Hex

Nowadays, building and maintaining Tableau dashboards is like building a canal with a spoon. If your company is migrating reports from Tableau to Hex, I built a skill that does it end to end — same queries, same layout, same filters and parameters, even the tooltips get rebuilt: https://lnkd.in/ddKm82ix I was at Tableau Conference 2018 in New Orleans, and I still remember how excited everyone was when Tableau introduced "Ask Data". The vision was right. The technology was just too early — and we all know what happened the following year. Eight years later, with LLMs, richer business context, and AI agents that can work across code, data models, and analytics apps, Hex is one of the leaders in this race: more robust MCP and CLI, and centralized context across data models and business definitions. Try it and let me know how it goes. #Tableau #Hex #BusinessIntelligence #AIAgents

Meet ✨PROMPT✨ — Hex's first-ever customer conference. It's a full day in San Francisco all about data in the age of AI. Come for the big ideas, in-depth convos, hands-on workshops with leaders and thinkers in tech and data, and, real tangible takeaways you can bring straight back to your team. Can't wait to show you what we've been working on! (Spots are limited so make sure you get on the list by emailing: prompt@hex.tech)

Well after 2 years Hex we've finally decided it's time for our own conference. A decision we didn't make lightly. Here is the decision-making criteria we used to ultimately decide it's time. 1. People asked for it - maybe the most obvious one but our customers kept asking for more IRL opportunities to connect and learn more. If you've been to a Hex event, they are rad and special and they TAKE A LOT OF CALORIES on our end so we're retiring the "road show" approach temporarily in favor of a big banger event betting that the ROI will be stronger. 2. We have something unique to say - we have been to a TON of conferences and events this year and it felt like everyone was saying some version of the same thing. We sincerely think we've got something different to say- and so do our customers- and we think people want to hear it. (No spoilers.) 3. It coincides with major Hex developments - what we call in the industry "a lightning strike moment." We will be sharing pretty significant developments on the company and product front. How better to share these things than to a captive audience of people who will care about it the most? 4. We have budget - maybe even more obvious than #1 but worth calling out. People expect not just events but experiences. We take this seriously and have a lot of pride in our brand, how we show up and what we produce. If you saw Club Hex, you got a taste of it. But now we feel properly resourced to put on a memorable, unique, and extraordinary conference that meets our Hex standard. So here we goooooo.... Contact me directly or email prompt@hex.tech if you want an invitation or you want to know if you're ready to do your own conference. (Yes it's invite only, that's a topic for a different post.) Barry McCardel Caitlin Colgrove Carlos Aguilar John Messina Katie Bauer Izzy Miller Olivia Koshy Charles Schaefer Jo Engreitz Rachel Herrera Liz Huang Christina Lee Dan Eisenberg Lawrence Dann-Fenwick Lili Jain Bryanna Clancy Peter Ryan Chelsea D'Angelo (she / her) Nisha D. Tahlia DeMaio #data #datascience #businessintelligence #BI

Doing something for the first time can feel a little scary. However, when you get the right people in the room (and especially when it is Hexans who know how to throw a party), it becomes less intimidating and more invigorating. The space we are building for data & AI people at Prompt is one-of-a-kind with thought-provoking questions, intentional discussions, and unique experiences (read: Hex loves Halloween). This is not a massive conference with bright lights and booths with free socks. This is what you are actually wanting: a place to learn from others and help craft the future of data & AI in your workplace. This event is invite-only, and attendance is capped. You can request a seat by emailing prompt@hex.tech. Hope to see you there! ⚡ #hex #data #ai #hexprompt

Evals are the next "thing" in AI and data. It makes a ton of sense; we need a way to test if agents are behaving like we'd expect and using the context we've built, or just YOLO'ing a SQL query. But after my conversation with Owen Quinlan, it's also so clear they have another job to do. Actually build external trust in what you're shipping! Dashboards sort of gave us trust for free. End users felt safe using them, and data teams added layers of protection from bad answers. Now, that trust has to be earned over and over and over again. You're on a razor's edge and one wrong answer away from someone rejecting the entire thing. You have to invest in context, and invest in evals, and market them using the results of those evals loud and often. Thanks, Owen, for the inspiration! I share more of my thoughts here: https://lnkd.in/giZCmj63

Our data team rebuilt the company data experience around agents instead of dashboards, letting LangChain employees ask through Hex, Slack, the CLI, or MCP. For agents to digest and analyze tables accurately, they need clear data models, metric definitions, business context, and signals about which sources to trust. Our data agent now handles roughly 40x the request volume our three-person data team could manage directly, letting our data team focus on the models, context, guardrails, and feedback loops that help make agent answers more useful over time instead of being the bottleneck for questions. Read on to see how we built an agent-first data stack, and see how we approached: ✅ Evaluating tooling ✅ Building business context into the agent experience ✅ What our feedback loop looks like, and what we’ve learned ✅ What’s next

✨𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗣𝗥𝗢𝗠𝗣𝗧✨— Hex's first-ever user conference One curated day in San Francisco dedicated to data in the age of AI, how our world is changing, and how we all need to change with it. Come for the deep-dives, intimate convos, hands-on workshops—and real, tangible takeaways to bring back to your team. 👉Spots are limited—Reach out to prompt@hex.tech to get on the list.

I'm thrilled to announce Prompt, our first-ever conference, coming this October in San Francisco – and we have some big goals for this little gathering! Prompt is a one-day, curated event exploring how our world is changing, and how we all need to change with it. It's meant to stake out a positive-sum vision of the future for our teams, and the organizations we serve. We'll have a full day of ideas and conversation, and tangible takeaways to bring back to your team. Prompt will be intimate, thoughtful, and emphatically not-salesy - and our team is cooking on making it feel truly magical 🧙♀️ Spots are very limited, get on the list by emailing: prompt@hex.tech

Clay is using Snowflake and Hex to turn data into action across growth, support, and sales. With Snowflake and Hex, Clay increased user activation by 300%, boosted trial-to-paid conversion by 200%, and reduced P90 time-to-first reply by 80%. Read more: https://bit.ly/3RZWYzM

The CEO at Apollo.io just wrote about building a reporting dashboard in 30 minutes for $30 in tokens (😱). This is a fascinating post, that perfectly illustrates how and why folks are so confused about where data is going with AI. It’s true: AI tools can now initiate analytics work that used to mean buying a dedicated tool. But I think the hard part is everything after: Where do the artifacts live? How are they shared, permissioned, governed? How does context compound across an entire org, instead of getting rebuilt from scratch – 30 minutes and $30 at a time? No one of these vertical sales/HR/functional tools is going to become the organizational source of truth – nor solve the biggest problems organizations have with data today. We obviously think about this a lot at Hex and I’ve become even more fervent in my belief that you can break this tradeoff between siloed chaos and organizational truth. Maybe in the future, you totally can initiate an analytic artifact in Apollo – but still have it wind up in a place that’s governed, consistent, and secure, and in a format that can be inspected, governed, trusted, and reused. And where your context gets smarter instead of scattered. I am not surprised, however, that people are experimenting and hacking around the current solutions here, trying to figure out how all the pieces together. No one has really cracked this yet and there are many more cards to turn. For data teams watching functional leaders (or CEOs 😅) spin up analytics everywhere: the choice is to embrace this and become “internal AI platform teams” or keep watching your influence erode. We’re very interested in helping you do the former and have a lot coming soon to help! Matt - I'd love to compare notes on this sometime!