Lenny's Podcast: Product | Career | Growth

How Block is becoming the most AI-native enterprise in the world | Dhanji R. Prasanna

October 26, 2025

AI Summary

5 min read

Block's CTO Dhanji Prasanna describes how the company reoriented as a technology-first organization and integrated AI deeply, particularly through their open-source agent Goose, which automates tasks and saves engineering teams 8-10 hours weekly while trending toward 20-25% company-wide manual hour reductions.

Shift to Functional Structure

Block transitioned from a general manager (GM) model—treating business units like Square and Cash App as independent companies with separate engineering and design teams—to a functional structure where all engineers and designers report to single leaders. This change, inspired by recognizing identity drift away from tech roots, enabled shared tools, policies, and technical strategy across units, per Conway's Law (org structure shapes products). It fostered alignment, mobility between teams, and technical depth, outweighing AI tools in productivity gains like faster builds through test suite optimization and deletions.

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What you'll learn

1 **[00:05:34] AI Manifesto & Path to CTO**
2 **[00:07:53] Refocus as Tech Company**
3 **[00:08:25] GM to Functional Org Shift**
4 **[00:15:46] AI Productivity Gains & Goose Overview**
5 **[00:21:49] Goose Deep Dive: Tech & Adoption**
6 **[00:28:41] Extreme AI Use & Future Engineering**
7 **[00:44:34] Hiring, Interviews & Culture**

+ Full timestamped outline available in the app

Show Notes

Dhanji R. Prasanna is the chief technology officer at Block (formerly Square), where he’s managed more than 4,000 engineers over the past two years. Under his leadership, Block has become one of the most AI-native large companies in the world. Before becoming CTO, Dhanji wrote an “AI manifesto” to CEO Jack Dorsey that sparked a company-wide transformation (and his promotion to CTO).

We discuss:

1. How Block’s internal open-source agent, called Goose, is saving employees 8 to 10 hours weekly

2. How the company measures AI productivity gains across technical and non-technical teams

3. Which teams are benefiting most from AI (it’s not engineering)

4. The boring organizational change that boosted productivity even more than AI tools

5. Why code quality has almost nothing to do with product success

6. How to drive AI adoption throughout an organization (hint: leadership needs to use the tools daily)

7. Lessons from building Google Wave, Google+, and other failed products

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Where to find Dhanji R. Prasanna:

• LinkedIn: https://www.linkedin.com/in/dhanji/

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Where to find Lenny:

• Newsletter: https://www.lennysnewsletter.com

• X: https://twitter.com/lennysan

• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/

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In this episode, we cover:

(00:00) Introduction to Dhanji

(05:26) The AI manifesto: convincing Jack Dorsey

(07:33) Transforming into a more AI-native company

(12:05) How engineering teams work differently today

(15:24) Goose: Block’s open-source AI agent

(20:18) Measuring AI productivity gains across teams

(21:38) What Goose is and how it works

(32:15) The future of AI in engineering and productivity

(37:42) The importance of human taste

(40:10) Building vs. buying software

(44:08) How AI is changing hiring and team stru