The point of a startup is to make usable technology for others. When you make software, you have to watch at least 10 people use it. Sit next to them and say absolutely nothing. Force yourself to marinate in the failure of your product design. Every version 1 of any software

Markets are voting machines in the short run & weighing machines in the long run. Sridhar took all the hits this yr but worked like a beast & just reminded the world that $SNOW will be a big winner in the Age of AI. Just one day - but well deserved- congrats to u & team! 🫡🚀

Clean Old Fashioned 𝓦 #GoDawgs

Gunner Stockton legacy drive 22 seconds.

cracked engineers will henceforth be known as Cracker Jack engineers

os/acc

pride versioning > semantic versioning 😂

If you are working on developer products, a big part of your daily routine should involve talking to developers.

the yankees hired a single smart guy to think about baseball bats for a year and he fundamentally changed the game forever the efficient market hypothesis is an total lie. the most important problems in the world go unsolved because no one spends the time to think about them

It’s time to build

Don’t debug with your eyes closed 👀 The Weaviate Query Agent is here to help you with all of your research tasks. Navigating through any number of collections, deciding whether to query or aggregate, taking the load off your shoulders when it comes to sifting through a maze of

The entire tech community is under the impression that AI coding will result in power flowing from engineers to “idea guys.” Wrong—it will always flow to whatever still has scarcity: those who know how to get distribution

Almost a 5x speedup in vLLM🤯 I was able to push a finetuned Mistral Nemo from 110 tokens/s to a peak of 517 tokens/s and acceptance rate of 57.7%. This is with Suffix Decoding from ArcticInference⚡

Build a complete RAG pipeline using our LlamaParse document parser with Snowflake Cortex for enterprise-grade document processing and search. This tutorial shows you how to combine LlamaParse's agentic parsing capabilities with Snowflake's powerful data platform: 📄 Parse

A lot of companies run on Snowflake ❄️. A lot of companies also depend on massive collections of PDFs. 📑 For the first time, you can now combine the two with high accuracy! This is a great tutorial by Josh Reini highlighting how you can use LlamaParse to parse complex documents

Need to parse and search complex PDFs, slide decks, and Word docs? Check out Josh Reini’s latest tutorial walks you through how to build a complete RAG (Retrieval-Augmented Generation) pipeline using LlamaParse from LlamaIndex 🦙 and Snowflake Cortex. It’s ideal for document-rich

Agent meetup in Amsterdam 🇳🇱 Finally a meetup on home turf 🚲 Amsterdam (and Europe) friends, we’re hosting an in-person event at the Snowflake HQ here with Josh Reini on July 31st: Document agents, building them and evaluating them 👇 lu.ma/vzwsj72w

We're partnering with Snowflake to bring you hands-on talks and concrete patterns you can implement immediately. Join us at our Amsterdam meetup on July 31st where we'll show you exactly how teams are building high-quality data agents in production. Build production-ready

Join Josh Reini (Developer Advocate, Snowflake) for a deep dive into building, deploying, and evaluating multi-agent systems. This hands-on workshop equips you with a repeatable framework to deploy trustworthy, production-ready data agents that scale. 🔗 hubs.li/Q03xv1K80

The first major breakthrough came with their Snowflake data warehouse integration. Portfolio managers could suddenly query complex datasets using natural language. What previously required technical SQL expertise now took seconds. But this was just the initial phase...