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E24: Self-Taught to Startup Success: The Unconventional Path of InfluxDB's Paul Dix

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Manage episode 422916973 series 3443743
Content provided by Data Council. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Data Council or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, I sit down with Paul Dix, the founder and CTO of InfluxData to explore his journey from a self-taught programmer to a leader in database systems. We discuss his role in building the NYC Machine Learning meetup, the creation of InfluxDB and the strategic move to make it open source. He shares insights into the decision to rewrite InfluxDB in 2020 and the power of community in tech development. We also touch on his transition from CEO to CTO and his advice for founders on making business-driven decisions. This discussion left me inspired and excited for the future of InfluxData.
Highlights:
[
00:48] - Paul shares his circuitous route towards getting to school after working in technology directly out of high school
[04:41] - Getting involved with Ruby meetups and developing applications on Rails
[05:50] - Paul talks about his motivation behind starting the New York Machine Learning meetup
[09:22] - We dive into how Paul's early experiences translated into what he built with InfluxDB
[15:08] - Paul shares how InfluxDB has approached open source and, later, commercialization, including how they've navigated challenges presented by the cloud providers
[21:57] - Paul talks through some of the changes they’ve made to InfluxDB recently and what motivated those changes
[27:40] - Digging into how the Influx team has taken a different approach to open source over the last few years
[28:42] - Paul shares advice for engineer-founders considering CEO vs. CTO roles

👉 👉 Don't forget to join us at Data Council Austin - where hundreds of data geeks, founders & investors join each other in building the future of data.

  continue reading

24 episodes

Artwork
iconShare
 
Manage episode 422916973 series 3443743
Content provided by Data Council. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Data Council or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, I sit down with Paul Dix, the founder and CTO of InfluxData to explore his journey from a self-taught programmer to a leader in database systems. We discuss his role in building the NYC Machine Learning meetup, the creation of InfluxDB and the strategic move to make it open source. He shares insights into the decision to rewrite InfluxDB in 2020 and the power of community in tech development. We also touch on his transition from CEO to CTO and his advice for founders on making business-driven decisions. This discussion left me inspired and excited for the future of InfluxData.
Highlights:
[
00:48] - Paul shares his circuitous route towards getting to school after working in technology directly out of high school
[04:41] - Getting involved with Ruby meetups and developing applications on Rails
[05:50] - Paul talks about his motivation behind starting the New York Machine Learning meetup
[09:22] - We dive into how Paul's early experiences translated into what he built with InfluxDB
[15:08] - Paul shares how InfluxDB has approached open source and, later, commercialization, including how they've navigated challenges presented by the cloud providers
[21:57] - Paul talks through some of the changes they’ve made to InfluxDB recently and what motivated those changes
[27:40] - Digging into how the Influx team has taken a different approach to open source over the last few years
[28:42] - Paul shares advice for engineer-founders considering CEO vs. CTO roles

👉 👉 Don't forget to join us at Data Council Austin - where hundreds of data geeks, founders & investors join each other in building the future of data.

  continue reading

24 episodes

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