A step-by-step guide to building, running, and monitoring a stateful customer support agent using Python, LangGraph, and Langfuse. The post I Replaced a 15-Minute Booking Process with a LangGraph AI Agent appeared first on Towards Data Science .
Building a production-ready web interface for a stateful LangGraph agent The post Building a Streamlit UI for My LangGraph AI Agent appeared first on Towards Data Science .
A practical guide to choose the proper tool for your agentic workflows and systems The post LangChain vs LangGraph: 4 Key Differences and When to Use Each appeared first on Towards Data Science .
A practical walkthrough using text-to-SQL as the example The post Why I Stopped Using One Agent and Built a Multi-Agent Pipeline Instead appeared first on Towards Data Science .
arXiv:2606. 28715v1 Announce Type: cross Abstract: While AI development and evaluation for Southeast Asia (SEA) has grown rapidly, agent capabilities in regional languages are still poorly understood despite its importance to sovereign AI.
A practical tutorial for recording model tool requests, real function results, patches, checks, screenshots, and a saved run log. The post How to Debug AI Coding Agents When They Change the Wrong Thing appeared first on Towards Data Science .
A reproducible 100-step LoRA fine-tuning run for OpenVLA, with dataset checks, Colab setup, training metrics, and W&B evidence. The post I Tried Fine-Tuning a Robot AI Model on Colab.
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
Mirakl is redefining commerce through AI agents and ChatGPT Enterprise—achieving faster documentation, smarter customer support, and building toward agent-native commerce with Mirakl Nexus.
A step-by-step guide to building a data agent and conversational interface that let business users to explore data in natural language without SQL The post I Built an AI Data Agent Which Can Query Data and Answer Business Questions. Here’s How.
A minimal loop with real API calls, validation, compact outputs, and trace evidence before adding an agent framework The post I Built a Tool-Calling Agent in Python. Here’s How I Debugged It appeared first on Towards Data Science .
Enterprise Document Intelligence [Vol. 1 #13] - Putting the patterns together, and why this is what “agentic RAG” should look like The post RAG Workflow and Loop Engineering: The Dispatcher That Decides When to Loop and When to Stop appeared first on Towards Data Science .
For years, web agents have worked one click at a time—and often fallen apart on long tasks. Microsoft Research’s Webwright makes a different bet: give the model a terminal and let it write the program instead.