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Content provided by Teasha Cable and CModel Data. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Teasha Cable and CModel Data 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://podcastplayer.com/legal.
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Why Most "What" Problems Are "Who" Problems

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Manage episode 504353210 series 3676734
Content provided by Teasha Cable and CModel Data. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Teasha Cable and CModel Data 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://podcastplayer.com/legal.

In this captivating episode, Teasha Cable sits down with Teja Yenamandra, co-founder and CEO of Gun.io, the premier talent matching platform that's achieved a remarkable 91% placement rate. Teja reveals how his company has revolutionized tech hiring by focusing on the quality of decisions developers make on actual projects, rather than traditional interview performance.

Discover why "most what problems are who problems," how to build teams where people make excellent decisions without your direct input, and why the best hiring approaches account for human psychology alongside systems design. Teja shares insights on scaling through venture capital, building a memo-driven culture, and why he considers sourcing one of the most intellectually challenging problems in business.

From startups to Fortune 500 companies, learn how Gun.io connects world-class software developers with meaningful opportunities through rigorous vetting and personalized matching. Plus, hear Teja's decision-making profile results and his framework for removing bias while maintaining the human touch in hiring.

This episode is essential listening for tech leaders, entrepreneurs, and anyone involved in talent acquisition who wants to understand how great companies are built through great people making great decisions.

Learn more:
Gun.io
CModel.io

Follow Teja on LinkedIn

Follow Teasha on LinkedIn

  continue reading

46 episodes

Artwork
iconShare
 
Manage episode 504353210 series 3676734
Content provided by Teasha Cable and CModel Data. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Teasha Cable and CModel Data 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://podcastplayer.com/legal.

In this captivating episode, Teasha Cable sits down with Teja Yenamandra, co-founder and CEO of Gun.io, the premier talent matching platform that's achieved a remarkable 91% placement rate. Teja reveals how his company has revolutionized tech hiring by focusing on the quality of decisions developers make on actual projects, rather than traditional interview performance.

Discover why "most what problems are who problems," how to build teams where people make excellent decisions without your direct input, and why the best hiring approaches account for human psychology alongside systems design. Teja shares insights on scaling through venture capital, building a memo-driven culture, and why he considers sourcing one of the most intellectually challenging problems in business.

From startups to Fortune 500 companies, learn how Gun.io connects world-class software developers with meaningful opportunities through rigorous vetting and personalized matching. Plus, hear Teja's decision-making profile results and his framework for removing bias while maintaining the human touch in hiring.

This episode is essential listening for tech leaders, entrepreneurs, and anyone involved in talent acquisition who wants to understand how great companies are built through great people making great decisions.

Learn more:
Gun.io
CModel.io

Follow Teja on LinkedIn

Follow Teasha on LinkedIn

  continue reading

46 episodes

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