The Cloudcast

Building Customer-First Products


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Siqi Chen (@blader, CEO/CFO @Runwayco), talks about his journey from JPL developer to Founder of a financial planning and analysis (FP&A) startup. We focus on how to build products that customers crave and how a customer-centric view differs from traditional product management.

SHOW: 923

SHOW TRANSCRIPT: The Cloudcast #923 Transcript

SHOW VIDEO: https://youtube.com/@TheCloudcastNET 

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SHOW NOTES:

  • Runway website
  • Behind What Seems Like an Overnight Success (video)


Topic 1 - Welcome to the show, Siqi. First, your combination of technical and business/financial background is fascinating. How did you go from coding at NASA to Head of Product at Zynga to CEO/CFO for a finance platform startup? Give everyone a quick introduction.

Topic 2 - One thing I’ve noticed as a trend in your background is the core concept of building. What has been your philosophy in building products? How do you build products that customers demand?

Topic 3 -  Let’s talk about AI and AGI for a moment. We hear all the time how disruptive this will be. What are your thoughts here, and how do we develop both adaptability and resiliency to new technologies?

Topic 4 - Let’s talk FP&A (financial planning & analysis). Our core listeners out there tend to skew more towards the tech and infrastructure side, but a core theme of this show is always to be learning as much of the business as possible to apply those concepts. As someone with a background in both worlds, plus now running an FP&A startup, what do you wish folks on the technical side of the house knew more about to make their jobs easier?

Topic 5 - We posted a link in the show notes for a video you did on the “overnight success” of Runway. It was a good representation and origin story of how something can go viral with the right mindset and product-market fit. Tell everyone about that as Runway approaches 5 years now. 

Topic 6 - What is your biggest challenge in the FP&A space today? Is it AI? We’ve seen a lot of AI disruption in coding, legal, and other areas requiring deep data pool insights. Is this any different?


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