Last month I wrote about data stacks in the Post-AI era. This isn't hypothetical, it's what working at @tryramp feels like today. 4.5 years ago I joined a corporate card company where data meant writing SQL and clicking through a BI tool's web UI to visualize card swipes. Today, Ramp is a finance intelligence platform building a router, data layer, tools, and agentic product experiences to help companies understand their ROI on token spend, AI tool vendors, and every other signal we can use to help them save time and money. We are meeting every business in the entire world wherever they are on their AI journey, and truly, the energy feels more like we're just getting started than it did 4.5 years ago. I'm looking for data teammates to build the next stage of Ramp with me. There's a lot that AI + "software factory" can solve for you, and we do that better than anyone. I'm not just looking for people who claude code within their own domain and can debug an agent trace, but people who are convincing enough to get hundreds of people to change what they prioritize. I'm looking for ML systems thinkers with strong product opinions who both can both deeply feel and explain customer pain. People with the judgement to build complex systems, combined with bulldozer grade resourcefulness, AI-pilled velocity, who care a lot. Plus you'll get to work with @ryanlstevens12 @arakharazian @ian_dot_so @rahulgs @karimatiyeh @geoffintech @hamidships @diegozaks! If this sounds like you, I'd love to meet. If you're in NYC, would love to grab coffee.

The Modern Data Stack is over, long live the Post-AI Data Stack🫡🤖 I wrote about how technological shifts change what a data team can build, the features of post-AI data stacks, what we've built at @tryramp, and what data teams can learn from @nbcsnl.

There is no substitute for looking at the data. Manually inspecting failure modes is how you discover the shape of the problem. Great AI products are built by teams who set up their infra + instrumentation to make looking at data easy. @austospumanto @bcherny @rahulgs

Our economist is in @TheEconomist "Ramp reckons that the 1% of clients that spend the most on AI per employee are racking up bills of about $7,450 per person per month on average. That compares with just $11 for the median Ramp customer." @arakharazian 💪💪

Ramp's monthly Top Software Vendors is one of the best signals for where to work, where to invest, or who to sell to. Here are May's breakout + fastest growing vendors. We observe that @tryramp customers with high AI intensity grow revenue ~4x faster. Great vendor selection is a critical part of being on the right side of the gap. Every month, @arakharazian publishes the playbook.