In this episode, Aaron Lee, Founder & CEO of Smith.ai joins me to discuss a variety of topics. First, we delve into the innovative strategies of tech giants like Google, and explore the future of AI in business. Then we journey back to the early days at Smith.ai, where AI was used to enhance productivity. Aaron shares a multitude of learnings from his time founding RedBeacon and then serving as CTO of Home Depot following its acquisition of RedBeacon. Next, we dig into the complexities of teaching machines to understand context, tone and nuance, and the potential for AI to develop emotional intelligence. We also explore the 'human in the loop' model, where AI efficiency is combined with human reasoning for maximum impact. Finally, we get to know Aaron a bit better through our Quantum Round of rapid-fire questions.Highlights[1:15] - Aaron walks us through his professional background, particularly digging into how his time at Google impacted him[2:27] - We speak high-level about the idea for Smith.ai[3:00] - Diving into how founding his first company impacted Aaron’s founding of smith.ai and how his customer learnings informed smith.ai[4:34] - Technical challenges in building RedBeacon and what interested Aaron about starting a marketplace company when he did. Aaron shares how necessary it is to balance supply and demand at marketplace companies.[6:12] - Considering verticals as well as going deep vs. wide when building marketplace companies, and then understanding what core tech will enable the marketplace you’ve decided to create[8:37] - Matching components as core values in marketplace companies and how the quality of those matches is key to being successful. The matching in the beginning requires going deep in one vertical to start before expanding further.[10:27] - The story of Home Depot acquiring RedBeacon and Aaron’s time as CTO at Home Depot plus the lessons he took away[12:50] - How scale impacts your perspective on how multiple audiences are interacting with your software and the need for ease-of-use when you have a massive number of people needing to use your software[15:06] - The origin story of Smith.ai and the core problem they were trying to solve as well as where they saw opportunities[17:36] - In the early days of smith.ai (before all of the advances in LLMs), exploring how far were the team was able to get in removing challenges for customers using AI as a copilot vs. an actual participant in calls[19:14] - What AI excels at vs. what humans excel at when it comes to using AI in customer service applications[20:12] - Sharing thoughts on AI’s ability to develop human-like emotions/EQ and if there’s specific architecture that can help solve that problem[23:02] - Exploring the human-in-the-loop idea and the power and limitations of AI systems as well as how to pitch software vs. services companies or companies that combine the two[28:40] - Quantum Round of rapid-fire questions👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

In this episode, we debut a new format where engineer-founders discuss key tech topics. Joined by Graham Thompson of Privacy Dynamics and Debo Ray of DevZero, we dive into modern software development. Topics include the role of developer productivity, challenges of new productivity tools and the problems that arise around data access. We also discuss the evolving role of database administrators, the shift to cloud-hosted dev environments and the impact remote development environments have on tech hiring. The episode wraps up with insights on infrastructure as code, the concept of a minimum valuable product and future trends in software development.Highlights[0:03] - Meet Graham Thompson, founder of Privacy Dynamics and Debo Ray, founder of DevZero, each working to revolutionize software development by improving developer productivity and experiences. [3:22] - Unpacking the crucial role of developer productivity in tech companies and the challenges of introducing new productivity tools. [6:31] - Exploring the evolution of database administration roles to platform engineering and its impact on setting up test environments.[9:18] - The rise of cloud-hosted development environments: how they're slashing start times for engineers and boosting efficiency.[10:28] - Navigating the new normal: how remote development environments are reshaping the tech hiring landscape.[12:03] - Cloud vs. local: weighing the pros and cons of moving development to the cloud. [16:20] - Leveraging infrastructure as code for efficient cloud management: empowering platform engineers to make more informed adjustments.[17:37] - The power of minimum valuable product: speed and efficiency in today's market.[20:43] - Predicting the future of the software development lifecycle and development environments.👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

In this episode, I have the pleasure of hosting Spencer Kimball, a former Google engineer turned tech entrepreneur, and now the Co-Founder & CEO of Cockroach Labs. Spencer shares his journey from working at Google to creating his project, Viewfinder, which eventually led to the birth of CockroachDB. Spencer discusses his advice for founders as they approach the challenge of starting a company, finding co-founders, and more. We also delve into the decision to change CockroachDB's licensing to protect it from being monetized by other companies. Highlights[00:00] - From Google engineer to tech entrepreneur, Spencer shares his journey and the birth of his project, Viewfinder. He reveals the dream that sparked his desire for more than just a tech job at Google. [01:02] - The struggle to find a suitable database for Viewfinder led to the creation of CockroachDB. Spencer discusses the need for a scalable, transactional, and open-source database that didn't yet exist.[03:24] - Passion and belief are key to weathering the ups and downs of a startup. Spencer shares how a founder's vision can drive the company forward despite inevitable disappointments.[08:53] - Finding the right co-founder is crucial. Spencer shares his advice, emphasizing the importance of shared experiences and mutual respect.[13:09] - The need for a database that could handle rapid growth and complexity was the key insight behind Cockroach Labs. Spencer discusses how this need led to the creation of CockroachDB.[18:40] - To protect CockroachDB from being monetized by other companies, Spencer explains the decision to change its licensing. He also discusses the challenges of balancing open source with business needs.[20:59] - The story of Elastic serves as a cautionary tale. Spencer shares how Amazon exploited Elastic's open core business model, leading to a reevaluation of Cockroach Labs' own model.[21:53] - The Business Source License (BSL) at Cockroach Labs provides a time period of protection from direct competition. Spencer explains how it reverts to a pure open source license after a certain term.[26:01] - Quantum Round (Rapid-fire questions)👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

Today on the podcast, I interview DJ Patil, an entrepreneur, investor, scientist and leader in public policy. The former (and first) U.S. Chief Data Scientist, DJ wrote the book on being Data Driven (literally: O'Reilly Data Driven) and now puts his knowledge to work as General Partner of Great Point Ventures. Highlights00:29 - Intro[1:50] - A discussion of the “Sexiest Job in History: Data Scientist” HBR article and how data science has changed since that article's publication[5:00] - As far as we've come with Data Science, there are still problems - DJ shares some of the problems he sees that remain and how the Data Science community helps solve them[5:43] - We dig into the emergence of the Data Engineer as a key role due to the requirements of usable data for Data Science (cleaning, prepping, etc.)[9:00] - Data Challenges are culture problems moreso than deployment or process challenges - it's more about how to think in the proper way and get an entire organization on the same page[10:10] - We discuss some of the difficulties of introducing ideas into the public sphere/government and how to create strategies to overcome them[14:44] - How the Data Community helped via "crowdsourcing" with the national Covid response[17:52] - Building off of the Covid response, DJ explains why he's begun to think of Data Scientists as a new kind of First Responder[19:51] - How do we make use of data in organizations and how do startups compare to enterprises when it comes to making use of data?[25:33] - Platform/Infrastructure shifts surrounding AI, LLMs, generative AI and how the industry is responding as well as how founders can better collaborate/respond[27:37] - Quantum Round (Rapid-fire questions)👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

Today on the podcast, I interview Matt Fuller, the co-founder of Starburst. Matt has worked in data for years ....Highlights[1:00] - How Matt got into data & the C-Store paper which led to him joining Vertica, an early columnar database prior to technologies like Hadoop, HDFS or Parquet[3:45] - The increasing adoption of OSS data storage tools and the growth of the Hadoop ecosystem that ultimately led up to Presto/Trino[6:00] - How Matt took the plunge as an engineer-founder to become a co-founder of Starburst and had to wear many different hats across customer support, GTM and product[10:20] - Matt's experience as a bridge between customer problems and the engineering team, and how to tailor your discussions to the appropriate place in the org that the customer contact sits[14:20] - How  OSS changes the GTM dynamic of an enterprise product[16:30] - What Matt is excited about regarding the future of Trino - the lakehouse architecture and open formats for data lakes (like Iceberg), and the Starburst SaaS product (Starburst Galaxy)👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

In this episode, I interview Eric Sammer, the founder & CEO of Decodable. Eric was previously an engineering manager at Cloudera, and before that the founder of Rocana, an early observability company that was sold to Splunk. Eric has an amazing perspective on the architecture of data systems based on his years of experience in the field. We chat about his thoughts on the opportunities and challenges specifically around streaming data. Highlights:[1:45] - Eric's start in ad-tech, which led him into the high-volume data world plus his experiences at Cloudera working on Avro, Parquet & Impala - an alternative to Hive & Presto[4:45] - Eric's opportunistic path to starting a company as an engineer[7:15] - Lessons learned while building his first company, Rocana, which was sold to Splunk in 2017, plus insights on the right way to find product-market fit [10:50] - Eric's thoughts on why the time for streaming is now and how the use cases have surpassed fraud, waste and abuse + his tech stack of choice (Debezium, Kafka & Flink)[14:55] - How streaming fits in the operational data landscape (OLTP)[17:10] - Eric's thoughts on the value in streaming analytics (OLAP) and how ML models might get bigger benefits from streaming than dashboards do[22:20] - Preview of the Streaming Data track @ Data Council Austin '23 where Eric is the track host👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

Josh Benamram is the the co-founder & CEO of Databand, a data observability company acquired by IBM. We’ll discuss Josh’s segue from an early career in venture capital, into becoming a product manager for a business intelligence company (Sisense) and then becoming a founder himself, where he eventually exited his company to IBM.Highlights:[2:00] - How Josh's start in finance led to his career in startups[6:25] - How working on cloud data warehouse connectors at Sisense, plus the growing need for data engineering led to the insight to start Databand[9:30] - Josh's thoughts on the difference between data quality & data observability and how vendors in this market have exploded[15:20] - The story to sell Databand to IBM - motivation and key issues in the decision, and  how the mechanics of the relationship transpired[19:45] - Josh's predictions on the data observability landscape for the future 👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

Alexis Le-Quoc, co-founder and CTO of Datadog, shares his entrepreneurial journey and insights on the tech landscape. He reflects on the early days of Datadog, discussing the unique challenges of raising capital in NYC and the pivotal moments in product development. Alexis emphasizes the importance of persistence and customer feedback for engineer-founders, exploring how to balance user needs in tech. He also delves into his angel investing experiences, highlighting the qualities he values in aspiring founders.

Brad is a repeat founder and is currently the co-founder of Census, an SF company that syncs customer data to go-to-market tools. Brad shares his path from initially joining a startup as an engineer and continuing on to become a co-founder himself.Highlights:[1:20]: on choosing Ruby for early stage product hacking & data integration[5:01]: Brad’s path from AWS engineer to startup engineer to becoming a founder himself[7:44]: insights on how to listen to customers and figure out the right product to build[11:10]: how they handled customer discovery w/ multiple co-founders[13:25]: on moving from prototype to product[17:10]: perspective on what Brad is excited to be building at Census[22:05]: on developing founder instincts + team building👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.

Pete chats with Wes McKinney, the inspiration behind many popular OSS data & data science tools like pandas, Apache Arrow, Ibis and others. We learn from Wes' experience in starting businesses around OSS tooling, and hear his thoughts on monetization, ecosystem building and challenges in starting his companies as an engineer-founder.Wes is currently the co-founder & CTO of Voltron Data, which is building accelerated computing technologies powered by Apache Arrow.Highlights:[0:50]: Wes’ thoughts on monetizing open source software (OSS)[3:10]: Potential ways of turning a library/utility into a business[4:53]: Example of DuckDB Labs + Motherduck partnership[7:05]: Advice that Wes would give other engineer-founders[11:00]: Working with design partners & early customers[13:02]: Building relationships across the Arrow ecosystem[14:45]: What’s the true value of OSS from Wes’ perspective[17:03]: Wes’ advice on personal brand building as an engineer👉 👉 Don't forget to join us at Data Council - where hundreds of data geeks, founders & investors join each other in building the future of data.