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Category: ai-agent

  • The Black Box Problem: Why AI-Generated Code Stops Being Maintainable

    The Black Box Problem: Why AI-Generated Code Stops Being Maintainable Same notification system, two architectures. Unstructured generation couples everything into a single module. Structured generation decomposes into independent components with explicit, one-directional dependencies. Image by the author The post The Black Box Problem: Why AI-Generated Code Stops Being Maintainable appeared first on Towards Data Science.…

  • How to Create Production-Ready Code with Claude Code

    How to Create Production-Ready Code with Claude Code Learn how to write robust code with coding agents. The post How to Create Production-Ready Code with Claude Code appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • Agentic RAG vs Classic RAG: From a Pipeline to a Control Loop

    Agentic RAG vs Classic RAG: From a Pipeline to a Control Loop A practical guide to choosing between single-pass pipelines and adaptive retrieval loops based on your use case’s complexity, cost, and reliability requirements The post Agentic RAG vs Classic RAG: From a Pipeline to a Control Loop appeared first on Towards Data Science. Mostafa…

  • Claude Skills and Subagents: Escaping the Prompt Engineering Hamster Wheel

    Claude Skills and Subagents: Escaping the Prompt Engineering Hamster Wheel How reusable, lazy-loaded instructions solve the context bloat problem in AI-assisted development. The post Claude Skills and Subagents: Escaping the Prompt Engineering Hamster Wheel appeared first on Towards Data Science. Ruben Broekx Go to original source

  • Build Effective Internal Tooling with Claude Code

    Build Effective Internal Tooling with Claude Code Use Claude Code to quickly build completely personalized applications The post Build Effective Internal Tooling with Claude Code appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • Can AI Solve Failures in Your Supply Chain?

    Can AI Solve Failures in Your Supply Chain? When your warehouse and transportation teams blame each other for late deliveries, who’s right? We can ask an agent connected to the data settle the debate. The post Can AI Solve Failures in Your Supply Chain? appeared first on Towards Data Science. Samir Saci Go to original…

  • 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

  • Building an AI Agent to Detect and Handle Anomalies in Time-Series Data

    Building an AI Agent to Detect and Handle Anomalies in Time-Series Data Combining statistical detection with agentic decision-making The post Building an AI Agent to Detect and Handle Anomalies in Time-Series Data appeared first on Towards Data Science. MADHURA RAUT Go to original source

  • Prompt Fidelity: Measuring How Much of Your Intent an AI Agent Actually Executes

    Prompt Fidelity: Measuring How Much of Your Intent an AI Agent Actually Executes How much of your AI agent’s output is real data versus confident guesswork? The post Prompt Fidelity: Measuring How Much of Your Intent an AI Agent Actually Executes appeared first on Towards Data Science. James Barney Go to original source

  • Plan–Code–Execute: Designing Agents That Create Their Own Tools

    Plan–Code–Execute: Designing Agents That Create Their Own Tools The case against pre-built tools in Agentic Architectures The post Plan–Code–Execute: Designing Agents That Create Their Own Tools appeared first on Towards Data Science. Partha Sarkar 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…

  • How to Optimize Your AI Coding Agent Context

    How to Optimize Your AI Coding Agent Context Make your coding agents more efficient The post How to Optimize Your AI Coding Agent Context appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • How to Keep MCPs Useful in Agentic Pipelines

    How to Keep MCPs Useful in Agentic Pipelines Check the tools your LLM uses before replacing it with just a more powerful model The post How to Keep MCPs Useful in Agentic Pipelines appeared first on Towards Data Science. Roman S Go to original source

  • 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

  • Agents Under the Curve (AUC)

    Agents Under the Curve (AUC) Towards understanding if your agentic solution is actually better The post Agents Under the Curve (AUC) appeared first on Towards Data Science. Lambert Leong Go to original source

  • How IntelliNode Automates Complex Workflows with Vibe Agents

    How IntelliNode Automates Complex Workflows with Vibe Agents Many AI systems focus on isolated tasks or simple prompt engineering. This approach allowed us to build interesting applications from a single prompt, but we are starting to hit a limit. Simple prompting falls short when we tackle complex AI tasks that require multiple stages or enterprise…

  • 4 Techniques to Optimize AI Coding Efficiency

    4 Techniques to Optimize AI Coding Efficiency Learn how to code more effectively using AI The post 4 Techniques to Optimize AI Coding Efficiency appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • How Agents Plan Tasks with To-Do Lists

    How Agents Plan Tasks with To-Do Lists Understanding the process behind agentic planning and task management in LangChain The post How Agents Plan Tasks with To-Do Lists appeared first on Towards Data Science. Kenneth Leung Go to original source

  • 3 Techniques to Effectively Utilize AI Agents for Coding

    3 Techniques to Effectively Utilize AI Agents for Coding Learn how to be an effective engineer with coding agents The post 3 Techniques to Effectively Utilize AI Agents for Coding appeared first on Towards Data Science. Eivind Kjosbakken 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

  • How to Maximize Agentic Memory for Continual Learning

    How to Maximize Agentic Memory for Continual Learning Learn how to become an effective engineer with continual learning LLMs The post How to Maximize Agentic Memory for Continual Learning appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • How We Are Testing Our Agents in Dev

    How We Are Testing Our Agents in Dev Testing that your AI agent is performing as expected is not easy. Here are a few strategies we learned the hard way. The post How We Are Testing Our Agents in Dev appeared first on Towards Data Science. Michael Segner 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

  • How to Create Professional Articles with LaTeX in Cursor

    How to Create Professional Articles with LaTeX in Cursor Learn how to rapidly create professional articles and presentations with LaTeX in Cursor The post How to Create Professional Articles with LaTeX in Cursor appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • How to Perform Agentic Information Retrieval

    How to Perform Agentic Information Retrieval Learn how to utilize AI agents to find information in your document corpus The post How to Perform Agentic Information Retrieval appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • How to Build Your Own Agentic AI System Using CrewAI

    How to Build Your Own Agentic AI System Using CrewAI This article demonstrates how to develop your own Agentic AI system using CrewAI framework. By orchestrating specialized agents with distinct roles and tools, we implement a multi-agent team that is capable of generating optimized content for different social media platforms. The post How to Build…

  • Build LLM Agents Faster with Datapizza AI

    Build LLM Agents Faster with Datapizza AI Intro Organizations are increasingly investing in AI as these new tools are adopted in everyday operations more and more. This continuous wave of innovation is fueling the demand for more efficient and reliable frameworks. Following this trend, Datapizza (the startup behind Italy’s tech community) just released an open-source…

  • Agentic AI from First Principles: Reflection

    Agentic AI from First Principles: Reflection From theory to code: building feedback loops that improve LLM accuracy The post Agentic AI from First Principles: Reflection appeared first on Towards Data Science. Mariya Mansurova 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 Tools for AI Agents

    How to Build Tools for AI Agents Learn how to design and build effective tools to be used by AI Agents The post How to Build Tools for AI Agents appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • How to Perform Effective Agentic Context Engineering

    How to Perform Effective Agentic Context Engineering Learn how to optimize the context of your agents, for powerful agentic performance The post How to Perform Effective Agentic Context Engineering appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • MCP in Practice

    MCP in Practice Mapping power, concentration, and usage in the emerging AI developer ecosystem The post MCP in Practice appeared first on Towards Data Science. Sruly Rosenblat Go to original source

  • How to Connect an MCP Server for an AI-Powered, Supply-Chain Network Optimization Agent

    How to Connect an MCP Server for an AI-Powered, Supply-Chain Network Optimization Agent From prompt to strategic decision-making: MCP-powered agents for cost-efficient, reliable and sustainable supply chain network design. The post How to Connect an MCP Server for an AI-Powered, Supply-Chain Network Optimization Agent appeared first on Towards Data Science. Samir Saci Go to original…

  • Building Research Agents for Tech Insights

    Building Research Agents for Tech Insights Using a controlled workflow, unique data & prompt chaining The post Building Research Agents for Tech Insights appeared first on Towards Data Science. Ida Silfverskiöld Go to original source

  • LangChain for EDA: Build a CSV Sanity-Check Agent in Python

    LangChain for EDA: Build a CSV Sanity-Check Agent in Python A practical LangChain tutorial for data scientists to inspect CSVs The post LangChain for EDA: Build a CSV Sanity-Check Agent in Python appeared first on Towards Data Science. Sarah Schürch Go to original source

  • How to Build Effective AI Agents to Process Millions of Requests

    How to Build Effective AI Agents to Process Millions of Requests Learn how to build production ready systems using AI agents The post How to Build Effective AI Agents to Process Millions of Requests appeared first on Towards Data Science. Eivind Kjosbakken Go to original source

  • Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs

    Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs How timeouts, truncation, and result sanitization keep Cypher outputs LLM-ready The post Preventing Context Overload: Controlled Neo4j MCP Cypher Responses for LLMs appeared first on Towards Data Science. Tomaz Bratanic Go to original source

  • LangGraph 101: Let’s Build A Deep Research Agent

    LangGraph 101: Let’s Build A Deep Research Agent Learn LangGraph fundamentals from Google’s open-source full-stack implementation The post LangGraph 101: Let’s Build A Deep Research Agent appeared first on Towards Data Science. Shuai Guo Go to original source

  • Beyond Code Generation: Continuously Evolve Text with LLMs

    Beyond Code Generation: Continuously Evolve Text with LLMs Long-running content evolution and an introduction to result analysis The post Beyond Code Generation: Continuously Evolve Text with LLMs appeared first on Towards Data Science. Julian Mendel Go to original source

  • A Multi-Agent SQL Assistant You Can Trust with Human-in-Loop Checkpoint & LLM Cost Control

    A Multi-Agent SQL Assistant You Can Trust with Human-in-Loop Checkpoint & LLM Cost Control Your very own SQL assistant built with Streamlit, SQLite, & CrewAI The post A Multi-Agent SQL Assistant You Can Trust with Human-in-Loop Checkpoint & LLM Cost Control appeared first on Towards Data Science. Alle Sravani Go to original source

  • Build an AI Agent to Explore Your Data Catalog with Natural Language

    Build an AI Agent to Explore Your Data Catalog with Natural Language Leverage LLMs to query your Databricks Data Catalog The post Build an AI Agent to Explore Your Data Catalog with Natural Language appeared first on Towards Data Science. Fabiana Clemente Go to original source

  • What If I had AI in 2018: Rent the Runway Fulfillment Center Optimization

    What If I had AI in 2018: Rent the Runway Fulfillment Center Optimization An LLM in 2018 would not have trivialized a complex project, although it could have enhanced the final solution The post What If I had AI in 2018: Rent the Runway Fulfillment Center Optimization appeared first on Towards Data Science. Hugo Ducruc…

  • 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…

  • From Data to Stories: Code Agents for KPI Narratives

    From Data to Stories: Code Agents for KPI Narratives HuggingFace’s smolagents framework in action The post From Data to Stories: Code Agents for KPI Narratives appeared first on Towards Data Science. Mariya Mansurova Go to original source

  • 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…

  • How I Built Business-Automating Workflows with AI Agents

    How I Built Business-Automating Workflows with AI Agents AI agents and automation are no longer just a trend — they are transforming how companies operate. In a previous article, I shared several case studies of AI Agents supporting the sustainability roadmaps of small, medium and large companies. AI Agents for Sustainability — (Image by Samir Saci) This is part of a…

  • 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…

  • AI Agents for a More Sustainable World

    AI Agents for a More Sustainable World As political support for sustainability weakens, the need for long-term sustainable practices has never been more critical. How can we use analytics, boosted by agentic AI, to support companies in their green transformation? For years, the focus of my blog was always on using Supply Chain Analytics methodologies…

  • 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…

  • Understanding the Tech Stack Behind Generative AI

    Understanding the Tech Stack Behind Generative AI Understanding the Tech Stack Behind Generative AI When ChatGPT reached the one million user mark within five days and took off faster than any other technology in history, the world began to pay attention to artificial intelligence and AI applications. And so it continued apace. Since then, many…

  • 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…

  • Japanese-Chinese Translation with GenAI: What Works and What Doesn’t

    Japanese-Chinese Translation with GenAI: What Works and What Doesn’t Authors Alex (Qian) Wan: Alex (Qian) is a designer specializing in AI for B2B products. She is currently working at Microsoft, focusing on machine learning and Copilot for data analysis. Previously, she was the Gen AI design lead at VMware.Eli Ruoyong Hong : Eli is a…

  • 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…

  • Automate Supply Chain Analytics Workflows with AI Agents using n8n

    Automate Supply Chain Analytics Workflows with AI Agents using n8n Why build things the hard way when you can design them the smart way? As a Supply Chain Data Scientist, I’ve explored various frameworks like LangChain and LangGraph to build AI agents using Python. Leveraging LLMs with LangChain for Supply Chain Analytics — A Control Tower Powered by…

  • 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…

  • Multimodal Search Engine Agents Powered by BLIP-2 and Gemini

    Multimodal Search Engine Agents Powered by BLIP-2 and Gemini This post was co-authored with Rafael Guedes. Introduction Traditional models can only process a single type of data, such as text, images, or tabular data. Multimodality is a trending concept in the AI research community, referring to a model’s ability to learn from multiple types of…

  • 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

  • Transform Customer Feedback into Actionable Insights with CrewAI and Streamlit

    Transform Customer Feedback into Actionable Insights with CrewAI and Streamlit Build an AI-powered app to analyze unstructured feedback, generate insightful reports, and create interactive visualizations Continue reading on Towards Data Science » Alan Jones Go to original source