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Why ChatGPT Isn’t Ready to Be an SE

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Manage episode 447419563 series 3598876
المحتوى المقدم من Vivun. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Vivun أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

ChatGPT may excel in conversation, but it’s not equipped to tackle the complex challenges that sales engineers face.

In this episode, CEO Matt Darrow speaks with Vivun’s Product & AI Leader, Russell Witham, about the criteria for AI that actually “gets” sales engineering.

Most existing models fail to appreciate the complexity and true value of SE work, resulting in outputs that fall short of what great sales engineers produce.

Tune in to discover a new, innovative approach to empowering sales engineers with AI that understands them.

In this episode, you’ll learn:

  1. The Essence of Sales Engineering: The core role of a sales engineer lies in crafting tailored solutions that address customer needs rather than simply answering product questions or filling out RFPs.
  2. The Limitations of Current AI Models: While AI and large language models are gaining traction, they often lack the nuanced understanding required for effective sales engineering. Successful integration of AI requires structured data and a top-down approach to fully leverage its potential in sales processes.
  3. The Four Core Benefits AI for PreSales: By focusing on the 60% of what SEs do, AI can free SEs from administrative burdens, collapse enablement times, improve agility to pursue new target markets, and increase operational efficiency.

Things to listen for:

(00:00) How companies are using AI in sales engineering
(04:42) The essence of a sales engineer's role
(08:48) Why Claude & ChatGPT isn’t good enough
(10:03) The importance of structured data for effective solutions in sales engineering
(11:53) The need for detailed knowledge representation in AI applications
(15:46) Why current AI approaches fall short for sales engineering

  continue reading

21 حلقات

Artwork
iconمشاركة
 
Manage episode 447419563 series 3598876
المحتوى المقدم من Vivun. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Vivun أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

ChatGPT may excel in conversation, but it’s not equipped to tackle the complex challenges that sales engineers face.

In this episode, CEO Matt Darrow speaks with Vivun’s Product & AI Leader, Russell Witham, about the criteria for AI that actually “gets” sales engineering.

Most existing models fail to appreciate the complexity and true value of SE work, resulting in outputs that fall short of what great sales engineers produce.

Tune in to discover a new, innovative approach to empowering sales engineers with AI that understands them.

In this episode, you’ll learn:

  1. The Essence of Sales Engineering: The core role of a sales engineer lies in crafting tailored solutions that address customer needs rather than simply answering product questions or filling out RFPs.
  2. The Limitations of Current AI Models: While AI and large language models are gaining traction, they often lack the nuanced understanding required for effective sales engineering. Successful integration of AI requires structured data and a top-down approach to fully leverage its potential in sales processes.
  3. The Four Core Benefits AI for PreSales: By focusing on the 60% of what SEs do, AI can free SEs from administrative burdens, collapse enablement times, improve agility to pursue new target markets, and increase operational efficiency.

Things to listen for:

(00:00) How companies are using AI in sales engineering
(04:42) The essence of a sales engineer's role
(08:48) Why Claude & ChatGPT isn’t good enough
(10:03) The importance of structured data for effective solutions in sales engineering
(11:53) The need for detailed knowledge representation in AI applications
(15:46) Why current AI approaches fall short for sales engineering

  continue reading

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