Welcome to Artificially Intelligent Marketing, a weekly podcast where we stay on top of the
latest trends, tips and tools in the world of marketing AI, helping you get the best
results from your marketing efforts.
Now let's join our hosts, Paul Avery and Martin Broadhurst.
Hello everyone, welcome to episode 20 of Artificially Intelligent Marketing.
We're glad you're here with us.
I'm also glad to be joined by my good friend, Martin Broadhurst.
Martin, how are you?
Fantastic, thank you.
Glad to be back home after the adventures over to Cleveland for MAKON 2023.
Listeners to last week's episode will have heard my report from there.
It was a great conference, met some fantastic people and got some insights and thought provoking
discussions around what AI means for organizations.
So a little bit less on the technology front.
I guess we're a bit inside baseball when it comes to the technology at this juncture,
but you really had some key insights and thoughts on organizational change and how do organizations
actually start to bring some of this generative AI, especially power into their businesses.
Yeah, very much so.
I think one of the most interesting discussions from the whole conference was a fireside chat
with one of the senior marketing team from VMware.
Now this is an organization with 35,000 employees globally, 650 marketing professionals in the
team and they have created earlier this year, I think it was February this year, they put
it together, an AI council.
Now this is made up of 30 employees from the marketing team and they meet regularly to
discuss how the organization is going to use AI across the marketing piece.
That's everything from predictive analytics, personalization through to generative AI.
And they're considering all sorts of things, including the ethics, but which tools should
they use?
And getting into the weeds to say, should we be using this generative AI copywriting
tool or this one?
They're really getting into that.
I think that was something that seemed to be a bit of a trend.
The companies at the leading edge of this are dedicating resource to it, whether it's
someone's full-time job, which seemed to be a rarity or somebody was built for it.
Somebody had the accountability for AI within the organization.
That definitely seemed to be more of a trend for the forward-looking organizations.
Very interesting stuff.
I'm glad you touched upon how to choose what tools to do what with because I can very effectively
segue into letting the listeners know what we're going to cover today because we have
a slightly special episode this week because Martin was lucky enough to catch up with Brennan
Woodruff, Chief Business Officer over at Go Charlie.
So we've got a fantastic interview with Brennan at the end of this podcast, the sort of the
sections that we normally do on the news, which we'll do in a moment, and then into
that interview.
So do look forward to that later on.
In terms of the news stories, because we want to respect your time, lovely listeners, we're
going to race through a couple of stories that we thought were the most important this
week and then get straight into that interview.
So the first story Martin is with you.
It's about OpenAI.
Tell us about it.
Yeah.
So OpenAI announced this week that they're providing a way to block its bot from accessing
your content, which is important because as marketers, we pour a lot of time, effort,
energy into creating all of that website content, whether it's blog posts or product pages,
it's all strategically designed to attract and engage with different customers and staff.
We don't necessarily want all of that IP getting slooped up by the AI bots without our permission.
And that's certainly the case with the major publishers such as newsrooms.
So OpenAI has given us the tools now that we need to protect our sites so we can control
which pages the GPT bot can access and analyze and then incorporate into the training systems
of their large language models.
So what they've done is they've provided specific user agent string and some IP address ranges
for their crawler so that we can now easily block the bot at a technical level by updating
our robots TXT file and our firewall rules.
So very much like we can block search engines from indexing certain pages, if we've got
maybe we've got thank you pages or pieces of content on our website that we don't want
indexed in search engines, it's the exact same theory as that.
So that's going to help us safeguard any proprietary documentation that might be accidentally spied
on by the crawler so we can, whether it's PDFs, we can de-index those from the crawler
and all sorts.
It's just going to help us keep proprietary information proprietary.
So another interesting thing to consider here is that there are loads of websites where
there might be personally identifiable information and user generated content, stuff that people
might be using our website, but they don't want, they're not saying that everyone in
the world can access, it's just maybe website users.
So now we can delist those pages to make sure that GPT-5 or whatever it's going to be in
the future isn't trained on all of this user generated content as well if we don't want
it to.
So yeah, at the end of the day, this is a great move for product marketers and just
for web masters and digital marketers to have more control over what is indexed, analyzed
and used in coming large language model training.
And yeah, hat tip to OpenAI for the transparency and acknowledging the concerns of publishers.
I think they have had their feet held to the fire a little bit with some of the lawsuits
that are coming up from the likes of New York Times and Sarah Silverman.
So yeah, this is good for digital marketers to have more control over their content.
Yeah.
I think it's an interesting one.
On the one hand, the horse has already bolted on this.
So all your old content, would I go through and try and de-index my old content from OpenAI
at this point?
No, we already scraped it.
Or at least, you know, especially if I was a publisher and had a lot of high quality
content on my website like in New York Times.
But it's good to know that we have control over restricting that information from going
into the model from here forward.
So in terms of building a strategy for this, it's probably a new content production, build
this into your workflow if you don't want it to be scraped by bots.
In terms of OpenAI bots for training large language models, in terms of a strategy, it's
not clear, is it?
Yeah, I don't think whether or not in some cases we might want our content indexed, especially
if it's quite brand heavy in terms of it's talking about what we can do specifically
as a business and how we do it.
Because actually, that might be the type of information and recommendations we want bots
to be giving if it's branded versus say general knowledge info.
Well, I saw a screenshot in a Facebook group that I'm part of and it was someone's sketch.
There was a chat GPT conversation and within it, it mentioned a particular brand and it
had a link to their website.
And the comment was, how has this company done that?
And the person sharing it was asking it almost as if it was like AI optimization, like in
search engine optimization, it'd been optimized for this.
Now, clearly it hadn't, that's not the way chat GPT works.
It wasn't a conversation with plugins or anything, it was just a raw chat.
So within the model, clearly the topic that they were talking about had this company that
was referenced within its knowledge base and it shared the website address of this company.
I think that's going to be, if you can get lots of content that says you are aligned
to a particular topic, that's going to appear more in the models going forward.
Now that's assuming that the architecture of these models stays the same as it is today,
which I highly doubt going forward.
On GPT-5, I imagine things are going to look slightly different, but yeah, I think people
already have this perception about we need to optimize for AI models, even if that's
not necessarily the case of how it works in reality.
Yeah, it's funny you should say that.
I remember pre-GPT-4, I asked chat GPT to give me five life science marketing agencies
and I was pleased to see that Biostrata was in the list because certainly I can imagine
that trying to make sure you end up in that list is not necessarily something that's going
to be easy to control, but it is the type of question that somebody might reasonably
go and ask a chat bot over a search engine in the future.
Expect a whole scramble to try and think about how we can engineer the content on our sites
to try and ensure that the models learn that we're a relevant brand in whatever areas that
we're playing in.
Right, let's look at our next story then.
There's been a couple of stories this week about generative image AIs and protecting
artists' work and how do we tell the difference between real images and fake images.
There's been some interesting stories here.
We heard about some initiatives, one of which was called C2PA, which stands for Content
Authenticity and Attribution.
It's kind of like a Twitter blue tick verification system, but in this case for images.
The tool uses cryptography to tag content that's been generated by AI so that as humans
or users of images, we can identify if an image is AI generated or not.
Adobe has even incorporated C2PA, which kind of sounds like a character from Star Wars
to me, into Photoshop and Firefly, making it accessible to users.
It is a system that you opt into though, so it's not as if every image that you generate
artificially is going to get tagged, at least not as it stands.
Another initiative we saw on this kind of topic this week is Photoguard, which has
been developed by the bods over MIT.
This tool protects your original images from being repurposed by AI and used as part of
image AI training runs.
What they've done is they've found a way to tweak an image's pixels so that AI models
like stable diffusion basically can't recognize them.
It's all code driven at the moment, but there are plans we hear to have Photoguard's API
baked into different platforms so that you can easily overlay your images with this watermark
or whatever that stops these tools from being able to index and use your images as part
of their training runs.
In essence, because even though humans can see what the image looks like, it's kind
of garbled for the AI tools.
Why does this matter for marketers?
Well, first and foremost, these are pretty interesting tools, but they're still a little
bit unproven at the moment.
How easy will it be to sidestep them?
Nobody knows currently as far as I can tell.
I think also you could argue that some of the larger AI models, mid-journey, stable
diffusion have already consumed a vast amount of images, so maybe that damage is going to
be a bit hard to undo.
It's a little bit like the first story from Martin in terms of probably images you've
already put online.
That ship has sailed, but your new images perhaps look at some of these tools.
I think as marketers, we really need to be aware of all these different developments
so that we can be informed about the risks and the potential solutions when we as brands
are creating content, but also just the overall complexities of how these tools work and whether
when we're using them, we're going to be infringing on the copyrights of other creatives and anything
that can be built into this whole system to give it more credibility, I think is going
to give brands more confidence in using these tools to generate images as part of their
creative workflows.
There's definitely a theme here, isn't there, of how do you stop AI consuming your content?
This is very much front and center of people's thinking at the moment.
I was intrigued by the Photoguard solution.
I'd like to get into the technical details of that to see how it's basically baffling
the diffusion models in the pixel level obfuscation.
I think my biggest challenge I've had with it in the conversations that I've had online
or voyeur'd online, some of which I've been proactive, some I've just read, is just the
belief that these things are going to be quite easy to sidestep.
They have been so far and they will be in the future.
Whether this ends up being non-news or not because it gets sidestepped very quickly,
I don't know, but I think you're right.
I think this is where we're at in terms of people going, oh, you took our content.
You shouldn't have.
We want some money for it.
And by the way, we want a mechanism to stop it happening in the future.
That's kind of where we're at.
Then hopefully that will get resolved very quickly and doesn't pull any of the tools
down in terms of stopping us being able to use them.
I think some of us have become somewhat reliant on maybe using them in our workflow.
We've probably got to be mindful of that, but that hasn't happened yet, obviously.
What about our next story then, Martin?
Tell us about A Meta's personas.
Meta are at it again announcing some new products.
So they've developed some AI-powered chatbots with unique personas to deploy across platforms
such as Facebook and Instagram and no doubt in the future, Threads.
If it's still going.
I saw it had an 80% drop off in active users in a news story this week.
This isn't a social media podcast, but yes, Threads asterisk.
If they can just add search to that tool, I will use it.
I'm in there frequently enough.
I just want to be able to search.
Let me click on a hashtag.
I don't ask for much.
Anyway.
Anyway, so these bots, these personas aim to boost user engagement through personalized
recommendations and conversational features, much like we'll have seen through the likes
of Inflections Pi, if you've been using that.
So it will allow Meta to also gather more user data, which you guessed it, can be used
for improved ad targeting, which I think has got some privacy advocates, got them a bit
concerned maybe, but you know, watch this space.
So I think we're going to see more details about this at their conference in September
at the Connect conference.
What can we kind of expect as marketers though?
What's important for us?
Well, I think, you know, opportunities and challenges are very much at play here.
On the one hand, these persona based bots should be able to give us a better understanding
of our target audiences and deliver more relevant personalized experience.
I imagine those experiences will be genuinely engaging if we can plug them into our, our
corporate brand tone of voice and you know, into things like knowledge bases and things
like that.
When you plug that into the likes of Llama and the recent update with Llama 2, this is
going to be quite a powerful tool, I would imagine.
So yeah, lots of new chatbot driven marketing opportunities.
I think Facebook Messenger chatbots always felt like they were slightly underpowered
historically.
I don't know whenever I've tried to interact with them or even launched one for a client
and I've done several times, they always just felt a little bit weak.
So this potentially could open up some really new and exciting avenues.
However, on the flip side, as I mentioned, privacy is going to be something of a concern
for people.
So I think we'll need to closely monitor how Meta plans to leverage this additional user
data.
This is obviously a massive consumer concern at the moment.
So we must ensure that whatever approach they take respects both user consent expectations
and boundaries.
Yeah, so that's an interesting new product.
I personally am quite excited to roll this out for some clients.
I think when you see consumer interactions on Facebook Messenger at scale, the existing
chatbots are quite limited and I think there's massive opportunity here to create more authentic
feeling brand experiences.
Yeah, I agree.
And I think it'd be really interesting to see how it plays out really.
Will it be like high, but maybe a bit more commercialized in terms of products and services
type conversations or is Meta actually trying to leverage this very large base of users
to actually over time switch those users to relying on its chat and persona interfaces
rather than chat GPT-Pi or others, which I think is a TBD at the moment and maybe we'll
get a bit more information in their conference in September.
While we're talking about Meta, they have released some more news this week around some
of the big AI bets that they are making on Instagram.
So outside of this persona's tool and work that they're doing, they've been cooking
up some new AI powered features for marketers and creators on the Instagram platform.
So they are reportedly developing tools that will label AI generated images, summarize
DMs and enhance editing for your images with AI driven super clever brushes.
There are no info really yet on when these new capabilities are going to be launched,
but certainly the news is chock-a-block with Meta AI developments.
For us as marketers, certainly the AI labeling could help manage misinformation and build
trust in terms of what images are real and what are not.
So again, back to the thread of this entire podcast so far.
Some of the other applications have very practical benefits.
So the DM summaries could help brands and influencers manage their direct message conversations
at scale.
And it looks like some of the new editing tools could make it easier for content creators
to create really high quality content quickly and easily.
So for us as marketers, we know that AI is playing a bigger role in lots of different
social platforms.
LinkedIn are doing a fair bit of this as well, but we just need to keep an eye on this because
if you use Instagram as a channel, really understanding how you can supercharge your
approach using these AI driven tools, whilst at the same time being mindful of other aspects
of how the platform works that you might need to be mindful of.
For example, for those of you out there generating AI images and passing them off as your own
photography, something like this automatic image labeling tool is probably going to get
you in a bit of hot water.
And we perhaps need to be mindful that whenever we are using AI generated images in our marketing
programs, especially on Instagram in this case, how we as a brand feel about the whole
world knowing that the images that we are using were created by AI versus human graphic
designers.
Could we see backlashes to brands?
Who knows?
So I think there's a bunch of other complex stuff that we just need to keep an eye on
here.
The DM summaries for brands that get a huge amount of views and engagement, I think that's
going to be massive.
That will help you know, just anything that can help manage a busy inbox.
So if you're a social media community manager, that is a tool to keep an eye on.
Yeah, auto flagging the high priority messages based on content and sentiment and all these
other things.
Yeah, completely agree.
What else has been happening this week, Martin?
Google, they're in the game.
Oh, Google.
Thanks for stopping by.
What have they been up to?
They are planning to give Google Assistant a major upgrade by incorporating generative
AI.
So that means that Google Assistant, which, Droid, you probably have this active quite
a bit, it will soon have similar capabilities to ChatGPT and Bard.
This has apparently been revealed in an internal email sent to Google employees.
So why does this matter?
Well, Assistant is a really big interface for consumers.
It's a channel that as marketers, we don't really think about, but it is how lots of
people interface every day with Google, the biggest search engine in the world.
So being aware of these new capabilities and thinking about how we use Google as a general
channel to reach people is going to be quite important.
Now, this revamp is taking place apparently on the mobile version first.
I think that's how most people will use Assistant anyway.
I'm not even sure I've ever used Google Assistant on desktop.
So that's where we expect the revamp to begin.
Google not the only company making moves in this area in terms of grading their smart
Assistant.
Amazon is also believed to be working on a bit of an AI powered reboot for the Assistant
who shall not be named the Fear of Triggering Kit right now.
Every time I come to that word, I think, stop.
And so yeah, if you're listening to this on your speakers at home, be thankful that I
didn't just trigger it.
Okay, so Google and Amazon, they've really put less focus on the smart Assistants in
recent.
They've remained relatively static in terms of their capabilities.
But the resurgence and influx of users into generative AI has them all scrambling to kick
start their digital Assistant programs once again.
It feels to me like we've been talking for years like SEO experts that want to be ahead
of the game and advising us on how we need to pivot and evolve our SEO strategies have
been like, yeah, you're going to be needing to think voice first.
You got to think voice first.
And I'm not really sure that has emerged yet.
This may further change how people interact with computers.
Again, we've got to use, I am on the potential future of chat GPT and the emergence of GPT-5
that we can look at in a moment that's also aligned to this, but it could certainly change
us how we're using them.
And as a little tangent, we've talked a bit on the podcast about building our own tools
with you've done some really awesome stuff taking auto, taking a recording of a piece
of audio like when you do some of your live conference workshops and automatically turning
that into a blog post through a transcription series of process steps, et cetera.
One of the things I've been getting really frustrated with recently is I asked chat GPT
to help me build a Chrome plugin.
It was awesome.
We had a great conversation about it.
One of the things I learned about it, assuming this is true, is you can do a lot of transcription
in the browser.
There is a built-in piece of code in the browser to do transcription, but it's the buggy transcription
that we're all used to using whenever we perhaps even speak to your keyboard, which I often
try and do when I want to send text messages or what have you or write emails, which just
completely lacks the power of what transformer models are brought to transcription.
So we're drifting into that period where it's going to be easier and easier to just speak
to your computer.
I find it much easier to get my ideas down if I speak.
I don't think I've mentioned it on the podcast yet, but as you know, Martin and I abandoned
some of the workflows I was building because I found this awesome tool called audiopen.ai,
absolute sexy transcription tool that I speak to on my phone or in the browser.
And not only does it transcribe it beautifully and keep a record of that, it uses the same
uses GPT-4 to summarize it in a number of any different styles that I want to use.
And you can certainly imagine that you might be able to now be in the kitchen cooking and
dictating emails to Google Assistant in a way where not only does it really understand
you well, but actually it can take the content you give it and transcribe it in a meaningful
way.
For me, that'd be pretty cool.
I think we even talked about, Martin, what are you thinking about doing this in a car
at one point?
Just as you were saying that, I thought, ah yeah, that reminds me of the use case I had
where I use Google Auto or Android Auto, should I say, all the time for sending WhatsApp messages
to my wife or telling it to make phone calls.
And the amount of times I've wanted to be able to say, add something to my calendar
or draft an email to such and such and just give it more complex tasks.
And I know it's not been capable of doing it.
I've just wanted to record voice notes that I wanted it to turn into blog posts.
Again, not being able to do it.
As an aside, the Android app for ChatGPT dropped a couple of weeks ago, I think it was, globally.
So I've been playing with that and that has audio input, doesn't it?
So you can actually voice record.
And that's been a revelation for me.
So as I was just wandering around the house, just capturing a few voice notes and seeing
what I get out of it.
Really useful if people aren't using that, check it out because it uses the Whisper API
and you can just say, right, draft me my email nurturing campaign for this.
In fact, I did it the other day for a client.
I came up with an email nurturing campaign for their upcoming product launch.
Yeah, it worked street.
And you were just dictating it as you were wandering around the house instead of having
to try and type it out, right?
Yeah, just I was literally making a cup of tea.
There's a movie called Her, which is about AI assistants where in the end people end
up falling in love with their AI assistants.
It's a little bit too left field probably for us to get into onto the podcast today.
But what the world ends up looking like in that world is everybody has an earpiece in
and they're not looking at their phone so much as constantly talking to their assistant.
So it would be interesting to think about whether it really does push us to interact
with computers via voice and a little segue into our last story this week, which oh no,
it's our second to last story I should say, which is that OpenAI has filed the trademark
for GPT-5, which is perhaps not super surprising, right?
We're going to need that, but the trademark application has certain aspects in it around
what they expect GPT-5 to include.
And so maybe that's where the more interesting stuff is.
So the application, which was submitted a couple of weeks ago, July 18th, is currently
in process and it covers various aspects of AI tech like artificial speech, audio to text
conversion, voice and speech recognition, and a bunch of other stuff as it relates to speech
processing.
And what it really feels like is trying to turn chat GPT from a text-based tool into
a tool you can speak to and it speaks back to you.
That's kind of, I think, some of the inferences here.
And as marketers, if we even just take the first order consequences of that, creating
more interactive and immersive customer experiences that are more like spoken conversations with
real people, right?
If you can skin that tech as part of your customer service offering, either when people
ring you on the phone or when they go on your website to talk to a chat bot, they can choose
to have it as a text interaction or as a spoken interaction.
It's just going to make it more like dealing with real people.
This is something you can already access a bit like this.
So we've talked on the podcast before about Pi.
So if you're using Pi on WhatsApp, you can basically record a voice note in WhatsApp.
It will transcribe it and then respond to you in text.
And if you interact with Pi on the web app, then you have to write what you are trying
to say, but then it speaks back to you.
So it's almost like they've untangled those two things and haven't brought them together
in the same place yet.
But there does seem to be a movement towards that.
And of course, with your news there, Martin, about Google Assistant, I do feel that's where
we're probably moving.
Another key question here is GPT-5 and the trademarking, is it really coming or is this
again a bit of sort of buzz and non-news?
And the senior team at OpenAI were quite lucky.
They're relatively vocal, aren't they?
We'll hear from them on Twitter.
We'll hear from them on a number of podcast interviews.
So we do get a reasonable stream of info coming out of the company.
But the story around GPT-5 is muddled at best as far as I can tell.
And whether we're going to see it in the near future is very open to debate.
The most recent thing I heard or read was they are basically primed to do a GPT-5 training
run at any moment.
But it sounds to me like they're actually using market conditions and the activities
of their competitors to inform that strategy rather than actually having a scheduled plan
for when GPT-5 will be trained and live.
But again, all of that just comes with a fairly large dose of salt.
I am not even thinking about GPT-5 until I've got multimodal image inputs with GPT-4 and
a 32k window.
As promised.
Yeah.
Let's get that first and we'll worry about the rest later.
I suspect that that is the truest state of affairs, Martin.
I agree.
Why don't you give us our last story?
Back to Meta for this one.
They've open sourced again because they are champions of open sourcing models, AudioCraft,
which is some kind of AI sound magic.
So it's a text to audio tool called AudioCraft and it can generate any type of sound that
you can imagine.
Apparently.
So we're talking about music, melodies, soundtracks, sound effects, even breaking down sounds into
smaller pieces.
So if you wanted to say a person stood in a large echoey cathedral clicking their fingers,
it would apparently be able to do this.
So what about its music capabilities?
Well, you can pretty much make songs, compositions, melodies, simply by describing it.
So whether you've got the kind of type of music, the genre, instrumentals, temp, all
of this, even maybe the style of a specific musician or a song, you can just say it and
then it will produce it.
Now, again, this isn't just music, as I say, so sound effects, you can use this for films,
video games, podcasts, add jingles, you know, it could be the next radio jingle and the
next earworm.
I love the idea of using AI to create a jingle that you then share using FM radio, old school
tech.
Yeah, that's what we marketers do.
So apparently Meta has gone above and beyond to ensure that every of the 20,000 hours of
music that has been used to train audio craft has been properly licensed.
So the discussion that we've talked about all in today's episode about having content
that is licensed and tagged and marked as training data, they have ticked that bill.
So we don't have to worry about any copyright issues there.
Audio craft is now open source, so I'm sure you're going to be able to see some very innovative
projects in the near future with various products being built on top of it.
So you can get your hands on the code and start building your own audio masterpieces
today.
Yeah, it sounds like from the chat online, I've only seen a bit of it, to be honest,
but this is the new standard in being able to synthesize different types of audio through
text alone.
And I think Google had some tools for this, but apparently these seem much better.
And I think take in in summary, the ongoing explosion in generative AI continues, whether
that's images and text, which we've become used to, but now we're starting to see the
emergence of video and music and other audio really starting to catch up and offer us a
bunch of opportunities to do cool stuff there.
There's one thing on that I just want to touch on, which is the, there's an interesting thought
in this space if you're following prompt engineering communities or anything, and it's basically
this idea that in order to get the best outputs from any generative AI model, so chat GPT
or what have you, the best way to get great outputs is to be a subject matter expert in
the thing that you're talking about, because you know the right questions to ask, the nuances,
the subtleties, you know where it's not quite got it right.
I think this is going to be exactly the same, right?
I do not have a musical bone in my body.
If you give me the audio craft, I will give you crappy audio output, but I would well
imagine that this generative AI model in the hands of a composer is going to be an awesome
tool that's going to be able to expand the capabilities of musicians, composers, SFX
engineers, all the rest of it.
It's going to be a boom for them.
I completely agree.
I guess the other way of looking at that would be also, if I think about image generation
tools, the early versions of this might be frustrating for skilled musicians to use because
they know what they want and they try and explain it, but the tools can't quite give
it and then they can't easily amend it or edit it, which is what mid-journey images
to a certain extent are still like.
You describe it, but if you can't quite get the thing you want, you've got to iterate
through your prompts forever and you think crumbs, maybe it would have been easier to
just do this a different way.
In some cases, maybe we'll see that as well in music and video generation for a while
yet.
Right.
Well, the last part today then is our interview with Brennan Woodruff.
Tell us a bit about this interview as a quick introduction, Martin.
In my conversation with Brennan, he is the co-founder of Go Charlie.
We explore all sorts of interesting themes from the realities of building a startup inside
the rapidly evolving AI space through to how the product itself will empower businesses
and marketers to make content at scale.
But we also have a fascinating discussion around AI agents and how AI agents could automate
passive income streams in the future.
The discussion around AI agents is definitely, or it's a space to watch in the future.
Not just the discussion, but yeah, AI agents, autonomous beings operating 24-7.
Imagine chat GPT just running in the background doing things for you all day, every day.
Yeah, it was definitely thought provoking.
Well, I will look forward to listening to it and hopefully all of you will now as we
segue into it.
Other than that, thank you for your time again, Martin.
I look forward to chatting to you next week.
Ladies and gentlemen, get ready to meet a pioneer in the world of AI.
He's at the cutting edge of generative AI using it to transform marketing and business.
With Go Charlie, he and his team have created the first multimodal generative content engine
purpose built for marketing.
Go Charlie has taken the world by storm, hitting number one on product hunt not just once,
but twice.
Brennan has a relentless spirit needed for leading a startup.
He's a supportive mentor and he's a great community manager as demonstrated by the passionate
and engaged Go Charlie fans on the company's Facebook group.
All 1700 of them, I believe.
Brennan has assembled a world-class team of AI experts to bring Go Charlie to life.
He's been an advisor to countless startups, always happy to pay it forward.
At his core, Brennan is an innovator driven by creativity and human connection.
He believes AI should empower people, not replace them.
It's this unique blend of tech expertise and emotional IQ that makes him such an interesting
person to speak to today.
So get ready for an enlightening and entertaining chat with the one and only Brennan Woodrow,
co-founder and chief business officer at Go Charlie.
Wow.
Quite the introduction.
I would love if you were able to introduce me for every event.
That was fantastic, Martin.
Thank you for such an in-depth discussion.
All the things that you hope that people say about you coming to life.
This is awesome.
What can I say?
You've got a good LinkedIn profile.
Charlie may have helped us some of those things.
Yeah.
Well, you know, you've got to practice what you preach on that.
So yeah, I mentioned the Facebook group.
That's one of the places where we've engaged a lot.
That's a great little resource that you've built out there.
Yeah.
I think early days with a startup, the biggest problem you can have is not talking to customers,
not engaging with customers.
And so fortunately for us, Facebook ended up being a great community.
We've seen a lot of AI companies go the route of Discord.
I don't know if there's any gamers listening to this, but Discord kind of reminds me of
Unreal Tournament versus like the Halo that is using Slack and Slack's a little more my
speed, Facebook community a little more my speed.
Unreal Tournament is just way beyond my speed.
So we've been fortunate enough to have customers that want to share feedback, want to share
with other customers.
And it's just been a big part of our ethos since we started.
Great.
Now it does seem like there's some good ideas and inspiration.
I see lots of people giving feedback and you're always asking for it as well.
So I feel like I've jumped ahead there maybe just a little bit.
In the introduction, I mentioned GoCharlie.
So can you give us an overview of what GoCharlie is for anyone that hasn't come across it?
Yeah.
So GoCharlie is a generative AI platform for creating top quality marketing content.
We have sort of a thesis on what makes perfect content.
Just a combination of a language model purpose built for the things that you need it to do
combined with a brand voice engine and knowledge of your products and knowledge of your competitive
landscape and then the target audience platform that you're planning to post to and a couple
other special ingredients.
But for us, we tried to build that into a subscription based product so that people
could ultimately grow their business and pursue their dreams.
Both my parents were entrepreneurs themselves and so I saw firsthand the impact that relationship
driven businesses took when everything moved to digital.
And so I wanted to give tools to my parents that they could use to market their own business
and that's where we really got the idea for GoCharlie.
So it's very much focused then on the marketing and kind of business content production and
this isn't a fluffy, I'm sure I can write poems, but this is focused on the business
user.
For now, yes.
I increasingly think that SMBs, even creators, even the everyday person is going to have
to know how to create content to market themselves on the internet.
So while I think B2B kind of fits the construct of what we sort of view as who our target
customer would be, I think that second B is becoming a lot more blurred with C if you
know that B2C versus B2B comparison.
But it's definitely more tailored towards marketers that need a more advanced tool.
But I do think with some of the AI models coming online that you'll start to see us
being able to do some of those more creative works such as poems or my personal favorite
dad jokes and dog puns.
Yes, you do love a dog pun.
What's the story behind the name Charlie and the mascot?
Yeah, so Charlie is, well, maybe a fun fact for listeners.
So originally the company was called Gaudium.ai and I'm going to be honest with you, most
of you probably couldn't pronounce Gaudium.
I couldn't pronounce Gaudium.
Everyone that we got on the phone call with was like Gaudium, Gaudium.
And then more importantly, no one could spell it.
So that was the other big piece of this.
And we kind of took that away.
We were like, well, we've been calling our AI model Charlie.
And then I was like, should we just call the company Charlie?
Like go Charlie.
Like literally you're telling your dog to go do something is kind of like you're telling
your AI to go do something.
It's fun.
It feels magical.
You're telling your dog to go do something same way as AI model.
And so Charlie was actually the name of Kostas, my co-founder's dog.
So there's a real Charlie, which we sometimes occasionally share content about in the Facebook
group, but that really gave birth to this new age AI puppy that many people think we're
selling instead of actual content generation.
Yeah.
Well, I saw that you were asking for a few months ago on LinkedIn asking if there was
any AI animated tools that you could get to animate the dog.
I did think at the time, that's a nice play, but yeah, people are going to start thinking
you're a character.ai before long.
Yeah.
I've actually went back and forth with our new newly hired CMO about like gifts that
I want to give to early customers and investors.
And I was like, we should do a dog collar so people can talk and show like the dog collar
on their dogs.
And she's like, we're not a dog company.
We are a Martech AI company that just happens to have a dog mascot.
And I was like, okay, fine.
But you know, if we get enough puppy lovers, maybe, maybe the Charlie dog collars will
come.
We'll see.
Let's not write it out.
I expect it's here at Martech conferences around the world.
Who needs a laptop sticker when they can work around with their dog collars?
You mentioned there your co-founders and the team behind it.
So who are the brains behind Go Charlie then?
What are their roles?
Yeah.
So we had a four person bounding team, which I know is a little larger than most these
days, but just some huge technical firepower.
So Kosis Hatalis is our CEO, AI PhD, 10 years of applied AI experience, was one of the fathers
of probabilistic forecasting neural networks, which ultimately was what transformers are
based off of.
So he's wicked.
He built pretty much our AI from the ground up.
And then we paired him with Despina Christu, who's our chief AI scientist.
I regularly refer to her as Wonder Woman.
She's built NLP solutions for Oracle and for 500 companies, and has really been tasked
with bringing Charlie to life in the AWS ecosystem as well.
So 20 years of applied AI experience.
And then we have a four time founder CTO, Ryan Carlton, who basically built the product
experience from the ground up by himself, which we have a very advanced product capability
wise.
And so the fact that he was able to do that on his own front end, back end, everything
is incredible.
So I'm just the lucky guy that gets to talk about all these amazing people, try to sell
the product, try to get partnerships, try to fundraise.
And I was previously at SoftBank and Uber's autonomous vehicle group before that.
So we have a pretty good team of AI expertise, I would say.
And now we're really starting to flex that technical muscle over the next year, I would
say.
Yeah.
And I mean, there are some credentials there worth paying attention to for sure.
On the technical things to come, I'm really interested in what you've done and what you've
been talking about.
So you've got kind of a secret sauce, haven't you, over at Go Charlie?
Your marketing focused LLM that is yours from the ground up.
Is that right?
And have I understood that correctly?
Yeah.
So we have taken a slightly different approach.
There's a lot of people trying to do AI for marketing.
I won't go too far into my thought about app layer until maybe a later question that we'll
probably get into, but app layer versus model layer.
But we felt that at the onset, we always wanted to create AI that was useful and valuable.
And for us, that meant creating an AI that could serve as the foundation for the rest
of our product suite.
And so in the early days, Go Charlie was a collection of models.
So we had some open AI, we had some of our own image recognition, computer vision, image
creation, and now we're consolidating that down into just our own product suite.
So we have Charlie, the large language model.
We're also in active development on a multimodal model.
So that will be text and image in, text and image out.
That's with SRI International, the guys that developed Siri, which is pretty cool.
The fact that those guys are in with us is pretty awesome for this guy from Evansville,
Indiana.
And then we're also releasing a Charlie the agent, which is kind of an AI brain that can
sit on top of the large language model and multimodal capabilities, as well as additional
API tooling.
So giving you the ability to execute across a number of thousands of tools and capabilities
and tasks, all with a few simple words.
So yeah, that kind of what we have on the technical horizon, but the large language
model itself has been pretty amazing.
We have like a blind user test, like kind of like a Coke versus Pepsi test, which I
think you may have even gotten to try, which is like you put a prompt in and you get a
prompt or you get an output from Charlie and another state of the art model.
And we're winning over 85% of those tasks, which is just truly exceptional given the
size of the team we have relative to some of these other state of the art models.
So yeah, we're excited.
That's hopefully going to be live to the public here soon via API.
So even more fun to be had with Charlie.
Yeah.
And that the, the ability to do the test, is that publicly available?
Can listeners go and play with that?
Yeah, we have, we have a playground.
We opened it up to the public, so you don't have to necessarily be a Charlie customer,
although we would love for you to be using the software product as well.
I think for me, one of the fascinating things with the playground was just understanding
the depth up in the value of having the software layer.
And I know you've probably experienced this yourself.
You go to open AI's chat, GPT, like that's pretty close to a raw model part, but then
you have apps like Jasper where they've been very successful building on top of those models.
And so you go into a raw playground and you're like, oh, I want it to do this or why can
I export or why can't I do that?
And it's like, okay, well, that's a software solve.
And so you start to think about like how much value does the AI model in and of itself have?
And then more interestingly, I think to both of us is like how that evolves.
Can the AI model be truly the entire product?
Whereas do you need a combination of software plus AI?
And I think the answer is the latter, but interesting thought exercise.
Yeah, I would agree.
And I think we actually see that in the way that chat GPT in and of itself came about,
didn't we?
The large language models are the underlying model behind chat GPT back in November.
November 1st, you could use GPT-3.
You could use it and you could build on it and you could access the model and play with
it.
But nobody did.
I say quote unquote, nobody did.
November 30th or end of December, everybody did.
And it was because it was suddenly as easy as using WhatsApp or using whatever Facebook
messenger.
But like you say, it still is very much the closest thing you can get to having that raw
model interaction that most people would want to use.
Send people to playground.openai.com and show somebody a top P setting and then watch them
panic slightly as they go, I don't know what it does.
And other people say to them, no, to be honest, I'm not entirely sure.
I just move the temperature one.
Yeah.
And you find that some of these early adopters, they're like hard code or hardcore coders.
They may want to get into the technical weeds.
I think mass adoption for these tools, it has to be super simple.
Prompting I think is it's going to have to go the way of obsolete and it's just going
to have to feel like you're talking to a friend.
But there's some people that really want to get into the technical weeds and the early
adoption side of things.
They're like, how do I change this scale?
And how do I do this?
That was something that is us building towards mass adoption was an interesting part.
You might be building bells and whistles for these early adopters that the masses don't
care about.
Yeah.
And very much so.
And actually would find actively off putting.
Yeah.
I found when you see tools like Microsoft Copilot and you see the video and how easy
that promises is going to make a classic office productivity and how it promises to do all
of that.
Even that is going to have to be incredibly simple.
You took there about prompting.
Users like my mother who has had an office job all of her life, she knows how to use
Excel.
She knows how to use Microsoft Word and Outlook and all of that.
But does she want to learn how to craft a prompt in order to get her spreadsheet to
do the thing that she's been doing by clicking here, here, here, here and here?
People might say, well, it will save you 20 clicks.
20 clicks is fine if you know the 20 clicks.
Having to sit there and be like, oh God, it's not quite doing it.
Maybe if I do chain of thought prompting, I can get it to make me a pivot table.
No, I can just click on it and it will make me a bloody pivot table.
Yeah.
It's like, I asked my team this question quite a bit, which is like, are we literally spending
a bunch of money and time and resources to get a 5% incremental improvement on this experience?
It would be great if this AI model could make a perfect image on the first try, but if it
doesn't, I'm throwing that image out or I'm giving a different prompt.
If the AI screws up my data table, I'm definitely not coming back to that.
I think we're just as iteration or two away from the AI actually being able to do it with
any sort of reliability, but it always sucks when you see the really plot demo video and
then you get into the product experience.
It is just nothing like it whatsoever.
It's basically like the internet games you see advertised all the time where they look
really cool in the video and then you start playing, you're like, this is awful.
Yeah.
It's the promised land versus the actual reality.
We had a similar thing, actually me and Paul were talking on the show recently about code
interpreter and how he stuck a bunch of data into code interpreter.
It was some data about a client project and he was trying to get it to analyze.
Oh no, it wasn't that.
It was time sheets within his agency and tried to analyze profitable jobs versus non-profitable
jobs and utilization rates and all of that.
He has this already, so he knows the data and that's why he was using it on a data set
that he was familiar with to see if it matched what it told him.
On several occasions it was just wrong.
It's like straight up hallucinated made up stuff.
You don't have to do that many times before you're just like, well, I'm just not going
to bother.
If autonomous self-driving vehicles had the level of reliability that people are flocking
generative AI software at, we would never have autonomous driving vehicles.
We were talking about this before the podcast, that influences where you can actually put
AI into service in your organization.
I even get there with many customers where it's like, maybe a rules-based solution is
what you need.
Maybe you don't need a massive generative AI model to create these personalized emails
where only three sentences are personalized.
Maybe that's just not the thing to do.
I think it's going to be really interesting to see play out.
I think some of that hype is already going away, but even on a personal basis, code interpreter
scared the hell out of me from its functionality suite because it is very impressive.
Some of the things I've seen it do, but reliability is just such a problem in this space, even
from the people that are the best at it.
Yeah, very much so.
It's interesting that you talk there about a rules-based approach.
I had a client approach me recently, wanted to bring me in on an AI project.
They were halfway through this kind of change management piece and wanted to introduce some
AI.
They were very keen to introduce some AI, I should reiterate this, they were really
keen to introduce some AI.
When I sat down with them, they didn't need AI.
They needed some fairly simple marketing automation.
Standard workflow stuff that you would build in a HubSpot campaign, just some rules-based
systems.
Because AI is everywhere, I think it's blinded people.
The solutions are really well established and work really quite well.
Yeah, I think it all gets back to that perception thing.
Most people's perception, even in the business world of what AI is, is all based off of Hollywood.
That's the narrative that the media has picked up too.
It's like mass labor replacement.
It's like, no, no, it's not there yet.
It could potentially get there.
I think that we're going to see a cooling off of the hype cycle as people start to see
that a little bit.
Yeah, I tend to agree.
Now, I said in the intro, you've just said something that's quite interesting about the
Hollywood jobs replacement.
I said in the intro that you believe AI should empower people and not replace them.
Give me that use case then.
I'm a business owner.
I'm looking for an AI solution.
How am I going to turn to GoCharlie in its present form?
What's it going to do for me?
Give me those use cases that your customers are finding really powerful.
Yeah, so I think our platform has been built flexible enough to where different life cycles
of the company, it can have different value levers.
We actually did a session for SF Tech Week.
It was AI driven content creation.
So we literally went through the life cycle of a company.
So I asked like, who in the audience wants to start a company, hasn't really put pen
to paper on it?
The person raised their hand, they came up, we created the name for the company.
We created a brand profile.
We created the channels that they should address first and then the first couple pieces of
content for that.
And then we kind of moved up the maturity cycle into company that already had a website
and was already starting to sell some product.
And for them, it's more just about growth and continuing to tell consistent messaging
across platform.
So we moved from foundational to growth stage.
And from there, we were able to create a bunch of content purely based off their website,
work they had already done.
Then they had already put the paper and turn that into several social media campaigns.
So they can now become omnichannel with their growth strategy.
And then I think for the more later stage companies where they have a new product launch,
we see it being more that assistant of telling that message across a number of different
channels, helping you with your SEO, helping you really just 10x, 100x the content that
you might have been putting out there with the same team using GoCharlie.
Our primary focus has mostly been on SEO, as well as social media content creation.
But I think we have a very interesting suite called content repurposing, which is a bit
of a mouthful.
But my thinking there is like, it allows you to create with anything in source material,
allows you to use videos, talks that you've given, blogs, maybe even co-write with people
that you respect their own thought leadership on.
And so we've given you those tools.
So it no longer becomes just a, hey, we're helping you market.
It also helps you establish authority.
And so for those businesses just starting out, I think that's the way we think about
it.
Content repurposer or whatever the product is called.
Every time I've shown that to people and I've shown that to dozens of businesses now on
various workshops, specifically the video.
So they're just rolling in a YouTube link and going, write me a blog.
And I'm watching people's response because they are so skeptical and the quality of it
is good.
As with any AI, I would always encourage people to make edits, make it your own.
But for a first draft, what it gives you is like, wow, that was pretty impressive.
I think that product itself is testament to when you put some of these models together,
you start to get some really insane workflow productivity benefits.
Like content repurposing, even just the workflow you were talking about, going from a YouTube
video to a blog.
In the past, you would have to use a transcription service to transcribe it.
Then you would have to go review that transcription and make sure that it was accurate.
Then you would have to take that and summarize it into the main points.
Then you would have to take those main points and determine what content you wanted to make
from that.
We're just doing that all in one step.
And then even in a couple other clicks, you can go from having a blog to having a blog
and social media campaign, having some leadership posts for social.
So now you're actually extending the life of your content over a much longer period
of time by just backlinking through additional pieces that all draw off the same source material.
So I think models working together is going to be a trend that we start to see a lot more
in the future.
I certainly see that in the way that I'm playing with certain tools as well.
Using Zapier to build workflows, using things like transcription tools.
So the Whisper API and sticking real-time content into there and having it grow into
my Google Drive, a summarization of the meeting that I was just at or what have you.
In fact, I went to a talk the other day.
It was back here and I just got back home from the Mekong conference.
There was a local talk.
There's some project going on in the city that I live in in Derby.
And I recorded that and just took it straight up to Whisper and got it to spit out a nice
little summary of the whole session with the key points and next steps and ideas for how
I could get involved.
And I thought that's just a really neat way of bringing these different models together.
I got to ask since you mentioned, who's your football club?
The mighty Derby County.
Oh, wow.
We're sitting all the way in League One at the moment, having been relegated from the
Premier League in 2008 with the lowest points total in history.
We scored 11 points and won one game all season.
Hey, you know, being memorable is always something worthwhile, right?
I'm personally a Spurs fan, but they seem poised to never return to Champions League
glory.
Yeah.
And you look like you're about to lose Harry Kane as well to the Munich.
I used to slick my hair back like his and people would call me Harry Kane.
I like to think I'm a little more distinguished now, but yeah, that's just me.
If you haven't seen it in the past week or two, he just did an episode on Hot Ones on
the first week.
Oh yeah.
It's worth a watch.
Hopefully my AI ambitions take me somewhere near sports at some point, but we'll see.
Are you a football fan?
No, I'm a basketball fan.
If there's any Hoosiers listening, I'm an Indiana Hoosier.
So basketball is my jam.
Baseball I enjoy going to a game every now and again, but basketball is definitely me.
I always try and catch a major league game when I'm over in the States, but fortunately
light cancellations this year scuppered me from seeing the Guardians, which was a shame.
Oh no.
All right.
We'll have to have you back over when I'm back in San Francisco and we can do a Giants
game.
Yeah, I'd be definitely up for that.
So let's get back on topic.
I'm interested in your building an AI startup.
I'm guessing that it's not all roses all of the time.
Talk me through some of the challenges of this business.
Yeah, I think there's some that are unique to us and there's some that are unique to
the space.
And so I won't spend as much time on the unique to us because maybe they won't be as relevant
for the listeners.
But I think just being first time founders, regardless of our pedigree, I think works
against you in a space that many people expected rightfully that incumbents would start to
move into once the dam sort of broke of getting these products out there.
I think another is just when you're starting out, like usually it takes a couple years
before you're kind of like, alright, this is the idea.
This is the identity we're going to be and we kind of shot out of the gate with one idea
of what we were going to be.
But then as the space just took off, you might find that that initial focal area is not the
area you want to spend the long term time in.
So that was that's definitely been a difficult spot for us to just how do you steer the
ship and have some sort of clear idea of where you're going as a space is constantly evolving
and more players are coming in.
Now being in the AI space itself is it's fascinating.
It's frustrating.
It's definitely not all roses, as you mentioned.
You have big players releasing models and spending money in a way that you will never
be able to as a startup.
You have startups that had a couple years head start and a much better go to market
motion like I respect a lot of Jasper for what they were able to accomplish so quickly
before many weren't even knowledgeable about the space.
And I think they will continue to be a player.
But much like us, we're still figuring out like how do you play alongside these large
incumbents and get them champion to your cause.
I think the other thing is just like we're a remote based team.
That's always fun.
And then I think you're kind of going through this pandemic transition into more people
wanting to be back in person.
And so a lot more business is being done in person.
And how do you change your startups capital spend when you need to incorporate travel
a little bit more?
That comes off the books versus that.
But the AI space is it's it's troublesome.
I think it's got a lot of the same risk though that you might have with being a retailer
that's selling on Amazon, right?
Like a retailer selling on Amazon always runs the inherent risk that you might get copied
and become a commodity good for Amazon and they might start selling your product at a
lower price.
Same way with AWS's cloud, same way with Google's cloud, same way with Microsoft's cloud.
They all have their own models that they're hawking.
So like how do you get them bought into your cause so that you can build on top of these
behemoths worth of infrastructure?
I actually think that's largely why inflection and open AI are starting to build their own
infrastructure because they realize in the power of these cloud providers and they don't
want to be a part of that.
It remains to be seen how that will work out long term.
But I think the other piece is just like there's so much noise.
There's so many celebrity founders that are getting funded by their larger VC friends
that they've cultivated over years, cultivated this image over a year.
We're a relatively new kid on the block.
And so in that regard, you have to like make a lot of noise in a new way.
And there's a lot more expectations.
You have to like pull off the 100X.
You can't get away with the 10X.
Like the celebrity founder doing 10X is going to be able to pull off a huge round.
The relatively unknown founder is going to have to pull off 100X to really make noise
and get the funding.
So I think it's just like keeping yourself mentally stable in an area of so much noise
and just keeping that determination going.
I know that's a lot more psychologically driven than like how hard it is to play in the AI
space.
But I think that's for me been more part of it than just like being in the AI space.
I think there is something to start up life which requires that resilience of mind.
And you know, that is, it's not a space I want to play in.
So, you know, hats off to all of you that are living in it day to day.
Yeah.
So it's all fun and games until you get a nasty gram from a customer at 3am and you're
like, I just want to respond really meanly to this.
Like, that's just not business.
You have to take it as like they cared enough to send this to me.
You know, I don't like what it says.
They cared enough to send it to me.
Yeah.
Customers, hey, who'd have them?
Looking for that immortal revenue model with zero humans, but still revenue.
Oh no, I'm a people person.
I'm a people person, Brennan, honestly.
So you spoke there about customers.
Are there any particular standouts where you think, or studies that you can share of people
that have used the product and come to you with some really amazing eye opening use cases
and they've killed it?
Yeah.
There's a bunch of these.
There's one moment that I always distinctly remember that like really, I don't know that
I could say that it's cemented.
My decision is being right to jump from SoftBank into a pre-revenue startup, but it certainly
made me feel like it was the right decision.
And that was the first time that we released the first iteration of content repurposing.
We were the first ones that have like YouTube to anything.
And I distinctly remember there was a customer in our chat or in Facebook community and they
simply responded, I was paying an agency $1,400 a month to do this.
And you guys are now doing this for a simple monthly price and I can do this for all the
content.
And right there, I was like, one, that's the firepower of AI, but two, like they can now
invest that $1,400 a month into their business, into making their dreams come true.
Like that for me was like, this is the thing.
This is a bigger dopamine rush than anything else.
I think I saw a lot of people, so we even still have this.
We have like a chat-based experience, but we also have a template-based experience.
And then we have an image generation experience.
And so I started to see people doing some really interesting stuff where they would
prompt the chat to describe a visual for an idea they were working on and then feed that
into the image generation model.
And so we started to think, how can we just bring the image creation part right into that
experience natively?
So you see that with the next iteration of the product.
But I think using the models in collaboration is where I started to see that really mind-blowing
stuff.
Yeah.
Again, I think in fact, actually, Pasi Kozakov, is that how you pronounce her name?
The chief decision scientist over at Google, she was keynoting at the Mekong conference
last week.
And her whole talk was that this isn't an AI revolution that we're going through now.
This is a design revolution.
This is all about design and designing workflows and designing systems and processes and taking
things from A to B to C. Effectively, recipes was the kind of analogy that she talked about.
And I think that's true.
Jasper on that, recipes.
Hers was actually more of a kitchen-based full work analogy.
But no, I didn't speak to the Jasper team when I was there, actually, because they were
exhibiting.
But yeah, I think workflows is the thing, isn't it?
How do you, that kind of multimodality.
But also, I want to get, I've got this idea.
I want to turn that into a thing.
Give me a blog outline.
Give me the blog outline into a blog with the social media post.
That kind of one-click campaign.
When people see that idea, that's great.
You've spoken about the content repurposing.
The steps involved in that are not as simple as watch YouTube video, make notes.
If you're doing it manually, that is not the workflow.
There are lots of steps to go through to get a blog post.
What you've done is you've managed to use AI and build a sequence of steps that does
it all for you in one go.
Yeah.
And I think this is interesting and I'm curious to explore this with you as well.
We talk about redesigning workflows.
Funny enough, I still get people asking for the intermediate steps.
I have still never been able to get someone to give me a solid intellectual reason for
what they use raw transcripts for.
Without fail, every time someone mentions, yeah, I can create transcripts with this.
I'm like, cool.
What do you do with those transcripts?
And then they tell me, oh, we create summaries or we create a blog post or we create social
media.
And I'm like, so then what would be the point of having a transcript versus just those outputs?
Like why would you want it?
It boggles people mind.
They can't come up with it.
But then like you extrapolate that idea out with this designing workflows situation we're
in.
What level of autonomy do you think people are willing to give to AI?
Do we have to get to this like versioning setup with AI where you could see all those
intermediate steps that are happening almost like you would version changes in a Google
Doc for people to allow AI to have any sort of autonomy, much less full autonomy.
And I think that's going to be the larger question we have to answer as we exit this
design phase is like, what are we willing to give up in this workflow?
Yeah.
And that reminds me of the Wired magazine after ChatGPT came out and made all the headlines.
They wrote an article.
It was an editorial piece saying how they as a publisher are going to use generative
AI or how they will and won't use generative AI.
And one of the things that they said in there was that for editing, they will not use generative
AI because editing requires judgment.
It requires human judgment to determine what is important and what is the, what requires
the kind of weight and emphasis within a story.
And that's not something that you can hand over to a bot or to an AI.
And I think that's right.
You know, when we, again, it's, I think it's one of the things going back to your point
about autonomous vehicles.
Ultimately, that is the big question about autonomous vehicles, isn't it?
Like that's how much are you prepared to relinquish?
The moment a bot driven car kills a person, even though it might do it, you know, a hundred
times less frequent than people on mass, people go, well, it made a decision and it ended
up killing a person, so we can't trust it.
Even though it might fundamentally be safer.
I was at, wittily my first week at Uber was when the autonomous vehicle hit that woman
and killed her.
And the ripples that sent through the company, as well as our long-term investment decisions
in autonomous vehicles, like was rather massive.
And I tried to think about this as well because I'm like people die in car accidents all the
time, not to get too morbid, but like every day it happens.
And the only reason I could get to is like, it's not news if someone dies in a normal
car accident.
It is news if someone dies in an autonomous vehicle car accident and we can blame big
tech for it.
And I worry that we're getting into that same cycle with a lot of these AI systems where
we may end up limiting the utopia that could be delivered by some of these systems purely
because we're just going to bury them with bad news stories.
Yeah, and this is where we need that balance, don't we?
You see actually in the news cycle recently, in fact, I've argued recently that for the
likes of Sam Altman talking about the capabilities of AGI and how it could be a kind of destroyer
of jobs and it's okay, we've got a kill switch.
We can turn it off at the wall if we need to.
We can definitely do that.
I think that's a really interesting piece of marketing hype.
People want to buy your product if you're telling people that it's this close to becoming
like, it's going to take over the world and we're having to really rein it in and restrain
it.
Whereas you listen to other people in the field that are at the leading edge and they're
just like, no, that's not it.
Yeah.
And then like what even is the definition of AGI?
I mean, we have a heavy discussion of marketing already.
Like I kind of think of AGI these days is like brand voice is for marketing.
Like every expert seems to have a different idea of what that is and what it constitutes.
And anytime that you can't agree on what the definition of something is, then typically
you're going to have people saying that they're already there.
So I think we should, my hope is we adopt a uniform way of thinking about to the valuation.
Yeah, let's get to consensus on that one point alone, just that everybody recognizes it when
they see it.
You're right.
So this has been quite a broad ranging discussion.
We should probably start wrapping it up soon, but I'm interested to know, you've talked
about AI agents and that being something that you're developing internally.
That excites me, when we can start to build pools or AIs that can use tools.
We see glimmers of this with the likes of Code Interpreter.
We see glimmers of this with plugins and various other auto GPT.
Although I think that's probably wildly hyped.
I don't think anybody's actually done anything useful with auto GPT from what I can see so
far.
But going forward when this can happen, what does the future look like?
And on from that, what do you hope the future looks like for the customers of GoCharlie
in say, let's say 12 months time when this landscape will be very different?
It's a fascinating thing to think about.
I'm in this AI agents DM group on Twitter that has been eye opening.
And one of our board members actually, his name is Dustin Dannenhauer.
He was one of the foremost thinkers on AI agents before this whole like LLM based agent
thing became a thing.
I think agents is such an interesting topic because for those that don't know, agents
is basically like you can execute a more complex task for you.
But at its simplest, it's in an environment and is able to execute a task.
So you might be able to think about a large language model and some of the things that
does is as an agent, a very simple agent, but an agent nonetheless, it was an environment
it does task for you.
Now if you think about agents is sort of we're thinking about what they constitute.
We would theoretically want an agent where you say, hey, I would like you to research
this topic, establish a stance on it, make a blog post about it, make a series of tweets
that kind of carry that messaging through, add some images and cite your sources.
So that's like very complex.
That would normally take one person maybe a week before AI.
Now it might take a day or two with AI.
We want it to do that whole thing all at once.
So that's what we're kind of envisioning our agent product is doing is like at your behest
doing thing.
But then where it gets super interesting is over time it warns you.
And so then the agent starts to become proactive.
So then instead of saying, or instead of you coming into the product and prompting, it's
coming to you and saying, hey, based upon your business, the competitive landscape,
the industry that you're in, here's what we recommend you create content about this
week and we've already created some graphs.
You want us to post this for you or would you prefer to come in and edit more?
So to me, agents are the bedrock of a more proactive AI system, more proactive assistant,
the more real collaborator with your business.
Now if I think about like, where does that go in the future?
First and foremost, I think that agents need to turn doorknobs.
They don't need to be talking to in special languages to one another.
I think that will probably come most likely, but I think the most successful agents will
learn how to use existing tools, APIs, because that will garner mass adoption.
If I could tell something from Go Charlie, create an email campaign and post it to my
Clavio account, I'm going to use that tool versus one that has to have some special sort
of coding to go into it.
So you need an agent to be able to turn doorknobs, not create code to make something happen.
Longer term, I think the agents just become part of your company.
I do think that because of AI, companies that are just starting will be smaller.
I think the companies that are larger will get smaller or will do more.
But I think also because of AI, those companies, when they make layoffs, you're going to have
a lot more companies started because you won't need as much.
My hope for the future is that I could have an AI agent that basically runs a passive
income side hustle for me.
So I can go wig on a beach in Mexico and paint at night.
But like, I think we're a ways off from there.
I think there's some regulatory concerns with that.
But ultimately, I kind of view AI as like, at its best, it's the digital twin of your
desires.
You tell it what you want to be done and it can go do it for you.
That's kind of the future world that I think we're moving towards.
But it all boils down to doing more with less.
So fast forward 18 months, go Charlie agent is flying, you're sat on a beach living off
the income from drop shipping dot agent AI.
That is that what I can expect to see.
I mean, it's funny that that's is a brilliant picture of agents.
And I think that what you've touched on is that the bit that's easy to overlook with
agents, because like I mentioned them, AI is being able to use calls and think about
auto GPT being able to plug into an API and do something.
But it's the proactive piece that I think is so often overlooked.
The idea that this is just running in the background, right?
The thing that lots of people are probably thinking when they use the likes of chat GPT
for any amount of time, you know, you use it for a month or so.
And then you're thinking, I wish it could just go and find this out for me now when
it's not available to you on your, you know, you haven't got your phone to hand or whatever.
If you've got an AI agent that's always there, always there, just kind of dialed in doing
little jobs for you, doing research, finding out what the market conditions are like, saying
here's a blog post, here's a trending topic that you want to jump on the bandwagon of.
If you've got that, I mean, that is an absolute game changer as if you're a marketing manager,
marketing assistant, whatever.
So you painted an exciting picture there Brennan.
Yeah.
I mean, we were talking about workflow design.
What if the best workflow is no workflow at all?
Oh, that is, if we can plug that in with the customerless revenue generation model, we're
in the dream ticket.
Then we'll both go retire and watch Giants baseball games and sit on the beach in Mexico.
How about that?
I'm into it.
Yeah, most definitely.
So where can people find out more about Go Charlie?
Yeah.
So our website, gocharlie.ai, we are actually doing a phenomenal event.
Not sure when this is going to air, but September 6th, we're throwing the AI party to celebrate
the close of our $2 million pre-seed round, the launch of our large language model publicly,
the launch of our agent product.
We're going to sit down with some people from SRI and NVIDIA, as well as the CEO of Hawk
Media and some other people on the future of AI marketing as well.
So definitely check us out there, but you can find us on Instagram, Twitter, LinkedIn,
gocharlie.ai is the handle.
We didn't do anything too, too fun with it.
We make the content fun, not our handles.
But then me personally, just Brennan Woodruff on LinkedIn.
I love hearing from customers, love hearing from AI enthusiasts, pretty active in the
site community.
So just shoot me a note.
And in terms of signing up, what are the plans to start from?
Have you got a free plan, free trial, teams plan?
What does that look like?
Yeah.
So we have three tiers, but we also have a free tier.
So we just recently made a free tier available.
We want everybody to benefit from AI.
It helps us improve the product.
And so there's some limited usage on a monthly basis.
And then as your business scales and you need more advanced content throughput, we have
a freelancer tier, then we have a professional tier.
Those are both single seat options.
One is limited use of the platform.
One is full use.
And then we have a team's tier for agencies, enterprises and beyond.
That's a five seat plan.
So those are evolved over time pricing wise, but yeah, we have flavors for everybody in
every walk of your business.
Great, well, as a user of GoCharlie, I would encourage people to go and check it out.
It was the tool of the week very early on in the podcast.
So people want to hear my thoughts on it.
They can go check that out.
Well, thank you very much for joining us today.
Of course, Martin, it's always a pleasure, my man.
We got to do this more often.
Thank you for listening to Artificially Intelligent Marketing.
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