How Block is becoming the most AI-native enterprise in the world | Dhanji R. Prasanna
2025-10-26 · 87 min · 69 entities
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Episode description as stored
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
—
Brought to you by:
Sinch —Build messaging, email, and calling into your product: https://sinch.com/lenny
Figma Make —A prompt-to-code tool for making ideas real: https://www.figma.com/lenny/
Persona —A global leader in digital identity verification: https://withpersona.com/lenny
—
Where to find Dhanji R. Prasanna:
• LinkedIn: https://www.linkedin.com/in/dhanji/
—
Where to find Lenny:
• Newsletter: https://www.lennysnewsletter.com
• X: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
—
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 structure
(53:45) The importance of using AI tools yourself before deploying them
(55:13) How Goose helped solve a personal problem with receipts
(58:01) What makes Goose unique
(59:57) What Dhanji wishes he knew before becoming CTO
(01:01:49) Counterintuitive lessons in product development
(01:04:56) Why controlled chaos can be good for engineering teams
(01:08:07) Core leadership lessons
(01:13:36) Failure corner
(01:15:50) Lightning round and final thoughts
—
Referenced:
• Jack Dorsey on X: https://x.com/jack
• Block: https://block.xyz/
• Square: https://squareup.com/
• Cash App: https://cash.app/
• What is Conway’s Law?: https://www.microsoft.com/en-us/microsoft-365-life-hacks/organization/what-is-conways-law#
• Goose: https://github.com/block/goose
• Gosling: https://github.com/block/goose-mobile
• Salesforce: https://www.salesforce.com/
• Snowflake: https://www.snowflake.com/
• Claude: https://claude.ai/
• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann
• OpenAI: https://openai.com/
• OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai
• Llama: https://www.llama.com/
• Cursor: https://cursor.com/
• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell
• Top Gun : https://www.imdb.com/title/tt0092099/
• Lenny’s vibe-coded Lovable app: https://gdoc-images-grab.lovable.app/
• Afterpay: https://github.com/afterpay
• Bitkey: https://bitkey.world/
• Proto: https://github.com/proto-at-block
• Brad Axen on LinkedIn: https://www.linkedin.com/in/bradleyaxen/
• Databricks: https://www.databricks.c