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

Oct 26, 2025 1h 26m 27 insights Episode Page ↗
Donji Prasana, CTO at Block, discusses their company's AI-native transformation, including their open-source AI agent "Goose" which saves employees 8-10 hours weekly. He shares insights on cultural shifts, measuring AI impact, and future work paradigms.
Actionable Insights

1. Reorganize to Functional Structure

Shift from a General Manager (GM) structure to a functional organizational structure, where all engineers report to a single engineering leader. This is key to driving technical depth and company-wide AI adoption.

2. Embrace AI for Specific Tasks

Actively embrace AI tools to optimize your particular workday and specific tasks. People who do this are showing the most impact from these new technologies.

3. Prioritize Technical Excellence

Make advancing technical excellence a core company goal and focus. This involves getting back to thinking like a technology company and putting engineering and design first.

4. Automate Company-Wide with AI

Set company-wide AI automation as a top priority, aiming to integrate AI forms of automation throughout the entire organization. This is seen as just the beginning of AI’s utility.

5. Empower Non-Technical Teams with AI

Enable non-technical teams to build their own software tools using AI agents, compressing weeks of work into hours. This has been a surprising and energizing use of AI within Block.

6. Leadership Uses AI Daily

Drive AI adoption by having leadership and executives actively use AI tools themselves on a daily basis. This helps them understand workflow changes and integrate AI effectively.

7. Question Base Assumptions Constantly

Consistently question the fundamental assumptions behind processes and tools, asking if a project should be built at all or if a different approach would better serve the core purpose. This helps avoid unnecessary complexity and work.

8. Focus on Core Company Purpose

Always come back to your company’s core purpose and avoid distractions, especially when considering building in-house tools. If a solution doesn’t clearly serve that purpose, it might not be worth the mental bandwidth and technical focus.

9. Start Small, Iterate Rapidly

Begin projects with small experiments and narrow your scope to achievable tasks, avoiding the temptation to ‘boil the ocean.’ This approach allows for building momentum and adapting based on early learnings.

10. Hire for AI Adaptability

When hiring, prioritize candidates with a learning mindset who are eager to embrace and learn AI tools. This is more important than specific AI practitioner skills from the outset.

11. Anchor AI with Human Judgment

Use human taste and judgment to anchor AI outputs, ensuring they align with user value and avoid generic or ‘AI slop.’ This is crucial for maintaining quality and relevance.

12. Leverage AI for Overnight Experiments

Describe multiple different experiments in detail to AI agents, allowing them to build solutions overnight. This enables rapid iteration and the ability to discard less effective options quickly.

13. Be Willing to Discard AI Code

Develop a willingness to discard large amounts of AI-generated code if it doesn’t feel exactly right. This fosters a culture of rapid iteration and experimentation.

14. Automate UI Tests with AI

Utilize AI agents for automating UI tests, which can save significant time and resources compared to manual testing. This can be achieved by having AI operate the OS at a native level.

15. Focus Senior Engineers on Complexity

Direct senior engineers to focus on complex architecture, design, race conditions, and orchestration, as these are areas where AI still underperforms humans. AI can handle more routine tasks.

16. Avoid Blind AI Tool Application

Do not simply throw AI tools at giant codebases hoping for good things to happen. Instead, apply AI strategically to areas where it is most efficacious and adaptable to its evolving value.

17. Utilize Open-Source AI Agents

Download and extend open-source AI agents like Goose, which are built on open protocols, to integrate with existing enterprise tools. This allows for rapid AI orchestration across systems.

18. Experiment with Proactive AI Agents

Explore using AI agents that observe your workflow (e.g., screen activity, conversations) and proactively suggest or perform tasks to improve productivity. This can include anticipating needs or nudging you out of conflicts.

19. Automate Routine Personal Tasks

Use AI agents to automate complex personal tasks by orchestrating across different applications and APIs. An example is collecting and organizing receipts from various sources into a single, shareable format.

20. Allow AI Agents Flexibility

Give AI agents the flexibility to try multiple approaches and iterate until a solution is found, especially when initial attempts fail. This allows them to make progress on complex problems.

21. Understand Conway’s Law

Recognize that your organization’s communication structure will inevitably be reflected in the structure of the systems you build. Changing outcomes often requires changing the relationships and structure within your teams.

22. Regularly Step Back & Assess

Make time on a regular basis to step back and assess things holistically, applying judgment. This is crucial for ensuring focus on the right problems, especially when things are quiet.

23. Prioritize User Problems Over Code

Focus on solving real problems for people and getting products into their hands, rather than prioritizing perfect code quality or architecture. Product success has little to do with internal code elegance.

24. Foster Controlled Chaos

Create a foundation of reliability, then allow brilliant engineers the freedom to experiment and iterate, even if it sometimes leads to ‘waste of time’ projects. This can breed creativity and amazing results.

25. Demand Open Source & Broad Benefit

Demand that companies default to making solutions open source and building for the benefit of everyone, not just internal teams or customers. This aligns with the internet’s promise of open sharing.

26. Prioritize Meaningful & Enjoyable Work

If your professional life isn’t meaningful and fun, reconsider your involvement or make a change. Don’t accept a status quo that doesn’t energize you.

27. Overcome Fear of Change

Remind yourself that what seems like a monumental, life-changing problem in the moment often appears trivial in hindsight. This perspective can help overcome the fear of making necessary changes.