In awe of SpaceX and its story - past, present and the future. You can think about it in 10 different ways and continue re-blowing your mind in circles. Huge congrats to the team! 🚀

"economists*" who have "done the maths" vs economists who have done the math.

"Being long humans requires long horizons. Our time horizon is forever." goes hard

we're hosting a 'Big Data 3.0' next Tuesday (June 16) in our SF office with @SpiralDB and @TigrisData. we'll have technical deep-dive talks from frontier AI labs about internet-scale distributed data systems for AI research. details below 👇

ASI may do many things, but it will never compete with peak nostalgia

“Corporations are people too” goes the argument

people have to build much faster software and interfaces so as to not Amdahls law the increasingly powerful and increasingly fast models

Artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships, and do not know from within what love, work, friendship or responsibility mean. Nor do they have a moral conscience, since they do not judge good and evil, grasp the ultimate meaning of situations, or bear responsibility for consequences. They may imitate or even simulate, but they do not understand what they produce, for they lack the affective, relational, and spiritual perspective through which human beings grow in wisdom. #MagnificaHumanitas

Google is fighting every final boss at once: OpenAI & Anthropic in models, Nvidia in chips, AWS & Microsoft in cloud, Meta in ads, Tesla in self-driving, Apple in phones and OS. At $4.6T, it feels weirdly undervalued.

Agents’ data needs will become increasingly complex. I didn't get the filesystems thing at first. I thought it was just hype. But now I believe that file systems are better suited to agents than DBs or object stores. I'm less convinced that today's file systems are...the future. Talking to senior folks building data infra, I heard some common refrains on why filesystems are right for agents: 1) Training corpora contain lots of file system operations – there are a lot of public Github repos containing file system operations, so these interactions appear frequently in data upon which models are trained. What’s more, filesystem semantics are dead simple. In contrast, database operations appear in training corpora but their semantics are kinda tricky; they are often missing critical context like schemas. 2) File systems do what agents need to work with data – agents typically need high-throughput, low-latency access to specific, small files containing unstructured data. Filesystems support this pattern well. Other data management systems don’t: OLTP databases require too much structure; object storage is too slow. But while file systems seem to meet the needs of agents, that wil probably change imminently. Specifically, I expect agents will need 4 capabilities: 1) Transactions – when thousands of agents operate simultaneously, reading from and modifying shared state, and writing it back, the file system must store data reliably and mediate interactions between independent processes. Traditional distributed file systems weren't designed for highly concurrent, fine-grained mutation of shared state. 2) Queries – today, an agent might retrieve a single file and make a single update. But as agentic retrieval advances, agents will need to pull data from multiple files, materialize intermediate results, and run operations across those results. As Claude might say, this is not retrieval; it is a query problem. 3) ACLs – file systems do support ACLs, but they’re typically defined at the level of files, directories, users, and groups. Permissions are static, evaluated at access time, and don’t extend to how data is used once it’s read. 4) File scale – today’s agent workloads operate over small files, modest context windows, limited working memory, and bounded outputs. As models improve and context windows expand, agents will start working over much larger artifacts. A coding agent won’t operate file by file, it will need to understand and modify entire codebases. There are teams starting to build the post-modern data stack for agents (so unoriginal, but I had to sneak some slop in here). @archildata gives agents fast, consistent access to data across environments, while explicitly meeting the latency requirements agents have and will have in the future. @SpiralDB built a columnar file format for extremely fast reads, including random access, selective reads, and large batch scans - it can give agents analytics capabilities. To be honest, I’m in awe that data infra has held up so well as agents become more prevalent. But this won’t last forever. Agents will need more. Concurrency needs stronger guarantees. Retrieval becomes a query problem over unstructured data. Access control moves from static ACLs to dynamic, execution-aware policies. And file systems need to support efficient operations over much larger artifacts. We’re starting to see early answers, but no dominant design. The choices we make now about how agents interact with data will harden quickly, so it’s worth getting them right. More in my latest blog post: amplifypartners.com/blog-pos…

at long last, our nation's enemies have stolen the most dangerous technology in America's arsenal: the California Environmental Quality Act

“Pope Leo was a math major? I wonder what his encyclicals will be like” Like this

Can’t believe I coded by hand for 15 years. 15 years of memorizing syntax, Vim, Stack Overflow, broken builds, cursed dependencies, merge conflicts, and “one last bug before sleep.” All of that just to end up typing “fix this” into a chat box and watching an agent do crimes.

Just found out that Berkeley course staff are writing hooks inside course repos so if a student opens an assignment in Claude Code or Cursor the agent will automatically ping the staff 😵‍💫 well played

Jeff Bezos: "If I do my job right, the value to society and civilization from my for-profit companies will be much, much larger than the good that I do with my charitable giving."

The pattern across all of these: - Modest statute creates a right to sue - Courts expand what compliance requires - New plaintiffs use the expanded precedent to extract more - Agencies over-comply defensively - No one has standing to sue for "too much process"

Over at Substack, @JoshEakle asks: "It's 2026, and I have yet to see an anti-almond farm protest."

this is KD joining the warriors for people who know linear algebra

Wow! If anyone ever invented a machine that could take symbolic inputs and then follow rules to produce outputs, they’d be able to rent those suckers out for a quarter-million a year apiece and still save the LIRR money on pensions!

What's happening right now is that the coding agents are promoting feature maximalism and making it easier to introduce paper cuts. Lower layers of the stack need opinionated design, minimalism, and robustness.