Chapter 1: What is the main topic discussed in this episode?
Hello, we're live. Whoa, there was not a countdown. That's bizarre.
There was a countdown, but you missed it.
I never saw that. It's 30 seconds, isn't it?
Oh, well, hello, everyone, and welcome. Welcome, humans. Thank you for joining us. We started a minute early here. We just want to kick things off now that people are joining.
Yeah, yeah, just getting set up here. Going to be a good one. We're going to have Dan Schipper from Every in a few minutes, and Grant will tell us a little bit more about who he is in just a moment.
Coming up before we get started, just a quick reminder that our NVIDIA contest is still active through this Sunday, so if you attended a session last week and took a screenshot, go throw it in there for a chance to win a free DGX Spark that we'll be giving away next week.
that is an extremely good computer y'all like you can win an extremely good computer for like four thousand four thousand dollar computer and have the envy of us both because neither one of us has one yeah and uh it is sad i would love to have one one of these days but uh
Yeah.
How do they sign up for that? What's the link? Do you know?
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Chapter 2: How did Proof go viral and what challenges did it face?
And it's, it's like people were, people were like talking to me, to me about this on Twitter today being like, Oh, like open clause. It's like, it's not a big deal. It's just, it just has a heartbeat and like it has gateways to all your, you know, all your messaging apps. And on the one hand, like technically that's true. And on the other hand, yeah, it just, it actually does change everything.
If you, if you actually use it, there's, there's a bunch of things in it that, um,
on their own don't really mean much but all together turn it into something totally different than what you yeah yeah is your personal one really buckled down from a security perspective or or did you uh i went pretty yellow yeah i didn't at first but i've gotten increasingly yolo with time
I probably, you know, shouldn't say on a live stream, but I'm kind of like a YOLO guy. But, you know, the way that we built plus ones is they have all like the sort of default, like good security practices. And essentially you can only reach him through Slack and you can only get in our Slack if you're. you know, a reasonably trustworthy person that we pay. Yeah.
And he also doesn't listen to anyone except for me. So there are certain things you can do like that, that make it a little bit safer.
It's own accounts and some things as opposed to like, you know, have a buffer in there between like, say your debit card.
yeah he doesn't have he doesn't have access to a credit card uh or you have a card so uh but fair people on my team do have their claws do that and they just provision um yeah you know provision a mercury or ramp card and it's it works pretty well it's really cool yeah so uh as far as like using it as another co-worker do people like because you know you're the ceo of every do people ever come to your claw uh or your plus one and ask for things like that they would have asked you for
Yes, and I think the biggest one is just proof, like because I built this thing and people are using it all the time internally, anytime they have a question about it, how does this thing work, or a bug, usually it's a bug, they just, instead of tagging me, which is like,
at a certain point I was like tired of being tagged into bugs, even though it was totally, it was totally my fault, but it's easier for them to tag my claw or my plus one.
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Chapter 3: What is Every's approach to agent-native engineering?
Um, and, uh, and so, yeah, it, and, and I can imagine right now it's not like a thing where if you asked him a strategy question, like what would Dan say about this? I haven't spent a lot of time doing that, but I, I think I could get that. I think I could get it to the point where he would be pretty good at that pretty quick. And, um,
pretty good at standing yeah and i do feel i i do feel generally that um you know like proof i would not be able to do it even even with like regular codecs and cloud code and whatever i would not be able to do it at the level that i'm able to do it at and run the rest of the company and do all the other things that i do if there wasn't this thing that's like hanging out on on a server somewhere just like
waiting to respond to requests and making me feel like okay that part of things is like more or less taken care of um obviously there's a lot i need to do myself but he's at least the the first line of defense and that's really cool yeah yeah is your suspicion that this is how all companies will go where we all have essentially like a digital like agent uh twin of us i suspect so but i'll say i don't think there's any one size fits all thing different companies are
going to be in use this stuff in totally different ways that are fit for like how their organizations work. And like, you know, there are there's a dry cleaner down the street from my house that like still doesn't take credit cards. So plenty will not have any of these for like a very long time. But I think there was there's like a real debate around
especially internally, but I think generally around, yeah, what does this look like when everyone has an agent? Are we all going to have one agent or are we going to have agents that specialize? And if we are going to have them specialize, how do we get them to specialize and what should they specialize in? And I think what we have found so far is specialization is definitely a thing.
Um, even if you have this super smart, always on alien intelligence that could technically go across all different functions, somehow having, having it just focused on being a good, you know, marketer makes the whole thing better and it fits in our brains a little bit better.
Um, and the, the other really nice thing about the way that clause work is because your reputation is on the line for them. Because people see them as yours. It's a little bit like your kid. Like you don't want your kid messing up because it reflects on you. And so people spend a lot of time making sure their claws are good. And I think that's like an underappreciated thing.
benefit of this whole setup where it has a personality and a name and all that kind of stuff is like it activates all the all the stuff in you that makes you want to care for it make it good and by it's the same thing it's literally the same thing um and by caring for it and making it good it's writing software to make itself better and uh you solve you solve a lot of problems in ai with like around trust and all that kind of stuff through this weird mechanism that you wouldn't
necessarily predict beforehand but once you see it you're like oh yeah obviously this is how it would work i find i use mine very much as like an actual in-person assistant like like i've got it trained on hey i need one of these things and it just it pulls a skill knows what this thing is and really quickly delivers it back can drop it into a google drive for me or whatever the case is
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Chapter 4: How does Every's product suite utilize AI tools?
And like you might follow up an hour later being like, hey, did you fix that bug? And I'll be like, what bug? And you're like, I'm literally going to kill you.
It's a lot. We'll eat you out of house and home with tokens if you're not careful.
Yeah, yeah, yeah. So that's why I'm really – I'm more of like an agent maximalist. Like we're going to have a lot of different agents doing a lot of different things. And the ergonomics of a codex right now for staying organized to make sure you actually like finish the work that you do and it's done well is I think quite helpful.
But then for your claw, like I'm just constantly being like, okay, how's usage today or – You know, like file this bug or like the whole way that we do bug reporting is changing first in proof. But I'm hoping we do that through the rest of the org where because proof is agent native, meaning agents can use it as first class users, it has a bug report function.
And so agents just submit bug reports. And the bug reports you get from agents are way better than the bug reports you get from humans, even if they're initiated by a human. Because they can be like, hey, this is exactly what I did. And here's the exact error message. And here's the line of code where I think it might be, depending on how much they know.
And what happens is every morning, my agent, R2C2, then goes through all the issues that were submitted by agents and then clusters them and says like here are the main issues that we need to solve um yeah and so that's just it just like totally changes how you how you work um even if you're using codecs mostly for coding yeah
Okay, we got a question from the chat, and I think we can tie this into some of the other conversations we want to talk about. Ravemaster2000 says, the only thing I don't know about AI is how to get the most out of agents. And luckily, we have Dan here, who has quite a lot of ideas around this.
I don't know if we want to jump right into agent native architecture, or how would you address this, Dan?
Well, I don't think that there's any one answer to that question. I agree. And there are, like, some of these things that are, like, real wow moments with agents. In particular, let's just narrow it down to OpenClaw because I think there's, like, there's lots of different agents and they mean different things and whatever, but OpenClaw are plus ones.
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Chapter 5: What are the benefits of using Plus One for Slack?
Oh, really? Yeah. See? And so plus ones come with that already built. So, like, what we try to do is figure out, okay, OpenClaw is this, like, blank canvas.
Like, what's the happy path to get you into it so that you don't have to think too much, you don't have to set up a Mac mini, you don't have to do any of that stuff, and it comes preloaded with things that, like, get you right to the, like, wow moment. We also wrote a guide called...
open claw the comprehensive beginner's guide which i'll drop in the chat yes um yes that has that has a lot of like our own ideas and experiences with what um what makes these things awesome like another another like magic moment that happens a lot is if you work out Using it to help you plan and track your workouts and find new workouts is a huge game changer. Oh, that's cool.
For me, I think my magic moment was... Um, was, uh, using it for reading. So I'll take a picture, I'll send the picture of the book to the, to my claw. And then my clock keeps this like webpage of all my reading notes on it. And that's like really sick.
Um, wait, how does that work? You like dictate your notes as you read or?
Yeah, I just, we just have a little conversation about this thing and I'm like, Hey, like, okay, I highlighted this, like throw it in my book notes and it's like, great. I love that. That's so cool. I think that the other big category is just seeing it do something you didn't expect. So Brandon, who's our COO, he was doing his email and had to run.
So he was like, hey – to his claw, he was like, hey – can you just call me so we can do my email while I'm walking? And it called him, and he was like, that's crazy. How? How did it do that? I don't know exactly. I mean, it used one of the easily available APIs to probably use Twilio or something like that, and it already had access to his email, and it had his credit card, so it just did it.
We had a weird one with my wife where one day she was in the living room, and I was up here working. And all of a sudden, at like max volume, my computer started talking to her in the living room. And she's texting me like, hey, something's wrong with your computer. And then she's like, it's talking to me. Next thing I know, she's standing here at the corner of my desk like, hey.
So I get down there, and it's got a Brave browser open with like 75 tabs. And one of them is some university lecture on efficient tokenization. It's studying up on YouTube. That's so funny. I've had a few just little funny moments like that. Something I love that it unlocked for me is that I have spent years trying to find the right task app, like a good checklist.
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Chapter 6: How do agents enhance team collaboration and productivity?
Yeah.
We got another question from the chat. FTLOD says, are you making a ton of alternate accounts for these agents on the apps we use every day, or how are you dealing with accounts or permissions? Good question.
A lot of the accounts, you actually just make an API key or you sign in with OAuth. And different people have different levels of comfort. I know a lot of people who have a separate email address and all that kind of stuff. I'm a little more like I give it access to not all my accounts. It doesn't have access to my bank account or anything like that.
But it has access to my work email, for example. And my feeling is as long as you have really locked down the server that it's on and the channels that people can access it so that you're really the only one that can access it, then it's like probably fine. But yeah, different people have different strategies. Cool.
And then another one, Saco Bambino says, how does your AI agentic based product avoid or address model drifting issues that we often see with most of the AI models?
So I guess this is referring to plus one, right? I guess so. And by model drift, are you talking about the like, you know, as models change, the harness is not as good or am I missing something about model drift? I think that's what they're talking about.
A lot of times I'll hear it referred to as talking about where... Over time, the answers start to skew and are just generally less good. Or you just get used to the baseline. Yeah, not just in a long context, but even over time where it just kind of... Sometimes it'll get continuously... I don't know how much of that is the actual model or if the human reaction to the output.
I don't know, Dan, if you know about that. I mean, over time... It should not be over time because each chat is like...
basically new the overtime thing would be as the maybe as the models get updated the like harness is not as good and luckily you know this is based on open claw so that this plus ones are based on open cost and we don't necessarily have to worry about that so much on all of our products i i have this like philosophy of your job building products in ai is to surf the models
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Chapter 7: What is compound engineering and how does it impact product development?
the that's one of the real benefits of having a agent who is tied to a person is
you're using it all the time for yourself, and you're using it usually in places you're an expert, so you're gonna have a pretty good idea of what is good at and what is not good at, and you're gonna try to fix things that are wrong, and it's being used publicly by other people on your team, and used in a way that might reflect on your own reputation, and so there becomes this major psychological incentive to make sure that it is working well, and I think that sort of solves a lot of the trust problem.
That makes sense. Related to this, TheBlindDragon13 just asked, have you found a great memory system that actually works for your claw?
i have not i think that i think it's out there though and uh willie who's our head of platform is the guy that's building plus ones and i know he's like experimenting with a lot of them i don't have one off top of my head where i'm like you should go check it out but we will definitely yeah yeah we'll definitely put more memory stuff into into the uh plus one and my friend nat elias and is also i think really good johnny miller if you haven't checked out their stuff they're you know
they're, you know, I feel like we're pretty ahead, but they're like miles ahead in terms of how, how clause, how clause works. So if you're looking for memory systems, I'd check out what they, what they do.
Cool. Let's, let's talk about proof because this is something that I think a lot of people can relate to. They have, we have these amazing coding tools. Now people are, you know, if they're not building stuff, they want to build stuff. You actually built something and released it. Tell us, walk us through that whole process and what happened.
Totally. So Proof is an Asian native document editor. And the underlying thought behind Proof is most word processors are built for humans. And now that we're, I mean, all word processors really.
And now that we have AI, we're kind of like bolting AI into it and trying to make it so that it can like write like you so that the stuff you put into the word processor is like mimicking what a human would do. And I think there's a whole interesting line of work there. But there's this other thing that's happening, which is that I am actually reading a lot of AI writing.
It's doing a lot of writing that I would prefer to read the AI's writing. I don't want to read a human's writing. And that's in certain tasks, so like planning, or especially planning a feature in your coding app, or a research report that uses a bunch of our growth and stripe data, for example. Yeah, right.
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Chapter 8: What advice does Dan Shipper offer for building with AI agents?
Yeah.
So... An extra 30 seconds to really explain what you want clearly can probably save you a lot of grief on the back end.
Yeah, exactly. Explain what you want, and also part of that is knowing what you want, and especially if you've vibe-coded it, like, you may not fully know. And so... basically, like, I had someone come in and help me just... Okay, just be like, okay, if we went back to first principles, how would we architect this? And I guarantee... Like, I already knew most of what he said.
It just, like, wasn't fully there because I was, like, trying to transition...
from I didn't even know that codex didn't know the best practices to okay I'm having codex do the best practices but it's still like slightly doesn't want to do the full like rewrite and delete a lot of code and whatever and the guy that I brought in who's super talented was just like yeah this is this is exactly the thing that we need to do and like I'll just rip out a lot of the code and he used codex to do it but
It doesn't necessarily come naturally to the AI models to do this yet. And now it's like fairly stable. I'm happy with it. Some of the code is different, but it's not a totally different app than it used to be. And it happened very quick. He was able to essentially stabilize it in a couple of days of work. So it's pretty crazy what you can do.
And certainly at the scale that we're at and the level of sleepless nights that I was having, I probably would be more careful next time, but I think generally this is fine.
Just curious, did you use Codex's plan mode first? I was using Codex's plan mode, yeah. I've had really good luck with plan mode. A lot of times I'll even go and use a different AI and be like, okay, I'm going to workshop this idea. You should know that I don't know what I'm doing entirely. I have ideas, and I can understand it if you tell me, but don't assume I know anything.
And usually I can get a good... here's the project I want to do prompt that has saved me some grief, but it's, it's always a coin toss, you know, you just never know. And, uh, I, I think you also kind of hit on that element of this thing. We've kind of seen since, since this all began is that in the hands of an expert who knows the right questions to ask, uh, it can do a lot more, uh,
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