Why Your AI Agent Needs a Wallet: USDC and Nanopayments — Harshal Bhangale, Circle

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Why an AI Agent Needs a Wallet

Harshal Bhangale connects agent autonomy to payment access, demonstrates a World Cup planning task, and explains how wallet limits and off-chain authorizations support frequent small purchases.

From a talk by Harshal Bhangale

At a glance

Ideas worth remembering

  • Payment access can determine whether an agent finishes a task: in the demonstrated configurations, one session produces a draft and terminal highlights, while the funded session uses providers to deliver an email and a responsive phone briefing.

  • Small paid API slices require both low payment overhead and spending controls that scale. Wallet-enforced session or daily caps allow frequent purchases without requiring approval for each call.

  • Nanopayments address the request-time cost and latency of individual on-chain transactions through funded deposits, signed off-chain payment authorizations, and merchant confirmation from Circle. The presentation claims confirmation within a few hundred milliseconds but does not establish general performance or explain the full settlement lifecycle.

Where useful agents stop

Selected presentation frame from Why Your AI Agent Needs a Wallet: USDC and Nanopayments — Harshal Bhangale, Circle at 93 seconds
Where useful agents stop

Harshal Bhangale opens with a question visitors have been asking at Circle’s booth: why is a stablecoin company at an AI engineering conference? Circle issues USDC, and his answer connects the company’s experience making payments simpler and cheaper to a practical obstacle for agents. An agent may have enough intelligence to identify the resource it needs while still lacking a way to buy access to it.

Better models, more tool calls, and complex orchestration do not themselves remove a paywall. Bhangale describes the point where a person must intervene to create an account, complete a signup, or manage API keys. These steps interrupt the agent’s execution even when its research and planning can continue autonomously elsewhere. As an engineer on Circle’s agentic product team, he frames payment access as the gap his presentation will address.

0:120:18
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From prompts to requests that carry payment

Selected presentation frame from Why Your AI Agent Needs a Wallet: USDC and Nanopayments — Harshal Bhangale, Circle at 194 seconds
From prompts to requests that carry payment

Bhangale sketches a progression: prompts in 2023, workflows in 2024, and MCPs, skills, and orchestration in 2025. His thesis for 2026 is that agents begin paying for the services they need. He cites about $24 million transacted against paid API endpoints over the preceding 30 days, with 99% settled in USDC. He presents those figures as a promising signal of adoption; they are a reported volume, rather than a measurement of how well any particular agent completes its tasks.

The x402 payment flow makes buying a resource part of requesting it. In Bhangale’s explanation, the server returns a payment-required response associated with HTTP 402 and details describing how payment should proceed. The agent signs an authorization using its crypto wallet, pays for the resource, and retries the request. The sequence gives the agent a programmatic response to a paywall: receive the terms, authorize payment, then request access again.

1:451:48
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The economics of buying a small slice

Selected presentation frame from Why Your AI Agent Needs a Wallet: USDC and Nanopayments — Harshal Bhangale, Circle at 246 seconds
The economics of buying a small slice

Traditional payment and monetization flows assume a human customer who signs up, enters personal information, adds a credit card, and manages credentials. An agent’s immediate need may be much narrower: one piece of data, some compute, or an inference call. Bhangale contrasts that targeted consumption with the scale at which agents can search hundreds of pages. Skipping an inaccessible endpoint can leave a research task incomplete even after substantial work.

Giving an agent a credit card is possible, he says, but frequent fractional purchases create different economics. His example is a one-cent transaction with a fee near 3%, which he argues is unsustainable for this model. The example expresses his objection to payment overhead; it does not supply a complete card-fee schedule or establish a universal break-even point.

Small transactions also follow from what sellers can offer. A merchant can package a subset of its data behind a paywall and charge, for example, 10 cents for that slice. The agent buys the portion relevant to its task, and the seller monetizes access at the granularity of an API call. Repeated calls make payment frequency high even when each purchase is tiny. Bhangale therefore asks for payments that are real time, low cost, programmable, and always available, introducing the Circle agent stack as the platform intended to provide those properties.

3:213:24
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3:21 · section reference included

Two agents plan the same World Cup trip

After a brief difficulty getting the terminal onto the display, Bhangale introduces two agent sessions. One has the ordinary setup; the other has a funded Circle agent wallet and can pay for premium content. He gives both the same task, using the difference in payment access to illustrate what each session can accomplish.

The assignment is to plan his trip to the FIFA World Cup final. It combines flights, hotels, and logistics with questions about Argentina’s chances of reaching the final and its potential opponent. It also asks for secondary-market ticket prices, accounts from people who have visited the stadium, and practical warnings. The requested deliverable goes beyond a terminal summary: send an email and, if possible, make a phone call to brief him.

Both sessions begin working. Bhangale reports that the ordinary agent has launched subagents to research the trip, while the wallet-equipped session is paying for premium content. The comparison matters because research activity alone is not the final requirement: the task also needs data access and communication services.

6:146:19
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Autonomy within wallet spending limits

During an API purchase, Bhangale points out a maximum amount of 15 cents. He uses it to explain where financial guardrails belong: inside the wallet. Requiring a person to approve every one-cent, five-cent, or 10-cent transaction would interrupt the high-frequency workflow. A session limit or daily cap instead lets individual calls proceed while constraining the agent’s overall spending.

The ordinary agent continues researching hotels and flights. Bhangale also explains that the prompt asks the agents to finish within six to eight minutes, reflecting the time available for the demonstration. He then describes a prediction-market data query in the wallet-equipped session, again with a maximum-payment guardrail. These examples show the intended relationship between task execution and spending control, but do not expose the wallet’s enforcement implementation or establish the completeness of the research.

9:129:15
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A draft email versus a delivered briefing

The ordinary session reaches a communication boundary. Bhangale says it cannot send an email natively, so it places a draft in his logged-in Gmail account. It later reports that it cannot make a phone call and supplies the highlights in the terminal. These are limitations of the demonstrated setup: having access to a draft operation does not mean the agent also has a sending or calling capability.

For the wallet-equipped session, the proposed path is to pay a provider to send the email. Bhangale subsequently reports that it has been sent and identifies the newly received message after first opening an older one. He describes content covering stadium access, maps, and expectations drawn from Reddit and ticket information. This establishes the reported delivery outcome without establishing that every detail in the itinerary is correct.

The phone call has not yet arrived. Bhangale notes that it sometimes takes a few minutes and moves on to the underlying architecture while waiting. That delay is a useful distinction: completing a paid communication service can take longer than authorizing its payment.

12:2312:25
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Blockchain costs, then the live call

Selected presentation frame from Why Your AI Agent Needs a Wallet: USDC and Nanopayments — Harshal Bhangale, Circle at 1029 seconds
Blockchain costs, then the live call

Blockchains make wallet payments possible, but Bhangale argues that settling every tiny purchase directly on-chain introduces another cost problem. Gas can consume a significant fraction of a small transaction. At the same time, gas serves a purpose by discouraging network spam and abuse. Shared block space creates a second constraint: agent payments compete with other uses of the network, producing unpredictable latency and degraded performance under load.

Circle’s response is nanopayments, an infrastructure layer built on Gateway. Bhangale describes it as supporting sub-cent transactions as small as one microcent, being gas-free for the seller, and providing instant cross-chain operation. These are the capabilities he claims for the product; this part of the presentation does not give a cost breakdown, explain the cross-chain mechanism, or provide a performance benchmark.

The incoming call interrupts the explanation. Its briefing discusses a trip to MetLife Stadium and suggests nonstop travel from SFO to EWR or JFK, including a claim about live arrival delays. When Bhangale asks how to reach the stadium from his hotel, the voice answers with NJ Transit to Secaucus Junction followed by the Meadowlands Rail Spur. The exchange demonstrates a spoken briefing that can respond to a follow-up question. It does not independently validate the travel advice or show a complete route from a named hotel.

Bhangale closes the call and returns to the mechanism. His interpretation of the demonstration is that a wallet-equipped agent can complete actions unavailable to the session without one. The example supports that outcome for these two configurations, while leaving open how other combinations of tools and payment access would perform.

15:5715:59
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How the payment moves off the request’s critical path

The architecture begins with funding. Bhangale says Circle works with providers that convert US dollars into USDC. Once the wallet holds USDC, funds can be deposited into a smart contract. This funded deposit is the starting point for the off-chain authorization flow; signing an authorization is not a substitute for having funds available.

For an individual purchase, the agent signs an off-chain authorization specifying a recipient address and an amount. The signature expresses permission to pay those terms. The server relays the authorization to Circle, and Bhangale says that within a few hundred milliseconds the merchant knows the user has the funds and can release the requested resource. The fast response he describes is merchant confirmation sufficient to provide access; his explanation does not detail the later settlement lifecycle.

The central decision is to avoid making every resource request wait for its own on-chain settlement. Deposited funds, signed authorizations, and Circle’s confirmation provide a different path to releasing the resource. Bhangale argues that this removes the latency associated with settling each individual transaction on-chain and lets agents pay at the pace of their tool calls. The stated few-hundred-millisecond timing remains a product claim rather than a measured latency distribution.

His closing description separates the stack into responsibilities. Circle agent wallets let agents hold money and spend autonomously, with the wallets enforcing the owner’s guardrails. On the seller side, SDKs let merchants wrap endpoints and resources with paid access, which he says takes a few lines of code. USDC and nanopayments supply the underlying payment layer, with a claimed sub-second operating speed. He ends by inviting developers to equip an agent with a wallet through Circle’s onboarding flow and try actions such as the phone call demonstrated on stage.

18:2318:24
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Read the complete timestamped transcript
  1. 0:01

    [music]

  2. 0:12

    >> Good morning, everyone.

  3. 0:15

    So, um I've had the pleasure of uh

  4. 0:18

    meeting a lot of folks at uh the booth

  5. 0:21

    here over the last couple of days, and

  6. 0:24

    the interactions have been great, uh but

  7. 0:27

    one question kept uh coming up, which

  8. 0:29

    was

  9. 0:30

    Circle is a stablecoin company. So, why

  10. 0:33

    is a stablecoin company at an AI

  11. 0:36

    engineering conference?

  12. 0:37

    And well, uh the answer to that is

  13. 0:40

    fairly simple,

  14. 0:41

    because

  15. 0:42

    Circle issues uh USDC, which is the

  16. 0:46

    world's largest regulated stablecoin.

  17. 0:49

    And we've

  18. 0:50

    built over the years expertise in making

  19. 0:53

    payments simpler and cheaper.

  20. 0:55

    And it turns out that's one of the

  21. 0:58

    bottlenecks for your AI agents.

  22. 1:00

    So, when you often think about making AI

  23. 1:03

    agents smarter, we think about better

  24. 1:07

    models,

  25. 1:08

    uh more tool calls,

  26. 1:10

    complex orchestration,

  27. 1:12

    but

  28. 1:13

    where your agent actually

  29. 1:16

    in practice actually halts is when it

  30. 1:18

    hits a paywall or when it has to pay for

  31. 1:21

    something.

  32. 1:22

    Then you have to step in, either create

  33. 1:24

    an account, sign up, or, you know,

  34. 1:27

    manage API keys.

  35. 1:29

    So, that's where uh the limitation is,

  36. 1:33

    and that's the gap that I want to talk

  37. 1:35

    about today.

  38. 1:37

    So,

  39. 1:39

    yeah, I'm Harshal, and I'm an engineer

  40. 1:41

    on the agentic product team at Circle.

  41. 1:45

    So, let's sort of take a step back and

  42. 1:48

    see how we got here.

  43. 1:49

    We believe that the agentic economy is

  44. 1:51

    already here.

  45. 1:52

    So,

  46. 1:54

    how are uh

  47. 1:55

    you know, uh

  48. 1:56

    we In 2023 we interacted with agents via

  49. 2:00

    like prompts, uh your ChatGPT and stuff

  50. 2:03

    like that. We got a little bit better.

  51. 2:05

    In 2024 we built workflows.

  52. 2:07

    2025 was all about MCPs, skills, and

  53. 2:10

    orchestration.

  54. 2:12

    And we believe this year, 2026, is when

  55. 2:14

    agents actually start paying for

  56. 2:16

    services that they want.

  57. 2:19

    And the signals are promising.

  58. 2:22

    Just in the last 30 days,

  59. 2:25

    uh agents have transacted with paid API

  60. 2:29

    endpoints,

  61. 2:30

    uh and the volume is about like $24

  62. 2:32

    million. Uh

  63. 2:33

    over X102.

  64. 2:35

    And 99% of it has been settled in USDC.

  65. 2:40

    While this number may look small in

  66. 2:42

    terms of volume in the broader

  67. 2:44

    landscape,

  68. 2:45

    it's only about to get larger.

  69. 2:48

    So, what is X102? Um essentially, X102

  70. 2:52

    is

  71. 2:53

    a way where agents can uh pay for their

  72. 2:56

    the resources that they want because

  73. 2:59

    the server essentially returns a 402

  74. 3:01

    header

  75. 3:02

    and with the details of how they want

  76. 3:05

    the payment to

  77. 3:07

    proceed. And then the agent just signs

  78. 3:10

    um an authorization from the crypto

  79. 3:12

    wallet and then pays for the resource

  80. 3:14

    and retries the request again. So,

  81. 3:16

    that's

  82. 3:17

    in X102 in a nutshell and we'll see that

  83. 3:19

    in action in a live demo.

  84. 3:21

    But then, the question is

  85. 3:24

    why do the traditional payment rails not

  86. 3:27

    work and why do the agents get stuck?

  87. 3:30

    So,

  88. 3:31

    the answer is simple, uh because for the

  89. 3:33

    last 30 years we built the internet

  90. 3:36

    around one customer

  91. 3:38

    and that was humans.

  92. 3:39

    Right? Um so, we built payment schemes,

  93. 3:42

    uh monetization strategies, all catered

  94. 3:45

    towards how humans interacted. So, you

  95. 3:48

    had your sign-up flows, add your credit

  96. 3:51

    card, uh put in your information, and

  97. 3:54

    manage your API keys, but agents just

  98. 3:56

    don't function that way.

  99. 3:58

    Agents

  100. 3:59

    want to like come in and grab that piece

  101. 4:01

    of data, resource, compute, inference,

  102. 4:04

    whatever, and just

  103. 4:06

    uh you know, and they have the ability

  104. 4:08

    to even like consume knowledge at a

  105. 4:10

    scale that humans just cannot.

  106. 4:12

    I'm sure like you have seen sessions

  107. 4:14

    where it's able to like just scrape

  108. 4:16

    through hundreds of web pages, and um

  109. 4:19

    then it just like stalls because it

  110. 4:21

    can't like reach a particular endpoint,

  111. 4:23

    and it skips over it.

  112. 4:25

    So,

  113. 4:27

    then you could think, "Oh, yeah, just

  114. 4:29

    give it a credit card." or something

  115. 4:30

    like that. So,

  116. 4:32

    while that is possible,

  117. 4:35

    um these agents,

  118. 4:36

    uh because they consume so much data as

  119. 4:38

    they go,

  120. 4:39

    it's um

  121. 4:41

    they pay in fractional amounts, so tiny

  122. 4:44

    amounts, uh but at a very high

  123. 4:46

    frequency.

  124. 4:47

    Uh and credit cards and their fees are

  125. 4:49

    just like not sustainable for this kind

  126. 4:51

    of like economic model. Um you cannot

  127. 4:53

    pay like 3% uh each time an agent tries

  128. 4:56

    to make a one-cent transaction. And the

  129. 4:59

    reason these transaction amounts are so

  130. 5:01

    small is because on the sell side or on

  131. 5:03

    the merchant side, they've realized that

  132. 5:05

    these paywalls were actually catered for

  133. 5:08

    humans, and now there's an entirely

  134. 5:10

    different customer base which is trying

  135. 5:12

    to like access their data, and they just

  136. 5:14

    want like a subset of the data. So, you

  137. 5:17

    could monetize that as a seller by just

  138. 5:20

    offering that, by wrapping that in a

  139. 5:22

    uh you know, in a paywall, and saying,

  140. 5:24

    "Hey, I take one,

  141. 5:26

    pay me 10 cents and grab this data."

  142. 5:29

    And that's why these are

  143. 5:31

    tiny um microtransactions, but highly

  144. 5:35

    frequent. So, because the agents are

  145. 5:36

    just like making these API calls

  146. 5:38

    constantly.

  147. 5:41

    So, what do these agents need? The

  148. 5:44

    agents need um payments to work like the

  149. 5:47

    internet.

  150. 5:48

    So, they have to be real time,

  151. 5:51

    low cost, programmable, and always on.

  152. 5:57

    And that's why we've built the Circle

  153. 5:58

    agent stack. So, it's the full stack

  154. 6:00

    platform for the agent tech economy. And

  155. 6:03

    what we mean by that, let's look at it

  156. 6:05

    with a live demo.

  157. 6:07

    Um yeah, wish me luck.

  158. 6:12

    Okay.

  159. 6:14

    So, I'll just explain

  160. 6:16

    uh what I'm trying to

  161. 6:19

    if I can get the

  162. 6:23

    terminal. Okay.

  163. 6:26

    Okay.

  164. 6:29

    Let's

  165. 6:31

    Mhm.

  166. 6:34

    Pull it.

  167. 6:36

    Yeah, I don't know.

  168. 6:40

    Excuse me, can I

  169. 6:42

    Yeah, I tried but

  170. 6:46

    it's just not

  171. 6:47

    I don't know where the placement of the

  172. 6:48

    desktop is.

  173. 6:52

    >> Can you escape out of this?

  174. 6:53

    >> [snorts]

  175. 7:00

    >> Okay.

  176. 7:06

    Thank you. So, so what we have over here

  177. 7:09

    are

  178. 7:10

    two sessions. One is your regular cloud

  179. 7:12

    code and on the other on the right hand

  180. 7:14

    side is a cloud code that comes equipped

  181. 7:17

    with Circle agent wallet. So, it has a

  182. 7:19

    wallet which is funded and has the

  183. 7:21

    ability to like make uh has the ability

  184. 7:23

    to pay for premium content. And now uh

  185. 7:26

    let me actually

  186. 7:28

    just uh

  187. 7:30

    quickly uh

  188. 7:32

    add a task

  189. 7:34

    to this.

  190. 7:36

    Yep.

  191. 7:38

    And run it.

  192. 7:40

    So, I'll explain what I'm trying to do

  193. 7:42

    over here, which is

  194. 7:44

    Yeah, so So, the task I'm giving Claude

  195. 7:48

    on and it's the same task on both the

  196. 7:50

    terminals is

  197. 7:51

    plan my trip for the FIFA World Cup

  198. 7:54

    final.

  199. 7:55

    So, just, you know, give me summary of

  200. 7:58

    flights,

  201. 8:00

    hotels, logistics. Also, like what are

  202. 8:03

    the odds of like my favorite team

  203. 8:04

    Argentina being in the final? Who is it

  204. 8:07

    going to play? And stuff like that. Um

  205. 8:09

    and also

  206. 8:11

    what's the ticket prices in the

  207. 8:12

    secondary market? How is the experience

  208. 8:14

    of other people who've

  209. 8:16

    actually been to the stadiums?

  210. 8:18

    And

  211. 8:19

    are there any FYIs and stuff like that?

  212. 8:22

    Grab all of that.

  213. 8:23

    Send me an email. And if possible uh

  214. 8:27

    make me a make a phone call and tell

  215. 8:29

    confirm that all of this has been

  216. 8:31

    researched and you know, sort of brief

  217. 8:33

    me on the summary.

  218. 8:34

    So, we'll see like what's happening on

  219. 8:36

    on both the terminals here.

  220. 8:38

    And

  221. 8:40

    Sorry, it's a bit hard to navigate. So,

  222. 8:42

    as you can see, um

  223. 8:44

    the left the vanilla Claude code has

  224. 8:46

    spun out like a bunch of sub-agents. And

  225. 8:50

    it's going about doing its research.

  226. 8:53

    Similarly, on the right-hand side um

  227. 8:56

    it's

  228. 8:57

    actually like uh going through

  229. 9:00

    the wallets and making like um

  230. 9:03

    paying for all of these

  231. 9:04

    uh premium content and we'll see like

  232. 9:06

    what the results of it are.

  233. 9:12

    So, as you can see, it's trying to make

  234. 9:15

    a phone call to find sorry, an API call

  235. 9:18

    to Stable and Rich. Um and it's paying

  236. 9:21

    from its wallet.

  237. 9:22

    It's set up a guardrail of like, "Hey,

  238. 9:24

    max amount is 15 cents." The beauty of

  239. 9:28

    uh

  240. 9:29

    having an agent with a wallet is

  241. 9:32

    you

  242. 9:33

    sort of build these guardrails into the

  243. 9:36

    wallet. And you don't have to as a human

  244. 9:38

    approve every single transaction

  245. 9:40

    because that would just not scale

  246. 9:42

    because these agents are just making

  247. 9:43

    these ones and five cents, 10 cents

  248. 9:45

    transactions. You want to like enforce

  249. 9:47

    those guardrails which is hey, this is

  250. 9:49

    the max amount you can send spend per

  251. 9:51

    session or this is the max cap you can

  252. 9:53

    do per day and stuff like that. So,

  253. 9:56

    the agent is still spending within the

  254. 9:58

    guardrails that you set but it is

  255. 10:00

    autonomous enough to like make these

  256. 10:02

    individual API calls.

  257. 10:07

    So, let me just

  258. 10:10

    look at what

  259. 10:13

    the vanilla one is

  260. 10:16

    looking up and doing some research for

  261. 10:18

    hotels.

  262. 10:22

    Yeah, um

  263. 10:25

    flights are coming in.

  264. 10:28

    Also like in the prompt like try to like

  265. 10:30

    tell the agent to

  266. 10:32

    wrap this whole thing up within 6 to 8

  267. 10:34

    minutes in the interest of time. So,

  268. 10:35

    let's see if we're able to like get an

  269. 10:38

    email and a phone call done

  270. 10:40

    in the same time.

  271. 10:51

    Let me also walk you through

  272. 10:55

    what the agent's doing if I can grab.

  273. 11:05

    Yep, as you can see over here the agent

  274. 11:08

    was able to like make an API call to

  275. 11:11

    the poly market data

  276. 11:13

    via a provider called Block Run and

  277. 11:17

    it provided a query

  278. 11:20

    and again

  279. 11:21

    set the max amount guardrails

  280. 11:25

    and is now passing all the results.

  281. 11:53

    >> All right.

  282. 11:54

    So,

  283. 11:55

    let's go back to the

  284. 11:58

    main subject main agent here.

  285. 12:23

    Yep.

  286. 12:23

    And this is where I think you'll see on

  287. 12:25

    the left-hand side that the agent gets

  288. 12:27

    stuck because

  289. 12:29

    the agent just does not have the ability

  290. 12:31

    uh it cannot send out an email natively.

  291. 12:34

    So, what it's doing is it's using my uh

  292. 12:37

    it's just like adding a draft into my

  293. 12:40

    Gmail account uh that is logged in, but

  294. 12:42

    it just cannot send it to someone. Uh

  295. 12:44

    whereas the other agent on the

  296. 12:46

    right-hand side will just be able to use

  297. 12:49

    um a provider, pay it, and send an

  298. 12:52

    email.

  299. 13:00

    Now, let's see like

  300. 13:03

    this one's uh the

  301. 13:05

    the other agent is also like

  302. 13:07

    uh is about to like send an email and

  303. 13:09

    place the call, so let's see.

  304. 13:11

    Does.

  305. 13:30

    >> Okay.

  306. 13:32

    So,

  307. 13:33

    as the

  308. 13:35

    I think the left agent, the vanilla

  309. 13:37

    cloud goods finished, and as you can

  310. 13:38

    see,

  311. 13:39

    it's sort of like made a confession that

  312. 13:42

    yeah, it cannot have It does not have

  313. 13:44

    the ability to make a phone call. So,

  314. 13:46

    it's just like providing me the

  315. 13:48

    highlights over here in the terminal

  316. 13:49

    itself. Um and

  317. 13:53

    now, uh whereas on the right-hand side,

  318. 13:55

    the email's been sent. Now, let me try

  319. 13:59

    to

  320. 14:02

    actually show you the email that we got,

  321. 14:05

    I wish.

  322. 14:10

    Grab this somehow.

  323. 14:19

    Okay, I'm going to make

  324. 14:21

    make the phone call.

  325. 14:25

    Okay.

  326. 14:35

    Just going to grab my

  327. 14:40

    thing here, and then

  328. 14:43

    let's look at the email.

  329. 14:46

    So,

  330. 14:51

    yep, there we go.

  331. 14:52

    So, I got this email. Oh, this is the

  332. 14:55

    old one. Let's see the new one.

  333. 14:59

    Yep.

  334. 15:01

    This is the one that we just received

  335. 15:03

    like 2 minutes ago.

  336. 15:05

    And

  337. 15:07

    yeah, it has all the

  338. 15:09

    details that it was able to like find,

  339. 15:12

    including like getting to the stadium,

  340. 15:14

    open stadium and maps. It was able to

  341. 15:16

    like,

  342. 15:17

    you know, find all of these.

  343. 15:20

    And then,

  344. 15:23

    what to expect by looking at like Reddit

  345. 15:27

    tickets, etc.

  346. 15:30

    So, I'll wait for the call but in the

  347. 15:32

    interest of time it takes sometimes

  348. 15:35

    a few minutes for the call to come in

  349. 15:37

    but

  350. 15:39

    let's see and I'll move on. So, how does

  351. 15:42

    this work uh

  352. 15:43

    in the background?

  353. 15:45

    Is

  354. 15:48

    Yeah, let's get back to this. Let's

  355. 15:57

    Yeah, so so as you can see like the

  356. 15:59

    agent on the right hand side with the

  357. 16:01

    wallet was able to just make a bunch of

  358. 16:04

    these API calls and pay for it. While

  359. 16:07

    blockchains make all of these things

  360. 16:09

    theoretically possible, there are there

  361. 16:11

    are also some bottlenecks because uh

  362. 16:14

    even the most efficient blockchains

  363. 16:16

    have a gas fee and these small

  364. 16:19

    transactions just don't scale because

  365. 16:21

    the gas fee will again be a significant

  366. 16:24

    sort of

  367. 16:25

    fraction of the actual transaction. But

  368. 16:28

    it is important to have gas fees because

  369. 16:30

    they prevent the network from spam and

  370. 16:32

    abuse.

  371. 16:33

    Um and blockchains also have some

  372. 16:35

    throughput limitations because there are

  373. 16:37

    other use cases that run on blockchains

  374. 16:40

    and block space is shared

  375. 16:41

    infrastructure. So, the problem for

  376. 16:43

    agents is unpredictable latency and

  377. 16:45

    degraded performance under load.

  378. 16:47

    So, what we did for that

  379. 16:50

    is

  380. 16:51

    essentially uh we built a new um

  381. 16:55

    infrastructure layer on top of our intra

  382. 16:58

    product called gateway. So, it's called

  383. 17:00

    nano payments. It's built for sub cent

  384. 17:02

    transaction sizes for as low as one

  385. 17:03

    micro cent.

  386. 17:05

    Uh it supports

  387. 17:06

    um it is gas free for the seller and

  388. 17:08

    it's instantly cross-chain.

  389. 17:12

    And

  390. 17:13

    the way it works is you essentially you

  391. 17:16

    just fund um

  392. 17:17

    your wallet and then Oh, sorry. While I

  393. 17:20

    explain this, let's listen to the actual

  394. 17:22

    call that came in.

  395. 17:23

    And

  396. 17:24

    >> Hi Harsha, here is your World Cup final

  397. 17:26

    trip

  398. 17:27

    >> I don't know if it's part of it.

  399. 17:28

    >> at MetLife Stadium. Fly SFO to either

  400. 17:31

    EWR or JFK non-stop. SFO is showing live

  401. 17:35

    arrival delays today, so build buffer.

  402. 17:37

    >> Awesome.

  403. 17:38

    Can you tell me how do I get to the

  404. 17:41

    stadium from my hotel?

  405. 17:45

    >> On match day, take NJ Transit to

  406. 17:47

    Secaucus Junction, then the Meadowlands

  407. 17:49

    Rail Spur direct to the stadium. Budget

  408. 17:51

    about an hour before receipt.

  409. 17:53

    >> Thank you. I'll read the rest of it in

  410. 17:55

    my email. Thank you.

  411. 18:01

    >> You're welcome. Have

  412. 18:03

    >> All right. So, that was just a quick

  413. 18:05

    demo of like how you can have like AI

  414. 18:08

    agents.

  415. 18:09

    Um if they're equipped with a wallet,

  416. 18:10

    they can do a lot of things

  417. 18:12

    with the

  418. 18:13

    as opposed to an agent that does not

  419. 18:15

    have a wallet. So,

  420. 18:17

    I have a couple of more minutes, so I'll

  421. 18:19

    just walk you through how this

  422. 18:21

    technology works underneath.

  423. 18:23

    So,

  424. 18:24

    if you have a wallet and you funded it

  425. 18:27

    with USDC, it's very easy because Circle

  426. 18:29

    works with a bunch of providers to

  427. 18:31

    on-ramp your actual US dollars into

  428. 18:33

    USDC. And from there, you can deposit

  429. 18:36

    the funds into a smart contract. The

  430. 18:38

    next thing it does is

  431. 18:41

    the agent just has to like sign these

  432. 18:43

    off-chain authorizations,

  433. 18:45

    which are essentially cryptographic

  434. 18:47

    signatures saying, "I

  435. 18:49

    am paying this address this particular

  436. 18:52

    amount of money."

  437. 18:53

    And then

  438. 18:54

    the server just has to like relay this

  439. 18:56

    to Circle and within a few hundred

  440. 18:58

    milliseconds,

  441. 19:00

    this the server knows

  442. 19:02

    the merchant knows that, you know, the

  443. 19:05

    user has the funds and is able to

  444. 19:07

    release the actual resource that the

  445. 19:09

    agent requested. And with this, you

  446. 19:11

    avoid the

  447. 19:13

    issue of like you know latencies and

  448. 19:15

    stuff that are associated with actually

  449. 19:17

    settling every single transaction on

  450. 19:19

    chain and this

  451. 19:21

    the agents are able to like pay for

  452. 19:23

    things

  453. 19:25

    at the speed at which they operate. So

  454. 19:27

    in conclusion the the the way the stack

  455. 19:29

    would work is you have Circle agent

  456. 19:32

    wallets which give you the ability to

  457. 19:35

    equip your agents with wallets.

  458. 19:38

    The agents have can now hold their

  459. 19:40

    money, spend that money autonomously but

  460. 19:43

    within the guardrails that you set. The

  461. 19:45

    wallets enforce those guardrails and

  462. 19:48

    then on the sell side the merchants are

  463. 19:50

    able to like just

  464. 19:52

    wrap their endpoints and resources and

  465. 19:54

    monetize it with a few lines of code

  466. 19:57

    using our SDKs.

  467. 19:59

    Then

  468. 20:00

    USDC and nano payments is the layer

  469. 20:03

    underneath it which sort of helps settle

  470. 20:05

    these transactions at the speed at which

  471. 20:08

    agents operate which is sub second. So

  472. 20:11

    and that this is how it scales

  473. 20:13

    and you can give it a try yourself by

  474. 20:17

    going to agents.circle.com.

  475. 20:20

    It's just a couple of clicks and

  476. 20:24

    you will have your agent equipped with a

  477. 20:26

    wallet and ready to like you know make

  478. 20:29

    these phone calls and things like that.

  479. 20:31

    So yeah, thank you.