Everett Nadkarni

MCP retrieves live data; RAG searches static indexes built in advance.

Reshape tool APIs for agents, not humans, to reduce failures.

Four tiers of action gates keep research agents fast while catching mistakes before they spread.

Machines need structured data to reason reliably on web text without silent failures.

Define your fields before you scrape, or spend months untangling the mess later.

Web data breaks traditional ETL; here's how to rebuild it.

LLM extractors handle messy, variable documents that break rule-based parsers.

Knowledge graphs move from research to production as the best fit for reasoning over web data.

Silent data failures haunt web scrapers long after site redesigns break selectors.

Crawlers waste bandwidth on duplicates unless they filter at both URL and content levels.

Learn how Google's search operators unlock publicly indexed data most people never find.

Knowing when to stop retrieving determines whether AI agents finish efficiently or spin endlessly.

Live web retrieval solves the staleness problem plaguing traditional vector databases.

Keep scrapers running by catching silent failures before they corrupt your data.