By Lior Gavish
Every few months, the world picks two technologies that do completely different things and decides they’re rivals. Right now, it’s RAG vs MCP. Here’s the thing, though. RAG (Retrieval-Augmented Generation) is a pattern for feeding relevant documents to an LLM at query time, while MCP (Model Context Protocol) is a standardized way for AI models … Continued
By Lior Gavish
For thirty years, “user” meant a human being. Every design principle, every interface, every experience framework assumed a person sitting at a screen. That’s over. In the last year, AI agents went from a curiosity to an operating reality. We first heard the term Agent Experience (AX) from Netlify’s Matt Biilmann. Salesforce declared a new … Continued
By Lior Gavish
In March we restructured Monte Carlo’s engineering organization. I want to write down exactly what we changed and why — because I think a lot of engineering leaders are circling these same decisions right now. The starting point: we were doing the right things — just not the new right things Before the restructure, Monte … Continued
By Lior Gavish
Every data leader is being asked the same question right now: “Can’t we just point Claude at our warehouse and let everyone ask their own questions?” The naive version works for about a week. Then two execs ask the same question and get two different numbers, Claude joins the wrong tables and answers confidently anyway, … Continued
By Lior Gavish
AI coding agents are writing SQL, building pipelines, and modifying schemas at a pace that would have been unimaginable two years ago. They’re fast, tireless, and increasingly capable. But they lack something every experienced data engineer has: the operational instincts to do data work responsibly. They don’t feel accountable like humans do, and they certainly … Continued
By Lior Gavish
You might not consider scalability a critical limitation of enterprise AI—but development velocity is undoubtedly at the top of executive agendas this year. Nearly every SaaS tool today comes with some sort of AI feature to expedite something or other—and that’s mostly a good thing. AI is unlocking new capabilities for teams of all sizes, … Continued
By Lior Gavish
Turn data health insights into actionable frameworks in half the time with an AI agent built specifically for data + AI teams
By Lior Gavish
Data quality monitoring is one of the traditional methods of managing data quality—but is it enough? Find out what’s missing, and how to do it better.
By Lior Gavish
Generative AI is taking the world by storm – here’s what it means for data engineering and why data observability is critical for this groundbreaking technology to succeed.
By Lior Gavish
Monte Carlo and Databricks double-down on their partnership, helping organizations build trusted AI applications by expanding visibility into the data pipelines that fuel the Databricks Data Intelligence Platform.
