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Working backward from winning & preparing for future tech innovation w/ Evan Welbourne #181

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Manage episode 420784662 series 2869838
ELC and The Engineering Leadership Community (ELC)에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 ELC and The Engineering Leadership Community (ELC) 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

We discuss how to navigate the delicate balance between meeting current customer needs while also preparing for future tech trends & opportunities with Evan Welbourne, Head of AI and Data @ Samsara. Evan dissects the rapidly transforming pace of developing AI/ML products, sharing strategies for merging conversations around differing product-building processes, tips for moving seamlessly / gaining approval between product development stages, defining what customer success looks like, methods for working backward from problems, and best practices for avoiding friction throughout the product development process. He also shares frameworks for envisioning & working toward future tech possibilities while simultaneously developing hypotheses that inform future direction, creating diverse AI/ML team composition, and effectively communicating with stakeholders.

ABOUT EVAN WELBOURNE

Evan Welbourne is the Head of AI and Data and Samsara, leading the organization’s machine learning, computer vision, data science, and data analytics teams – as well as data engineering and data platform for the company. He has a long-standing career in both machine learning and IoT. Before Samsara, Evan held various roles at Amazon, including the Head of Machine Learning for Alexa Smart Home and Manager of the Computer Vision Research Group. He also led research teams at Samsung and Nokia.

Evan earned his Ph.D and M.S. in Computer Science and Engineering from the University of Washington and holds a B.S. in Computer Science and Mathematics from the University of Toronto.

"With AI, there's something new every week. You could stay in those stages forever. You can just keep iterating and trying new things, but at some point you have to kind of cut it off. You've got to time box it and just go with something that you know will work. You're constantly also calibrating between the quality of what you're delivering and the time it takes you to deliver it. A lot of that problem backs into this early stage of the process. We do want to do a good job of understanding opportunity but there's analysis paralysis. We don't want to just get stuck there.”

- Evan Welbourne

Join us at ELC Annual 2024!

ELC Annual is our 2 day conference bringing together engineering leaders from around the world for a unique experience help you expand your network and empower your leadership & career growth.

Don't miss out on this incredible opportunity to expand your network, gain actionable insights, ignite new ideas, recharge, and accelerate your leadership journey!

Secure your ticket at sfelc.com/annual2024

And use the exclusive discount code "podcast10" (all lowercase) for a 10% discount

SHOW NOTES:

  • Staying customer-focused while working toward the future @ Samsara (3:22)
  • Merging forward-looking technology & customer-problem-focused product-building conversations (5:54)
  • Defining customer success & working backwards from winning (8:38)
  • How stage gates can confirm / assess feature accuracy & maturity (10:58)
  • What the approval moment looks like while moving from stage to stage (15:29)
  • Understanding what stages offer the greatest opportunity for risk / friction (17:11)
  • Signals to watch for that allow you to move forward with confidence (19:30)
  • Best practices for anticipating & preparing for future possibilities (21:13)
  • Using smaller-scale projects to inform future direction of larger-scale products (23:12)
  • Communication strategies for working with less technical stakeholders (25:22)
  • Methods for effectively communicating complex, technical information (27:59)
  • AI / ML team composition at Samsara (30:04)
  • Frameworks for aligning & motivating folks to focus on customer needs (32:59)
  • Strategies for introducing new technologies & scientific research into your teams (35:06)
  • Introducing AI into mission-critical internal tools (36:34)
  • Rapid fire questions (39:17)

LINKS AND RESOURCES

This episode wouldn’t have been possible without the help of our incredible production team:

Patrick Gallagher - Producer & Co-Host

Jerry Li - Co-Host

Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/

Dan Overheim - Audio Engineer, Dan’s also an avid 3D printer - https://www.bnd3d.com/

Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

  continue reading

202 에피소드

Artwork
icon공유
 
Manage episode 420784662 series 2869838
ELC and The Engineering Leadership Community (ELC)에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 ELC and The Engineering Leadership Community (ELC) 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

We discuss how to navigate the delicate balance between meeting current customer needs while also preparing for future tech trends & opportunities with Evan Welbourne, Head of AI and Data @ Samsara. Evan dissects the rapidly transforming pace of developing AI/ML products, sharing strategies for merging conversations around differing product-building processes, tips for moving seamlessly / gaining approval between product development stages, defining what customer success looks like, methods for working backward from problems, and best practices for avoiding friction throughout the product development process. He also shares frameworks for envisioning & working toward future tech possibilities while simultaneously developing hypotheses that inform future direction, creating diverse AI/ML team composition, and effectively communicating with stakeholders.

ABOUT EVAN WELBOURNE

Evan Welbourne is the Head of AI and Data and Samsara, leading the organization’s machine learning, computer vision, data science, and data analytics teams – as well as data engineering and data platform for the company. He has a long-standing career in both machine learning and IoT. Before Samsara, Evan held various roles at Amazon, including the Head of Machine Learning for Alexa Smart Home and Manager of the Computer Vision Research Group. He also led research teams at Samsung and Nokia.

Evan earned his Ph.D and M.S. in Computer Science and Engineering from the University of Washington and holds a B.S. in Computer Science and Mathematics from the University of Toronto.

"With AI, there's something new every week. You could stay in those stages forever. You can just keep iterating and trying new things, but at some point you have to kind of cut it off. You've got to time box it and just go with something that you know will work. You're constantly also calibrating between the quality of what you're delivering and the time it takes you to deliver it. A lot of that problem backs into this early stage of the process. We do want to do a good job of understanding opportunity but there's analysis paralysis. We don't want to just get stuck there.”

- Evan Welbourne

Join us at ELC Annual 2024!

ELC Annual is our 2 day conference bringing together engineering leaders from around the world for a unique experience help you expand your network and empower your leadership & career growth.

Don't miss out on this incredible opportunity to expand your network, gain actionable insights, ignite new ideas, recharge, and accelerate your leadership journey!

Secure your ticket at sfelc.com/annual2024

And use the exclusive discount code "podcast10" (all lowercase) for a 10% discount

SHOW NOTES:

  • Staying customer-focused while working toward the future @ Samsara (3:22)
  • Merging forward-looking technology & customer-problem-focused product-building conversations (5:54)
  • Defining customer success & working backwards from winning (8:38)
  • How stage gates can confirm / assess feature accuracy & maturity (10:58)
  • What the approval moment looks like while moving from stage to stage (15:29)
  • Understanding what stages offer the greatest opportunity for risk / friction (17:11)
  • Signals to watch for that allow you to move forward with confidence (19:30)
  • Best practices for anticipating & preparing for future possibilities (21:13)
  • Using smaller-scale projects to inform future direction of larger-scale products (23:12)
  • Communication strategies for working with less technical stakeholders (25:22)
  • Methods for effectively communicating complex, technical information (27:59)
  • AI / ML team composition at Samsara (30:04)
  • Frameworks for aligning & motivating folks to focus on customer needs (32:59)
  • Strategies for introducing new technologies & scientific research into your teams (35:06)
  • Introducing AI into mission-critical internal tools (36:34)
  • Rapid fire questions (39:17)

LINKS AND RESOURCES

This episode wouldn’t have been possible without the help of our incredible production team:

Patrick Gallagher - Producer & Co-Host

Jerry Li - Co-Host

Noah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/

Dan Overheim - Audio Engineer, Dan’s also an avid 3D printer - https://www.bnd3d.com/

Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

  continue reading

202 에피소드

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