Andrew Hungate

product @catena_labs

[Andrew Hungate @AndrewHungate]

it's a fun time to be in tech, people are turning to philosophy, religion, political economy, and not just the usual girard or nietzsche, realizing we are all learners and such is mortal life. hoping to see a talk on polanyi or jacob taubes at the next stripe sessions @patrickc

[Patrick Collison @patrickc]

Two things I’ve been thinking about regarding AI:

• People often highlight the risks involved in AI, which are surely very real. I’m struck, however, by how hard it is to understand the contours of the positive scenario. There are easy-to-perceive and frequently invoked elements of a positive vision — more diseases cured, more material abundance, etc. — which sound great, but these are by themselves just ingredients. I’m curious what the larger equilibrium is supposed to look like. Do people work? If so, why? What is their marginal contribution? If not, how are resources allocated? What is scarce? What is the ratio between humans and AIs? Are humans in control, whatever that means? One sometimes hears the Culture novels invoked as one scenario, but I’m not sure they depict a desirable outcome. (AI runs everything and humans compete in games? Iain Banks himself said that the humans in the Culture are “somewhere between passengers, pets and parasites.”) There is Richard Brautigan’s famous poem, but do we want to be “returned to our mammal brothers and sisters”? (Isn’t that rewinding Genesis?) We could say that it was hard to imagine the world of 1900 from the vantage point of 1700, and that’s assuredly true. But nobody in 1700 was trying to recast humanity itself within a couple of years — things necessarily unfolded slowly and by increments, and therefore with the possibility for error correction. Given how rapid the rate of progress in AI may be, it feels strange for the upside case to be so opaque.

• There is increasing discussion of whether AIs are conscious or how we would know whether they are, with conclusions there often assumed to be relevant to matters of moral worth. At first blush, this seems a rather arcane, benign, or even absurd issue. (Remember the response to Blake Lemoine’s fears.) Setting aside the terms of the debate itself, or the relevant demarcation criteria, it seems to me a quite high-stakes question, for an affirmative answer — that is, granting moral worth to AIs — would presumably mean that the aggregate worth of AIs would soon outweigh that of humans in any utilitarian calculus. The AIs will be exceptionally wise and intelligent, and vastly more numerous (especially once one considers the imminent future and the AIs not yet born). As such, even epsilon of moral worth will multiply to a lot once one considers the quadrillions that could soon exist. (This is effectively a distributed version of the Nozick’s utility monster.) If this conclusion is unpalatable, I think one of three propositions needs to be rejected: the premise AIs can have moral worth; utilitarianism itself; or the belief that there is even a possibility that they will be far more numerous than humans.

With both of these matters (contours of future society; AI moral worth), there is the possibility of dramatic change. Today, people argue about datacenters. I’m curious how popular support for AI will evolve as more people come to understand these medium-term questions and the relevant stakes. What is the vision for AI that most people would be excited about?

[Sam | Arc and Circle Dev Community @samconnerone]

AI agents can buy movie tickets...But can they make sure you're not stuck in the front row? 🍿

In our latest stream, @catena_labs shows how agents can make purchases on @arc while respecting policies, approvals, and even seat preferences.

On Arc House! https://t.co/OyY3tk6l80

[Andrew Hungate @AndrewHungate]

@Floridap8triot average sebald reading experience

[Andrew Hungate @AndrewHungate]

@0xDesigner ousd, usdc, base, arc, tempo, all seamless 1:1 on @catena_labs

[Andrew Hungate @AndrewHungate]

great chatting with the legend @samconnerone - agent identity, controls, financial infrastructure, stablecoins, the full stack

see for yourself at https://t.co/grE2BHn399

[Arc @arc]

Arc x Catena: Building Financial Infrastructure for AI Agents on Arc https://t.co/iiewhsn7lp

[dinhdat @vdinhdat]

Reminder: @arc x @catena_labs is happening today, November 5!

Join @samconnerone and @AndrewHungate for a discussion on building financial infrastructure for AI agents on Arc.

Topics will include agent identity, payment policies, and approvals, along with a live Arc demo and Q&A.

⏰ Time: 3:00 PM – 4:00 PM UTC

Register here: https://t.co/1tGxf9N5fw

Don't miss it!

[Andrew Hungate @AndrewHungate]

@sytaylor @mattyven and the team is building this out at @catena_labs - agent policies / mandates / authority that is flexible beyond specific tasks / intents

[Andrew Hungate @AndrewHungate]

a great write-up, and touches on many of the things we're working on at @catena_labs around the policy and intent side

of course, the gaping hole in all of this is pricing. folks are convinced that agents will be great for optimizing idle consumer cash, getting money out of those inertia-riddled 0% checking accounts, while somehow also confident that those consumers will happily pay a 1-3% fee for the privilege of having their agent complete an online checkout...

[vignesh sreedhar @vigstar1]

thank you to everyone in the past week who took the time to share their views and observations on the space. understanding the broader ecosystem is critical to scaling agentic commerce.

can't wait for us all to build a future we can be proud of! https://t.co/B8LFF0NmjY

[Andrew Hungate @AndrewHungate]

@wolfgangg37 @arc @catena_labs @samconnerone you'll have to come and find out

[Andrew Hungate @AndrewHungate]

opentable basically just calendly now

[Instinct @instinct]

We’re partnering with @OpenTable so your Instinct can find and book restaurants that fit your taste, diet, and budget. Ask your Instinct to book your next night out.

[Andrew Hungate @AndrewHungate]

Come join and learn about what it means to build banking for agents!

[Arc @arc]

Arc x @catena_labs

Building financial infrastructure for AI agents on Arc.

Join @samconnerone and @AndrewHungate on Nov 5 at 10AM ET for a conversation on agent identity, payment policies, and approvals, plus an Arc demo and live Q&A.

RSVP: https://t.co/yte51w1l9v

[Turnkey 🔑 @turnkeyhq]

.@catena_labs is a banking and governance platform for AI agents.

As agents move real money at machine speed, Catena's governance platform and Turnkey's signing policies keep humans in control.

Agentic guardrails, secured by Turnkey.

[Andrew Hungate @AndrewHungate]

Please stop sharing your observations after spending 2 seconds in San Francisco

[Andrew Hungate @AndrewHungate]

@SenSanders It's on banks to put together the right approach to identifying and governing the agents they deal with. Tremendous opportunity if they do.

[Andrew Hungate @AndrewHungate]

@_chenglou philosophy comes next

[Andrew Hungate @AndrewHungate]

a lot of personal agents end up feeling kind of like spotify discover weekly - trying to be helpful, but working off an increasingly sparse and misguided dataset

[Andrew Hungate @AndrewHungate]

And so a few of us start to peer beyond the edge of positivism into something more interesting...

[Andrej Karpathy @karpathy]

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.

The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

[Andrew Hungate @AndrewHungate]

@patrickc There will, however, be new territory for price discrimination.

Inefficient price discovery acts as a boundary on discrimination (the buyer's precise criteria against the seller's pricing methods). Agent transactions can make this much more efficient, and thus more targeted.

[LINK 🐂🫎🦃🍂 @BullMooseLink]

There are so many fake stops on the 1 train below Penn Station. 18th street? Are you fucking kidding me?

[Andrew Hungate @AndrewHungate]

It's crazy to see so many people disagreeing with this. When we call something "art" we are acknowledging spirit; this is categorically apart from AI.

[Pope Leo XIV @Pontifex]

In this era of artificial intelligence, it is becoming urgent to distinguish human art from what machines produce. There is an ontological difference, even before an aesthetic one, between art and what a machine can generate through statistical calculation based on millions of images created by others. Algorithms lack the spark of humanity. For this reason, the Church wishes to renew an alliance with artists and cultural institutions to safeguard our humanity.