Artificial Intelligence

Most AutoGPT tutorials stop at "get it running", but that's the easy part. The harder part that determines whether your agents are useful is connecting them to live data, and AutoGPT helps you fix that. This guide covers AutoGPT local setup, UI navigation, custom Python block development, and the integration patterns that turn AutoGPT into a production workflow tool.

Google AI Mode was launched as a Search Labs experiment in March 2025. It's powered by Gemini 2.5, which synthesizes answers from multiple sources and allows you to ask follow-up questions. Google AI Mode isn't the same as Google search results; it's an entirely full-page conversational interface using different URL parameters, rendering pipelines, and scraping logic. This guide provides a walkthrough of two different approaches: a working Playwright script you can execute right away, and the Decodo Web Data API for production.

Images, video, and audio are harder to collect and clean than text, and much less useful without context. Multimedia scraping helps you collect media, preserve the metadata that gives it meaning, and turn scattered files into training-ready datasets. The hard part is treating each media type differently from the start.

Switching from ChatGPT to Claude no longer means starting from scratch. Anthropic’s memory import tool lets you transfer preferences, context, and instructions in under 5 minutes. This guide covers 3 migration paths – from a quick memory import to a full data transfer, plus feature comparisons, export steps, and power tips.

AI-powered automation has moved from niche tooling to a 2026 priority. Tools such as OpenClaw turn large language models into proactive messaging assistants, while n8n offers a visual workflow builder for connecting apps and orchestrating processes. This guide compares their architecture, AI capabilities, pricing, and best-fit use cases so you can quickly decide which tool matches your needs.

Web scraping used to mean wrestling with Python scripts, brittle selectors, and an ever-growing list of sites that suddenly stopped working. AI-powered agents are changing that. This guide walks you through setting up OpenClaw with Decodo's scraping skill to build a reliable, proxy-backed web scraping setup. By the end, you'll have a working configuration that handles JavaScript rendering, bot detection, and proxy rotation out of the box.

Artificial intelligence is transforming various fields, ushering in new possibilities for automation and efficiency. As one of the leading AI tools, ChatGPT can be especially helpful in the realm of data collection, where it serves as a powerful ally in extracting and parsing information. So, in this blog post, we provide a step-by-step guide to using ChatGPT for web scraping. Additionally, we explore the limitations of using ChatGPT for this purpose and offer an alternative method for scraping the web.

With all the buzz about AI taking over our jobs, why not flip the script and employ AI to help you write efficient code and boost your productivity instead? In 2026, the best AI tools for coding are designed to be your new sidekick, helping you code smarter, faster, and with less stress. Let's explore how you can make AI work for you before the inevitable machine world domination.

Web scraping has become increasingly complex as websites deploy sophisticated anti-bot measures and dynamic content loading. While traditional scraping approaches require extensive manual coding and maintenance, artificial intelligence offers a transformative solution. Claude, Anthropic's advanced language model, brings unique capabilities to the web scraping landscape that can dramatically improve both efficiency and effectiveness.

AI web scraping with Python lets you extract data from websites without relying on fragile parsing rules. AI helps handling page inconsistencies and dynamic content, while Python continues to manage fetching. In this guide, you'll see how models extract data from unstructured pages, reduce manual parsing rules, support automation, and scale into reliable pipelines.

AI web scraping is the process of extracting data from web pages with the help of machine learning and large language models. It uses them to read a web page the same way humans do, by understanding its meaning. The problem with traditional scrapers is that they tend to stop working when the HTML structure is inconsistent or incomplete. In these cases, AI helps scrapers to quickly adapt and find the right information. Sometimes, even a single misplaced tag can ruin your whole web scraping run. AI solves that by shifting focus to the meaning of the content rather than relying on rigid rules to define what data to scrape. That's why AI web scraping is becoming a practical choice for many projects.

SoundCloud is a mother lode for AI training data, with millions of audio tracks spanning every genre and style imaginable. In this guide, we’ll show you how to tap into that library using Node.js, with the help of proxies. You’ll get hands-on code examples and learn how to collect audio data for three key AI use cases: music generation, audio enhancement, and voice training.

Production RAG fails when it relies on static knowledge that goes stale. This guide shows you how to build RAG systems that scrape live web data, integrate with LlamaIndex, and actually survive production. You'll learn to architect resilient scraping pipelines, optimize vector storage for millions of documents, and deploy systems that deliver real-time intelligence at scale.

AI has evolved from programs that just follow rules to systems that can learn and make decisions. Businesses that understand this shift can leverage AI to tackle complex challenges, moving beyond simple task automation. In this guide, we'll walk you through how to connect modern AI tools with live web data to create an automated system that achieves a specific goal. This will give you a solid foundation for building even more sophisticated autonomous applications.

GPT models power 92% of Fortune 500 companies, but generic ChatGPT is amazing at everything and perfect at nothing. When you need domain-specific accuracy, cost control, or data privacy that vanilla models can't deliver, training your own becomes essential. This guide covers the practical methods, tools, and step-by-step process to train a GPT model that understands your specific use case.

Individual AI agents are powerful, but their true value is unlocked when they operate cooperatively as a collective. This coordinated effort, known as AI agent orchestration, is fundamental to creating truly autonomous systems capable of managing intricate, multi-step business processes. This guide will walk you through the core patterns of AI agent orchestration and build a practical, autonomous agent using the robust, low-code combination of n8n and Decodo MCP.

Building an LLM from scratch in 2026? It's totally doable if you know what you're doing. This guide covers everything – from architecture, training, fine-tuning, and deployment to tips on how to handle the tricky parts. You'll walk away with a clear plan and best practices for building your own high-performing large language model.

If you're tired of duct-taping complicated scripts just to grab web data, this n8n web scraping tutorial is for you. You'll see how to use n8n for web scraping, why it beats DIY scrapers, and what you need to get started. Perfect for developers and coding beginners looking to automate data extraction without the headaches.