In Good Company with Nicolai Tangen - HIGHLIGHTS: Sridhar Ramaswamy - CEO of Snowflake

Starting point is 00:00:00 Hi, everybody. Tune in to this short version of the podcast, which we do every Friday for the long version. Tune in on Wednesdays. Hi, everyone. I'm Nikola Tangan, the CEO of the Norwegian Soinwell Fund. And today I'm joined by Shreda Ramoswami, the CEO of Snowflake. Snowflake is basically the data platform than many of the world's biggest companies run on. So when your bank approves a loan or when a hospital pulls together patient data, Snowflake is often the engine underneath. Shreda spent 15 years at Google where he built the advertising business

Starting point is 00:00:32 from one and a half billion to over $100 billion. Then he walked away to start his own company and two years later he became the CEO of Snowflake. Now here at Mbim we are investors in Snowflake and we are also big users of the products. We have two petabytes of data in Snowflake which is the equivalent of 2 million gigabytes and we have roughly 3 million queries

Starting point is 00:00:58 into the database every day. So big welcome, Shreda. Thank you, Nikola. Happy to be here, excited for the conversation. First of all, how would you describe Snowflake to somebody who's never heard of it, in brief? Yeah, we are a data platform. We are like a cloud computing platform, like an AWS,

Starting point is 00:01:18 but with a strong focus on data, we help you do everything from bringing data from various different systems, analyze it, get insights from it, and then take it. into the systems where you take action. So we are an analytic data platform. Who are your clients? Gosh, half the global 2000 companies that are addressable, that is non-China companies, are our customers and hundreds of customers in financial services, healthcare, advertising, industries,

Starting point is 00:01:53 the list goes on and on. And we operate out of more than 25 countries and have customers in way more than those. Continuing on AI, in what ways are you benefiting from this revolution? I take a reductive approach when it comes to AI and a software company like Snowflake. You know, at our core, we do two things. We create and run great software. This is what my engineering team does, we sell and help customers like you implement our software. So a lot of our energy is focused very much on how do we make this go faster. On the sales side, our sellers now have tools that give them instant access to information. It's a sales agent that sits in their phone.

Starting point is 00:02:41 Our solution engineers can do a custom demo for Nikola in 30 minutes that has data that will look like it came from your bank. Their ability to use these tools, drive outcomes for you is incredible. And then on the software engineering side, coding is being revolutionized. I just came from a meeting where we are talking about how we need to get more people into spec-driven coding development, which is you write an English language spec for what it is that you want to produce, and then you automate the entire rest of the process of writing the first version of the code and testing it and deploying it and so on. And so software engineering is nothing like what it was two years ago.

Starting point is 00:03:23 How to get every engineer in your team to act like that, to internalize these great possibilities is the biggest challenge that we have. But we have the superstars, people that are 50, 100 times more productive than the average software engineer. How will agents change the way you work? This is a big question. And the word agents themselves itself is a little bit misunderstood. The way you should think about agents is it is a model and a piece of code that has access to different kinds of tools underneath

Starting point is 00:04:00 and it knows how to call them smartly. So, for example, if you ask it a question and say, write a little program for me, it knows how to create a file, write some code into it and then call something local. to execute that piece of code. But exactly the same thing can be used. If you say, I want to know how my portfolio is doing, it knows how to call the portfolio tool,

Starting point is 00:04:24 analyze it, and give you back the result. And so agents are changing work at every level, even though you tend to hear most about things like coding agents, but the general concept is very powerful. These coding agents are effectively abstraction agents. So even somebody that never wants to write a lot, write a line of code is going to benefit enormously from having their basic functionality, access to all of your documents, access to the structured data that is in Snowflake.

Starting point is 00:04:54 If I give you, for example, Snowflake Intelligence to access to all of it, practically any question that you would want to ask of the data, the agent can come up with a plan and help you execute. That's why there's so much excitement about things like the work concept, Cloud Co-Work, are snowwork because they're changing how people think about work. Everything is programmable and also everything is interconnected. If you want to send an email based on an analysis you did, you don't have to cut in page.

Starting point is 00:05:21 You can just tell your agent, please send this email to Stefan and outgoes the email. Absolutely. Now, I'll tell you one thing. We spent years cleaning up our data and it's not a fun job. Now, when you look at data, it's messy, duplicates, gaps, decades of legacy systems, stitched together. Just what kind of barrier is that to the usage of AI and to the usage of your product? Used to be a bigger, a huge barrier to getting value from data. I think it is getting simpler by the day.

Starting point is 00:05:52 That's the magic of coding agents applied to the data problem itself. Used to be that changing a pipeline for just adding one additional column of information in a complex dataset, that it easily be a week-long job for some poor programmer that I'd toil through all of the details. We now have things like skills, which you can think of as English language programs, that automate that entire process from start to finish so that they can start it, and they can come back in an hour and just ensure that everything has been taken care of. We are working on things like agent-driven migrations, where you can move data from

Starting point is 00:06:33 legacy systems onto Snowflake. in a matter of days and small number of weeks, as opposed to the multiple quarters and the multiple years that it used to take. And AI can be very, very powerful in the data modernization journey overall. And it's an area that we are very heavily invested in. Is GDP are good or bad for Europe? I think it's a very mixed back.

Starting point is 00:06:59 I think it had a lot of unintended consequences, and it also tells you how regulation needs to be very surgical. about what it does and people really need to think very hard. What are the unintended negative consequences? Yeah, I'll tell you the positive things first. The fact that you as a consumer can go to a company and say, you need to delete everything that you know about me. That came as a result of GDPR.

Starting point is 00:07:24 That is a huge positive. It forced every company. It forced my Google Ads team to make sure that we were actually able to track down everything that we knew about Nicola. I think that's a huge positive. On the other hand, those walls of prompts that you have to, at this point, you just give up and say yes. I think that's an unintended consequence.

Starting point is 00:07:42 I think it has raised the cost of doing business for every European company. And the people that ultimately benefited from GDPR, where the giants were able to spend the money, follow all the rules, and be compliant, while every new company that comes up in Europe has to struggle to follow all of these rules right out of the gate. That's what I mean by unintended consequences. You grew up in Tamil Nadu. how did that shape you? I grew up in Tamil Nadu. I was also in Bengaluru, which is in a nearby state until I went to college. I grew up in a lower middle class neighborhood.

Starting point is 00:08:21 Most of the time when I was growing up, you know, there was one living room and one bedroom for a family of four. But this was a family that profoundly believed in education as a way forward that was intellectually curious about things. Neither of my parents went to college. finished high school, but they stressed education and there was nothing that they would not do to help me and my sister reach for a better life and educate ourselves. So the virtues are very much that of being knowledgeable, being smart is important, that it is helpful and that working

Starting point is 00:09:03 hard can create a better future for all of us. And these are qualities that I keep to this day. And I'll also tell you that, you know, my parents were also remarkably malleable. I went to a college that they did not want me to go to because the idea of sending a young son to a college that was 300 miles away was something that they were very hesitant about, but they supported me in doing that or in who I choose as my life partner. I think that kind of malleability is also important. If I had to crystallize all of these back, I would say it's all about the value of education, the value of hard work, and the value of being malleable to a changing world. These are all things that I take very much to my heart, and these are very much the qualities that I talk to

Starting point is 00:09:58 my children about.

In Good Company with Nicolai Tangen - HIGHLIGHTS: Sridhar Ramaswamy - CEO of Snowflake

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