Hex

A Head of Data told us they had to migrate 300 dashboards to Hex. They didn't. What they really needed was the answer underneath each one: the metric definitions and trusted calculations their whole org relies on. Rachel Herrera breaks down how to decide what to migrate, what to leave behind, and why moving the logic (not the UI) is what finally makes self-service work. Link in the comments for the full story 👇

On October 1, we’re bringing together a small group of NYC data leaders (with Hex) to compare notes on what’s actually working in agentic analytics, what isn’t, and what teams are still figuring out. Joining the conversation: → Ian Macomber, VP Data @ Ramp → Josh Hanson, Technical Lead, Data @ Clay → Ali S., Head of Digital & Data @ Blank → Duncan Fraser, Data Lead Some topics we’ll get into include: 🦆 Semantic layer vs. context layer 🦆 Getting teams comfortable with AI tooling 🦆 Keeping answers consistent across Slack, BI, and wherever else data shows up 🦆 What changes when agents become consumers of company data No polished case studies. Just practitioners comparing notes with a room full of people living the same problems. Space is limited, register to join us here-

The session list for Prompt is live 🤩 Prompt is our conference for the people actually doing the work — data, ops, product, and engineering — figuring out what their teams look like now that AI is in the building. You'll hear from leaders at The New York Times, Chime®, the National Hockey League (NHL), Lyft, Ramp, Apollo.io, LangChain, Whatnot, and Databricks on what's actually working (and what isn't) — plus hands-on workshops on evals, agents, and shipping generative apps. A few we're especially fired up about: • Champions in sport and data: How the NHL sees the future of AI for BI across the league, with Oliver Gomes • What's left for humans when AI automates analysis?: Chime's vision for trusted AI insights, with Jordan Farrer, Dori Wilson, and Connor Macdonald • We were never chart builders: Human intelligence in the AI era, with Andy Cotgreave • There's never been a better time to be a data person: How StubHub data roles have adapted with AI and what remains the same, with Nova Wang and Meghana Reddy Haven't grabbed your spot yet? 👉 prompt@hex.tech

Big day for model releases – Opus 5.5 and GPT Sol/Luna 6 are both out! We've also released a new version our analytics benchmark, Databench (https://lnkd.in/gHqTf3zN) which shows some really fascinating trends. We're starting to see frontier models cluster into two groups: intelligent models like Opus, Fable, and Astra that are pushing the boundaries of what's possible with AI, but increasingly we see a cluster of models like Luna that are actually quite good for day to day work and so cheap you basically don't have to worry about cost. All of these are live in Hex today!

What happens in Vegas ends up in a LinkedIn photo dump. Thanks for a great dbt summit, see you at the next one!

Yesterday at dbt Labs Summit, LangChain's Emily Hawkins and Logan Cochran shared their playbook for building and managing context when the business evolves faster than they can document it. Their take? Perfect context doesn't exist. Instead of waiting until the business is fully developed, their team built workspace guides that gave the Hex agent enough direction to get started. As more users asked questions, Hex's Context Studio gave visibility to where the agent needed more information and they use those signals to continuously enrich their context over time. Their work drove a ~40x increase in questions asked via Hex vs what their team could answer. Emily recently published a blog about their context workflow and Hex has a story that highlights their success. Check it out both links in the comments!