Lenny's Podcast

Dhanji Prasanna: How Goose agents save Block 10 hours a week

After Block reorganized from GM silos into one functional org; the open-source Goose platform now saves AI-forward teams 8 to 10 hours weekly.

Lenny RachitskyhostDhanji R. Prasannaguest

Oct 25, 20251h 26mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

Inside Block’s AI Revolution: Goose Agents, Culture Shifts, Real Productivity

CTO Dhanji R. Prasanna explains how Block became one of the most AI‑native large enterprises, centered around their open-source AI agent platform, Goose. Goose and its mobile cousin Gosling are already saving employees roughly 8–10 hours per week on average in AI-forward teams, with early data suggesting 20–25% manual hours saved company‑wide. The transformation wasn’t just about tools: Block redefined itself as a technology company, reorganized from GM-based business silos into a functional org, and pushed leaders to personally use AI in their daily work. Along the way, Dhanji shares counterintuitive lessons on org design, when not to build tools, and why code quality is largely orthogonal to product success.

IDEAS WORTH REMEMBERING

5 ideas

Organizational structure is more decisive than tools for AI impact.

Block’s biggest unlock was moving from GM-run business silos to a functional structure where all engineers and designers report into single leaders, enabling shared platforms, consistent standards, and a unified AI strategy.

AI is already saving substantial time—this is the new baseline, not the peak.

AI-forward teams using Goose report 8–10 hours saved per week, and Block estimates 20–25% manual hours saved across the company, yet Dhanji emphasizes these are early, conservative numbers that will only grow as models improve.

Non-technical teams may gain the most from AI agents right now.

Functions like risk, legal, and support are using Goose to build internal tools and automate workflows themselves, compressing weeks of engineering requests into hours and dramatically reducing bottlenecks on central eng teams.

Leaders must use AI personally to drive real adoption.

Jack Dorsey, Dhanji, and the executive team all use Goose and other AI tools daily; their firsthand experience with what AI can and can’t do has been more impactful than any top-down mandate or slide deck.

Agents should work continuously and explore multiple options, not just respond on demand.

Dhanji envisions a near future where LLM agents run for hours or overnight—building multiple versions of features, refactoring code, and even improving themselves—so that humans wake up to options instead of empty backlogs.

WORDS WORTH SAVING

5 quotes

Our number one priority is to automate Block.

— Dhanji R. Prasanna

This is the worst it will ever be. This is now the baseline.

— Dhanji R. Prasanna

A lot of engineers think that code quality is important to building a successful product. The two have nothing to do with each other.

— Dhanji R. Prasanna

All these LLMs are sitting idle overnight and on weekends while humans aren’t there. There’s no need for that.

— Dhanji R. Prasanna

If you’re not waking up in the morning feeling energized about what you’re going to do that day in your professional life, then change something.

— Dhanji R. Prasanna

Block’s transition to an AI-native, technology-first companyGoose: Block’s open-source AI agent platform and the MCP ecosystemPractical productivity gains from AI across technical and non-technical teamsReorg from GM/business-unit structure to functional org (engineering/design-first)The future of software development: autonomous agents, vibe coding, frequent rewritesCultural adoption of AI, hiring profiles, and leadership’s roleCounterintuitive lessons on product success, code quality, and process vs. tools

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