We reject: kings, presidents, and voting. We believe in: rough consensus and running code. —David Clark, 1992

“Above all, do not lose your desire to walk.” — Søren Kierkegaard

Now launching: Cash App is now the first major U.S. payments app to let you pay over time on money you've already sent. Convert P2P sends into installments — transparent fee, no compounding interest, six-week term. Eligible for sends of $25+ made in the last 30 days.

This drip is different

This is fire and something all artists should do

Block has an incredible world class hardware team. You can tell by the passion that goes into the design of all our physical products. The Square Handheld was one of my favorite products I had the pleasure of working on last year. Here’s a snippet of one of my favorite sequences.

There is no line to pass. No AI box to check. Your creativity is no longer gated by technical expertise. If that doesn’t excite you, you’ll get beat as an IC.

Block is bringing back the bitcoin faucet. The original, launched by Gavin Andresen in 2010, gave away 5 BTC to anyone who solved a CAPTCHA. That's $500,000 per person at today's prices. The new version goes live April 6 at btc.day.

Little one, but helpful You can now add money with Apple Pay on @CashApp

tuitter - twitter for your terminal

people are sleeping on how excellent goose has become under the hood (interface needs some work but team is pushing). it's a superpower. github.com/block/goose

Block just open-sourced mesh-llm, a peer-to-peer system that lets anyone pool spare GPU compute to run large open-source AI models without relying on any cloud provider. If a model fits on your machine, it runs locally at full speed. If it doesn't, the system automatically splits it across multiple machines on the network. Dense models get split by layers. Mixture-of-experts models like DeepSeek and Qwen3 get split by experts. Zero configuration required. Discovery happens over Nostr. Nodes find each other through relays, score by region and VRAM, and self-organize. No central server coordinates anything. Weights are read from local files, never sent over the network. Dead nodes get replaced in 60 seconds. It exposes a standard OpenAI-compatible API on localhost, meaning any existing AI tool can plug in without modification. Block is building infrastructure for AI that doesn't route through OpenAI, Google, or Anthropic. Frontier-class open models running across a mesh of commodity hardware, discovered via Nostr, with no cloud dependency. That's the direction AI needs to go.

"In practice, Spectre is the beginning of a company world model: a live picture of what is happening inside Harvey and what needs to happen next." harvey.ai/blog/autonomous-ag…

NEW EPISODE: @jack & @roelofbotha unpack @blocks 40% staff cut and rebuilding the entire company as a mini-AGI. This isn’t “use AI to make people more productive.” It’s making the company itself the intelligence. If you’re a founder or operator wondering what work looks like in the next 5 years… this is the episode. The evolution looks like: • Manager mode = Pyramid 🔺 (command & control) • Founder mode = Flat ➖(founders decide fast) • Dorsey mode = Circle 🔵 w/ AI at the center, humans at the edge, and decisions flow from customer inputs → AI → humans steering it I’ve tried killing org charts before. Brutally hard. But we never had these tools. This is rewriting the CEO playbook for the AI era. Buckle up. 00:00 Existential Dread & Hope 02:56 AI Replaces Hierarchy 07:22 Block’s New Three Roles 26:47 Flattening the Company, Fast 35:23 Getting the Board to Buy-In, Fast 36:50 Building a Great Board 41:29 Founder CEO Lessons 48:18 Second Acts & Conviction 56:22 Timeless CEO Traits

In 2005 I built Fon on a simple idea: millions of WiFi routers sit idle most of the day. Share that spare capacity and you build a global network without laying a single cable. Millions of homes joined. Telcos partnered. No infrastructure needed. Now Jack Dorsey’s Block just launched mesh-llm. Same idea, applied to AI. Pool your idle GPU and suddenly a group of people with modest machines can run large open models that none of them could run alone. Models split automatically across nodes. No cloud provider, no API fees, no one controls your data. The timing matters. Google DeepMind released Gemma 4 today under Apache 2.0. A 31B model that competes with much larger closed models. A 26B MoE variant that only activates 3.8B parameters at inference. Edge models that run on a phone. All free to download, free to use commercially, no restrictions. Combine mesh-llm with Gemma 4 and you get the Fon of AI. Distributed compute running frontier open models. No central server. No per-query cost. Total privacy. The intelligence stays with the people who pool the hardware. Twenty years ago the scarce resource was connectivity. Today it is compute. The solution is the same: share what you have, access what you need.

protecting with intelligence engineering.block.xyz/blog/p…

Excited to launch Gemma 4: the best open models in the world for their respective sizes. Available in 4 sizes that can be fine-tuned for your specific task: 31B dense for great raw performance, 26B MoE for low latency, and effective 2B & 4B for edge device use - happy building!

mesh-llm: pool compute to run open models. built by @michaelneale at block: docs.anarchai.org

Olde Money Mode. Alas, Moneybot speaketh the King’s English.