Auth for Agents: Let AI Sign Up for Your Product with auth.md — Michael Grinich, WorkOS

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Auth for Agents: Let AI Sign Up for Your Product with auth.md

Michael Grinich introduces a registration spec built on OAuth standards, then follows an agent from an inaccessible local app to a Cloudflare deployment. The key change is letting an agent obtain access before a human has to complete a vendor’s signup flow.

From a talk by Michael Grinich

At a glance

Ideas worth remembering

  • Registration is a distinct obstacle: knowing how to use an API does not give an agent an account or access token.

  • auth.md describes registration procedures, accepted identity proofs, authentication flows, access limits and later human or organization custody.

  • In the Cloudflare example, the agent presents a signed identity assertion, receives an API token and uses Wrangler to deploy; the conversation still includes human approvals.

  • Providers retain the decision about verification and initial access. Free usage is application-specific, and payment can follow usage rather than block registration.

Longer runs move the bottleneck beyond writing code

A coding agent can work for hours and still stop at a signup form. Michael Grinich, founder of WorkOS, opens by tracing how that mismatch emerged: interactive coding once alternated between a human prompt and a small amount of generated code; longer-running agents can now attempt whole features or products from a single prompt. Several runs can proceed in parallel, leaving the human to keep track of their context.

Autonomous vehicles supply the analogy. A dashboard and cruise control still assume a person is driving. A driverless ride takes a destination and handles the journey. Grinich remembers being astonished by his first Waymo ride, then scrolling X about three seconds later. Delegation quickly becomes ordinary; attention moves from operating the machinery to choosing where it should go.

That autonomy requires more than a capable model. The surrounding harness supplies several distinct needs:

  • Runtime: a safe, secure and performant place to execute.
  • Tools: ways to take actions outside the model.
  • Context: information about the project, system and goals.
  • Feedback: ways to run the work, check it and continue when it is wrong.
  • Human review: code review, evaluations or other checks that the result serves the intended goals.

The model is the engine; the harness supplies the rest of the car. More engine power does not make a vehicle useful without a transmission, drivetrain and wheels. Likewise, improving models creates a reason to adapt the tools and execution environment around them. Registration becomes consequential when those tools need access to services the user has never joined.

0:120:35
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0:12 · section reference included

An agent choosing a vendor still has to become a customer

Building an application creates purchasing decisions even before anyone purchases anything. An agent may decide it needs a database, deployment service, image resizing, video transcoding or email delivery. It can research those options while building. Grinich sees this as a new customer acquisition channel: agents increasingly choose which services become dependencies in a project. His proposed update to “Make something people want” is to make something agents want as well.

The obstacle appears at the first interaction with a new provider. An agent may understand the API and know how to use it, yet lack an account or credential. Connecting tools and supplying context do not complete that first registration step. A service can therefore be technically useful and practically inaccessible to an autonomous run.

Signup defenses grew around a different assumption: automated traffic was something to stop. DDoS protection and defenses against credential stuffing helped harden the login box against automation. Legitimate agents now encounter those same barriers. CAPTCHA-solving features in browser execution services expose the awkwardness: a useful agent tries to defeat the mechanism a provider uses to reject bots, while abusive automation remains a problem.

Even without a CAPTCHA, the workflow assumes a human can read a landing page, enter an email address and password, open a verification message, choose a paid plan, and copy an API key into another system. An agent may have no mailbox of its own. Each assumption creates a possible handoff, turning an otherwise autonomous build into a list of accounts the user must create.

5:275:57
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5:27 · section reference included

auth.md declares how an agent can obtain access

Agent registration needs an explicit way to discover whether a service accepts agents, what it offers and how an agent should establish its identity and intent. Risk assessment still matters. Some harnesses may carry a user’s identity; others may require verification through another channel. Company use introduces organization identity, permissions, entitlements, credential issuance and auditability. These are separate decisions a provider must make rather than consequences of simply allowing automated form submission.

The proposed auth.md file gives the agent a description of the registration path. Its useful declarations answer different questions:

  • Service and procedure: What does this service do, and how can an agent register?
  • Identity and authentication: Which identity proofs are accepted, and which flows—such as SSO, email or MFA—are supported?
  • Access and limits: Which scopes and entitlements are available, and what free-tier constraints apply before further verification or payment?
  • Later custody: How can a human or organization claim the account after the agent creates it?

MCP addresses a neighboring problem. In Grinich’s example, connecting PostHog to Claude means a human adds the MCP server, signs in with existing PostHog credentials and gives consent. That supplies a connection to an account the person already has. The proposed registration path must also support the earlier moment when no such account exists, without requiring a human to complete the initial signup.

The scope is deliberately narrow. auth.md builds on existing OAuth standards to describe registration; it does not claim to solve the whole problem of agent identity, permissions or long-running connections. A declaration can tell an agent which proof a provider accepts. The provider still has to verify that proof and decide what access to issue.

9:079:37
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9:07 · section reference included

From localhost to a deployment without a human signup

The demonstration starts with a concrete failure: friends cannot access an app running on the developer’s machine. The agent identifies the cause—localhost only works locally—and proposes deploying the app to a public service. It offers to look for providers that let it handle signup. Grinich presents this as an illustrative conversation backed by a working demo, rather than an unguided production run.

Discovery changes the vendor choice. In the example, two candidate providers do not advertise agent registration, while Cloudflare has an auth.md declaration. Cloudflare wins because the agent can complete the work there: obtain access and deploy. The practical differentiator is whether the service lets the build continue past account creation.

The agent then creates an identity assertion and presents it to Cloudflare. The provider can verify it, including through an out-of-band process, and choose the initial access policy. Grinich uses a deployment lasting “maybe for 72 hours” as an illustration, not a fixed Cloudflare entitlement. The policy depends on the service’s risks: a small database allowance might be acceptable, while email delivery or actions in the physical world may justify tighter restrictions before any free use.

Successful registration returns a token. The human has not opened a signup page or created the account manually. The agent knows how to use Wrangler, prepares the deployment configuration, makes the necessary changes and deploys the app. The result to look for in the demonstration is the transition from an inaccessible local application to a live deployment after credentials become available.

The demo reports a successful Wrangler deployment and shows the resulting live workers.dev URL and version ID.Open full source frame
The demo reports a successful Wrangler deployment and shows the resulting live workers.dev URL and version ID.
Uploaded demo (5.27 sec)
Deployed demo triggers (0.65 sec)
https://demo.agentic-registration-f49bc.workers.dev

Human approvals remain in the illustrated conversation: look around, choose Cloudflare, make the changes. Grinich jokes that the prompting amounts to “Yes, yes, do it, please.” His proposed next step is to collapse those repeated approvals into one initial instruction. The demonstrated behavior supports registration without manual signup; completing the entire task in one shot is the further capability he says should follow.

12:4713:18
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12:47 · section reference included

An identity assertion goes out; an API token comes back

The architecture separates the harness, user identity and service provider. The harness contains the model, memory and context layers, and connects to a backing identity service. It discovers the target provider’s registration instructions, then sends an ID-JAG: a signed credential representing the user. Grinich also names Firecrawl as another service with which the registration approach works.

The important distinction is between the proof submitted during registration and the access credential returned afterward. The ID-JAG represents identity; the returned API token enables service requests. How do those exchanges fit around the existing application interface? The relationship below shows registration messages flowing between the harness and provider, followed by ordinary API or MCP use.

This keeps the change concentrated at the beginning of the relationship. Once the provider issues an access token, the agent can make normal API requests or call MCP. The provider’s API and the rest of its documentation can continue to serve the same purpose. Registration removes the interruption between deciding to use a service and having the credential needed to use it.

Registration adds an exchange before ordinary service use

Backing identity serviceThe user identity connected to the agent harness.
Agent harnessContains the model, memory and context; discovers registration instructions and presents the signed identity credential.
Service providerCloudflare in the example; returns an access token and accepts ordinary service requests.
The backing identity service supplies the user-identity context. The harness discovers registration instructions and submits a signed identity credential; the provider returns the API token used for subsequent requests.
Read the diagram as text
  • Backing identity service. The user identity connected to the agent harness.
  • Agent harness. Contains the model, memory and context; discovers registration instructions and presents the signed identity credential.
  • Service provider. Cloudflare in the example; returns an access token and accepts ordinary service requests.
  • Agent harness → Backing identity service: Connects to backing user identity.
  • Agent harness → Service provider: 1. Discover auth.md registration instructions.
  • Agent harness → Service provider: 2. Submit ID-JAG signed identity credential.
  • Service provider → Agent harness: 3. Return API access token.
  • Agent harness → Service provider: 4. Make ordinary API or MCP requests.
15:5716:27
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Let usage begin before asking for payment

“I hate the planning step,” Grinich says. The desired output of a prototype request is something running that the user can open and explore. A plan followed by a list of vendors to join leaves the operational work unfinished. Agent registration lets an available free allowance carry the prototype through to deployment before the user has to manage those vendor relationships.

For providers, that extends the signup funnel to agents acting on people’s behalf. Grinich compares the opportunity to product-led growth and freemium: many experiments may be short-lived or never reach production, while some become lasting customers. His expectation of substantial growth is a business hypothesis, not a measured result presented in this recording.

Payment belongs downstream in this proposal. Grinich mentions x402 and work by payment providers, but does not make a payment protocol part of the registration mechanism. Requiring a credit card before the agent can try a service would restore an early barrier. Instead, the provider can permit initial use under its own limits, then ask for payment according to its pricing model. That leaves room for stricter policies where even trial usage carries meaningful risk.

17:0217:31
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A headless entry point, with an open implementation path

The closing example broadens the idea beyond new developer services. Grinich cites Marc Benioff’s description of Salesforce, Agentforce and Slack becoming available through APIs, MCP and CLIs: “Our API is the UI.” He immediately corrects the suggestion that this means removing dashboards. The relevant change is giving agents ways to operate the product alongside the interfaces people use.

auth.md is presented as an open spec with a GitHub repository and a WorkOS-hosted implementation. Builders can also implement and run it in their existing systems. That choice matters for a registration mechanism intended to span vendors: adopting the approach should not require every provider to run its signup infrastructure through WorkOS.

Grinich closes with the iPhone’s introduction as his reference point for a new software platform: a change that enabled other companies to build products on top of it. Agents, in his view, offer a comparable opening. The practical invitation is to build prototypes, talk to users and report where registration gets stuck. The proposed contribution of auth.md is specific enough to try: let an agent become a legitimate service user, obtain constrained access and keep working.

18:4519:15
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Read the complete timestamped transcript
  1. 0:12

    Hello, everyone. Good morning. My name is Michael Grinich, I am the founder of WorkOS, and I'm here to talk to- with you today about agents, and specifically about how we can make agents more autonomous and allow them to access more services on the web. So let's jump in and get started. Shout out to those of you in the front row also. I see you out here.

  2. 0:35

    So about a year ago, software engineers were writing code like this. We were using AI, but we would prompt it, and then we'd write a little bit of code, and then prompt it again, and it would write some more code. And you would continue to do this human-in-the-loop interactive software engineering. Later in the year, we had things like Ralph loops, if any of you remember those, where we kind of automated this. But more or less, this is the way that we were working. It was this human, agent, human, agent back and forth. However, as the models got better and better, they were

  3. 1:05

    able to write more and more code and run for longer periods of time. And so today, a lot of software engineering looks like this. You write a single prompt, and then the agent can spit out a lot of code. And sometimes it can actually build a whole feature, maybe even a whole product, and maybe run for not minutes, but, uh, hours and hours or even days and days. This has really transformed the way that we all write code. I don't write code by hand anymore. Probably you don't as well. And it's not just this one thread. You can actually parallelize

  4. 1:35

    this. So there's many different tools out there, including, you know, the major co- coding harnesses from the labs, that allow you to run many of these in parallel. The limiting factor here, really the bottleneck, is your brain. How much context you can keep in your mind to keep all of these going at once. And this has transformed software engineering. People can be more productive. I think we've all seen in the industry how much faster things are moving. At the root of all of this is actually agentic engineering, agents. Going from these token prediction

  5. 2:05

    language models to reasoning and now long-running processes that can actually do things autonomously for us. And what I think we've seen in software engineering here around agentic workflows is gonna come to a lot of different categories. It won't just be engineers that have this way of working. It'll be people in many different fields. Agents are the next big thing.

  6. 2:26

    I think a good reference for this, a way to think about it, is actually what's been happening with vehicles. So, you know, this looks like a pretty modern car. It has a, you know, digital display on it. This is probably what you would've bought in the last, you know, five to ten years. But if you live in San Francisco or one of the cities with these autonomous vehicles, you've probably seen that we're starting to delete the interface. No longer do you get inside of the car and actually, you know, pull up your phone and get maps, where you as the human are in the loop. There might be cruise control, but you're still in the loop. Instead, these are autonomous

  7. 2:56

    systems. You just say where you wanna go, you get in the car, you don't even say anything, and it just takes off and takes you to your destination. I remember the first time I got into a Waymo, I was blown away, mind totally blown, and then after about three seconds, I pulled out my phone and started scrolling X. It became commonplace. And I think we've seen this already happen with engineering. The power of agents allows us actually to work and think at a higher level, for us to, you know, exercise more of our executive function versus just planning and execution.

  8. 3:29

    There's a question here of what do agents need to be successful? Actually, when they execute, what do they need? Well, first, they need a runtime, a sandbox. They need somewhere that they can run that needs to be safe, secure, performant. They also need tools. They have to be able to go do stuff in the world. An agent's not very useful if it can't take actions, so it needs tools. Third, it needs context. You know, these new models, the power of the intelligence in them, it's kinda like taking the smartest person you know and dropping them into a company or a project or a team where they don't know anything. They can't

  9. 3:59

    really get anything done. They need to have context, information about the system, information about the goals. They need feedback, so a way that it c- they can actually run and validate, that they can check that their work is correct, and if it's not correct, keep going. Then last but not least, of course, they still need human review. This might be code re- review. This might be other forms of evals. This might be forms of checking their work to make sure that these agents are sort of aligned with your goals.

  10. 4:27

    The LLM, the intelligence engine, this new technology we've created in the last, last few years, you can think of as like an engine. It's like a really high performance, you know-- I think this is a, a V8 engine. You know, puts out a lot of horsepower, can convert fuel into, you know, output. But an engine by itself isn't very useful. For a car, you need to drop this into the actual car itself. You need the chassis. You need the transmission. You need the drivetrain. You need the wheels. And only with all of that is it gonna be effective to take you

  11. 4:57

    places. And this is what a lot of people refer to as the harness. Harness engineering is this new domain where if the models get better but you don't have a good harness, you know, it's not gonna be very effective. So as the models improve, we change our harnesses, we adapt them to it, and those things that I mentioned earlier are sort of a form of a harness. So agents execute within these harnesses to get stuff done, and they, they need all of those elements to actually be effective. And when they drive, they drive really, really fast.

  12. 5:27

    So say you have one of these agents that's going off. You prompt it to go build something for you. You know, it spins for a while. It says, "Okay, I'm gonna need this feature and this feature, and I'm gonna need a database, and I'm gonna need, you know, this ent- uh, you know, system to deploy, and I'm gonna need, you know, maybe this thing for image resizing or video transcoding or sending email or whatever." And your agent can actually go do all this research and build all these systems. And today, what's happening with agents is they're actually selecting vendors. You've probably seen the rise of some of these systems where, you know, like, the CEOs will

  13. 5:57

    tweet about their growth graph, and it really takes off, and it's because agents are picking them. They're picking their systems for sending email or deploying code, their systems for storing data. Today, actually, it might be more important to build for agents than to build for people. Agents are kind of this new consumer class. I'll talk about that in a bit. There's this, uh, kind of popular thing that people say in San Francisco and Silicon Valley, "Make something people want." This comes from Y Combinator, you know, the startup factory from Paul Graham. And

  14. 6:27

    I think it's time to maybe edit this a little bit, and going forward, we also need to think about making something that agents want. There will be more agents in the future than people, maybe even today. They'll be faster to spin up. They'll do things quicker. They'll be making decisions on our behalfs. And so if you want to build for the next era of consumers, you should be building for agents as well as people.

  15. 6:51

    But there's a problem today. You can access the web, you can access mobile, but agents themselves can't really access systems. Your business probably isn't open for agents today, even though there's a lot of them out there, they can spawn very quickly. The door's not open.

  16. 7:10

    And we think this is because there's a missing primitive: agentic registration, agent registration. There's a lot of great stuff around agents connecting and bringing context to systems and different open source frameworks, but that first step of an agent actually signing up for a service is actually missing, hasn't been solved, and is a huge blocker to getting adoption.

  17. 7:33

    For the last, like, twenty years, maybe thirty years, automated traffic on the web has been bad. We've tried to block all of it, and so there's all these systems that we've put in place to detect automated actors and stop them in their tracks. DDoS prevention, credential stuffing and attacks. The login box, for example, is very hardened against agentic registration today. Not intentionally, but just because of the legacy systems of what we've built. And it's very hard to distinguish between what's

  18. 8:03

    a good automated user versus a bad automated user. If any of you have used any of these, like, cloud-based, uh, browser execution environments, one of the selling features they often have is to break CAPTCHAs, which is pretty wild. You know, we're trying to go backwards. The CAPTCHA today, though, is, is still kind of dead. There's rampant abuse. There's lots of token fraud. And so we need to find a better way to allow the good agents in and then block the bad agents, right? Because like I said earlier, if you don't build for the agent economy, your product might

  19. 8:33

    not win. It might not be successful.

  20. 8:38

    Today's sign-up flows assume that a human can read the landing page, that they can fill out a form, you know, put their email address, their password in it, that they can solve a CAPTCHA, that they can verify their email, not just put it in, but go click something somewhere. Remember, an agent probably doesn't have an email address. If it's signing up for a service, it needs to have a-- you know, a human can choose a plan to pay for it. You know, a human can copy the API key out, paste it somewhere, use it somewhere else. And really even a dashboard, think of a dashboard experience. It's not really

  21. 9:07

    agent native. All this stuff is built for people. It's kind of a human interface, not an agent interface. Agents need something else. They need native discoverability. Can they register for a system? Are the doors open for agents or not? Capability declaration. What can it do? Registration intent. Why are you registering? What are you trying to do within this? Or the intent to actually just sign up. There's a lot of stuff around risk here. So for an agent native registration, maybe you wanna-- you're not sure if the agent signing up is

  22. 9:37

    gonna be good or bad, so you need to actually do an, a risk assessment of that. There might be different forms of identity verification for an agent. If something like Claude is going and signing up, maybe it can bring the user's identity with it. Or if you have a, you know, OpenClaw or, like, your PyHarness or something else, maybe it doesn't bring the user's identity and gets verified out of band. There's the whole thing around organizations doing this. So if I'm building something within a company, how does my company identity come in? You know, my organization.

  23. 10:08

    Entitlements, permissions, credential is-issuance, auditability, the list goes on. There's so many things that need to be changed. In fact, probably most things need to be changed going from, you know, human registration to agent re-registration, agent native systems.

  24. 10:26

    I'm sorry to say MCP is not enough. Probably more than anybody, I'm a big MCP fan. We've done a bunch of events in San Francisco around MCP. I see somebody wearing one of our Run MCP shirts up here that we made. Love MCP. MCP is great for connecting, for providing tools, skills, context, but it doesn't solve the registration step. Today, authentication through MCP requires your human to still be in the loop. You give consent. You add an MCP server, say, for PostHog to Claude. You sign in with your PostHog

  25. 10:56

    credentials. What we're talking about here for agent native registration needs to happen without the human involved, or at least not involved initially.

  26. 11:06

    So we've been working on this for a while, and our proposal to this is a new spec we have called Auth.md because Markdown files are the future, right?

  27. 11:18

    Well, how does this actually work? What is Auth.md? Well, the idea here is that Auth.md tells agents how they can become legitimate users. It's a set of instructions that tells an agent registering for a service, "This is what you need to do to sign up and be considered legit and for me to give you access." And the goal here is to give these service providers, you know, people that are building, building services, an agent native sign-up experience, but it's built on existing standards instead of inventing a crazy new religion or

  28. 11:48

    something really complicated. With Auth.md, we're not solving the whole problem around agent identity, you know, permissions, long duration, uh, you know, connective services. We're just trying to solve this narrow one around registration because I think it's a huge blocker. Let's start small and grow from there. This is built on open standards. It's built on a bunch of work that's already been done across the OAuth spec, specifically tailored to that registration step.

  29. 12:17

    AuthMD can answer what does the service do? It can tell agents how to register. It can tell them what identity proofs are accepted, how do- how, how an agent or a user is proving their identity. What auth flows are supported. Can you sign up with SSO or email address or MFA? What scopes and entitlements in- can exist? Kinda what capabilities are here. What free tier constraints apply? You might have a system where you wanna give an agent a little bit of free capacity, but not too much until they verify or pay in some way.

  30. 12:47

    And then, of course, how does the human get involved later? A human or an organization claiming it afterwards. So an agent can sign up, but you want the human to have custody later on. This is what AuthMD is designed to solve. These are the big questions around the registration stuff. So how does this actually work? Well, here's a little, uh, kinda cartoon demo that I'll show you. And all this works by the way. You can go try it after this. So say I'm here in, um, whatever coding harness or system using Py or

  31. 13:18

    Claude or something, and it says, "Welcome back, Michael at WorkOS." That's actually my email if you wanna email me. "Do you wanna keep working on your spelled app?" I'm like, "Yeah, sure. I'd like to share this with my friends, but they can't access it." And the agent's like, "Oh, well, localhost only works on your machine, so your friends won't be able to hit it, of course. To share it, I need to deploy it somewhere real. Some providers actually let me handle the signup, so, you know, you wouldn't have to sign up and do this. You want me to look around for you?" "Yes, please."

  32. 13:48

    And then the agent can go look for services that advertise through AuthMD that they support registration. Just some examples, Stratos, Helio Deploy, they don't support it. But Cloudflare here does have an AuthMD, and so the agent here can say, "Ah, Cloudflare, that's the one. Cloudflare's a winner 'cause I can go sign up for it. I can access this service. I can actually use it. So I can do the whole thing. Do you wanna go with it?" "Yeah, let's do it." This is the registration step. This is kinda where the magic happens.

  33. 14:18

    What my agent is actually doing is minting an identity assertion and giving that to Cloudflare, and then Cloudflare is able to verify that or not. Cloudflare can choose actually to verify out of band. AuthMD is very flexible. There's different ways you can dial it in depending on the behavior that you're looking for. One size does not fit all. Every application is different. Constraints are totally different. If you're building something that's like a database service where there's gonna be very little amount of information, you might wanna give away a little bit of traffic for free. But if you're building something

  34. 14:49

    maybe like an email service or something certainly if you access the physical world, you s- you maybe don't wanna give anything away for free. It's very application specific. So here Cloudflare says, "Okay, we're willing to let you deploy maybe for 72 hours or something like that." Get the identity assertion, boom, boom, boom, go through. It's called ID-JAG is what the standard is. And then it returns back and says, "You're set up with a Cloudflare account now." In this experience, my, you know, human, I didn't go click anywhere. I didn't sign up anywhere. It just, it just got the token. I can make a couple small

  35. 15:19

    tweaks. It knows how to use Wrangler. Want me to make those changes? Go ahead. Does anybody prompt their agents like this? It's just like, "Yes, yes, do it, please." Not really saying much. It's able to write the Wrangler, get the thing set up, go through the full deployment process, and then boom, it's live. We actually have this working as a live demo. We did some collaboration with Cloudflare on this too. It's pretty cool. And you can tell the prompting that I was giving through this, not exactly rocket science. The agent could just run through the whole thing actually. There's nothing actually

  36. 15:49

    that I was doing through prompting it other than just approving, approving, approving. It should be able to do this one shot.

  37. 15:57

    This is what it looks like graphically. So agent registration with AuthMD, you have your agent harness, Py for example. Within that is your LLM, maybe your memory, different, you know, context layers. It connects to your backing identity service, so this is the user identity. And when that agent goes and registers, it sends the discovery call to Cloudflare. It looks for that AuthMD or whatever service. We also have this working with Firecrawl. It's pretty cool. It sends that ID-JAG, the identity, uh, JSON

  38. 16:27

    access grant. It's essentially a signed credential that represents the user. Says this is an identity. Receives back the access token, actual API token, and then boom, it's, it's done. You can make normal API requests. You can call MCP. Everything else still works. So you can see that AuthMD is just for the registration step. Your normal API keeps working. The rest of your docs don't have to change. It's just that registration step for agents. But with the simplicity comes actually an enormous amount of power

  39. 16:58

    because suddenly it lets agents do things end to end.

  40. 17:02

    I hate the planning step . When I write something, I just want the agent to go do it. Usually, it kind of knows what I'm trying to get at, and I wanna come back to actually a running prototype and not like, "Hey, here's my long plan and here's a bunch of services to sign up for." If I'm building new prototypes especially, I would prefer it just to get deployed on something for free so I can see it and click around and not put me through the burden of going signing up for all these different vendors, and that's what AuthMD allows for. And if you're a service provider, if you're building APIs or services, this allows you to become a customer of those

  41. 17:31

    systems, and you can think about it increasing your growth funnel. Starting from, you know, maybe just humans and adding the whole world of agents on top. Pretty great.

  42. 17:43

    We think this is gonna be huge. Your door will be open for agents to actually sign up, register, use your services. This should be an immediate growth boom for your products. And I'm not saying everything that agents are gonna build will be useful. Maybe not everything they build will go into production or last that long, but some things will. Just like with PLG or freemium before that, this is the way to grow your business and get more customers and actually become, you know, larger and more successful. And where there's usage, we believe there's also intent to

  43. 18:13

    pay. There's a lot of interesting work being done for agents to actually... pay for stuff. There's crypto-based protocols like x402. There's other things that the payment providers are building. But we think that should be downstream. We don't want payments to be upfront. We don't want to have to force your agent to sign up with a credit card. That seems backwards. We moved away from that in the world of SaaS. With AuthMD, agents can sign up, they can register, they can start using it, and then downstream choose to pay on your terms based on your own pricing, based on your own model.

  44. 18:45

    If you don't believe me around the headless type of products, this is Marc Benioff. He's the CEO and founder of Salesforce, the guys with the big building here in town. They believe in agents more than anything. Our API is the UI. Entire Salesforce and Agentforce Slack platforms are now exposed as API, MCP, and CLI. Talk about going agent for-- first. A company that many people consider to be sort of a legacy SaaS vendor really invented the category of software as a service. They're getting rid of their dashboard and UI. I mean, they're not getting rid of it, but

  45. 19:15

    they believe that agents are the future. So if you're not thinking about this, I definitely encourage you to start building some prototypes talking to users because you don't want to miss, miss this. If you want to use this, this is available today. We have an open spec for it. There's a GitHub repo. You can actually have your agent go implement it. I know it's kind of meta. It's an open spec. WorkOS doesn't control it. We have a version of it that we host, but you can build it yourself. You can run it yourself in your existing systems. I think this is so important that no single vendor owns this.

  46. 19:46

    It's one-click enabled if you're a user of stuff, but you can build it on whatever platform you want instead.

  47. 19:52

    Last thing I'll close with, this actually happened almost twenty years ago, I think actually here at Moscone, which is pretty awesome. In, uh, January of twenty-- uh, two thousand and seven, I believe, Steve Jobs introduced the iPhone. And I was in college, and I remember-- Or, yeah, like first year of college, and I remember this super, super clearly. It was the next great software platform that got built. So many companies got started because they could build on top of these devices, the smartphone revolution.

  48. 20:21

    And there hasn't really been a moment like this since, I think, in the, the era of technology, at least for, for me. The stuff we did around B2B SaaS and cloud and all that is great, but this was a totally new paradigm, a new software platform.

  49. 20:35

    And I think agents are this. Agents are the next big wave. And so what I would say to all of you is go out and build. With AuthMD, we're hoping to unlock this for you, unlock this for your business and for your growth. But we want to hear from you, hear the places you get stuck, and I think together we can build for this next exciting era of software and build for the agentic revolution. Thank you so much.