A team of researchers from University of Liverpool, Huawei Noah’s Ark Lab, University of Oxford and University College London presents a report explaining Deep Research Agents (DR agents), a new paradigm in autonomous research. These systems are powered by Large Language Models (LLMs) and designed to handle complex, long-horizon tasks that require dynamic reasoning, adaptive…
Table of contents What is an AI Agent? Why AI Agents Matter in 2025 Types of AI Agents Key Components of an AI Agent Leading AI Agent Frameworks in 2025 Practical Use Cases for AI Agents AI Agent vs. Chatbot vs. LLM The Future of Agentic AI Systems FAQs About AI Agents Conclusion What is…
In this tutorial, we build a complete multi-agent research team system using LangGraph and Google’s Gemini API. We utilize role-specific agents, Researcher, Analyst, Writer, and Supervisor, each responsible for a distinct part of the research pipeline. Together, these agents collaboratively gather data, analyze insights, synthesize a report, and coordinate the workflow. We also incorporate features…
On July 17, 2025, OpenAI launched ChatGPT Agent, transforming ChatGPT from a conversational assistant into a unified AI agent capable of autonomously executing complex, multi‑step tasks—from web browsing to code execution—on a virtual computer environment. Bridging Previous Capabilities ChatGPT Agent builds on two earlier tools: Operator, enabled limited web interactions—clicking, scrolling, and form‑filling—with a Browser‑based agent. Deep Research, provided…
Research & Cutting‑Edge Agents AlphaEvolve (Google DeepMind) – An evolutionary coding agent powered by Gemini, AlphaEvolve autonomously invents and optimizes algorithms across domains—including mathematics, data center scheduling, chip design, and language model training. It’s a general-purpose system that can improve and discover state-of-the-art solutions to a wide range of algorithmic problems, requiring only a user-defined evaluation…
In this tutorial, we begin by diving into Griffe, positioning it as the center of our advanced AI Code Analyzer. By leveraging Griffe’s rich introspection capabilities, we can seamlessly load, traverse, and dissect Python package structures in real-time. This tutorial guides you through the process of integrating Griffe with complementary libraries, such as NetworkX for…
In this tutorial, we set up an end-to-end AI agent system powered by CrewAI and Google’s Gemini models. We start by installing all required packages, configuring the Gemini key securely, and then building a suite of specialized agents, including research, data analysis, content creation, and quality assurance, each optimized for rapid, sequential collaboration. With clear…
Amazon has unveiled Kiro, a groundbreaking agentic Integrated Development Environment (IDE) designed to change the way developers build, ship, and maintain software. Positioned well beyond the capabilities of today’s AI coding assistants, Kiro brings a mature, structured approach to software delivery—offering innovations in specification-driven development, intelligent automation, and adaptive user interfaces. Here’s an in-depth look…
MLflow is an open-source platform for managing and tracking machine learning experiments. When used with the OpenAI Agents SDK, MLflow automatically: Logs all agent interactions and API calls Captures tool usage, input/output messages, and intermediate decisions Tracks runs for debugging, performance analysis, and reproducibility This is especially useful when you’re building multi-agent systems where different…
Google DeepMind recently released GenAI Processors, a lightweight, open-source Python library built to simplify the orchestration of generative AI workflows—especially those involving real-time multimodal content. Launched last week, and available under an Apache‑2.0 license, this library provides a high-throughput, asynchronous stream framework for building advanced AI pipelines. Stream‑Oriented Architecture At the heart of GenAI Processors…