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Sequoia Capital에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sequoia Capital 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.
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Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent

59:43
 
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Manage episode 509242261 series 3586723
Sequoia Capital에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sequoia Capital 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.

As CTO of Block, Dhanji Prasanna has overseen a dramatic enterprise AI transformation, with engineers saving 8-10 hours a week through AI automation. Block’s open-source agent goose connects to existing enterprise tools through MCP, enabling everyone from engineers to sales teams to build custom applications without coding. Dhanji shares how Block reorganized from business unit silos to functional teams to accelerate AI adoption, why they chose to open-source their most valuable AI tool and why he believes swarms of smaller AI models will outperform monolithic LLMs.

Hosted by: Sonya Huang and Roelof Botha, Sequoia Capital

Mentioned in the episode:

  • goose: Block’s open-source, general-purpose AI agent used across the company to orchestrate workflows via tools and APIs.

  • Model Context Protocol (MCP): Open protocol (spearheaded by Anthropic) for connecting AI agents to tools; goose was an early adopter and helped shape.

  • bitchat: Decentralized chat app written by Jack Dorsey

  • Swarm intelligence: Research direction Dhanji highlights for AI’s future where many agents (geese) collaborate to build complex software beyond a single-agent copilot.

  • Travelling Salesman Problem: Classic optimization problem cited by Dhanji in the context of a non-technical user of goose solving a practical optimization task.

  • Amara’s Law: The idea, originated by futurist Roy Amara in 1978, that we overestimate tech impact short term and underestimate long term.

    00:00 Introduction

    01:48 AI: Friend or Foe?

    03:13 Block's Journey with AI and Technology

    04:47 Block's Diverse Product Range

    07:04 Driving AI at Block

    14:28 The Evolution of Goose

    27:45 Integrating Goose with Existing Systems

    28:23 Goose's Learning and Recipe Feature

    29:41 Tool Use and LLM Providers

    31:40 Impact of AI on Developer Productivity

    34:37 Block's Commitment to Open Source

    39:09 Future of AI and Swarm Intelligence

    43:05 Remote Work at Block

    45:15 Vibe Coding and AI in Development

    48:43 Making Goose More Accessible

    51:28 Generative AI in Customer-Facing Products

    54:09 Design and Engineering at Block

    55:38 Predictions for the Future of AI

  continue reading

66 에피소드

Artwork
icon공유
 
Manage episode 509242261 series 3586723
Sequoia Capital에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Sequoia Capital 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.

As CTO of Block, Dhanji Prasanna has overseen a dramatic enterprise AI transformation, with engineers saving 8-10 hours a week through AI automation. Block’s open-source agent goose connects to existing enterprise tools through MCP, enabling everyone from engineers to sales teams to build custom applications without coding. Dhanji shares how Block reorganized from business unit silos to functional teams to accelerate AI adoption, why they chose to open-source their most valuable AI tool and why he believes swarms of smaller AI models will outperform monolithic LLMs.

Hosted by: Sonya Huang and Roelof Botha, Sequoia Capital

Mentioned in the episode:

  • goose: Block’s open-source, general-purpose AI agent used across the company to orchestrate workflows via tools and APIs.

  • Model Context Protocol (MCP): Open protocol (spearheaded by Anthropic) for connecting AI agents to tools; goose was an early adopter and helped shape.

  • bitchat: Decentralized chat app written by Jack Dorsey

  • Swarm intelligence: Research direction Dhanji highlights for AI’s future where many agents (geese) collaborate to build complex software beyond a single-agent copilot.

  • Travelling Salesman Problem: Classic optimization problem cited by Dhanji in the context of a non-technical user of goose solving a practical optimization task.

  • Amara’s Law: The idea, originated by futurist Roy Amara in 1978, that we overestimate tech impact short term and underestimate long term.

    00:00 Introduction

    01:48 AI: Friend or Foe?

    03:13 Block's Journey with AI and Technology

    04:47 Block's Diverse Product Range

    07:04 Driving AI at Block

    14:28 The Evolution of Goose

    27:45 Integrating Goose with Existing Systems

    28:23 Goose's Learning and Recipe Feature

    29:41 Tool Use and LLM Providers

    31:40 Impact of AI on Developer Productivity

    34:37 Block's Commitment to Open Source

    39:09 Future of AI and Swarm Intelligence

    43:05 Remote Work at Block

    45:15 Vibe Coding and AI in Development

    48:43 Making Goose More Accessible

    51:28 Generative AI in Customer-Facing Products

    54:09 Design and Engineering at Block

    55:38 Predictions for the Future of AI

  continue reading

66 에피소드

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