Topic
9 facts from 1 episode, in date order. These are what speakers said on the shows, each linked to the moment it was said. They aren't independently verified.
Undated
Christian Kleinerman said he had been at Snowflake for eight years and runs its product team, including product management, design, technical writing and data science.
“I've been with the company eight years, very happy, very proud of what we do.”
Undated
Christian Kleinerman said that in his 25 years in enterprise databases, vendors typically used a single standard demo, often a bicycle shop, for every audience.
“I've been doing enterprise and databases for twenty five years, and for the longest time, you had a canonical one demo, oftentimes something about a bicycle shop”
Undated
Kleinerman said coding agents can work for an hour or four hours on a command and return results for tasks that would take humans days or weeks.
“I give a command, and maybe an hour later, sometimes four hours later, I get solutions, answers to the problem or the prompt that I specified.”
Undated
Kleinerman recalled that trying a database appliance once required a waiting list of about eight months, followed by roughly one week of use.
“you would get on a sign up sheet and they would tell you, well, your turn to get the appliance shipped to you is eight months from now, and then you get it for a week.”
Undated
Kleinerman predicted that bank and wire transfers will be among the last operations fully automated by AI because they must be 100% correct.
“probably one of the last operations that will be fully automated with AI is going to be things like a bank transfer or a wire transfer.”
Undated
Kleinerman described a consumer mobile app that made large language model calls to improve recommendations, where the quality gain did not justify the AI cost.
“Some consumer level mobile app was trying to make some LLM calls in a critical path of the application, just to show a slightly better recommendation.”
Undated
Kleinerman said data governance and data quality are the key prerequisites for data-driven AI solutions, and that the most common customer question is how to make data AI-ready.
“The data governance, data quality is an important prerequisite for leveraging data driven solutions in the enterprise.”
Undated
Kleinerman advised using AI as an assistant rather than a decision maker for people matters such as hiring, citing input subjectivity and output variability.
“I would think of AI for people related matters as an assistant, not a decision maker.”
Undated
Kleinerman advised against large-scale AI rollouts such as buying 100,000 licenses, recommending small production use cases that are scaled if they succeed.
“Don't take on large-scale AI rollouts. When you hear, we're going to buy 100,000 licenses of XYZ solution and put it out there, and it's like, Well, do you even know if it works or not?”
Episodes