Blockworks

Paradigm co-founder Matt Huang announced on Thursday that his firm and Stripe are incubating Tempo, a payments-focused blockchain designed to streamline stablecoin use in real-world financial flows.



Tempo has <a href="https://x.com/matthuang/status/1963633379284587017">entered</a> private testnet with support from initial design partners including Anthropic, Coupang, Deutsche Bank, DoorDash, Lead Bank, Mercury, Nubank, OpenAI, Revolut, Shopify, Standard Chartered, Visa, and more. The project represents Stripe’s most direct step into blockchain infrastructure, extending its payments business toward native onchain settlement.



Tempo is engineered to handle more than 100,000 transactions per second with sub-second finality, according to project materials. Its payments-first architecture enables transaction fees and gas to be paid in any stablecoin through an enshrined automated market maker (AMM).



Additional features include dedicated lanes for payments, support for memos and access lists, and opt-in privacy settings. Built on Reth, an Ethereum execution client, the chain maintains compatibility with existing Ethereum smart contracts and tooling.



Huang said Tempo is intended to support diverse financial applications such as payroll, remittances, global payouts, and embedded accounts. The protocol will follow a principle of “stablecoin neutrality,” allowing any issuer to deploy tokens for settlement. Validators will initially be curated but are expected to transition toward a permissionless model.



This is a developing story.



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This article was generated with the assistance of AI and reviewed by editor&nbsp;<a href="mailto:jeffrey@blockworks.co" target="_blank" rel="noreferrer noopener">Jeffrey Albus</a>&nbsp;before publication.



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OpenAI

Stripe and Paradigm incubate Tempo blockchain for stablecoin payments

Donovan Choy

This is a segment from the Lightspeed newsletter. To read full editions, <a href="https://blockworks.co/newsletter/lightspeed" target="_blank" rel="noreferrer noopener">subscribe</a>.



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Would you rather invest in the business model of a cinema or Netflix?



A theater needs real estate, seats, projectors and staff. When it’s full, you top out at ~200 paying customers per show.&nbsp;



Netflix beams the same video to its first customer and its millionth customer with basically the same operational cost.



That zero marginal cost is the intuition behind why investing in tech is attractive. Once you’ve built the product, each additional user generates a high gross margin, which produces sky-high multiples.



Now, that mental model — of zero marginal cost + uncapped demand — is being stress-tested.



In AI, for instance, serving the next user is not free. Your “software” rides on someone else’s model (OpenAI, Anthropic, Google, etc). Each user interaction burns inference tokens, which in turn costs real compute, power and data center capacity.&nbsp;



Even as unit prices per AI token trend down, token consumption per task rises, so the bill goes up.



For a few years, Anthropic aggressively courted developers with enterprise-friendly pricing mechanics (e.g. prompt caching, batch discounts).&nbsp;



That strategy worked! In enterprise usage share, Anthropic has overtaken OpenAI — 32% vs. OpenAI’s 25% by usage.



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1303" height="581" src="https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=1024&amp;h=1024" alt="" class="wp-image-107077" srcset="https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=1303 1303w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=300 300w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=1024 1024w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=768 768w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=428 428w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=470 470w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=389 389w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-19.png?w=80 80w" sizes="auto, (max-width: 1303px) 100vw, 1303px" /></figure>



OpenAI lately responded by slashing prices. GPT-5’s API recently launched with $1.25/M input and $10/M output tokens, explicitly leaning into coding and agent use cases.



That’s dramatically cheaper than Anthropic’s Claude Opus’ prices at $75/M output tokens ($15/M input)!



With that, AI wrapper companies like <a href="https://www.youtube.com/watch?v=UbFtbiR7PrA">Lovable</a>, <a href="https://cursor.com/en/blog/gpt-5">Cursor</a>, <a href="https://www.linkedin.com/posts/boltdotnew_we-are-excited-to-launch-gpt-5-into-bolt-activity-7359288231617581056-XVpa/">Bolt</a> and more have quickly moved to integrate GPT-5.



&#8220;For the first time in SaaS history, the marginal cost of adding on a user is not close to zero,&#8221; said Amanda Huang of Bain Capital Ventures, per <a href="https://pitchbook.com/news/articles/how-long-can-ai-agents-like-cursor-keep-burning-cash-investors-are-divided?utm_medium=newsletter&amp;utm_source=daily_pitch&amp;sourceType=NEWSLETTER">Pitchbook</a>.



Crypto often looks like software economics. Once a chain is live, serving the marginal user is close to free.



That is theoretically true, but not necessarily so in practice.&nbsp;



Because while validators (proof-of-stake) incur zero marginal costs to produce the next block, when demand spikes, users want to pay to jump the queue.



That’s why MEV (maximal extractable value) persists. Being first in line is valuable, and blockchain networks explicitly price that preference.&nbsp;



On Ethereum, EIP-1559 formalized congestion pricing via a base fee plus optional tip. On Solana, “priority fees” exist precisely because blockspace is scarce at the margin — even if the average transaction is cheap.



Crypto investors like Multicoin’s Kyle Samani have explicitly <a href="https://x.com/KyleSamani/status/1838718619339100351">argued</a> in favor of valuing blockchains solely on MEV.



In the month of August, Solana did $68 million in MEV.



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="686" height="486" src="https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-17.png" alt="" class="wp-image-107075" srcset="https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-17.png?w=686 686w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-17.png?w=300 300w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-17.png?w=363 363w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-17.png?w=368 368w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-17.png?w=309 309w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-17.png?w=80 80w" sizes="auto, (max-width: 686px) 100vw, 686px" /></figure>



Across the same month, Ethereum saw $32.5 million in MEV.



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="691" height="524" src="https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-18.png" alt="" class="wp-image-107076" srcset="https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-18.png?w=691 691w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-18.png?w=300 300w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-18.png?w=339 339w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-18.png?w=344 344w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-18.png?w=289 289w, https://blockworks-co.imgix.net/wp-content/uploads/2025/09/image-18.png?w=80 80w" sizes="auto, (max-width: 691px) 100vw, 691px" /></figure>



Classic SaaS multiples assume high, stable gross margins and flat marginal costs.&nbsp;



But in both AI and crypto, that logic can be sometimes inverted. In crypto, even with low nominal fees, blockspace scarcity created pricing power (priority fees, MEV).&nbsp;



And in AI, “wrapper” applications that pass through model costs behave more like usage-metered utilities. Margins compress unless teams negotiate discounted batched rates.



What does this mean for the players involved? I guess you could just raise more venture money to subsidize usage.



Anthropic, for example, yesterday <a href="https://x.com/AnthropicAI/status/1962909472017281518">raised</a> $13 billion at a whopping $183 billion valuation to compete with OpenAI.



L1/L2 chains have also raised hundreds of millions historically, but you don’t need that much money to build a chain. Similarly to Anthropic, the money is merely a competitive weapon to fund subsidies, incentives and liquidity programs.



In both arenas, the bulk of venture dollars flow to subsidies aimed at entrenching network effects.&nbsp;



In the near term, consumers benefit from lower prices and better service. Enjoy it while it lasts.



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Is zero-marginal-cost tech no more?

Katherine Ross

This is a segment from the Empire newsletter. To read full editions, <a href="https://blockworks.co/newsletter/empire" target="_blank" rel="noreferrer noopener">subscribe</a>.



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That’s one way to describe yesterday’s action both in crypto and outside of it.&nbsp;



Galaxy Trading summed the action up to a “function of broader crypto market movements” while GSR’s Carlos Guzman said that the AI narrative dominated the day.&nbsp;



Basically, DeepSeek — a Chinese AI company — was able to rival OpenAI’s very expensive model for much cheaper on older (and much less expensive) chips, hence the selloff in Nvidia.&nbsp;



(Sidenote here: Decide AI’s Jesse Glass doesn’t think that the cheaper GPU story will last because DeepSeek will still need larger GPUs as it scales.)



What we then saw was folks scrambling to recalibrate how to approach the big AI plays, some of which, like OpenAI, now have <a href="https://www.nytimes.com/2024/10/02/technology/openai-valuation-150-billion.html">multibillion-dollar</a> valuations.&nbsp;



For the crypto side of things, the narrative was much the same according to Guzman. The AI tokens caught up in the selloff were largely overvalued given the use cases currently out there.&nbsp;



“I do think crypto and AI agents are a real thing, and we&#8217;ll eventually see a lot of real use cases of AI agents that use crypto … But, as often happens in crypto, the tech wasn&#8217;t quite there … The excitement got a little bit ahead of where the tech was,” he explained.&nbsp;



Galaxy noted that AI tokens weren’t trading near all-time highs before the recent correction, which shows that some aren’t quite sold on how they fit into the space yet. And AI researchers, like Glass, will carry some skepticism until projects can integrate or emphasize edge computing in their projects, instead of just launching tokens.



“For AI-focused crypto projects to break out of speculative cycles, they must demonstrate clear blockchain-native advantages — whether through cost efficiencies, trustless execution, or new incentive mechanisms. Accessibility also remains a challenge, as memecoin trading is one of the few areas that has broken through mainstream barriers,” the Galaxy Trading team explained.&nbsp;



So does yesterday’s action change a lot of the bullishness we’ve seen around the AI/crypto intersection and these tokens? Doesn’t seem like it. Guzman believes that more development and use cases will reopen the excitement around the tokens.



As for the current AI landscape, it’s honestly not looking too bad right now despite the sea of red. The thing is, as Guzman explained to me, in the long run, the DeepSeek saga might actually be healthy.&nbsp;



The current crop of AI companies in the US can now use the compute and data to improve their own models, allowing them to replicate and build on what they learned from DeepSeek.&nbsp;



I guess there really is always a silver lining.



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