Articles from the Zyte blog in Large Language Models (LLMs).

Quickly compare e-commerce products across any site with an agent, a skill and an AI-powered web scraping API.
Programmers were raised on long-standing core principles of the craft. What if those tenets are no longer relevant?

From LLM-powered extraction to agentic pipelines, here's how AI is reshaping every stage of the web scraping workflow in 2026 and what it means for your stack.

Mastery of computer code used to be an engineer’s differentiator. Thanks to AI assistants, code is now the commodity, sensibility is the real premium.

Learn how to build your own Model Context Protocol (MCP) server to connect LLMs with real-time web data using Zyte API, FastMCP, and the Docker MCP toolkit.

What a failed experiment taught me about curated data, prompting, and when scraping actually matters.

Three ways to bring Zyte-powered web data into your AI workflow — from production spiders to conversational extraction.

Learn how Claude skills can automate HTML fetching, AI parsing, selector generation, and structured data extraction to build faster, smarter web scraping workflows.

AI-enabled code editors can now conjure scraping code on command. But is it any good? Here’s how Zyte re-engineered LLMs with Web Scraping Copilot to drive best-in-class output.

Claude Sonnet 4.6 is now the top model in Zyte’s Web Scraping Copilot benchmark, narrowly beating Gemini 3 Pro on extraction quality, with a small increase in code complexity.

2025 was the year AI learned to reason. From reasoning-first LLMs to autonomous agents and a reshaped web economy, this retrospective explores what changed—and what’s coming next.

Gemini 3.0 Pro outperforms GPT-5, Claude, and other leading LLMs in Zyte’s Web Scraping Copilot benchmarks, delivering the highest code accuracy and lowest complexity. See full results, pros, cons, and recommendations for production workflows.
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