Quillbot on How Is AI Changing the Way People Think at Work

[00:00:00] - [Speaker 0]
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[00:00:30] - [Speaker 0]
AI can now write the words. It can build the slides, generate the image, research the idea, and increasingly turn one person into something resembling an what would have been an entire creative team ten years ago. But when everyone has access to the same extraordinary technology, What makes work feel truly yours? Well, today, I'm joined by Eric Wang. He is the VP of product and AI at QuillBot.

[00:01:03] - [Speaker 0]
And together, we're gonna talk about why human taste, judgment, creativity, and even a little imperfection could become even more valuable as AI continues to get better. Now Eric has been working in AI since 2006, long before most of us were asking chatbots what to cook for dinner, and he believes AI is changing far more than productivity. It's now changing what one person can create, how we think through problems, and even the boundaries between traditional jobs. So rather than have just another tired conversation about humans versus machines, today, we're gonna explore a much more interesting question. And that is, how can we use AI to give our ideas more flavor, more personality, and maybe even a little more soul.

[00:01:55] - [Speaker 0]
And certainly, a lot more than those generic LinkedIn posts that you may have seen. But enough for me. Let me introduce you to Eric right now. So thank you for joining me on the podcast today. Can you tell everyone listening a little about who you are and what you do?

[00:02:13] - [Speaker 1]
Yeah. Well, first off, thank you so much for, having me on, Neil. I am Eric Wang. I am the vice president of product and AI at QuillBot. I've been here actually, it's it's, I'm still new, so I'm still getting my feet wet.

[00:02:30] - [Speaker 1]
Joined at December of last year because I really wanted to get back into the b to c space. It's fast. It's exciting. And I thought to myself, you know, I really I was getting too much rest, and I wasn't stressed out enough. I wanted to step back into the space.

[00:02:45] - [Speaker 1]
Prior to that, I'd spent seven years as VP of AI at Turnitin, which is one of the largest ed tech companies, in the world. And then before that, stints at Chegg and in government and national security research. Yeah. So I've been in the AI space for since probably since I stumbled into it as a new grad student hoping to avoid the real world for a few more years way back in 2006. Didn't know what AI was.

[00:03:16] - [Speaker 1]
Didn't know what machine learning was. Professor said, you could you could, stay on, get a master's or a PhD. This is at Duke. And I thought to myself, you're gonna pay me to watch basketball and not not have a real job. I'm in.

[00:03:29] - [Speaker 1]
What do you do? I do something on machine learning. No idea what that is, but I'm pretty good at math. Sign me up. And that's how we that's how we ended up here.

[00:03:37] - [Speaker 0]
Brilliant. And fast forward to present day, you're at Quilbot. And for people listening that are hearing about Quillbot for the first time, I know it's a company that's been on quite a journey, but tell them a little about what it is and the problems that you solve for your customers.

[00:03:51] - [Speaker 1]
Absolutely. Great question. Quillbot is, at heart, a company that helps people take their ideas and make them into real concrete things in the real world, like words or images, slides, things that can then bring other people along into that idea. We began with words because Yeah. Obviously, that makes sense.

[00:04:14] - [Speaker 1]
We're also called Quillbot. And, back in 2017, we began with what's become very well known as the Quillbot paraphraser. Yeah. This is right at the beginning of the transformer revolution, which has led us today to LLMs. Back then, we were one of the first pioneers into the world of transformers, and we built a model that could take your words, your text, and through a transformer deep learning network that actually looks a lot like today's LLMs, just smaller, it would paraphrase it, give you multiple versions of your words back but in different ways.

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And what people realized all of a sudden is this is really powerful because finding the right words to convey your idea is one of the most common problems people have when they compose. I have an idea. I can sort of dump it out to you as gibberish. It makes sense in my head, but I can't quite find that compact, beautiful way of representing that idea, in words. And our transformer helped people do that.

[00:05:19] - [Speaker 1]
And so since 2017, we've really built a whole business around that. First, the paraphraser, then grammar checker, more recently into content authenticity as AI has continued to evolve and become pervasive throughout the world. So yeah. So we help people write. And then our latest products are really centered around how AI and the latest generation of AI can help you create beyond words, designing slide decks, for example, or images to put on social if you have a small business and you wanna advertise.

[00:05:53] - [Speaker 1]
Agents that can help you go research the paper that you're about to write, not just help you find the right words for it afterwards. Yeah. So we're we're continuing to build off of that. Really, really excited. We have a really large user base measuring into the tens of millions, and, really excited to bring them some of these very powerful AI capabilities that are built not just with the latest and greatest AI, but also all the expertise that we've gathered, you know, since 2017 in terms of how what it means to to actually create something.

[00:06:29] - [Speaker 0]
Yeah. And there's so much noise around AI right now, and it's so great to hear and incredibly cool how you guys were doing this before everybody else was doing it, and, it's great to watch you as a company grow. And before you came on, I was doing a little research. I was also reading that you argue that AI is now changing how people think, not just helping them write faster. So what patterns are you seeing in how users structure their ideas, solve problems, and and make decisions that go way beyond just writing with AI beside them?

[00:07:01] - [Speaker 1]
Yeah. I think the world's changes so much. And your question about what's changing, where my mind immediately goes to is let's first talk about what I don't think is going to change. And what I don't think is gonna change is it's really important to be passionate about solving a problem. And in fact, I would argue it's more important than ever.

[00:07:22] - [Speaker 1]
I don't think the need to deeply understand that problem because you're passionate about it, because you're interested in it, because you really want to understand the full context of it. Those are two things that have always been important, and I would argue they're more important than ever.

[00:07:39] - [Speaker 0]
Yeah.

[00:07:39] - [Speaker 1]
What is changing is AI is sort of changing the I the scope of what DIY means. What used to take a team of people with different skill sets can now be basically done by one person with a clear understanding of the problem. Because ultimately, AI, from my observation, what it does is it drives the cost of execution down. Probably not towards zero, but it's gonna continue to fall. And in that world, the cost of bad judgment or the reward of good judgment becomes outsized.

[00:08:13] - [Speaker 1]
So then it really comes down to someone who says, I'm passionate about this problem. I deeply understand it, whatever that is. I bet other people also have this problem, and I have a great way of solving it. And with AI, all of a sudden, I don't also have to be a marketer. I don't a developer.

[00:08:29] - [Speaker 1]
I don't also have to be able to run cloud IT systems. Those are things that increasingly we'll see the technology be able to handle. What it can't do, though, is that human spark of creativity, the idea of saying, this problem, here's what it means to me, to other people, what it means to other humans, and all of the context that goes around imagining an innovative solution to problems.

[00:08:57] - [Speaker 0]
And, of course, AI can help someone clarify a creative or strategic direction, but it can also steer the argument somewhat through its suggestions. And I'm curious from what you're seeing and hearing, how aware do you think users are of that influence, and how can they retain ownership of their reasoning? Because there's a a lot of talk around critical thinking at the moment and the dangers of almost outsourcing it, but what are you seeing here?

[00:09:23] - [Speaker 1]
Yeah. Yeah. I mean, I think going back to the the last question, the value of good judgment Yeah. Is going to become incredibly valuable. Style, taste, those are things that are suddenly going to become the scarce resource.

[00:09:38] - [Speaker 1]
Right? We we lived in a world where execution and the technical wherewithal to implement the idea was a scarce resource, and that's that's suddenly gonna get unlocked. So to your point, what we try to do is bring in AI models. When we build AI products, we bring in AI models from all the different providers. So that way, users can come to Probot, and they don't experience just provider a or ecosystem b.

[00:10:09] - [Speaker 1]
They are able to say, hey. Here's Frontier models, all the name brand ones, from every single lab. And I'm actually able to, from QuillBot, in one place, ask questions to all of these different models. This is something that we're really excited to release. We already are using a bunch of a lot of different models across different ecosystems today.

[00:10:30] - [Speaker 1]
But in the very near future, user users will actually be able to come to QuillBot and interact with all of the models, and they'll be able to know exactly what and who they're interacting with, oftentimes in the same conversation. They you know, one of the more fun things you'll be able to do is actually come in, start a conversation with one AI, kick over to a different AI, mid conversation, same stream from a totally different provider and say, hey. The last messages were from this model, and this is what they thought. What do you think? And the new model will actually take over and say, oh, yeah.

[00:11:03] - [Speaker 1]
Okay. I see what's going on. But all the context and everything is preserved. I think it's really neat. It leads to some fun experiences.

[00:11:10] - [Speaker 1]
So yeah. So I think it's really important to be able to provide a wide variety of views to the to every single user because, otherwise, we humans, yeah, it's it it is dangerous. It is easy for humans to say, oh, I'm talk I'm talking about something that feels human, sounds human, and that triggers a little part of us in our lizard brains to to trust it. Even if we know explicitly it is not human, we are talking to a machine, One of the most interesting things from our UX research recently is that there is there are more people it's anecdotal, but there are more people who now call AIs by he or she

[00:11:52] - [Speaker 0]
Really?

[00:11:53] - [Speaker 1]
Or they. Then I mean, I guess they is a little bit more neutral, but he or she, you definitely hear it more. And that suggests something. It's it's this little it set off something in my brain that said, you know, people are starting to really think of these as closer to human than machine or at least living somewhere in between. And that that is the signal that the amount of trust you're willing to place in this in the machine is shifting, and it's growing.

[00:12:18] - [Speaker 1]
So we have a responsibility really to to to manage that.

[00:12:22] - [Speaker 0]
And we will have some business leaders listening that just assume that their employees are using AI mainly to automate some routine tasks in the workplace. But I'm curious from what you're seeing. What does real usage tell you about what those or where those assumptions might be wrong and and which less obvious applications are are proving incredibly useful under their radar.

[00:12:44] - [Speaker 1]
The obvious use cases, I think, are actually starting to fade away. Yeah. The obvious use cases being, oh, I can have AI do a job that a human used to do. And what people are realizing, a lot of employers are realizing, and we've always known is that ultimately, point of an employee, the point of a human in a job, in a role, is actually to exercise judgment. The higher up in the organization you go, the later in the career you progress, the more of your job is spent exercising judgment.

[00:13:21] - [Speaker 1]
When you're at the beginning of a job or of a career, you're spending more time doing mechanical work. Right? The the work that is critical thinking, and it's hard, and it's, you know, important. And it's just beyond the capability of computers up till very recently. But you could use computerized tools, and if you got good, you could very efficiently complete that work.

[00:13:43] - [Speaker 1]
That AI can do a lot more of the mechanical type work. So what's happening is when a lot of employers are starting to realize as they the ones that mistakenly believed, I'll just use AI to wholesale, do the work of employees. They actually lost a lot of that judgment capacity. And oftentimes, it's the more it's new folks or folks beginning their careers that actually have a quite a bit of that judgment even though they they may not know it. They may not have the confidence to voice it, but they have that.

[00:14:13] - [Speaker 1]
So what are some of the the less used cases of AI? I think it's when AI is used by a person, by a creative person to help create something that they otherwise couldn't create. You know, a good example would be, like, a product designer or product manager that's now able to prototype wholesale new capabilities from scratch. Right? This was the this was the niche that Lovable cracked.

[00:14:40] - [Speaker 1]
And I think there will be so many more opportunities like that where all of a sudden the lines between jobs, between you have job a, I have job b. We sit in swim lanes. You know, swim lanes. The the whole idea of swim lanes in corp in in, corporations, I think will start to fall away. You see more companies taking on the member of technical staff moniker.

[00:15:02] - [Speaker 1]
That's not an accident. They're kinda saying Yeah. Everyone's here to contribute. And with AI, all of a sudden, you don't have to stay in your swim lane. You can say what job needs to be done.

[00:15:11] - [Speaker 1]
I what I bring to the table is my judgment, my expertise, my knowledge, and then the AI helps me contribute fully in the ways that my specialty maybe doesn't extend. That's a new way of working. It's a new organization, and, some companies get it and are moving there. I think it's also why you see startups thriving in this space. Because startups by construction don't have swim lanes.

[00:15:37] - [Speaker 1]
Everyone wears every hat all the time. So so yeah. So I think that's where we'll see a lot of opportunity and the the new ways of working with AI.

[00:15:45] - [Speaker 0]
I love the swim lane analogy you made there. And, again, it feels like Quillbot has also evolved from just offering writing point solutions in that particular lane, busted out of that, and you're now offering an AI native creative and workflow platform with so much happening there. How do you see this evolving? Where are you heading from here do you think? Because it it seems it's getting bigger and better and and introducing so many different things.

[00:16:09] - [Speaker 0]
But where do you see it all heading?

[00:16:12] - [Speaker 1]
Yeah. I think you've captured it really well from a direction standpoint. We really believe that we can help people create and come take their ideas from abstract things sitting in their heads to things that are shareable with the entire world faster and and better than ever before. And specifically, the people that excite us the most, there's a lot of groups. But the the group that sits at the top for me are solopreneurs.

[00:16:38] - [Speaker 1]
Yeah. And I think we're gonna see a lot more of them. You know, at the beginning, we started off talking about the scope of DIY just grew by 10 x or a 100 x. And that's certainly not we're not going back to a world where that's not true. So being able to help someone who you know, they might have a day job.

[00:16:56] - [Speaker 1]
They come home. You know, their day job is fine, but they let's say they wanna be a they wanna open a bakery. That's their dream. They love to bake. And they wanna open a bakery.

[00:17:04] - [Speaker 1]
And 9PM, they sit down. Kids are finally in bed, and they open their computer. My dream is for them to go to Quillbot and they say, yeah. I wanna open a bakery. And I know how to bake, but I'm not really sure about the rest of it.

[00:17:23] - [Speaker 1]
And Kobot, our AI says, okay. I got you. And what we what we walk them through is this step by step journey to go from 9PM at their kitchen table to they're ready to open a bakery. Now, of course, there's obvious question of, you know, why wouldn't they just go to Chad GPT to do this or or Claude? And my answer to that is for the same reason that you don't fly on Boeing Airlines.

[00:17:52] - [Speaker 1]
The the Frontier companies are incredible. Just absolutely beyond, you know, comprehension levels of brilliance there. At the same time, they are technology providers, and they specialize in that. Where I see our role is really being the service provider. Right?

[00:18:09] - [Speaker 1]
The ability to say to the user, we can take this technology, build value upon it, whether that's gonna be specialized agentic workflows that help you write really good business proposals to get a loan or create that perfect flyer that's gonna bring in traffic on day one across your town to helping you build a website that is optimized for small business. Those are things that the big FrontierLab AIs out of the box are gonna be a little bit they're gonna be less reliable in doing. They're gonna hallucinate a little bit more. They're gonna be they may not stay on brand as much, and that's okay. That's they're not intended to.

[00:18:52] - [Speaker 1]
These are general purpose AI systems. And, you know, we'll be able to really provide that next tier that gets people from that gets the output from pretty good to this is perfect. This is exactly what I'm looking for. And, you know, at the core of that is what we've always been known for, which is words. Our paraphraser, all of our, you know, systems that help you take the words that you've conveyed and give you different versions that are maybe a little bit more personalized or a little bit more optimized to a specific audience you're trying to reach.

[00:19:26] - [Speaker 1]
Those are things that we've spent ten years perfecting and I think becoming the best in the world at. So I'm really excited to to find where that niche is. Solopreneurs are again a huge huge field. It may not even be, you know, like, where like, the question we have right now is where do we start? It's such a good problem to have.

[00:19:44] - [Speaker 1]
Still a problem because focus is important, but there's so so much opportunity. And we see it every day. We see in our tools even today as we're building them. We try to do homework out in the open. So we like to put our tools out there for people to use a caveat of, hey.

[00:20:00] - [Speaker 1]
We're still working on this. Partner us, but we'd love to have you have your feedback. So as a result, we can kinda see what people are trying to do on these tools. And I think it validates the direction that we're going in. People are looking for tools that help them with their creative outlets.

[00:20:16] - [Speaker 1]
Right? So it's not a tool that replaces people. It's a tool that helps them do things, achieve their dreams that they otherwise couldn't. And it's really, really exciting to potentially help them do that.

[00:20:28] - [Speaker 0]
And I'm curious. When you're talking to businesses and your customers around the world, what what type of questions have you seen arise around things like trust, control, oversight, especially when building tools that that act on their behalf like an agent. Are there any trends in the kind of things that people are asking you here?

[00:20:47] - [Speaker 1]
Yeah. I mean, on the I guess I would I would title this entire topic on the agency of agents

[00:20:55] - [Speaker 0]
Yeah.

[00:20:55] - [Speaker 1]
Which I should probably maybe I should copyright for a book down the road. I think, you know, there's always gonna be some degree of concern about things like OpenClaw going rogue and escaping confinement. I mean, that's all over the news. Right? Oh, use different labs, models are escaping confinement.

[00:21:14] - [Speaker 1]
It's almost a marketing point at this point. Look at how good our model is. They can escape confinement. But it is real, and it and it is potentially disastrous. So one of the things that we've been investing in and actually, spent about a half my time in the labs building with the team much to the chagrin of my growing email inbox.

[00:21:34] - [Speaker 1]
Well, what we've been doing actually is building out agentic workflows that are hybrids. So what we found is at the core of this new Quillbot that that is we're so excited to get in front of people is, of course, frontier level intelligence across multiple LLMs. And the center of it is is this incredible orchestrator that can route, that understands the user, contextualizes it, enriches the user's prompts, and then decides what is the best expert to hand this task off to. And those experts are not surprisingly, we ended up those experts are not themselves full blown open ended agents. What we realized is what people want is they want a tool that's incredibly high quality, that's fast, and that is comes in at a price point that makes sense.

[00:22:26] - [Speaker 1]
We've all heard about how expensive AI is. And so our approach to these sub agents is actually building them as these orchestrated workflows where we've taken our expertise and laid out what we think is a great path. Now, of course, along the way on these steps, you know, you might have a dozen or two dozen steps. Those are agentic steps. Those are steps where we're very carefully tuned prompts.

[00:22:51] - [Speaker 1]
Our agents are stepping through those prompts and executing them. Otherwise, it would take us years just to build one of these. Now we can we can build one and evaluate it against a you know, rigorously evaluate it and have it out in front of users in a fraction of that time. But the the core of it is trust. Because when you're into that workflow, when that's when we kick off that sub agent, you know that that sub agent is running on a harness that is going to produce a great result.

[00:23:17] - [Speaker 1]
Now you might say, okay. I kinda wanna tweak it. Or you might say, love it. But what's not gonna happen is that sub agent going rogue and deleting half your repo or exposing your credit card information where it shouldn't. That's not gonna happen because, again, this the this orchestrated workflow is ensuring that safety.

[00:23:38] - [Speaker 1]
And I think that is the path of the future. So what does that mean? That means, I think, from a business opportunity standpoint, building great orchestrated workflows is almost kinda like the moat of the future because that's where the business' creativity and expertise and depth of knowledge in understanding how to take AI and blend it to a workflow that actually solves real problems well for users starts to matter. So you might have two different orchestrated workflows that are trying to solve the same task, and workflow a is orders of magnitude better because it has an extra couple of steps in there where the builder just has that expertise to sort of finesse it, and it makes less mistakes. And it's and it just produces things that, you know, have a little bit more flavor.

[00:24:30] - [Speaker 1]
If, you know, that's the right word. Right? Then the orchestrate then workflow beat. And all of a sudden, people are gonna say, oh my gosh. The company that builds workflow a, they have something special.

[00:24:40] - [Speaker 1]
You can't quite put your finger on it, and it's hard to duplicate. And all of a sudden, that becomes something that people really want. I'm excited to enter that world because, you know, for a long time, we went through a whole year

[00:24:52] - [Speaker 0]
Yeah.

[00:24:52] - [Speaker 1]
Where every business that's not that that isn't called OpenAI or Anthropic question, like, why why are we why do we even exist? Do we even have a moat? And now I actually feel completely the opposite. I I I could not feel more opposite of that. I I am I think to myself, no.

[00:25:11] - [Speaker 1]
Not only do I is there a moat? There's a more durable moat that can be achieved than ever before because, ultimately, it's it's not the data moat which people can can, cross in the past if they had enough money, enough capital to go collect that data, buy that data. It's not a model moat. It's actually a taste moat. It's a judgment moat.

[00:25:35] - [Speaker 1]
And that is really exciting because then I think to myself, we can compete. We're really good at those things.

[00:25:42] - [Speaker 0]
And I love the line you used a moment ago about adding a little more flavor, and I think that captures it because I it feels like there's a real fine balance between relying on AI to just do creative tasks without any critical or innovative thinking or using all these, using it heavily to rely on just to create something unique. So how do you see the difference in tools that add real value, that add that extra failure, and those that just generate AI slop that which is, again, another big topic right now?

[00:26:12] - [Speaker 1]
I think I think the the best analogy that comes to mind, although I'm a car guy, so, in my head, every third thought is like cars. I think people like to create, to think, to do things by hand even when automation and AI can do it. So the car example, why why did I even bring that up? There's a dedicated group all around the world of people who love to drive manual transmission cars.

[00:26:41] - [Speaker 0]
Yeah.

[00:26:41] - [Speaker 1]
They're clunky. They're annoying. God help you if you're parked uphill and need to get going, especially in San Francisco. Right? It's why the Mazda Miata exists at all.

[00:26:51] - [Speaker 1]
Or, you know, I think that when you look at AI, it's sort of at its best when you help people find that core sense of joy in in the act of creating. So when you talk about taste, that certain bit of something extra that you can't get by just prompting a generic AI, it's sort of like when you sit into a a sports car that's been built by someone with a lot of opinions. It just doesn't have to be an expensive sports car. Miata is a great example. You you pop down into it, and it's a car.

[00:27:28] - [Speaker 1]
It's a car. Get you from a to b, makes noises. It's built in a factory, mostly automated. Right? But at its core, it was built by a small group of people that were very opinionated about how it should feel, about how it should move and respond and sound.

[00:27:46] - [Speaker 1]
And they said, you know, I'm okay that this isn't for everyone. Because I believe, as a human, the way this feels makes me feel something, and I bet there are others out there that also feel the same way. And I think that's what ultimately what we're trying to do is create AI that helps inspire that motion for people. We don't believe in replacing people with AI, but we believe that AI can help people create at their best partially by automating all the stuff that you most of us, even the creative jobs, spend most of our time doing. Right?

[00:28:33] - [Speaker 1]
So you just have flat out more time being creative, more time thinking, more time reflecting, more time coming up with ideas and imbuing your taste into whatever it is that you're doing. And also, just giving you possibilities. The human mind can only sort of think so fast. So Yeah. You know, the power of saying, what?

[00:28:51] - [Speaker 1]
Did you think about doing it this way? Or how about this? And a partner that's able to do that and kind of volleyball ideas back and forth with you where you know it's not gonna get offended. It's not gonna get tired, and it genuinely is interested in helping you achieve your your full creative potential. That's really powerful.

[00:29:12] - [Speaker 1]
And I think that's ultimately how you create things that have that, what's the word that we often use? Again, in the car world, they'll say this car has soul. It doesn't. It doesn't have soul, but it was built by people who do. And that opinionated soul shows through.

[00:29:28] - [Speaker 1]
And I think that really that fabric is gonna be so important. That authenticity is what people are gonna be looking for in a world. Yeah. Like you said, that's increasingly filled with AI slop. Think about how you feel when you're on LinkedIn.

[00:29:39] - [Speaker 1]
We're talking to a professional audience here. When you're on LinkedIn and you're scrolling, you're scrolling, and you're scrolling, and every single post is, you know, that AI style, like, hard stop sentences that looks like it's, like, hard hitting investigative journalism. And then you come to a post that was clearly written by a person and slightly imperfect. Yeah. And it well, it doesn't matter what it says.

[00:30:00] - [Speaker 1]
You think to yourself, this is like a breath of fresh air.

[00:30:03] - [Speaker 0]
Yeah.

[00:30:04] - [Speaker 1]
How do we have more of that moment?

[00:30:06] - [Speaker 0]
Yeah. A 100%. We I think that is a powerful moment to end on because we all scroll down LinkedIn, and you see that generic content. It's empty. But you you kinda find yourself thinking, I just wanna feel something.

[00:30:17] - [Speaker 0]
I want something with that flavor, as you said a moment ago, something with soul and authenticity. And as humans, we just pick up on that straight away. So being able to add that extra flavor using these tools, incredibly cool. And for anyone listening that would like to find out more information about Quillbot, anything we talked about today and carry this conversation on, where should I point everyone?

[00:30:40] - [Speaker 1]
Yeah. Point head on over to quillbot.com. Find me online on on LinkedIn. I try not to use AI when I write things. I usually throw a lot of dad jokes out.

[00:30:49] - [Speaker 1]
But, yeah, quill.com is where you want to to check out. If you do quillbot.com/projects, that's actually where you'll see a lot of our latest capabilities. You could get started creating right away. We're very committed to making sure people get a great chance to try out the products before they have to even create an account. It's a new world.

[00:31:10] - [Speaker 1]
A lot of these capabilities, we're just excited to have people on them and trying them out and giving us feedback. And whether that feedback is, oh my gosh. I love this and it's life changing, which happens. Or the feedback is like, you know, these are five ways it could be better, which also happens. You know, we see the the former starting to happen more than the latter, which I think tells us we're we're on the right track.

[00:31:30] - [Speaker 1]
But, yeah, come on over. Check it out. I'm excited to have you, and be on the lookout for a lot. In the next couple of months, it's a really exciting time. I won't be sleeping much, but, really excited to have people try out, the new Qobot.

[00:31:47] - [Speaker 0]
Oh, wow. You've left us with a teaser. So it sounds like we're gonna have to get you back on later in the year to find out more information on that. But, I will add links to everything, and thank you for being a real breath of fresh air in talking about this stuff. I will add links to everything you mentioned.

[00:32:03] - [Speaker 0]
I'll try and stick a few videos in the blog post associated with this episode as well. But more than anything, just thank you for bringing this topic to life today. Really appreciate your time.

[00:32:12] - [Speaker 1]
Thanks so much, Neil. Really, really appreciate it. I'm really glad to clean my office then if you're gonna put video out. Alright. Thanks.

[00:32:19] - [Speaker 0]
I just love Eric's sports car analogy there because it captured something that I think we're all going to be talking about so much more as AI improves. Yes, a car doesn't have a soul, but the people who designed it do. And somehow, their opinions of how it should feel, sound, and respond really comes through when you drive it. So maybe our relationship with AI should work in a similar way. Because Eric argues that, yes, execution becomes cheaper, but taste and judgment becomes scarcer, and therefore, far more valuable.

[00:32:59] - [Speaker 0]
So AI can remove the mechanical work, offer possibilities, challenge our thinking, and help us create things that previously required an entire team. But we should never lose sight of the fact that we remain responsible for deciding what feels right. And perhaps that antidote to the endless stream of AI generated content that we scroll past every day is don't use these tools to create more. Use them to create something that makes another human stop and feel something. So a massive thank you to Eric for joining me today and bringing this topic to life.

[00:33:40] - [Speaker 0]
An even bigger thank you to each and every one of you for not only listening, but reaching the end. And if you walked away having felt something today or felt that this conversation had a little extra flavor or taste than usual episodes, let me know. Techtalksnetwork dot com. You can send me an audio message over there. Let's keep it human, and I'd love to hear from you.

[00:34:03] - [Speaker 0]
And remember, I am on the road a lot of tech events throughout the year, so have a look at the events page. If we are attending the same event, maybe we can, have a hot coffee or a cold beer. But I have taken up far too much of your time today, so time for me to go now. I'll be back again tomorrow with another guest. Thanks for listening.

[00:34:24] - [Speaker 0]
Bye for now.