Every Harness Will Become A Claw — Sam Bhagwat, Mastra

I'll get us started. Um, so, long day of talks, and how are y'all feeling?

Cool. Yeah, good to see we still have some energy. You know, I know there's a lot of, like, evening events. Um, we've heard a lot about the present, and I'm going to talk about the future. Um, so my talk is called "Every Harness Will Become a Claw."

Um, here's a little bit about me. Um, I am the co-founder and CEO of Mastra. We are a TypeScript agent framework. Um, I am also the author of a book that you may have gotten a copy of, either outside or at a previous event.

Um, we have seen a lot of agents running in production, um, over the last 18 months. And I'm not, uh, I'm saying that as kind of context for and stage setting for the thoughts and ideas that I'm about to shareright now.

Um, and, uh, the thing that I'm going to say is, is welcome to the harness era. What do I mean by the harness era? Um, well, uh, let's just talk about the types of harnesses that we seeright now.

We see local harnesses. Um, we use them every day, daily driving our, our coding,right? Um, we see cloud harnesses. Um, these are both products that we can purchase, as well as if we work in some of these, uh, companies that have built their own internal coding agents that live on Slack.

Um, and then, of course, we have the your friendly local, uh, open source frameworks that have some of these primitives and give you the, the tools that you need to build your own. Um, and that's where we that's where we fit in.

Um, now let's talk about where we are, sort of collectively as an industry, um, and how things have evolved over the last, we'll say, year to, to 18 months. Um, last year at, at AI Engineer, we were talking a lot about agents.

We were talking about the agent loop. We were talking about agents versus workflows. Um, so, so I want to, you know, there's as we're thinking about, um, the agentic spectrum, I often compare it to, uh, self-driving as a spectrum,right?

There are different levels of self-driving autonomy, whether that's, like, lane assist, whether that's Tesla FSD, whether that's I'm sitting in the back of my Waymo and there's nobody behind the steering wheel,right? Um, there are various aspects to the agentic spectrum between LLMs, agents, harnesses, and claws.

And I'm going to talk about what we've seen and where we're going. What makes an agent different than an LLM? Hopefully we mostly know this, but just as a quick refresher,right? It's the agent loop. It's tool calls. It's memory.

It's the ability to retry failed tasks. It's Context Engineering. Um, Dex is a close friend and an inspiration for this, uh, one of the inspirations for this talk. Um, and it's agent state,right? These are some things that, like, hey, I'm running an agent in a loop, and I can't just do this with a one-shot call, uh, to, to an LLM,right?

I didn't I've tried to make these qualities. I don't not sure what the quality of taking actions is, active or something, so I just put action. But, um, you know, qualities here are starting to emerge when we move from an agent to a harness.

Durability and doggedness. Um, a friend of mine was referring to an agent that he was using, and he called it dogged, which I really like, and I'm, I'm taking that for this talk,right? So durability, just the sheer quality of, like, being able to run not for minutes, but for hours or days.

Um, you know, what, what, what, what encompasses this? Well, sometimes it's like, hey, I, you know, I, uh, lost a connection in the middle of the turn and, uh, you know, but I persisted the stream, and so now I can resume from the place where I started,right?

There's planning mode. We all see this in Claude Code. Um, parallel subagents being able to fan out multiple tasks at the same time. Uh, we have more affordances with a TUI and slash commands. We have skills. Um, we don't have to define all our agents up front, but we can dynamically create them on the fly.

This is, you know, very powerful. Um, you can spin the, the harness can spin up background bash tasks,right? Um, it will auto-compact when it runs out of the context window. Uh, you know, these are all things we'll see when we use Claude Code or Codex,right?

Um, it persists it will persist threads,right? You can resume a thread once that's you've, like, disconnected from later. Um, you can skew. You can steer. You can interrupt. You're not just blocked waiting on the LLM. Hey, I take a turn and then you take a turn.

I'm playing, playing Civilization here, and I can't take a turn until all the other civilizations are playing. No, I'm playing StarCraft. I'm playing Age of Empires. Um,right? Uh, you know, session long. Um, tool approval. So it's not just like, yeah, I approved this specific tool call, but yeah, you can run all instances of rm rf /,right, that, that you see in the session.

Even though the first one will probably wipe your machine. Um, okay, so there, there's, like, you know, there's a, um, there's a few steps here, and I'm, I'm, I'm about halfway through these, and then afterwards we're going to talk about what it means.

And this is kind of a in-between step. I think this is something we've seen over the last, really, three months. Um, and I think we're all still starting to grapple with what it means, which is this movement from a local harness to a cloud harness where the harness is always on.

What do I mean by a harness that is always on? Well, you might be talking to it in Slack. Maybe you're talking to it in Slack along with your colleagues,right? Um, maybe you're each giving it instructions and has to figure out how to parse that and use user metadata.

Uh, maybe you have a mobile app. I was just, uh, uh, you know, maybe you have a mobile app. Maybe it tunnels to your local, um, to, to your local machine. Some of these, uh, some harness mobile apps do this.

Um, often, like, cool, how is this running? Well, it's probably running in a cloud sandbox because it's maybe it's running locally in your machine. You're tunneling into it, but maybe it's just running in a cloud, in the cloud somewhere, and it's got a bunch of sandboxes, which enables more parallelism.

You can get more, um, parallel subagents beyond what you can do on your machine. This is always a trade-off and always something you get with distributed systems,right? You can do more in the cloud than you can do locally.

You have more resources. It requires a different architecture. It's more powerful. Um, and then lastly, you're not creating code, you know, on your just on your local machine or maybe even in a Git work tree. Um, you're, you're probably creating, you know, if you're writing code, you're probably creating a PR that, that pushes,right, to, to GitHub.

Um, so, so, you know, there's a shift,right, from, from local harnesses to these always-on kind of, like, cloud harnesses. We're still in the middle of this. You may have you may only be working with a local harness. You may have started to see cloud harnesses pop up in your, your organization,right?

You may be figuring out how to use them. Your teams may be figuring out how to use them. Um, and then I want to talk about what the harness to claw transition is, which is imbuing these agents, imbuing these harnesses with initiative and, and learning,right?

What is initiative? Well, um, if you've used, let's say, a, a personal assistant, uh, agent,right, and that agent texts you and says, "Hey, I saw anurgent email come in." Is that email actuallyurgent? Was someone, like, you know, spamming you?

You know, but, like, like, the, the agent is listening, um, to external feed services. It has a heartbeat, which means it wakes up every, you know, defined amount of time and, um, and does something,right? Uh, again, like channels, uh, you might be able to text it, WhatsApp it, Telegram it, wher whatever you want.

Um, you, you may persist the memory memory in a more accessible later place than just simple sort of, like, file storage,right? Um, you, you might it might have a, a daemon. It might have a, a gateway, uh, for, for sending and, and receiving incoming, outcoming requests.

Uh, it often will do continual learning,right? So this concept that, you know, the agent, the harness runs, and then, you know, based on the traces that it generates, it, it sort of auto-improves itself. And there's different ways of doing this.

You see, um, skill gen automatic skill generation, for example, is a common one. Um, it could modify the code driving this as well. Um, we haven't figured out what theright way of doing it is yet. We're still exploring, you know, the industry is still exploring options.

Um, now, the reason that and, and maybe this is, like, our unique vantage point here, but, you know, for the last three months as a framework, we've just seen this as a f as the future. And so we furiously looked at the, the, you know, the features that, you know, OpenClaw have, that Hermes Agent have, and say, and, and we, we've said, like, look, you know, a lot of people, a lot of folks want these features, but they want them with power and control.

They don't want to just put a, you know, a claw on a box,right? They want to have more. And so, you know, we, we've been thinking about this because we, we, you know, my I'm not doing my job well if I'm not giving everybody the tools that they need to build agents, to build harnesses as with the maximum power,right?

Um, so, so hopefully, like, again, we've hopefully I've walked a little bit through the step transition with actions, durability, doggedness, always on, initiative, learning. Again, I've, I think I failed in, like, making them all theright tense phrase and making them all qualities, but I hope you get the idea here,right?

Um, we're sending on the agentic spectrum. Um, and what was a simple LLM 18 or 24 months ago is a lot more powerful. So I've called this without sort of asking consent from Pete, but I've called this Steinberger's law, which is I, I believe every harness will expand until it becomes a claw.

And, and, and that's a little bit, um, technological. That's a little bit economic. That's a little bit psychological. So let me walk you through the reasoning here. Um, the first thing that I've observed, um, that we've all observed, um, as a, as a, uh, is that harnesses tend to expand.

And they expand because we want them to expand. Um, we want to DM them in Slack. We want to text them and, like, start overnight, uh, tasks before bedtime. We want this dopamine casino that we get when we put in tokens and get out code,right?

Um, or, or whatever other actions, you know, um, agent agents are bigger than just coding agents, but, um, we want our own dopamine casino. And this, this image just thinks to, uh, to Dex Horty. Um, but I see something else in our future, um, which is that and, and it's something that, like, I don't think we, we sort of talk about as much.

Uh, but after this, after this phase where, where we're sort of making everything more and more powerful, um, there will be a shakeout. Um, and, and let me walk you through sort of, uh, through my reasoning here, which is that in the 2010s, we had these platforms.

We had Android. We had iOS. And all of a sudden, there were all these things we could do on our phones that we previously weren't able to do. We could get directions. We could hail rides. Um, we could send payments.

Um, we could play music. Um, other ones emerged over the course of the decade. We could watch short-form video. Um, we could watch long-form documentaries. We could browse the internet. You know, some were kind of ported over from the desktop.

We could browse the internet. Um, again, you know, some, you know, we could order food,right? Um, we could book accommodations. But, but if you look at most of these kinds of categories, and there are quite a few categories, there are really only, like, one or two, you know, logos here that we use.

You know, okay, how many maybe, you know, we use Uber and we, we use Lyft, but, like, do anyone use another ride-hailing app here? You know, like, and, and, and so when you talk to people that are smart about, like, consumer behavior, the, the reason they say that this is, is because you only really have space in your brain for, like, a limited number of things.

Like, if, if think about something like Thumbtack. So, uh, Thumbtack didn't really serve a very high economic value. Like Airbnb, like, we only use Airbnb occasionally, but when we use it, we, like, really want it. We really need it.

You know, it's really valuable to us. Thumbtack, like, a little bit less so,right? Um, and then it's also, like, not frequent,right? Like, maybe maybe, like, you know, something like DoorDash or Uber, people can use multiple times a day,right?

So there's, there's sort of, like, it either has to be very economically valuable or has to be very frequent. And if it's neither one of the two, um, we just forget about it,right? It's like that, you know, college friend that, like, we haven't really talked to in years.

It's not because, like, they weren't important at one point in our life, but, like, there's just nothing that maybe they moved to a new city or we moved to a new city or our lives, our friend groups, our careers diverged.

And all of a sudden, like, you know, maybe we're calling them once, uh, once a year or once every other year or, or whatever. And, you know, there's just nothing that makes them pertinent and brings them up in our, our, our brains.

And soright now we're, like, really excited because there's all this energy and excitement, and we're all excited to these harnesses that we're, like, you know, putting in tokens and getting out, like, useful things that we all love. Um, and, and I think that in the not-so-distant future, there will be this very real shakeout, and, and these categories will kind of emerge, and we'll realize that we only have space in our lives for so many of these claws.

They're very powerful. We, we love them very much. Um, and so I would I would think about, um, what, what, what does that mean for you? So the, the first thing is, um, the first thing is don't get this is the reason that, like, events are, are, are important that, like, staying up with, like, if the rate of change increases three to four X, that means, you know, we need to figure out what's going on even more frequently.

That's why we're all here. Um, but if you're building an agent, make sure that it has the capabilities that your users need, because if it doesn't, and if, if there's newer things that come out, like, they may just, you know, pick, pick something that's more powerful because that, that's happening very quickly.

Um, and then keep in mind that if you, if you, if you aren't, if you're the thing you're working on, um, even if you climb up to the top of the hill, keep in mind there's going to be another wave of this sort of these, like, this, this shakeout coming in, you know, probably sometime in the later 2020s.

Uh, so, um, that I'm Sam. Um, I'm the, uh, I'm the co-founder of Mastra, the, the TypeScript agent framework. I'm the author of Principles of Building AI Agents. Hopefully, you can get a copy of a book outside or I've got a few here.

Um, please stop by, say hi. Um, it's great to see all of you. Thank you all for coming out. It's a real pleasure. Um, enjoy the rest of the conference.