Build Smarter Teams
with Generative AI

Dust's mission is to harness the power of LLMs to help teams craft better content, understand their environment faster, and ultimately take better decisions. Here we document our voyage.

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Build an AI Assistant to Track Internal Project Status

Stay on top of key projects with a custom Dust assistant.

From rolling out Dust and assistants across companies, we've seen tremendous value in creating AI assistants that provide project status updates.

This best practice outlines how to build an assistant that delivers timely, relevant info on any project. While the temptation may be to connect every data you have, we've found limiting sources boosts accuracy. Focus on where updates are typically posted or documented - the more tailored the inputs, the better the output. With precise prompts and selected data, your custom Dust assistant becomes an invaluable project tracker.

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Automate SQL Query Generation with a Custom Dust Assistant

Take the load off your data analysts with a Dust assistant specialized in SQL.

From wide-scale rollouts, we've seen immense value in AI assistants that automatically generate SQL queries.

This article outlines building a Dust Custom assistant that outputs analysis-ready SQL. Simply include your most relevant table schemas in the prompt, and direct your assistant to produce queries that plug right into your data tools (Metabase, Snowflake, etc.). Ask it to generate SQL that answers specific questions - no coding needed!

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Announcing our seed round

We’re excited to share that we’ve raised €5M in seed funding led by Sequoia Capital with participation from XYZ, GG1, AIGrant, Connect Ventures, Motier VC, Remote First, Tiny Supercomputer, Seedcamp, and others, to build the operating system for smart teams.

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A first version of our Product Constitution

The opportunity opened by Large Language Models (LLMs) is vast. It’s allowed the birth of Dust, an AI-native company that wants to make work “work better” for smart teams. Deciding on a product constitution to guide what Dust would focus on in the vast space of possible directions was important to us. It will will help us decide locally more effectively. We look forward to continuously improving this first version we’re sharing here.

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Why work doesn’t work

Information overload is a millenia-old challenge that's only been amplified by digital technology. With Large Language Models (LLMs), we can leverage technology to overcome this challenge that every company faces. A new approach is needed: adaptive software that helps teams better harness information flows with software and free up their own time for value-added worked.

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