Tutorials, comparisons, and deep-dives on RAG pipelines, LLM data pipelines, and web scraping for production AI systems.
Your compliance docs live on your website. Build a chatbot that reads them automatically, stays current when pages change, and answers questions with source citations.
Context engineering is replacing prompt engineering as the key skill for AI developers. Learn how to design, manage, and optimize the information you feed your LLMs.
Context engineering is the defining AI skill of 2026. Learn how to pipe live web data into agent context using KnowledgeSDK — just-in-time scraping, webhooks, and temporal metadata.
Support agents that only know your FAQ hallucinate. Support agents that extract and search your entire documentation site answer correctly — every time.
Build an open-source deep research agent in Python and Node.js. Search sources, scrape top results, synthesize a cited report. Cheaper than Perplexity's $5/1000 queries.
Build a DSPy RAG pipeline over live web content with KnowledgeSDK. Use BootstrapFewShot and MIPROv2 to automatically optimize retrieval prompts and improve answer quality.
How to build an AI-powered e-commerce data pipeline — extracting products, prices, and reviews from any website, structuring the data, and making it searchable.
Replace keyword search with semantic product search — customers find what they're looking for even when they don't know the product name. Here's how to build it.
MTEB scores, licensing, latency, and cost for every major embedding model — with a decision framework for RAG, semantic search, and knowledge base use cases.
The EU AI Act enters full enforcement August 2, 2026. Here is what Article 53, GDPR, and the US AI Accountability Act mean for developers who scrape web data.
Firecrawl and Browserbase are both popular with AI developers, but they solve different problems. Here's an honest comparison with a clear decision framework.
A head-to-head comparison of Firecrawl and ScrapingBee for AI developers. We cover pricing, features, markdown quality, AI use cases, and when to use each — plus a third option.