Build a production-ready agent with Claude Managed Agents

Hi everybody. How's everybody doing? Yeah. Okay, cool. Um, raise your hands if you've heard the phrase cloud manage agents get brought up like 50 times today. Okay. And keep your hand raised if you have have any idea what cloud manage agents even is. Okay. Not a lot of hands. Cool. Um and raise your hands if you're excited to learn about cloud manage agents today. Okay, there we go. I like that. Um hopefully this will be a little bit more of a technical deep dive. Um myself and a couple of my uh peers earlier today talked at a very high level. We showed you some slides. Um we talked about the primitives and whatever. And we'll do a little bit of that here today. But uh really what I want to make sure that we do is like have our laptops out, start coding. I have a little starter repo for us to kind of go through together. Um and my hope is that by the end of the session, you will be able to go get started with building on cloud manage agents today. Does that sound good to everybody? Cool. Quick agenda. Uh we'll do a quick overview of what cloud manage agents is. We'll go over a lot of the same kind of um discussion points from earlier today. Um and then we'll we'll spend some time actually building something um relatively from scratch. um and actually get something that you could be deploying to production today if you wanted to. Um and then we'll wrap up the session with some more advanced topics around cloud manage agents and just the the composable things that you can do with it. So um cloud manage agents at a high level is just a set of API endpoints that we've developed and released. um you can go use them with any API key today. Um that give you uh access to uh like scaled ready, production ready uh agent uh and all of the primitives around it that you can just build your own products on top of. You can pick and choose whatever primitives you need um and ditch the rest and then build whatever product experience you need on top of. So we took care of a lot of things like giving cloud access to a computer. Um giving it access to credential vaults if you want to inject things like MCP authentication for your own end users if you need to like get access to their linear MCP or cloud more accurately needs access to that. Um the tool calling um harness and everything uh retries and error recovery that might happen uh in production. um as well as a bunch of really nice primitives around like memory and context management and uh multi- aents uh that make it really really easy to be able to really like skate the exponential and like just benefit from each increased model uh family as they come out. Um, and then the the the really nice thing with cloud manage agents, which we'll show a little bit later today, is that um we built a lot of really nice observability um views into our developer console um that you can go to today in order to like just live debug what these agents are up to. And we'll show a little bit of that as well. Cool. So, the the main kind of like building blocks for cloud manage agents are the agent itself, which is really just like think of it as like a template. You want your agent to have a certain system prompt. You want it to have access to certain skills. Um, maybe you want to define what tools you want that agent to have access to. Um, some agents you want to have access to the bash tool and web search. Some agents you want to really make sure don't have access to the web because you don't want them to get prompt injected or whatever. Um, and you can like really pick and choose which which tools they have access to. Um, and you can also choose which MCP servers they get connected to which is also really really nice. Um, another really nice added uh aspect of like setting up all these agents is that you can also define um certain permission controls on a per tool basis. So you can decide that something like the file read tool um can just autoexecute whereas something like um executing bash or uh calling your databases MCP server um requires explicit approval from from your own end users. Um once you configure that agent you also can configure an environment. Um these environments kind of define the template for how the sandboxes that claude has access to behave. So you can define whether or not you want those containers to have network access. Maybe you want to pre-install certain packages from npm or from uh pip. Um so you can kind of define that in your environment level. And today since we announced uh self-hosted environments and sandboxes, you can also bring your own sandboxes uh that don't just run on anthropics infrastructure. You can use something like Cloudflare or Modal or Versel um and use those out of the box or even your own um sandboxing fleet. Um once you configure those two things, you can then just like get started on talking to to that agent, right? you you have an ID for your agent, you have an ID for your environment. That's kind of all you need to get started with a session. Um, and a session is just you can think of it as kind of like an ongoing conversation with you and Claude. It's the equivalent of going to claw.ai and clicking new or uh entering cloud code from your terminal. Um, once you do that, you can like start submitting events from your own end users. Something like them asking for something to to happen. Um, maybe you that that end user is asking for a PR to get put up. Um and that that all of that kind of happens on the session layer. Um and when you create these sessions, you can also include certain GitHub repositories that you want cla to have access to or um certain files that you might want to be preloaded into the container itself. Um so all of those will kind of be downloaded and and provisioned on on your behalf. Um and then finally there's just like the events, right? Like these sessions are just like ongoing event streams uh where you submit messages from your client um and we return s responses that claude is processing them doing whatever it is that it's it needs to be doing. Um and that's that's effectively like the the four major aspects of cloud manage agents. There's a couple of other things um along the sides but those are like the main primitives that that you kind of have to worry about. So diving a little bit deeper into the events that we have um like I mentioned there's like user events. These are things that you might want to submit from your own application. Maybe your user said something or maybe your platform just autosubmitted some sort of um user event. Um these can include images, documents, text, whatever it is that you need. Um you can also send interrupts from your own uh product, your your own platform. Um and you can use those in order to cut off Claude if if it was like going off on a bad tangent or or doing something wrong and you wanted to steer it. Um so you can kind of use that to prevent it from doing any sort of like dangerous action. Um you can also submit uh tool results for custom tools that you define and execute in your own uh platform. Um or confirmations for human in the loop controls for any sort of server executed tools. Um and then you can also define uh outcomes which allow you to like essentially pass us either a file or like a blob of text that you um wrote that uh is almost like a spec that claude will like try to do a first pass at implementing or or doing the thing that the spec defines. Um and then it will launch uh it will essentially enter a mode where it tries to like iterate and check its work against that rubric over and over again until it finds that it can like it actually satisfy that rubric. Um which we found to be really really powerful. Um it was a really really great way to like set up uh your agents for success. Um next we have agent events. Agent events are just anything that Claude is doing. So these are like messages that Claude is sending back to the user. compaction for if cla is uh needs to like uh you know compact its context window because it got too large. Um the tools that it's kind of executing on your behalf whether those are MCP tools or the uh default agent tools that we've defined. Um and then there's also multi-agent coordination events for when claw decides to spawn other agents to help it in doing its work. And we'll show a little bit of what that looks like uh during the live uh demo. Um next we have session events. Session events are just like life cycle events that let you know when the status of the session is changing. Maybe it entered a a retry loop. Uh maybe there's some sort of error. Maybe there the the the session needs to like idle for whatever reason. Um or if it needed to terminate. So there's just like a a bunch of like state transitions um and error uh events. Um and then there's also like an event for like outcome processing. So you just know when claude is entering this mode of like iterating against that outcome rubric. And then finally, we have span events, which are just used to like let you know when certain things are starting and ending that we know are going to be long long lasting. So like everybody here has probably experienced uh Opus 4.7 like you know generating an entire document that's really really long. So we just wanted to make sure that you know when that's kind of starting and ending so that um you don't think things are like just getting stuck on our end. So, um, in addition to kind of like those core primitives and the events that I went over, like I mentioned, uh, earlier today, we launched, uh, self-hosted sandboxes, which allow you to bring your own containers, um, instead of using the ones that we provide. Um, a lot of people already have existing, uh, like accounts with Cloudflare or Versell or Modal. Um, and, uh, a lot of the time you have your private data up there and you just don't want that to like exit your own VPC or your own perimeter. So um to to get around that we uh are able to like connect to those sandboxes natively um and use those instead of using the ones that we had on our own end um and then you can kind of configure how those sandboxes operate end to end, right? Like at that point that that's entirely up to you. We'll just let you know when Claude needs a new sandbox and then that's it. You just spawn one and connect it. Um, we also launched MCP tunnels which very similarly allow you um if you have like a you know private MCP servers within your private parameter um you might not want those exposed over the internet. So we set up a way for you to have a secure tunnel um that accesses those MCP tunnels or those MCP uh servers that you have privately in your own network. Um and then Claude can directly connect to that safely without uh those MCP servers ever being exposed on the internet. It's a really really uh nifty way for you to be able to connect more private uh data sources to to cloud and to cloud manage agents. So uh that's pretty much all I have for slides. Maybe we'll get back to them a little bit later, but let's uh let's actually do some like fun stuff. So um I'm going to be working out of this repository. I'm going to zoom in on the screen a bunch so you guys can see it. It's a public repo if you guys want to go clone it, get started with it today. Um there's a bunch of really interesting content in here from some of the other workshop presenters. So highly recommend going through a lot of this. There's a lot of really interesting patterns here. Um today we're going to be focused on on uh the production ready agents. Um and in this directory I included both like a starter version of this web app that I'll be showing you shortly. Um and then the solution version of it if you want to you know cheat skip to the end and just see how things work uh end to end. So what what are we actually building here? Um I built this very contrived deal uh product. Um you can imagine that we work uh on some mergers and acquisitions. We have some data available maybe in linear or maybe in our private data sources and we want to use cloud in order to like help us make decisions on whether or not we should invest or maybe acquire certain companies. Um I'm going to show you a kind of like a finished version of this demo. Um there's nothing like particularly fancy here. There's just like a very basic chat UI with all of my sessions on the side. Um, and some information about the session itself uh on the right side. Um, but really the main thing is kind of like this ongoing conversation between uh me as an end user and Claude. And uh the way that we set up uh this deal is uh to actually use uh the new multi- aent feature that we launched uh two weeks ago and uh use that in order to like have various agents with their own kind of personas and their own ways of doing things. So maybe one agent is like in charge of figuring out macro trends in the over in the overall industry that you're working with whereas another one is like really good at like financial analysis. Maybe it has access to a bunch of tools that uh make it better at that or a bunch of MCP servers it has access to. So these are all just like individual uh threads that are happening here that like our main agent thread like kind of kicked off um in order to like answer a question that we that we gave it earlier on. Um, but this is kind of like the finished version of this demo. And and I want us to actually like take the time to learn how to build something like this or build even something more advanced than this. If you were to go home and get started with Cloud Manage agents today, um, all the companies that I've made here are obviously fake and deal is not a real product, but I'm hoping that you guys build really, really interesting things with this. So, um, let's get let's get started on doing that. So, we're in the This is too small, isn't it? Okay, I'm going to zoom in a bunch. Um, so we're in this starter, you know, directory of this uh of this codebase and I'm just going to start my uh server for it so we can test it locally. Um, I'm using bun because we all love bun here. Um, and because it's the starter version of this codebase, immediately we run into some problems. Uh, something's not implemented. Um, and I did this very intentionally because I wanted to walk us through some of the APIs that we have to use in order to build something like this product. Um, so very very basic at the beginning. We just want to have a sidebar that lists all of the sessions that we have, right? So, well, yeah, of course. How's that? Of course. Um, not really optimized for being super big, but that's okay. We're going to deal with it. Um, and here's my code here. Is this big enough? Yes. Okay, great. So, first thing that we ran into is we stubbed out some sort of endpoint for listing all of our sessions. So, obviously that's not going to work. Um, and I'm going to try to implement this function. I haven't written code by hand in a little bit of time. I don't know if you guys have, but please forgive me if this is wrong. Client beta sessions.list. I guess I have a little bit of a hint up top. Okay. Yeah, let's copy paste this. Um, and really what am I doing here? Um, I'm using the Enthropic SDK that I've imported. Uh, and all of these endpoints are kind of available in production right now. So, I just set up the SDK. Um, and I'm calling the list sessions endpoint within the the SDK. Um, and just returning that data. Relatively straightforward. And I didn't even have to refresh the page. That's how amazing Bun is. We we now have uh we now have a uh like the sessions listed from my my workspace. Um and we'll go over and talk about what these look like in the developer console shortly. Um next, maybe we want to implement I don't know. I wrote a bunch of to-dos that are numbered, but I don't think we should do these in this order. Um let's retrieve the session. So to-do number four. Why not? Cool. Are you going to refresh? There we go. And now we have all the data available here. Really, this is just the API response from get session. That's that's really all I'm doing here, right? Like you you list the agent here. Uh you can see all the tools that it has available. It's connected to the linear MCP. Um and maybe would have had some outcomes defined for it, but we didn't in this case. Um now we want to implement the chat view that this is kind of the more the more interesting aspect out of all of this right so there's two kind of aspects to it there's one there's like sending session events uh which is just like the you know a very relatively straightforward endpoint that we have and then the other one is the the streaming endpoint which like streams the events that uh claude is generating or the session is generating from the server to our client. Um, this one might be a little bit more complicated. So, instead of actually doing this myself, I'm going to be extremely lazy and I'm just going to use cloud code. Um, the really really nice thing is that uh cla code ships by default with the claude API skill. Claude API skill uh which makes Cloud really really good at using all of the entropic APIs. Uh, specifically the managed agents APIs that we have. Um, and that's really all you have to do to like make Claude really really good at at using this thing. So, um, I'm just going to tell it, hey, I have a bunch of to-dos in this codebase for using clawed managed agents. I think there were some about streaming events and sending events. I don't know. I'm lazy. Look through the to-dos and figure it out. Make no mistakes. We all know that works so well. Okay. So, while while Claude is doing this for us, um it's going to it's going to read through the skill. It's going to kind of like learn, all right, this is how the manage agent set points work. Um it might even help me like optimize things and make them a little bit better. We're probably going to see over time this thing kind of build and and become more live as we go through it. Um, and yeah, that's pretty much all I had to do to like set up this demo. Like literally when I was setting up this demo, I did a very very like I did a version of what I'm doing right now on this stage where I just like ask Cloud to help me with building this thing, which is really really nice, right? It it it means that like Claude can help you build your own cloud. Um, but uh while while this is like really interesting and we can sit here and watch Claude process things all day long, we know Opus is a little bit slow. So while Claude is doing all of this, um I wanted to quickly go over some of the docs and APIs that we have available today for cloud managed agents. Um so this is our like official developer documentation. I know nobody really reads docs these days. Everybody just points cloud at them. But um I wanted to make sure that everybody here kind of knows that these are available. We have a bunch of endpoints for each of the primitives that I defined earlier for like creating an agent and and updating it and fetching it and everything. Um same thing for our environments. Um and same thing for sessions as well. Um including a bunch of like sub endpoints for like listing all the events in an in a session or listing all or streaming those. Um you can also list all of the uploaded resources uh in that session. So if you included a file in your container or you included a GitHub repository, you can kind of like list those and add those over time to make sure that your um session really stays alive. And then with multi- aent um cloud can like spin off individual threads of other agents kind of like what I showed earlier. Um, so there's a bunch of endpoints that are associated with that as well. Um, and then finally, there's a bunch of endpoints for uh, credential vaults and for memory stores. And credential vaults allow you to um, provision a bunch of MCP servers authentication tokens one time, store them very very securely on uh, with Enthropic. Um, and we will make sure that whenever Claude wants to use one of the MCP servers like the linear MCP or the Figma MCP, um, we will inject those authentication tokens. if you like include that vault in your session without claude ever seeing what those tokens are. So we make sure that like Claude it never enters Claude's context window or anything like that. Um and makes the whole thing a lot more secure. Um with memory stores we give Claude access to like one or several memory stores that it can then read and write memories from over time so that every session that it interacts with can like read from those previous memories and get better than the one before. Um, and we we use all of these things within this this uh demo that I've been working on. Hm. Let's see how Claude is doing. Why would you not implement the rest of these? Finish up the rest, dude. H. Um, Claude Cloud sometimes gets a little lazy. Anyway, um, there's a bunch of APIs here. I highly recommend you read through these. I highly recommend you read through some of our like more long form docs on cloud manage agents as well. they do a great job of kind of outlining all of this stuff. Um, but uh, you know, beyond just like reading this static information, you can also like really use the cloud console uh, to like monitor uh, and get better observability around what each of these sessions is doing. Um, and use a lot of this UI for driving what your manage agents integration looks like. Um, if you just want to get started really quickly, you want to have some a more guided experience, um, we built this quick start that allows you to actually have a chat with Claude and Claude will like help you build your uh, agents and your sessions uh, with you. Um, you also have a bunch of like, you know, predefined templates that you can use as a as a starting point. Um, here you can like go browse to like the actual agents that you have. So here I have a bunch of test ones. Um, clearly I made a bunch of these. Um, and like you can actually see what each one like looks like. Agents are versioned, so if you ever feel like you made an update that you're not happy with to like the system prompt or the list of tools that it has access to, you can always go back to use a previous version. Um, and we never like get rid of that. Um, and this is kind of like where you see the the certain things that it has configured. So in this instance, I configured it with the linear MCP. I didn't give it any skills, but I gave it access to a bunch of other agents that it can interact with. Um, and we'll see shortly what that looks like in our sessions. Do we think Claude finished yet? Do we do we think it's still working? Okay, Claude says it's done. I We'll see. We'll see about that. Okay, sweet. Uh refreshing the page. Looks a little awkward with the with the zoomed in screen, but um generally speaking, it seems like we can like go and create new sessions. Everything here looks good. I'm seeing all of my events. Everything looks pretty good. So, let's let's actually run this thing. So, we're going to create a new session. In this instance, I want to use the linear MCP and I want to use memory stores for this uh demo. Um, and this is just calling our create session endpoint. Um, and here I stubbed out a couple of like, you know, uh like suggestion chips for myself for for this demo. Uh, one is just a regular message uh like just give me a quick read on Acme Robotics in order to get uh information about their financials, I guess. Um, but that's kind of boring. What I really want to show you is uh outcomes. So I have this other suggestion chip that I set up that uh includes a bunch of information about like hey like there's like three companies that we're looking at. Bridgewell Dynamics, Norwood Automation, and Acme Robotics. Uh we have a bunch of data about them all over linear and some files that we uploaded. Um but like we really we want to make a a good decision here. So like can you please like iterate on like finding information about it and then like criticize your own work and like let us know whether or not this uh these these findings that you're saying are like actually like satisfied to to the rubric that we gave you. So let's use that. So all I did was just send a outcome event or an outcome definition event. And now Claude is just like off to the races. It's going to start using a bunch of tools. Um I guess it's going to try to delegate to a bunch of other sub aents. uh and maybe read some of the files that we have uploaded. Um but this is nice and dandy but like I don't know I feel like I am not understanding what's going on under the hood here. So maybe we can go and monitor what the session is doing live. Um and to do that we can go to the sessions view um for this uh agent and actually click into a running session and see the the model kind of like processing things live. Right. So, it it looks like it's already spawned the four other agents that we wanted it to work with. And each one of those has their own context windows and they can like chat with their coordinator and like give it updates as as they're coming along. So, they might say like, "Hey, I don't know, I found this in the in the financials or maybe I looked this up on the internet. Um, you should know about this and maybe give another agent uh that information." Um, so you're going to see each one of these uh kind of like horizontal lines is an independent like agent that's running on its own. Um, and then here you can kind of like take a peek at like individual events that are happening. So, I guess this agent is doing some web searches. You can see the actual inputs and and outputs from those web searches. Um, I don't know what it's actually looking for, but it's looking for something. Um, and then yeah, this these things are all like iterating with one another. Um, you can also like monitor how long these things are taking. So if you find that a tool call of yours is taking a particularly long period of time, you can also just go and debug that and say like, okay, maybe maybe there's a file that is like really inefficient. Um I see you kind of have a question. What's up? So you uh the question was uh can you put plugins into these agents? Uh we're working on something along the lines of that. We want to make sure that like the clawed ecosystems kind of like all cohesively make sense. So, uh, we have started thinking about what these things look like to make things a lot more extensible and like open-ended. Um, we don't have anything quite yet, but the agent definitions themselves kind of operate like these plugins. Um, there's a lot of like similar uh ideas behind a lot of them. So, we're we're going to have something there soon. No, it's a good question. Um, anyway, that's kind of like the main like console view that we have. Um, you have a bunch of like other tabs for, you know, the environments that you create. if you created a self-hosted environment, you can see those here. Um, or the credential vaults that I mentioned earlier. Um, and then really what I love doing is going and reading through these uh, memory stores because you'll see what Claude is like filling in as information for itself. And sometimes I I want to just edit that information if I feel like it it got something wrong. Sometimes Claude messes up. Um, which is really really nice here. Or you can generate and add your own memories uh, by default. Um, so that's kind of like it for this demo. Um, you know, at the end of all of this, Claude is probably going to have something like a like an outcome event where it said like, "Okay, yeah, like I feel like I have enough information for you about these um individual agents." Um, and then it gave me some sort of like uh like outcome evaluation. It seemed like it it it seemed like it was able to get to a conclusion for its uh for its uh things that I asked it to evaluate. So, um, getting back to the slideshow, I probably skipped ahead a little bit, but if we were to do all of this by ourselves, we would have had to build our own agent loop or maybe use the agent SDK, figure out a way to host it somewhere remote. Um, figure out things like context management and handling state transitions and recovery from those state transitions or integrating something like skills and MCP servers. We would have had to figure out a durable storage layer um where you can store all of the events and all of the data about all of your agents or all of your threads. Um we would have had to figure out a sandboxing fleet uh like using something like Cloudflare, but like figuring out how to make that react to what Cloud is doing. Um and then we would have had to figure out the world of like endtoend user uh or end user authentication which like is not easy to figure out uh or or do in a secure and reliable way. Um, so all those things are things that we would have had to build by ourselves if we were to get started on it today. With cloud manage agents, we kind of were able to get all of these things out of the box. We didn't use all of these primitives immediately in this demo, but if we wanted to, we could have. It would have been a very complex looking demo, but that would have been it. Anyway, that's all I have. We finished a little bit early, but if anybody has any questions, I'm happy to answer them or we can leave a little early.