a Custom AI Jira Agent

    Building a Custom AI Jira Agent How I used Google Mesop, Django, LangChain Agents, CO-STAR & Chain-of-Thought (CoT) prompting combined with the Jira API to better automate Jira Photo by Google DeepMind on Unsplash The inspiration for this project came from hosting a Jira ticket creation tool on a web application I had developed for internal users.…

  • Evaluation-Driven Development for agentic applications using PydanticAI

    Evaluation-Driven Development for agentic applications using PydanticAI An open-source, model-agnostic agentic framework that supports dependency injection Ideally, you can evaluate agentic applications even as you are developing them, instead of evaluation being an afterthought. For this to work, though, you need to be able to mock both internal and external dependencies of the agent you…

  • 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

  • Agentic AI: Building Autonomous Systems from Scratch

    Agentic AI: Building Autonomous Systems from Scratch A Step-by-Step Guide to Creating Multi-Agent Frameworks in the Age of Generative AI Continue reading on Towards Data Science » Luís Roque Go to original source