How to Reorg After AI Changes Everything | Block's Owen Jennings on the a16z Show

David Haber speaks with Owen Jennings, executive officer and business lead at Block, about how the company rebuilt itself around AI agents, small squads, and internal tools like Goose and Builder Bot after restructuring more than 40% of its workforce. They discuss what it took to execute a major restructuring, how teams of three are now doing what teams of 14 used to, and how Block is shipping AI-native products like Money Bot and Manager Bot that generate custom interfaces on the fly for tens of millions of users. Timestamps: 0:00—Introduction 6:06—How the RIF Actually Executed 9:08—The Most Meaningful Difference in How We're Operating 12:57—AI Infrastructure Build Across the Org 17:09—The Shape of the Business: Square, Cash App, Afterpay 20:00—From Static UI to Generative UI 23:23—Defensibility in the AI Era Read the full transcript here: https://www.a16z.news/s/podcast Resources: Follow Owen Jennings on X: https://twitter.com/owenbjennings Follow David Haber on X: https://twitter.com/dhaber Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Owen JenningsguestDavid Haberhost

Mar 31, 202627mWatch on YouTube ↗

WHAT IT’S REALLY ABOUT

Block reorganizes around AI agents, shrinking teams, accelerating product delivery

Block’s ~40% reduction in force was driven primarily by a step-change in AI-assisted productivity, especially once models became effective on large legacy codebases, allowing far smaller teams to ship comparable roadmaps.
The reorg was designed “from first principles” around reliability, regulatory/compliance safety, and durable growth, with development teams changing most while compliance capacity was largely protected.
Day-to-day work shifted from linear, meeting-heavy execution to supervising many parallel AI agents that draft PRs, automate workflows, and compress idea-to-production timelines.
Block invested in internal AI infrastructure (Goose agent harness, G2 agentic OS, Builder Bot) to make AI model-agnostic, deeply integrated with company systems, and usable beyond engineering in ops and support.
On the product side, Block is moving from static interfaces to generative UI via bots like Money Bot and Manager Bot, while grappling with QA, non-determinism, and proactive prompting to create customer value.

IDEAS WORTH REMEMBERING

5 ideas

AI broke the historic “more headcount = more output” assumption at Block.

Jennings argues that once AI tools became strong on complex existing codebases, one or two “on-the-tools” builders could be 10–100x more productive, changing the optimal staffing for a given roadmap.

Block treated the RIF as an org redesign problem, not a cost-target exercise.

Instead of picking a percentage to hit financial goals, leadership asked what the company should look like with AI in the loop, guided by reliability, customer trust/regulatory posture, and continued growth bets.

Development orgs change first and most when AI becomes a true production tool.

Cuts were concentrated on development while functions like outbound sales saw minimal reductions, and compliance teams were intentionally protected to avoid regulatory and safety risks.

Work becomes “agent supervision,” not sequential task completion.

Teams shift from linear PR workflows to running many agents in parallel (writing PRs, drafting docs, automating steps), with humans context-switching to review, nudge, and finalize outputs.

Internal AI infrastructure is a strategic prerequisite, not a nice-to-have.

Goose (model-agnostic agent harness), G2 (agentic OS for deterministic workflow automation), and Builder Bot (autonomous feature-building/merging) make AI adoption scalable and integrated rather than ad hoc.

WORDS WORTH SAVING

5 quotes

There's been this correlation between the number of folks at a company and the output from the company uh, for, you know, decades and decades. I think that basically broke the first week of December, and what we were seeing is that one or two engineers or a, a designer and an engineer who is on the tools, quote unquote, a-as we say, is able to be 10, 20, 100X more productive.

— Owen Jennings

You don't make really, really significant cuts on the development side if you're not seeing a technology and a tool that's just fundamentally changed how we build. I mean, we're, we're, like, we're not writing code by hand anymore. That's over. That's done.

— Owen Jennings

We said, "What should the org look like given how these AI tools are flowing through now and what we expect to happen in the, in the coming months and quarters?"

— Owen Jennings

The biggest shift, uh, uh, myself included, I, I have, you know, countless agents running right now that I have to go, I have to go check on. Uh, it's, it's not, um, it's less of a linear workflow, and it's more of like in the background there's ten or twenty agents who are doing a whole bunch of stuff, and then I have to check in on the work and nudge it and change it and what have you.

— Owen Jennings

I think the, the biggest moat is gonna be like which companies understand something that's super hard for other people to understand. And if your answer to that is, is, um, "I don't know," then, uh, then you maybe could get vibe coded away.

— Owen Jennings

40%+ RIF rationale and timing shift in model capabilityFounder-led decisiveness vs incremental layoffsMeeting reduction, fewer layers, wider spans of controlSmall squads and fluid staffing across productsGoose agent harness and model-agnostic orchestrationBuilder Bot autonomously building/merging PRsGenerative UI (Money Bot/Manager Bot), proactive intelligence, QA risk

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