¶ Introduction & What is Wordware
I'm joined today by, uh, Robert and Filip from Wordware. Hilarious guys. Wordware is just like we will talk about it, but wait, we're okay. Sorry, Filip. I'm just gonna go
for it. We're building agents that automate repeatable processes in your life. You get to basically describe the whole assignment for an agent in document like form Feels are very friendly and familiar. And then once you click, uh, go, you schedule it based on explicit or implicit triggers. It runs in your life. And you sometimes get a notification, did you get to approve, reject stuff that the agent has done for you? You feel incredible about it.
One of the main indexes we, uh, we measure is a poop index, and that means productivity, uh, optimization on potty. How much time are you, uh, able to save in 10 minutes when, uh, you're sitting on the toilet? So, uh, we're trying to bring a, a world where you don't do busy work. Uh, you do creative deep work that you love.
But seriously, I tried Wordware today. I had like so many cases where it's actually gonna be super useful for scaling dev tools. Like legit, like I, for like, I mean, the blog post is the obvious one, but there's also like tons of other things that wouldn't be worth me doing. But like, so for instance, when I go transcripts, it's like often the names are wrong for the company names and people. Hate it when you like mis case, you know, mis case, a logo, like a company name or something.
Um, Wordware very rarely gets picked up on transcripts as Wordware. It's uh, yeah, the proof of like a space or something like, and then it's like, or wood wear or woodwork or I
hate, like also I'm Polish and my effect pronunciation is not perfectly British as Robert. So whenever I say Wordware. People are like, what? And I just hate it. I'm like, it's like software, but with words. And they're like, words. What? I'm like, oh no. It's like my whole life is gonna be like this.
Um, but like to kind of, and maybe this will explain word, word to people a bit as well, is that there's like, you know, Chad, Chad g PT had the like. Kind of app store thing. I can't remember what they called it. Plugins, I think for, yeah, yeah. You could build your own things. It was very much like, you basically put a prompt in there and then it's like, hopefully you just don't have to copy paste as much, but it's like, ah, GBT is, that was the one. Yeah, GBT, that was it. That was it.
Um, and I tried to set up like a few of those and it just like, wasn't that helpful? But for Wordware, like I could set up like, okay, here are my inputs. So I could have like my transcript and my description, and then I could say, okay, so check the transcript, make sure the words are like. The logo, all the company names are actually like correct and like the transcript matches all those things. Also generate me a blog post based on these different criteria.
Also do various other things, which should be like a total pain to doing code. But it's like, and there are all things you can do in chat wt. Yeah, that's like, like, you know, we don't add a lot of magic on top of the lm. But we just help you. The way we used to describe this to the kind of non-technical people was when you use chapter fatigue, you're a wizard and you're casting a spell, and you're muttering the incantation.
You have to be a bit of a, you know, a learned wizard to know the, the right prompt. Engineering to do. Yeah. Um, and then, you know, you'd be back and forth waiting for it to happen. Um. But with Wordware, you become a potion maker and you're able to like distill all that. You do it once, you like, mix up your cauldron and then you can bottle it and then you can just pull that potion on your, on your new data.
Or you can like give it to your friends and they can be powerful wizards without having to learn the, the match. Just
what we strive for. It's uh, you know, chat, GPT, clot, whatever research tool is for oneself. Uh, and we are for the repeatable tasks. Mm-hmm. Um, and hopefully, you know, we, uh, introduce just a little bit more effort when you know that something, uh, but when you know you're creating an assignment for an AI agent that you're gonna do repetitive. Yeah. And you're okay with doing. Just this tiny bit more. And you also feel like you are almost like training your own ai Yeah.
In doing things in your work that will not, um, complete the work, but will eliminate it.
Yeah.
And, and that's kind of our goal. You know, we want people to be running around and still working, but doing more deep creative work. And in between that deep creative work background agents just come to you and say, Hey, I've done this, this, this, and this. Would you like to approve? Would you like to change or would you like me to try it? And, um, I think this is where the world is heading.
We are not gonna all be sitting by the beach, you know, we're gonna be doing, uh, more creative things, things that make us truly human, not the, uh, productive knowledge work that we claim that is so innovative. But actually we're sitting on email taking things from Google Drive and mixing it with some, uh, word documents somewhere, and creating a PDF to send to our accountant. That sucks. I don't want to be doing that work. I want to be doing really cool creative work.
Yeah. And uh, yeah, I think recently I've gotten an executive assistant. I never had an assistant before and my life changed really, I, I'm so much better at my job. And I think we want to create that for everyone with background agents, kind of automating big parts of your life and doing this in kind of like a document interface when you get to explain and have control over it. And then a mobile app where you kind of get to approve the work.
¶ ChatGPT vs Wordware: Wizards vs Potion Makers
So you always feel in control. Seems like the answer, uh, that nobody has cracked yet, and there's a lot of difficult engineering there. Or we can get to that later. That's a, that's a hot scoop. You know, this is the first time you're hearing it publicly of, uh, of other, other things we're introducing into the web, web platform. Oh, very cool. Okay. Yeah,
don't release it too early. Right. We'll, we will verify with you. I also want to verify from Robert that, uh, Filip is actually better at his job since the Filip is better at his job. It is. Uh, you
know, I like, we get the vibes and feelings, you know, we had a low wine, you know, we're in a very good place. Yeah. Normally, normally I might answer no. Uh. No, I think, I think as you grow as a company, more and more of your day is reactive to interrupts. You are like, you know, you get an email and it's like something to do, or there's more people that want your attention.
And um, when you have a hundred emails in your inbox every few hours, it takes long enough just to go through and work out which ones do you need to action. And if you, you can choose the bury my head in the sand option and ignore them all for 24 hours and then like do it once a day. The problem is you then miss really important things. Mm-hmm. Um. On the flip side, you can be checking it every hour.
And then you, all you are doing is reacting to, to things that come up yours, other people's jobs for you. And I think the only way to truly be productive is to be in charge of your own time. And, you know, having hired, hired our first D she helps manage our emails. No longer do we have that like anxiety, like, oh my God, what's, what, what am I missing if I'm not checking my emails? Um, but also.
We get to, yes, we get to do deep work without the anxiety and, but if there is something important, Lucy can come in, knock and be like, Hey, this happened. Or she can slack us and you know, slack if we were at to a little bit more, because it's all internal company stuff. It's all the, the kind of, you wanna be unblocking your team.
So the first agent, you know, I wrote for myself and Wordware was, um, based on this quite complicated prompt that, um, understands my priorities at this particular period of time in my company. I want these things surfaced to me. Immediately. Mm-hmm. So now I get like a, uh, slack message where the priority as, um, as kind of decided by my AI agent is higher than 90 onto the a hundred, right?
And I get this message and I immediately get a link and I can just go there and, and respond, or I can respond in afraid. And, you know, it makes it so that I don't have this anxiety in the back of my head being like, is there anything concussion? I should be on it. You know, I'm waiting for this and this and this thing. If any of these comes, I need to respond to you.
Yeah. I feel like a lot of that stuff that like people have in their lives, if they have assistance, can be introduced very quickly and very easily to people's lives, uh, when they're working with that.
Mm. Yeah. It kind of makes me think of like, if, if you, Ima like, if I imagine how like someone like Bezos works, like I imagine he's not like kind of doing that. He's his own email.
He's doing something wrong outside. Yeah. I, I think goes, it goes like this. I think if you're extremely junior, I. You respond to each email in like super verbals way and you like, you know, you, you put so much work into each one of them and that, that was me when I was like, 22, started my first company in Silicon Valley and I was like freaking out about each email. I was like, those are important people.
Um. And then once you, like when you progress in your career, you realize that nobody gives a shit and you start caring about just like the information. And those are the type of people who respond on superhuman with one
¶ Executive Assistants & Email Management at Scale
sentence, no Dear John, or no kind regards and know all the best. It's just like information for set forward. Yeah. Almost like email for these people, WhatsApp. I actually loved Sam Altman's tweet, uh, where he was life. The number of people that are probably using chat DT to convert four bullet points into a full paragraph or like set of paragraphs for emails, and then they're being received on the other end and being used.
That person using chat t to convert it back into bullet points is, is vast. So, and then you go one above. And you like deal with really important people and those people don't touch their keyboard. Yeah. So I'll say they don't like, you can kind of see when something is written by like the still a busy person that blurted out four words to someone else. Yeah. And someone.
Human GPT did into a, a nice email that actually makes sense with the context and, uh, I, I can kind of see where is each one of these people on their like, journey in life, you know?
Yeah, yeah. Yeah. That's, uh, that it makes sense. I, yeah, I know it's the classic is the Bezos question mark one, but, um, the ultimate. The ultimate form of, uh, what is it, question mark. I think it was like, so I, I did try it a few times. Like if Amazon really cocked up, like you could email Bezos at, like Jeff at Amazon. Oh. And then, like, I did it a few times where like it was like something stupid. And then in the book that. That was written about in the Everything Store.
They talk about how he would forward this to like the relevant person with just like a question mark. And that was like, you are like, you better drop everything and work on this. And it, it worked like sometimes like you could do that, you get like a refund or like something like that would happen.
I mean, he's the guy who was like. I think he was trying to prove that their customer service sucks. Yeah. And then, uh, all of the VPs were telling him that like an average response time on the customer call is like four minutes. And then he was like, people are reporting it's 60. And then on the board meetings you just call the customer service. That was him. Yeah. And he was just like, just sit here. And then everyone was sitting there and they sat there like.
And then somebody picked up and Jeff was like, Hey,
I don't know. He's a true story. No, I think he talked about that on like Lex Freedom. I mean it's true,
but I am known to make up stories like this. Ah, so narratives you.
Scaling dev tools is sponsored by work os if things start going well, some of your customers are gonna start asking for enterprise features. Things like audit trails, SSO, skim provisioning, role-based access control. These things are hard to build and you could get stuck spending all your time doing that instead of actually making a great dev tour. That's why Work OS exists. They help you with all of those enterprise features and they're trusted by OpenAI, CEL, and perplexity.
And for user management, the first million monthly active users are completely free. Let's hear from Upal, from Digger Dev, a dev tool using
Work Os. How it's designed is that you can start as early as day zero, but for us it wasn't day zero. It was closer to when we first started monetizing because we didn't have a sign up at all. People could just anonymously use our tool. So it was a little later. Coincided with when we wanted to start monetizing and like we needed a nice enterprise feature set.
If you're open source and you're doing enterprise first, the minute you think about monetization is when you should think about work Os to be honest, if we do that again, I think we think about that on day zero to be honest. 'cause like we should have done it on day zero. Ideally, anonymous usage should be permitted, but you should know who's using your tool. It should be optional a hundred percent. It should be opt-in a hundred percent, but it'd be great to have auth from day zero.
You don't necessarily think about. These enterprise features, but they still lead revenue and it kind
¶ What Does "Developer" Mean in the AI Era?
of is a no brainer in that sense. So yeah, I highly recommend,
so we think of developers as like people that you know, right? React or that they're experts or go and there's like 30 million developers. And so someone might think like Wordware is like kind of, it's a question is like, oh, is this. Are these people that are building these workflows? Are they developers? And what does it even mean to be a developer anymore? Oh God, yeah. I think that has changed so much, uh, since AI came out.
The number of people that are just like technically minded that now are unlocked to be able to build things. It's insane. And you know, we've seen these, these stories of like Casa and well CASA's unlocked the developers themselves plus the sort of. PMs that were technical but not technical enough to call themselves developers to fly.
Um, and then you've got like lovable on the other end that's unlocked the, the sort of non-technical PMs that anyone with an idea to be a, a builder and like, you know, what is a developer other than a builder. I think I describe myself as a maker, um, a lot of the time and, uh. Um, I, I was so wanted to make stuff so much that I taught myself to code, 'cause that's the, the easiest way to make stuff.
Um, or like, was the only way to make stuff, um, that could scale to like infinite people and use the power of the internet. Um, so like AI has truly changed the definition of what it, what. It requires to be a developer or a builder or a maker. Um, and I think the Wordware itself is about the makers that want to build things with this new reasoning engine that is these lms, like it's this thing that can think and nothing in the history of humanity has been able to think.
It's like, it's incredible. You can, you can teach this thing. And we used to use the intern test. We used to say, okay, what would you do if you had a thousand interns? Um, and like, what kind of, what kind of tasks would that unlock? Because there's, there's things you just wouldn't do. And like, the same with your podcast. You just wouldn't go through the transcript and rewrite every word from like, oh, word wire or something into the right word where spelling.
But with like with ai, you could now do that. Um, and so it's like what are those kind of tasks that you otherwise wouldn't do or would be too expensive to do or just would. You would do, but would be way more expensive. And now they're like free and cheap and you can just pay 5 cents to anthropic and it'll be done. Uh, so yeah, it's kinda exciting times. Yeah, it is.
And do you think, what, like, what would you say is the skillset of, if someone doesn't need to know, like the syntax of like different JavaScript libraries and stuff, what, what is actually important? What makes your Wordware aficionado? Um. I mean, you need to be able to speak English, uh, or not English. You need to speak to lm. I think whatever happens you to, to break down problems into their steps.
Um, so if you can't communicate clearly what needs to be done to an intern, then you're probably not gonna be able to automate it with ai, let alone word. Where,
yeah, that's the one. Oh oh, it's gonna go like this. Um. That's, that's the one I would, I would agree with. I think we've got quite a lot of clients where they just want, um, like we have the saying in Polish, um, apples from a per tree, and they just want impossible things. You know, like this one guy wanted to um, optimize, optimize, like. The gas consumption, all of Polish houses based on weather. And he was like, just let the AI do it. I dunno if you were watching, but that was stupid.
Uh, and uh, and he just didn't know how to get there at all. And if you don't know that, like AI is not gonna help you. It's not, it's not magic, you know? Yeah. Yeah. It's like if you want to. Like you need to know how to do it.
And I think what AI is great at, it's almost like whatever you do as services, even in a company that's not services based, because you have these huge customers and you give them that beautiful treatment, you know, because they're worth $4 million a RR, you know, you can now do that to everyone and, and that's like the power of ai. It's like once you know something, you can automate it. But like the knowing. Is the important part.
Um, and if you cannot write down, you know, step by step, we always ask our customers, and even like performers who want to like automate something a little bit more, um, difficult is like, hey. Think of this as a piece of paper. Take a piece of paper, take a pen, write down what needs to happen and what decisions need to be made. And if you can do that, word work can do that. But if you can't do that, then you're just wishful thinking, you know? Mm-hmm.
Yeah, I think that's actually such a good point because it's like, I always think, like I'm often explaining to like friends that aren't, it's like very rare that a friend who isn't a developer is like actually doing anything. Like more than just asking chat GPT something. Yeah. Even though they could, and there's no programming barrier there, but
¶ Stochastic vs Deterministic Systems in AI
it's like, I think it sounds like that actually is like quite good frame the way you put it, that like they have to kind of understand what's possible. They can't just ask, like, I think you also talk to a non podcast about like, they want it to predict the weather or something. And it's like, well that's not like the, the, it just, it's not gonna be able to do that. Yeah. Yeah, it is, it is a chaotic system.
The weather, there's no, there's no AI that's gonna solve, like, or LMS aren't gonna solve that. That's, that's a whole, whole separate research problem.
Yeah. It's like people mistake ML problems with, which need vast amounts of data with like LLM problems and LLM problems are good at, you know, taking a vast of data and like. Especially text or human produced data and distilling it down to a summary, um, or writing content. EL labs are actually incredibly good at things which cannot be determined as good or bad. Uh, sorry, can be determined as good or bad, but cannot be determined as right or wrong.
Mm. And what we are trying to do is bring enough structure. To these LLMs for them to be able to make real life decisions. Mm-hmm. And that's difficult because you know, in software you're like intrinsically dealing with a terministic system that can be checked. Mm-hmm. If you're dealing with the words, with humans, with fuzzy world, you are dealing with a stochastic system. And, and now what needs to happen is like those systems will eternally be. Somewhat stochastic. Mm-hmm.
And what you need to do is you need to actually weigh the benefits of using stochastic systems and the disadvantages of them. And stop thinking like everything that the computer does will be deterministic. And when you get to a stochastic system that actually earns you money and you need to embrace it and you know. Every human is a stochastic system, yet we hire people, we pay them a lot of money, and they, you know, they perform.
And now AI is entering this world and you need to just kind of flip. You're like, I will not sometimes understand everything that AI does, but I'm getting so much benefit and so much money out of this. Makes sense.
Yeah. So like the way you would a human, but they're like, they're not, they're not like, well robots are maybe not a helpful word to use, but like. There is variation. It's variation. It's not, it's not software anymore. It's, it is this kind of new fuzzy thing. Um, and I think it's trying to achieve the same goal. So like software for the last 30 years has been automating processes.
Pretty much all software has been some kind of automation, even if it's just around like automating your contacts book or, um, but a lot of it is like automating communication, like email and things. Um, with. LLMs, you've suddenly unlocked the ability to deal with the fuzzy real world. So software had to be if else, and structured data LMS can deal with, you know, PDFs and audio and like just unstructured webpages and text.
Um, which is incredible because now that's a lot of what humans were doing and are doing in admin roles is taking in some email, uh, reacting to that by like looking up some data somewhere else, maybe reading some documentation, turning that into a, an answer and writing that out. And. Passing it into, I'm probably also turning in something that they put in some form that then runs software.
And so like combining these two together, you get something that's more than some of its parts that can deal with the fuzzy, real, real world, can deal with the unstructured nature of, of life, but also have the repeatability, the reliability of software, um, and leverage. Like computers are amazing at like arithmetic and like logic and like reliability
and, and it makes me actually think like right now. We just came back from AI engineering conference and, you know, in this stochastic world, um, you kind of like the, you, you kind of want to, um, you kind of want to go to evolves and evaluations to become like, make a little bit more sense after this stochastic processes and kind of understand them a little bit more. And I was just thinking when Robert was talking that, um. We don't do that for humans.
The evals for humans are actually extremely fuzzy. Yeah. And you know, there's even these rules where, which say like, Hey, 80% of work that you do should be correct. 20%. Like, you know this, there's these rules being like, take risks. Yeah. Like be yourself. Yeah. Imagine if we start applying that towards agents, it's like 20% of the task. Totally. Okay. If you fuck up. Yeah. You know, and it's like the 80% should be right and you should be learning as you go.
¶ Go-to-Market: Cross-Functional AI Teams
If we would apply the same rule. Being like, Hey, we are gonna really embrace this stochastic, newer world. Like, I wonder how far could we get, you know, even with the current models, we we're getting there slowly. I think, uh, now with things like Codex and these like agents that you can just kick off, I now will fire off any bug that I see.
I will first fire it to something like Codex before writing a ticket and passing onto the, like, the bugs channel for triage and like engineers to tackle just because there's, there's about a maybe 30% chance that it'll do it. One shot. Yeah, and maybe about a fifth cent chance that it'll do it. Correct at all. And then if it doesn't work after like one little comment, I will make the bug ticket still. And it's cost me very little amount of time and effort to first get the AI to try.
And that's only gonna go up. Um, it has, I guess it kind of does mean like, you know, my, my barrier bar is lower. It's like, you know, you could be wrong 70% at the time 'cause I'm not gonna merge you to Maine. And I also think like the um, cost of that is incredibly low. People say like, oh, LMS are so expensive. Like, convert to Robert's time. Fuck, they're so cheap and, uh, pacs or, uh, and I think what we're, what we is trying to do, uh, kind of, you know, the same for knowledge work.
We're trying to say, Hey, have a bunch of background agents that you wrote an assignment, you wrote this kind of description of what should happen. Running behind the scenes and being like activated based on. Implicit or explicit triggers do work for you. You can trust it, you can, it can come to you with an end result and you can approve or reject that. Same as like if your assistant wrote an email for the first couple weeks, you don't really let your assistant send off emails on your behalf.
You know, still like, actually, some people never do that and others people are just like, yeah, that's good enough. You go. You go to a level. And they just allow you to do that. So I think like embracing that stochastic mindset and embracing the fact that like you can have work being done when you're not doing work is so powerful. Like I have the notification for deep research running on like. On my, um, on my app, on my chat BT app, and shows me the progress bar.
Yeah.
I could be like eating lunch. I look at it and there's four processes that have been kicked off. It's same with callbacks. It actually shows you the progress bar, what being done. It's great. It's like you, you're just like eating food. You're waiting a queue, you're in a Waymo. You're like, cool. I'm, I'm being productive right now. Yeah. Yeah.
Yeah, that's actually so true. Um, and then also I guess like in terms of pro, we kind of talked about what it means to be a developer, but like also what does it mean in terms of like go to market because like you're at this, like in this kind of like, almost like intersection where I'm like, I'm like thinking like, who is this because this does this something that you sell to like software engineers.
This something that you go like straight to like domain specific, like marketers, like, and then like you kind of show them how to use like Yeah. I mean, I can answer this one more based on, you know, what we see out there today with Wordware. So Wordware is really built for these cross-functional AI product teams. And that sounds like a lot of words. And what it really means is that there are so many teams trying to build.
Things. AI features, AI products, um, that are leveraging their domain expertise to, you know, automate some processing. There's like all these verticals, SaaS companies are trying to build something. Um, and what we see time and time again is you have the engineer kind of writing the prompts and the codebase and they show the output of those prompts to the PM or the CEO. It's a small startup, but generally the one with domain knowledge, the one who's got experience doing that thing.
Um, and that domain expert will be like, Hmm, the vibes are off. And that'll be the feedback they give to the engineer. And the engineer will be like. What are you doing? Give me vibes. Like what are the requirements? And then the domain expert were like, well, I don't really know. It's, it's like, it's all that tacit knowledge that you've never, like you've learned over like years of experience.
Yeah. And like I think like an SDR, they can tell the difference between like a good code email and a bad card email, but they can't tell you why one's better than the other necessary. Like sometimes it's obvious and other times it's like, mm, this one feels better, feels salesy. It feels, yeah, that one feels salesy. This one feels like I've done some work and like more human and. And, and it's the same in healthcare, in legal, in finance, in marketing.
It's like just this broad array of industries. So what word web really tackles and what where Word Web really helps is we put the domain expert in the driving seat. We allow them to iterate on these prompts, on these chains of prompts. Um, actually put their domain knowledge, their taste into these agents. And they still collaborate with the engineer. So it's like that's the cross-functional part. It's like they're trying to build a product.
The output is an API, they can put that into their code base. And we have a bunch of people doing this today, um, across all those different industries.
So let me now give you, uh, in the, the future and also a, a little bit of a, uh, uh, spicy take on what actually is happening and what are all these people behind the, the, the window working on. Um. We've realized that, and I'm gonna put one of the companies I really like in a difficult spot if I say this, but, um, what we realized is that there is an equivalent of what we're trying to do in the land of programming.
¶ Future Product Direction & Background Agents
And we have lovable here where it's basically for news, you know, and it's, it's great, it's incredible. Great. I don't know, these, these people that would otherwise not be able to code or build anything. And then you have rep lit. And then you have cursor. Yeah. And you know what, like if I could choose any of these two positions being cursor or lovable, like I would choose these two over rep, 'cause rep is fighting on two fronts. Mm-hmm. It needs to go both ways.
Yeah. Rep is awesome, but Yeah. But it's, it's, it's the difficult go to market strategy and we, we, we had the same. You know, uh, being that infrastructure, um, play where you both need engineers and you need to remain experts, we've realized that like the go-to market is difficult and the world of ai, the. Like the, the, the whole market is doing buck flips underneath us. Mm-hmm.
And so we've, they have actually been designing a, uh, much simpler entry point toward where, where you just literally say what you want in a way that you would've written down that description for the intern, I. Mm. Or the ticket for the linear ticket. Yeah. Or the, yeah. And, uh, sign up for the waiting list. Uh, it's, it's gonna be coming out soon. It's rolling out to all our users.
That's interesting. So it's even simpler than what you have already and even way more, because what you have already is also way more simpler. No, no waiting. We, we've leveraging a lot of what we built. Um, but it's, yeah. It's, uh, there is an entry point where, you know, the point of Wordware is that you can just write words and create. I guess software and for us, software is workflows, automations, these kind of things.
Um, and so that is true, but if you look at web, web today, and I'm sure you used it, there's elements of needing to like, think more logically, be able to think like a systems person break down the problem, like work out, when do you split from one flow into sub flows and like, when do I use an EV else or a loop? It's, it requires more. A little bit more of an engineer's mindset. Yeah. Um, so it's been great for these like cross-functional product teams.
Often PMs are slightly more technical than the average user. Now we're really saying anyone should be able to build equivalently powerful software. The models have got good enough in the last sort of six months or so that. We can, we can build a copilot that can build effectively hardware flows, um, which might, may or may not be what's going on under the hood. So,
uh, and that's, we shouldn't talk about that. And, uh, I think, you know, you'll have, you'll get a personality and a agent that will help you crop that assignment. Ask the right questions a little bit like what deep research tries to do when it asks the clarifying questions. Yeah. But, um. Way more than that. And because we will know a lot more about you and it will help you draft the right exact assignment with the tasks being there.
Mm. And once that's drafted, and you can read through it in a very simple, you know, step-by-step way, uh, you get to click run and you click get to like basically schedule that based on implicit or explicit triggers being every new email, every new calendar, event, whatever. And that gets to just. Come alive and document that comes alive, and there is a lot more that we do in terms of. Making it a little bit more inefficient, even if you would, if you would.
And because it, it's a basically a reflection agent running behind and trying to, you know, fill all the gaps that you actually did not explain. And trying to use AI intelligence, uh, and, and, you know, costing tokens, uh, in order for you to have to do a minimal amount of work and only improve it with time. I think that's another thing that we've seen the era of AI and the era of like. Slightly technical people, they have way less patience than engineers. You need to deliver a time to Wow.
That is like probably less than two minutes. Yeah. Like probably even less. You know? And engineers have intrinsically been trained like by years of education to be patient. Yeah. And, and that like those people that are willing to make investments for like the payoff that that. They'll be able to do something really useful and build software that scales infinitely. Most people do not have safetys running the be like in the background, you know?
And it's because the binary switch of unlocking automation, um. Has not been flipped. What we are trying to say is like, you'll have thousands of, of, of background agents running behind, uh, the scenes because we will create them both, uh, implicitly, and you will also get to create them explicitly, uh, in a way that's so easy that we want to be the ones who unlock that automation. It's a, it's a audacious goal. Yeah. It's a multi-trillion dollar, uh, market and, uh.
It's just fun to do it with people we like to do it with on a, in an office on a beach, you know? So, uh, we're actually moving very soon. So you're moving to the beach? To the beach, really? Very great. Yeah, we're getting a kite surfing, rock kite surfing lessons for everyone. Where's that? Chrisy Fields. Chrissy Fields opposite the Golden Gate Bridge. It can't be more San Francisco than Oh, wow. Yeah, so we probably will have the sexiest office in the world.
¶ Hiring & Building AI Companies in San Francisco
Okay. Just, you know, not even playing. You're hiring. I mean, if I'm in the office, uh, those guns
feel like you've gotta, you've gotta say. Work alongside those guns. If people are, if people are just listening, Robert is flexing his Oh yeah. Biceps. But you are hiring, they, they're really big as well. Just,
just, uh,
if you're, just listen, if you
had
a prompt turn on the video.
Oh, he just took off his shirt. My god. No he didn't.
Okay. But I'm trying to get, I'm trying to, so you guys are hiring as well? We are hiring guess. Okay. Very actively. Yeah. So I'm looking especially, well, I'm looking especially for top tech talent. Um, so engineers, we actually, the entire engineering team, bar one is an ex CTO. So we, I really care about people that can ship things end to end.
Can empathize with like what the user wants and turn that kind of fuzzy noise of all this user of feedback into concrete, shipped to high quality features. Um, we give you so much autonomy, but we really expect a lot from you and, uh, it's the place that you can do the best work of your life.
We don't have PMs as well. Uh. We are the only two PMs I think in this company. And, um, additionally outside of that role, which is kind of like most of our engineers, we are also looking for people who are consumer heavy. Uh, so they've shipped beautiful, beautiful, um, products. Um, and then, uh, basically like gen. Freaks. If you think you're an agent freak, you can come to work for us if you speak in pro.
Yeah, if you like have been thinking about swarms of agents for the last year and a half and tried a bunch of frameworks and you know how to cut for the noise of everything that's coming out, I. Come work for us. And additionally, we need a marketing person and kind of head of content, head of story, um, persona, which helps us draft a narrative around the shift in the economy, uh, that's happening.
I think there's so much exciting things there that I would like to make it like public and talk about it more in the world. I'm just really fucking busy. Uh, actually what time is it? We've got two minutes. You need more? You need more.
So wrap it up. You need more Wordware running behind the scenes. Okay. So I be okay. We'll, we'll call it that. Um, do you have like one very last takeaway for people listening? Is there like, anything that you think you guys are like do that most other people don't do?
Build with friends. This is not gonna be a two year journey. There's no like a 50 million acquisition waiting for you. You gotta build something that you really believe in and not listen to the market or the VCs that much. Just build something you really fucking want. Build it with friends. Uh. Set up your company as if you would be setting up like your, like relationships. Really think about who are you doing it with.
You're gonna be spending more time with these people than you're spending with your kids and your wife. Um, and then come to San Francisco if you're an AI build an onsite team. Um, there's so many benefits out of that. It's ridiculous. Uh, so that's, um, in terms of like, just. Startup. It's a long one last thought, but I, I, I would, I would echo echo the, uh, San Francisco is where the Renaissance is happening. This is Florence, uh, and AI is the new Renaissance. So like, come here.
If you're building an AI company, um, hire slow, hire great people. It really pays dividends. When people come into our team who are possible hires, they see who they're working with and they're like. This is a team I want to be called. It gets easier as well. It gets, yeah, it gets easier to close amazing people. The, the more time you spend, the more
you have good people. But it does mean you spend like weeks being like, why is there no one good enough that's coming through? Um, so yeah. And just don lower the bar below the bar. Okay. Amazing. Well, thank you Robert. Thank you Filip. Um, thank you Jack. Thanks for having me at Wordware. Of course. It's great to have you.