Switzerland
Joined October 2010
A reminder to myself on retaining and growing agency in this age of acceleration: start with the self, then immediate relationships, then communities, only then the world at large.
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Dominic Wörner retweeted
everything that can be will be converted into `state = memo { f(log) }` all other state management is just too complex at the limit
Something new we've been cooking on: 🍳 Overeasy: A durable filesystem overlay, backed by immutable logs on S3 Overeasy makes your FS: - forkable - resumable across machines (demo 👇) - revertible to any prior state
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Dominic Wörner retweeted
agree - a good software emerges through iteration, stacking small, well-tested automations/loops and triggers over time. If you set out to "build a factory" you are gonna struggle. The only "factory" wisdom you should be following is: Figure out your bottleneck, automate it, then find the next bottleneck. Thanks Eli Goldratt
Very hot take: you should not be building a software factory
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Today, we are releasing Rampart: a 14.7MB machine learning model designed to protect citizens’ privacy by redacting personal information directly in your browser before it gets sent to any server
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Dominic Wörner retweeted
i don't want to use your products agent, i want my agent(s) to be efficiently enabled to use your product
everyone's happy to keep building agent frameworks while ignoring every single agent in the products they use
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Dominic Wörner retweeted
It feels like every startup is building stuff that's going to be hard to sell into companies because you have to teach people how to use it. I haven't met many founders yet who have figured out how important dev-rel and sales are. They're like, "Oh, we'll build the right thing and then hire dev-rel and sales later." But your dev-rel and sales will literally shape your product to fit the orgs you're trying to sell into. You can't do it without them.
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Dominic Wörner retweeted
This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time. I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!
Replying to @claudeai
Fable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision. The longer and more complex the task, the larger Fable 5’s lead over our other models.
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Dominic Wörner retweeted
Good take My guess is - demand for intelligence is near infinite - but 80% of workloads will be running on 99% cheaper models within 12-18 months - 20% of workloads will still run on latest gen models where IQ maxing is important (scientific breakthroughs, higher level ochestrator agents?) - rough analogy might be what % of macbooks or gaming PCs sold have the maxed out specs for CPU/GPU, prices are falling much faster than Moore's law here though - this leads me to think the limiting factor will be energy and compute, not better models At Coinbase we're working hard on routing prompts to cheaper models where appropriate, and in some cases have been able to keep costs roughly flat, while token usage continues to grow exponentially.
The most basic way AI could blow up imo. I'm not saying it does but this is the most obvious way I can see it happening - Per seat subscriptions are massively subsidized. The flat fee was priced way below what heavy usage actually costs - For real business use you have to move to the API anyway. Data protections, work integrations and compliance officer approval - On the API you pay metered rates, and businesses are burning credits way faster than the per seat pricing ever led them to expect - This is everywhere right now. Internally for us, Codex users, Uber torching its entire 2026 AI budget in 4 months, the Microsoft comments. Just go try an API I shared more on this here: xitter.cf/Shaughnessy119/status/… - And I don't think most businesses have the money to keep paying increasing API rates without a real change to how they operate (caps needed) - Because they have a cheap alternative. They can reach open source models through any aggregator (OpenRouter, Venice, Baseten, Together) and still get strong privacy. Venice private data centers, or E2EE/TEE serving GLM 5.1. More on open source inference provider raises here: xitter.cf/Shaughnessy119/status/… - And the discount is enormous. DeepSeek V4 codes within a hair of Opus on SWE bench at roughly 1/30th the price, and the cheapest open models run closer to 1/100th - Chinese labs open source frontier grade models. The model is the single biggest cost an inference provider has, and they get it for free - This idea dies if China goes closed source. That is actually bullish web2 AI labs, because if everyone is closed you pay up for the best intelligence. China goes closed source if they are tired of giving away an asset and they want the revenue and data flow to train new models - Is this showing up in web2 AI lab revenue yet? No. Revenue is off the charts. Anthropic went from 9B to 47B run rate in five months - So go forward, what happens? - I think revenue slowly starts leaking to the open source inference providers (see Venice usage, OpenRouter's $113M raise, Baseten is raising at $11B or triple its valuation in three months, on revenue that went from $200M to $600M annualized in a single quarter) - It doesnt move overnight, but it caps the labs ability to raise prices, and margins are already deeply negative. OpenAI is reportedly running near negative 122% - With margins that bad there is no cash flow, so the labs are fully dependent on outside capital to buy GPUs, train models, and keep subsidizing usage (I.e. see Google tapping $80b equity sale, granted 30b for employee RSU taxes. Clearly they think Equity is overvalued or you wouldn't sell it) - The break comes when that capital stops. Pricing is capped so margins cant improve, and the moment investors lose conviction on payback, the whole flow reverses - Why would they lose conviction on payback? Back to the start - the inability to improve margins or get businesses to pay more - This is also limiting, if we start making new drugs with AI or create entirely new businesses, you better believe people will pay up to the max for AI usage
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Dominic Wörner retweeted
It's about decentralized permissionless, trust less compute. With one application being finance. The web was never meant to be centralised and controlled by big corp and nation states
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Very close to @dfinity‘s „Chain-key Cryptography“
With @tempo, what you can see is just as impressive as what you don't. In each round of consensus, Tempo validators emit a set of BLS12-381 threshold signatures that can be verified against a static network key (maintained across validator set changes) 🔐
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Vaults are the natural next thing after stablecoins. Checking account -> Saving account
Vaults + onchain asset management is about to explode. What makes this different from past "metas" is: 1. It's far more real than memes and JPEGs 2. It will inject credit into markets 3. It will test DeFi's infra and value prop (transparency) Exciting times.
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Presenting.. 𝐌𝐞𝐫𝐜𝐞𝐬, by TACEO Demonstrating the first 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐭𝐢𝐚𝐥 𝐬𝐭𝐚𝐛𝐥𝐞𝐜𝐨𝐢𝐧 𝐭𝐫𝐚𝐧𝐬𝐟𝐞𝐫 system operating in 𝐏𝐫𝐢𝐯𝐚𝐭𝐞 𝐒𝐡𝐚𝐫𝐞𝐝 𝐒𝐭𝐚𝐭𝐞 Confidentiality x Performance  x Compliance, onchain merces-demo.taceo.io/base
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Dominic Wörner retweeted
I’m thrilled to announce the launch of the on-chain Ordinals Indexer — the latest contribution from @OmnityNetwork to the open-source community after overcoming countless engineering challenges. The Ordinals Indexer has indexed all Bitcoin blocks since genesis, utilizing nearly 200 GB of on-chain storage on the @dfinity Internet Computer (IC) — yet another testament to IC’s remarkable on-chain computation and storage capabilities. Everyone knows that Bitcoin DeFi holds enormous potential, but the lack of on-chain infrastructure has long constrained its growth. Sixteen months ago, Omnity Network released the on-chain Runes Indexer, and today, the vast majority of Runes issuance and trading activities occur on IC. In fact, ICP Chain Fusion stands as the only practical Bitcoin DeFi platform. Bitcoin DApps built on Chain Fusion offer a trustless experience with usability comparable to, or even surpassing, that of Ethereum. With today’s launch of the Ordinals Indexer, the ICP Chain Fusion infrastructure is now complete, unlocking decentralized Bitcoin NFTFi. Combined with the emerging NFT strategy trend, this opportunity could revitalize the Ordinals ecosystem. To all Bitcoin builders — now the stage is ready for creating your legends. Testing the Ordinals Indexer via the link below; additional APIs will be made available gradually. a4gq6-oaaaa-aaaab-qaa4q-cai.…
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Dominic Wörner retweeted
🎨 Jump in at yabadabadoo-j1z.caffeine.xyz… — anyone can draw! If we all retweet, this might become the #1 painting of the hour! 🚀
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