100M CU blocks need @solana validators relaying shreds faster than they do today. XDP is how they get there: it speeds up Turbine's outbound propagation 750x, ensuring every block reaches the whole cluster before the next slot starts. We moved our entire fleet to XDP, and to help other operators get there, we upstreamed two patches to @anza_xyz's Agave, removing common adoption blockers: → VLAN tagging in userspace for segmented datacenter networks. Operators who split traffic across VLANs can now turn on XDP without the switch dropping their shreds → Multicast MAC derivation unlocks multicast retransmit on XDP for group sends. Useful on @DoubleZero and anywhere per-peer duplication isn't viable If there's a validator you'd like to see on XDP, tag them below👇

NEW sendtx endpoint: direct HTTP path for sending Solana transactions, with SWQoS included by default. Landing fast on Solana comes down to three things: low sending latency, fewer network hops, and stake-weighted QoS. Yellowstone Jet, our specialised sending engine, already covers all three, but the standard sendTransaction path still leaves some processing overhead on the table. It wraps your signed transaction in a JSON-RPC envelope that the server has to parse before it even sees it. New sendtx drops it entirely, letting you POST the raw bytes, or a base58/base64 string, directly to Jet: 🟣No server-side JSON parsing 🟣Smaller request, less bandwidth used 🟣Browsers skip the CORS preflight round-trip 🟣Runs over HTTP/3 and QUIC 🟣SWQoS on by default Live on every Triton endpoint, and open-sourced in yellowstone-jet.

What advice would you have for developers that are starting out? “Contributing to open source.“ @wjthieme, Head of Engineering at @orca_so, on the value of having open source work to show. Check out the full episode with @nocircuit 👇

Jane Street made ~$40B in 2025 with 3,500 employees, a ~2x from the year before. At ~65-70% profit margin, that's $8M profit / employee, the highest for a 1000 ppl company. High-frequency trading continues to be the most efficient money making engine. I want to share an old story about my Jane Street interview in 2014. Jane Street was known for hiring a lot of math, physics and CS olympiad winners from top universities and putting them through many rounds - including, for trading roles, a gauntlet of mental math. It was my 6th interview and my final round and I recall being asked "What is the next day after today in DD/MM/YYYY where all the digits are unique?" They'd toy with you and say "You can use a pencil and paper, if you want" but you knew that was an instant no. Painstakingly and as quickly as I could, I came to an answer. "How confident are you that this is correct on a 0-1 probability scale?" the interviewer said. "0.95", I blurted out, not fully knowing how to answer that. "Are you sure?" After thinking harder for a few more seconds, I realized I could've flipped the digits around to get a closer date. I gave the interviewer my answer. It was correct. "0.95 huh?" he chuckled. That's when I knew I failed. Note: fwiw, other companies that come close in efficiency are - Tether ($90M profit/emp) - Hyperliquid ($80M profit/emp) and on revenue: - Valve ($50M/emp) - OnlyFans ($37M/emp) - Craigslist ($14M/emp) - Anthropic ($12M/emp, run rate) - OpenAI ($8M/emp, run rate) For comparison, Nvidia is very efficient at scale and is $4.4M/emp.

John Ternus, Apple's SVP of Hardware Engineering, explains why Apple deliberately made the iPhone harder to repair, and why the math says it was worth it: In a conversation with MKBHD, John frames the design challenge by asking you to imagine two extremes: "Sometimes for me I find it helpful to kind of think about the book ends. Like if you imagine a product that never fails, right? That just doesn't fail. And on the other end, a product that maybe isn't very reliable but is super easy to repair." His position is clear: "Product that never fails is obviously better for the customer. It's better for the environment." When pushed on whether infinite repairability and infinite durability have to be mutually exclusive, John acknowledges they aren't always, but explains why the tension is real, using the iPhone battery as an example. Batteries wear out. If you want to extend the life of the product, they need to be replaced. But in the early days of iPhone, one of the most common failures wasn't the battery, it was water: "Where you drop it in the pool or you, you know, spill your drink on it and the unit fails. And so, we've been making strides over all those years to get better and better and better in terms of minimizing those failures." That work led Apple to an IP68 rating, the point where customers fish their phones out of lakes after two weeks and find them still working. But there was a cost to achieving that level of durability: "To get the product there, you've got to design a lot of seals, adhesives, other things to make it perform that way, which makes it a little harder to do that battery repair." That's the deliberate tradeoff. Apple chose tighter seals and stronger adhesives, knowing it would make battery replacement more difficult, because the reliability gains were worth it. John argues the math backs this decision: "It's objectively better for the customer to have that reliability and it's ultimately better for the planet because the failure rates since we got to that point have just dropped. It's plummeted, right? The number of repairs that need to happen and every time you're doing a repair, you're bringing in new materials to replace whatever broke." His conclusion reframes the entire repairability debate: "You can actually do the math and figure out there's a threshold at which if I can make it this durable, then it's better to have it a little bit harder to repair because it's going to net out."

Find yourself a team that is half as good as Triton and you can move oceans.

BREAKING: We're partnering with @SolanaFndn to rebuild Solana's read layer from the ground up. @anza_xyz and @jump_firedancer have done incredible work scaling execution and networking, but the read layer has stayed largely unchanged since genesis. It was built alongside the validator and never got its own architecture. By 2026, that gap shows: slower access, expensive customisation, and growing limitations at scale. The teams closest to the problem built great tools behind closed doors because the read path was too deeply coupled to the validator to improve without massive effort. It's time Solana's data access layer matched the ecosystem's needs, and we're proud to be the ones building it: Big news: reads are moving out of Agave into two modular systems, independently scalable, in sync with the network tip, open-source and managed by @SolanaFndn: - Accounts: an adaptive indexing engine that ingests, stores, and serves the exact account data your app needs at extremely low latency - Ledger: full architecture to ingest, store, and serve the entire ledger faster and more efficiently in a columnar engine purpose-designed for how builders query data Every infrastructure provider, builder, dApp, and institution benefits, with the biggest impact coming from what gets built on top. Full architecture overview: blog.triton.one/announcing-r… More technical posts coming as we build through 2026, so make sure to follow us on X and subscribe to our blog.

We sent our Comment. Now it’s your turn. The new IT Rules expand censorship and weaken safeguards on online speech. Three simple ways to act. Just a few minutes. Deadline: 14 April.