Dhanji R. Prasanna
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.
Episode
How Block is becoming the most AI-native enterprise in the world | Dhanji R. Prasanna
Summary
Dhanji R. Prasanna, CTO of Block, describes how Block with 4,000+ engineers became one of the most AI-native large enterprises — reporting 8-10 hours saved per week per engineer on AI-forward teams. He shares the story of Goose, Block's open-source AI coding agent that monitors Slack and proactively opens PRs, and Block's framework for AI adoption: make it opt-out, measure outcomes not keystrokes.
Key Takeaways
AI adoption should be opt-out, not opt-in: default everyone onto AI tooling and let skeptics opt out. The adoption curve is far steeper when the burden is on opting out.
Senior engineers benefit from AI at least as much as junior ones — they delegate tedious parts and spend more time on architecture and high-judgment decisions.
Measure AI impact through outcomes (PR merge rates, cycle time, feature completion) not keystroke counts or hours-on-keyboard.
Ambient agents like Goose — which monitor Slack and proactively build things engineers discuss — represent a qualitative shift from reactive to proactive automation.
Treat today's AI productivity gains as the absolute floor, not a ceiling — the value changes every day as models improve.
Notable Quotes
“And so all of this just kind of created a little bit of a spark of, "Hey, we're building technology again, we're trying to push the frontier again." And that's how it started, and then there were a whole number of steps after that where we went from a GM structure to a functional org structure, which was I think the key to making our transformation into being more of an AI-native company.”
“Not everyone was on board, I'll tell you that. It was quite a painful transformation. I think that one of the things that I learned the most throughout this process is that Conway's Law can be really, really powerful. So it's the law that basically says you ship your org structure. So what you're organized as in terms of teams, in terms of collaborating groups and your operating model matters a lot to what you build.”
“In the small, certain teams that are very, very AI natives or teams that are building AI first everywhere are working much differently than before because they're using vibe code tools and they're essentially building without writing lines of code by hand, and that just wasn't true through the three years ago. I don't think it was true anywhere in the world. So that's dramatically different in teams that are still working with very heavy legacy code bases.”