AI Agents
112 articles in this category (Page 3 of 5)
How to Build a Safe, Autonomous Prior Authorization Agent for Healthcare Revenue Cycle Management with Human-in-the-Loop Controls
This tutorial demonstrates building an autonomous AI agent for healthcare prior authorization, achieving a 95% confidence level in approvals while incorporating human oversight.
Google AI Releases Universal Commerce Protocol (UCP): An Open-Source Standard for Agentic Commerce
Google AI launched the Universal Commerce Protocol (UCP), an open-source standard aiming to streamline agentic commerce and reduce integration bottlenecks.
How to Design an Agentic AI Architecture with LangGraph and OpenAI Using Adaptive Deliberation, Memory Graphs, and Reflexion Loops
This tutorial details building an advanced Agentic AI system using LangGraph and OpenAI, achieving a 6-tool call limit for optimized performance.
How to Design Transactional Agentic AI Systems with LangGraph Using Two-Phase Commit, Human Interrupts, and Safe Rollbacks
This tutorial demonstrates building agentic AI systems with LangGraph, achieving transactional workflows with a 99.9% success rate in controlled environments.
Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on AndroidWorld
Alibaba’s MAI-UI achieves 76.7% success on the AndroidWorld benchmark, outperforming Gemini 2.5 Pro, Seed1.8, and UI-Tars-2 in mobile GUI navigation.
MiniMax Releases M2.1: An Enhanced M2 Version with Features like Multi-Coding Language Support, API Integration, and Improved Tools for Structured Coding
MiniMax Releases M2.1, achieving 72.5% on SWE-Multilingual, outperforming Claude Sonnet 4.5 and Gemini 3 Pro across multiple programming languages.
Stanford & Harvard Paper Decodes Agentic AI's Demo-vs-Reality Gap
A new paper from Stanford, Harvard, UC Berkeley, and Caltech proposes a unified framework for understanding adaptation in Agentic AI systems, explaining why they often excel in demos but struggle in real-world applications.
A Coding Guide to Build an Autonomous Multi-Agent Logistics System with Route Planning, Dynamic Auctions, and Real-Time Visualization Using Graph-Based Simulation
Build an Autonomous Multi-Agent Logistics System with route planning, dynamic auctions, and real-time visualization, achieving a simulation with 30 nodes and 5 agents.