DEV Community: benjamintan.eth (💙,🧡)

Startup founders & early-stage teams, this one's for you!

benjamintan.eth (💙,🧡) — Fri, 28 Aug 2026 12:35:47 +0000

benjamintan.eth (💙,🧡) for Arbitrum

Aug 28

Builder's Block #024: Robinhood Chain Commits $1M in Funding to Open House & ArbOS Elara Now Live

#arbitrum #blockchain #startup #ai

4 min read

Builder's Block #024: Robinhood Chain Commits $1M in Funding to Open House & ArbOS Elara Now Live

benjamintan.eth (💙,🧡) — Fri, 28 Aug 2026 12:22:48 +0000

📣 What's Important This Week

Key updates from the Arbitrum ecosystem and Foundation

Robinhood Chain Continues to Back the Next Generation of Founders at Open House Singapore

One of the fastest growing chains is backing the next generation of founders. Robinhood Chain has committed $1M in funding to early-stage teams building through Arbitrum's Open House. Teams looking to bring a finance idea onchain can apply to our upcoming 3-week online Buildathon.

➡️ Register for the Online Buildathon to Compete for $115K in Prizes

ArbOS Elara Upgrade is Now Live on the Arbitrum Platform

Following approval through Arbitrum governance, the ArbOS Elara upgrade is now live on the Arbitrum Platform, bringing new capabilities to dedicated blockchains and important improvements to Arbitrum One.

➡️ Read more here

ZK proving is Coming to Arbitrum One & Dedicated Blockchains

This paves the way for private Arbitrum chains and allows for faster Ethereum withdrawals (from days to hours). Thanks to SuccinctLabs and Offchain, Arbitrum chains will be able to implement this new technology soon.

➡️ Read more here

📚 Learn & Build

New learning drops and hands-on resources from across the Arbitrum ecosystem

What Ethereum Developers Need To Know Before Deploying to Arbitrum

The Arbitrum Platform offers a familiar experience for Ethereum devs, but there are a few differences that can impact how contracts behave. From transaction ordering to dynamic pricing, @0xjesstech breaks down what they should know before deploying to Arbitrum One.

➡️ Read the Article

Prototype to Production Fireside with Openzeppelin

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AI Writes More Code Now. So What Becomes the Developer's Job?

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🛠️ Dev Tooling & Infra

Updates to SDKs, CLIs, and developer workflows across the stack

What Does Multidimensional Gas Pricing Change for Developers?

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Nitro v3.11.3 is Now Fully Released

This update improves validator stability, more accurate transaction filtering, and clearer debugging tools through better RPC error messages, tracing, and logging for filtered transactions. The source code is published on GitHub and the standard Docker images are live on Docker Hub.

➡️ See what it brings

🗓️ Events

Workshops, builder and founder programs, and ecosystem meetups to watch

Open House Singapore online Buildathon kicks off September 14

Open House Singapore will kick off with a 3-week, online Buildathon on September 14, designed to help founders refine their direction and iterate towards an MVP. Teams that are looking to bring novel financial products to the Arbitrum Platform are welcome to apply today.

➡️ Register for the online Buildathon

🧵 Forum & Community Discussions

What builders are debating and proposing this week

Arbitrum Security Program

The Arbitrum Foundation proposes to continue and evolve the Arbitrum Audit Program (AAP) - launched on 1 August 2025 with a one-year mandate into a broader Arbitrum Security Program (ASP), running for a further 12 months on a rolling-application basis.

➡️ Read the full proposal

[CONSTITUTIONAL] AIP: Authorize Priority Gas Auctions and Establish the Fast Feed

This AIP proposes to combine two separate actions into a single on-chain vote for the ArbitrumDAO to consider: transitioning Arbitrum One's ordering policy from Timeboost to Priority Gas Auctions and sunsetting Timeboost on Arbitrum Nova; and establishing the Fast Feed, a paid and authenticated data streaming product for Arbitrum One.

➡️ Read the full proposal

That’s all from Builder’s Block #024. Stay Ahead of What's Next!

Subscribe to Builder’s Block for more updates, opportunities, and upcoming events from the Arbitrum ecosystem.

The Agent Economy Has A Verification Problem

benjamintan.eth (💙,🧡) — Tue, 28 Jul 2026 14:25:35 +0000

Written by Ben Greenberg

When you call a model API, you trust the provider to run the model you asked for. Not a quantized variant. Not a cheaper substitute routed in when load spikes. You can check tokens. You can diff outputs. What you cannot do is verify that the bytes flowing through the GPU were the bytes of the model you were promised.

A March 2026 paper from Offchain Labs, Towards Verifiable AI with Lightweight Cryptographic Proofs of Inference, gives a concrete answer for the inference piece of that question, collapsing proof generation from roughly 15 minutes per query down to milliseconds. The direction of the answer should feel familiar to anyone who has thought about how Arbitrum works.

The trust gap we've already accepted

Per-token pricing creates an economic incentive to cheat. Serving a 7B parameter model is cheaper than serving a 70B one. Quantized inference is cheaper than full precision. If a provider can route some fraction of requests to a smaller or cheaper model and bill at the headline rate, the savings compound at scale.

This is not hypothetical. Stanford researchers showed that the behavior of GPT-3.5 and GPT-4 shifted measurably between March and June 2023 on the same evaluation tasks, and a follow-on line of work has formalized the problem of detecting outright model substitution in LLM APIs. None of this is an accusation against any specific provider. The point is that today's API contract gives you no mechanism to know either way. For an individual developer that is a nuisance. For regulated industries, model governance teams, and the emerging agent-to-agent settlement layer, it is a load-bearing gap.

Why the cryptographic answer does not work yet

There is already a class of cryptographic proofs that can show a server ran a specific computation correctly without the client having to re-run it. The same family of tools used by zk-rollups. Attach a proof to the response, the client verifies it in a fraction of the original work. So the obvious move is to do the same thing for AI inference.

The math works. The numbers do not.

State-of-the-art schemes like zkLLM produce a proof of inference for a 13B parameter LLM in around 15 minutes. For a smaller model like Llama-2-7B, the published numbers are 388 seconds of proving time per query, with a 183 kB proof and a 2.36 second verification.

That is fine for a research demo. It is not fine for an API expected to respond in under a second. Inference is fast and customers expect it to stay fast, so the proof has to be comparably fast or it becomes the bottleneck.

The bet: spot-check instead of re-prove

The Offchain Labs paper takes a different route. Instead of cryptographically proving every multiply-and-add inside the neural network, the server commits to two things up front:

A fingerprint of the model weights, published once after training.
A fingerprint of the internal values the model produced while answering a specific query.

Then the client picks a random spot near the network's output and walks one path back through the layers, asking the server to reveal just the values along that path. At each step, the client checks one thing. Does this value actually follow from the values feeding into it, using the weights it committed to publicly? If the server swapped in a different model, the values along the path will not line up, and the check fails.

Different models can't fake the same internal values everywhere

It is closer to spot-checking a math exam than re-grading it. A single path samples a tiny fraction of the network, but faking values that stay self-consistent across many possible paths gets exponentially harder as the network grows. The authors tested this against the attacks an adversary would actually try, including reverse-engineering the activations from the output and swapping likely tokens. None produced a forged set of values that fooled the test across millions of evaluated paths.

The intuition behind why this works comes from machine learning research, not cryptography. Two networks that produce noticeably different outputs on the same input have to differ in their internal computation somewhere. You do not need to re-execute the whole model to catch a cheater. You need to catch them in one consistent lie.

From minutes to milliseconds

The performance difference between proving every step and spot-checking a path is not a few percent. It is several orders of magnitude.

The cost of switching from full proof to spot-check

Both numbers are on the same model, Llama-2-7B. The tradeoff is honest. The proof is larger, and the client no longer gets cryptographic certainty per query. What it gets is a tunable detection probability that compounds across repeated queries, which combined with a real penalty for being caught is enough to deter rational adversaries.

An API serving millions of inferences a day does not need a per-query proof that holds up against an attacker willing to brute force a single transcript. It needs verification that runs at the speed of the request and detects cheating with high probability across volume. That is the shape the new protocol fits.

Why this story belongs on Arbitrum

Sub-second verification of an outsourced computation is the question Arbitrum was initially built around.

Optimistic rollups rest on the same intuition the paper formalizes for AI. Re-executing every step of a long computation on every machine is expensive. Sampling the contested step is cheap. If the system can guarantee that any disagreement gets surfaced and resolved by a tiny onchain check, you get the security of full re-execution without paying for it on the happy path.

The paper makes the connection explicit. Its protocol can extend to a setup with two competing servers, and when they produce different claims about the same inference, a bisection procedure narrows in on the disagreement in a logarithmic number of rounds. That is the same dispute resolution structure that secures Arbitrum One, applied to neural network values instead of blockchain state transitions.

Figure 2 from the paper: the prover commits to the trace, the verifier samples a path, and the prover opens just the values along it, which is the same commit, challenge, reveal shape that secures optimistic rollups.

The takeaway is not that AI inference needs a blockchain. It is that the verification problem in the agent economy has the same shape as the verification problem Arbitrum already solved. Spot-check rather than re-execute. Trust the willingness to be challenged rather than the cryptographic load on the happy path. Arbitrum has been operating in that paradigm for years.

What this means if you build with AI APIs

Settlement is converging on commodity rails. USDC, x402, agent-native payment flows are infrastructure questions now, not differentiation questions, and the more interesting layer is what the agent can prove it did, not how it paid.

Today, "we use model X" is a trust statement. A protocol like this one turns it into a verifiable statement. For customers in compliance-heavy domains, the distinction starts to matter quickly. A model transparency claim that holds up under audit is worth more than a marketing claim that does not.

The pattern also generalizes. Anywhere you outsource a deterministic computation to an untrusted service, spot-checking is a viable alternative to re-executing. Inference today, other workloads tomorrow. Audit flows benefit too, since a regulator who needs to verify that a certified model is the one actually running in production does not have to ban remote APIs to do the job. They can ask for a commitment, send queries, and check.

None of this requires that you, the application developer, refactor your existing stack. It does require that someone in the system, the provider, the auditor, or the platform routing requests, produces a verifiable claim instead of an asserted one. Once that primitive exists at speed, it gets adopted in the places where the trust gap is most expensive.

Where this is going

The agent economy has mostly been told as a money-movement story, and moving money is perhaps the part with the most familiar primitives. The verification layer is less well-formed, and that is exactly why this research is so interesting right now.

The Offchain paper does not solve the integrity problem entirely. It offers a way forward for the inference piece against a meaningful threat model, in milliseconds. That is worth paying attention to, and a useful indicator of where the future of verifiable AI inference is going.

Register for the Open House NYC now 🗽

benjamintan.eth (💙,🧡) — Wed, 28 Jan 2026 12:03:16 +0000

Open House NYC

benjamintan.eth (💙,🧡) for Arbitrum ・ Jan 26

[Boost]

benjamintan.eth (💙,🧡) — Tue, 27 Jan 2026 03:24:19 +0000

Open House NYC

benjamintan.eth (💙,🧡) for Arbitrum ・ Jan 26

[Boost]

benjamintan.eth (💙,🧡) — Mon, 26 Jan 2026 17:39:26 +0000

Open House NYC

benjamintan.eth (💙,🧡) for Arbitrum ・ Jan 26

Open House NYC

benjamintan.eth (💙,🧡) — Mon, 26 Jan 2026 17:37:06 +0000

Open House first started out in India. Now in 2026, it’s back - with its first stop in NYC 👉🏻 Register Now 👈🏻

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Open House NYC consists of a 3-week Online Buildathon (Feb 5 – Feb 26, 2026) and an IRL Founder House (Mar 6 - Mar 8), designed to help experienced builders go from prototype to something that actually ships onchain.

This isn’t about rushing demos; It’s about building with intent and follow-through.

What to expect

Deep technical sessions on the Arbitrum stack
Live coding demos and hands-on workshops
Founder-focused sessions on GTM and shipping post-buildathon
Mentorship from builders in the Arbitrum ecosystem
$60,000 in prizes and grants to keep teams building // Detect dark theme var iframe = document.getElementById('tweet-2015007731724525872-286'); if (document.body.className.includes('dark-theme')) { iframe.src = "https://platform.twitter.com/embed/Tweet.html?id=2015007731724525872&theme=dark" }

Join Open House NYC

If you’re looking for a structured, builder-first way to take your project further, this might be for you.

Apply here

See you at Open House 🗽