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AI Agents Real Help for GTM? Or overhyped Buzz? Adam Smith of Workbounce

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Manage episode 429329027 series 3563480
コンテンツは Coach K によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、Coach K またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

www.gtmaiacademy.com www.workbounce.com

AI Agents: The Future of Work or Just Another Buzz?

I recently had a fascinating conversation with Adam Smith CEO and Cofounder of Workbounce about the evolving landscape of AI in business. I wanted to understand his POV of how AI agents are revolutionizing workplace productivity, particularly in sales and enablement. Adam shared insights on WorkBounce's innovative approach to AI implementation, emphasizing the importance of context and human expertise in leveraging AI effectively. We also explored the broader implications of AI on work culture, decision-making, and future job markets.

Key Highlights: 1. WorkBounce's unique approach to AI agents for sales enablement 2. The concept of breaking down jobs into "units of work" for AI automation 3. The importance of providing context to AI for better outputs 4. The potential of AI to free us from screens and mundane tasks 5. The growing acceptance and demand for enterprise AI solutions 6. The challenges and opportunities for junior employees in an AI-driven workplace 7. The need for human expertise to guide and interpret AI outputs

Key Quotes from Adam:

"We don't believe... that you can really solve sales enablement as a top-down project."

"The main thing people misunderstand... is that [large language models are] really good at compressing information. They're not very good at expanding information."

"We're not even asking it to make up a good answer, we're saying, look at the sources and just tell us if there's an answer in there."

"The thing that I'm most excited about... is just the immediate short-term gain of can I get away from my screen and still do work successfully?"

"We have as human beings... a bandwidth problem, right? We can only read so many words per minute and we can only speak so many words per minute and type so many words per minute."

"If I don't have to understand every aspect of everything that I'm doing, and if I don't have to look at every single detail, this kind of feedback loop of having this kind of AI bandwidth shield around me that says, here are the important things." Loved the discussion and look forward to working with Adam and the team some more.

  continue reading

31 つのエピソード

Artwork
iconシェア
 
Manage episode 429329027 series 3563480
コンテンツは Coach K によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、Coach K またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

www.gtmaiacademy.com www.workbounce.com

AI Agents: The Future of Work or Just Another Buzz?

I recently had a fascinating conversation with Adam Smith CEO and Cofounder of Workbounce about the evolving landscape of AI in business. I wanted to understand his POV of how AI agents are revolutionizing workplace productivity, particularly in sales and enablement. Adam shared insights on WorkBounce's innovative approach to AI implementation, emphasizing the importance of context and human expertise in leveraging AI effectively. We also explored the broader implications of AI on work culture, decision-making, and future job markets.

Key Highlights: 1. WorkBounce's unique approach to AI agents for sales enablement 2. The concept of breaking down jobs into "units of work" for AI automation 3. The importance of providing context to AI for better outputs 4. The potential of AI to free us from screens and mundane tasks 5. The growing acceptance and demand for enterprise AI solutions 6. The challenges and opportunities for junior employees in an AI-driven workplace 7. The need for human expertise to guide and interpret AI outputs

Key Quotes from Adam:

"We don't believe... that you can really solve sales enablement as a top-down project."

"The main thing people misunderstand... is that [large language models are] really good at compressing information. They're not very good at expanding information."

"We're not even asking it to make up a good answer, we're saying, look at the sources and just tell us if there's an answer in there."

"The thing that I'm most excited about... is just the immediate short-term gain of can I get away from my screen and still do work successfully?"

"We have as human beings... a bandwidth problem, right? We can only read so many words per minute and we can only speak so many words per minute and type so many words per minute."

"If I don't have to understand every aspect of everything that I'm doing, and if I don't have to look at every single detail, this kind of feedback loop of having this kind of AI bandwidth shield around me that says, here are the important things." Loved the discussion and look forward to working with Adam and the team some more.

  continue reading

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