Systems | Development | Analytics | API | Testing

You ask your agent a question. The answer is slightly off. You point out the gap. Spotter fixes it, and that fix doesn't disappear when the session ends. Your team doesn't re-explain the same thing tomorrow. The next analyst doesn't start from scratch. The correction stays, and the work gets better from here. That's what memory makes possible. Not just for you. For everyone who comes after.

I spend my days helping organizations modernize analytics to drive tangible business outcomes and liberate analytics teams from legacy processes. At this year’s Snowflake Summit ’26, I had the pleasure of sitting down with AJ Subbarao, Director of Business Intelligence & AI at Intuitive Surgical (ISRG).

Webinar recap: Andy Cotgreave (co-founder, How to Speak Data) and Francois Lopitaux (SVP of Product, ThoughtSpot) on hallucinations, accountability, and what it actually takes to trust AI with your data.

A CFO asks her AI agent a simple question: "What was our ARR at the end of Q3?" The agent finds the subscriptions table, spots a column called arr, sums it up, and returns $16.4M. Strong quarter. Everyone nods. The real number was $13.9M, but no one in the room knew it yet. I hear some version of this story from nearly every data leader I talk to right now, and it almost always starts the same way. They stand up an AI pilot. It looks sharp in the POC.

At the recent data:unplugged 2026 in Münster, Europe’s biggest festival for data and AI, the stage was set for a masterclass in data transformation. Julian Stock, Analytics Reporting Team Lead, and Andreas Weiß, Senior Reporting Engineer, from PAYBACK, Germany’s premier loyalty program, shared the stage to detail a decade-long evolution: the journey from a strict, ticket-based reporting system to a thriving, AI-ready data culture.

At Snowflake Summit '26, Chris de Groot, Manager of Data Engineering Customer Service, and Jay Stricks, Group Product Manager, Insights Platform, took the stage to share Booking.com's massive data transformation. In their session, "Booking.com's Data Travels: Platform Foundations to Agentic Analytics," they laid out a masterclass on how to make a colossal, fragmented data landscape entirely AI-ready.

Soccer is a game of stories, but the most fascinating stories are often buried deep inside the numbers. And this year on the world's biggest stage, the tournament has expanded by nearly 60% – traditional scouting reports and pundit hot-takes simply can't keep up with the sheer volume of new data. That’s why we’re looking at the tournament through a much wider lens.

I had the distinct pleasure of hosting a Snowflake Summit ‘26 session with Agustin “Augie” Del Rio, CEO and Founder of Gallus Insights, an analytics platform tailored specifically for mortgage lenders. As we sat down to discuss the future of analytics, one core truth echoed throughout the room: the most ambitious AI goals live or die by the quality of the underlying data.

Finance leaders are operating in one of the most demanding macro environments in recent memory. Interest rates are moving faster than most models anticipated, reshaping the cost of capital almost overnight. Supply chain fragility has also turned working capital management into a moving target, and geopolitical uncertainty is changing how you plan for the future. Yet for many finance functions, the analytics stack hasn't kept pace with that urgency.

Live from Snowflake Summit '26, tech leaders from around the globe gathered to discover how the world’s most innovative companies are making AI real for business. But few sessions delivered as much raw, practical insight as the one presented by Frankie Woodhead, Chief Product & Technology Officer at Thrive Learning. Heading up a fast-growing, £20m ARR LearnTech business that serves over 500 global customers and 5 million users, Woodhead didn't give a standard product pitch.