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Alexander Grieve

Verified account Paradigm

@AlexanderGrieve

@paradigm | 🇺🇸
Washington, DC paradigm.xyz Joined July 2012
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Alexander Grieve Verified account @AlexanderGrieve
Personal agents are everywhere (Muse! Instinct! Hermes! GrokBot! Dots! Duet!).

And, increasingly, they're running into walls – similar walls to the ones banks threw up during the Open Banking fights of the past decade, as fintech users struggled to connect their apps to their bank-held financial data.

It's time for Open Agentic Commerce.

In Dodd-Frank Section 1033, the backbone of Open Banking, the definition of “consumer” reads: “an individual or an agent, trustee, or representative acting on behalf of an individual.” Congress obviously wasn’t contemplating AI agents when it wrote Dodd-Frank — but technology changing doesn’t obviate the underlying principle: consumers should be able to choose who, or what, transacts on their behalf.

Banks and companies like Amazon have real, legitimate concerns about agents becoming vectors for fraud or unauthorized transactions. But those are arguments for building portals for secure access, not for prohibiting agents altogether. Open Banking offers a useful lesson here, in that secure, standardized interfaces are preferable to forcing third parties into credential sharing or screen scraping.

We propose some basic guidance that relevant regulators (FTC, OCC, CFPB) could consider to help the market to coalesce around open norms before incumbents obtain sufficient lock-in, freezing the current landscape to their advantage.

With standards like these established, agents can make decisions that better serve the consumer, and will index on things like quality or price, rather than being funneled into a constrained set of options.

The push for Open Banking resulted in better experiences and lower prices for consumers. As agents become principal commercial actors, it is imperative that we lay the groundwork now so that an agent acting on your behalf is equally capable – if not more so – of delivering value and cost savings to you as you would be acting on your own.

Read our proposal below:
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Alexander Grieve Verified account @AlexanderGrieve
One thing if CME is doing market research to support their litigation against CFTC on perps — but the fact this is from someone on their retail marketing team indicates they’re trying to launch a perps product of their own.

Which then begs the question, doesn’t that entirely undercut the argument CME is making in their lawsuit, and bolster that of the CFTC’s? (E.g. that CME just wasn’t ready for market so is suing to slow things down)
Luke Cannon Verified account @lukecannon727 1d
The CME Group is currently conducting retail market research about perpetuals.

Source: my inbox
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Alexander Grieve Verified account @AlexanderGrieve
🤠⚡️🤖
Matt Huang Verified account @matthuang 1d
Swarm riders and Swarm-native companies

AI-use even among highly AI-native people is power-law distributed.

There seems to be a new class of people — call them “swarm riders” — who are capable of consistently commanding large swarms of agents to productive ends.

This is a new kind of managerial skill, analogous to the skill it takes to manage large organizations of people, but wholly different in nature and of course more technical.

Based on the swarm riders we know (including many at @Tempo and @Paradigm), these people are capable of productive token spend that is 1000x-10000x higher than median software engineers, and 100x higher than top 5% Claude Code users.

The art of swarm riding is different from software engineering and more akin to machine learning, where practitioners grapple with black box systems: defining reward functions and evals, transmuting non-verifiable problems into verifiable problems, running experiments, etc.

Swarm-native companies are a new class of company founded by and populated by swarm riders. These companies are organized around swarms in a way that conventional companies will struggle to replicate, as the cost of internal human coordination is sand in the gears of an effective swarm. Effective swarm-native companies will define the right reward functions and evals, remove functional and bureaucratic barriers, and then let the swarms cook.

We’ve gotten to see a few swarm-native companies up close — reshaping financial rails @Tempo, building a new gaming platform @Spawn, cyber swarms at Cathedral Systems — and it’s clear these teams wield a significant advantage over pre-AI teams.

Some questions I’ve been wondering about:

1) How fast will swarm riding diffuse through the economy? The implications for token spend could be significant.

2) Can swarms be effectively adopted by existing companies or will it generally track the formation of new swarm-native companies?

3) What becomes scarce as swarm capabilities themselves commoditize (through frontier models becoming better at swarming, swarm capabilities built into harnesses, etc)? Cultures and teams that can define reward functions well and otherwise get out of the way?
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