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.
I'm delighted to announce a guest to artificially intelligent marketing this week.
Say hello to Ankur Pandey, CEO and co-founder of Longshot, which is an AI driven content
marketing suite of tools with everything from content generation to content optimization
with some clever sophisticated workflows to make your life easier as a content marketer
baked right into the tool.
Ankur has founded multiple SaaS startups, always in the AI space and launched Longshot
about two and a half years ago, which in the world of AI feels like several millennia,
I guess.
We've seen quite a few changes in that time.
So welcome to the show.
Thanks a lot, Martin.
It's my pleasure to be here on this show.
Excited.
You've been around the content marketing space for a while now.
You've had a tool helping content marketers.
I'm interested to get your thoughts on how that content marketing landscape has really
changed over the last few years in no small part due to AI.
First of all, when it comes to content marketing, by now pretty much every serious content marketers
would use AI in their workflows.
The degrees might differ or where they use it, how they use it, et cetera, but then it
has become pretty universally accepted.
So the biggest change, if I can just call it one change, is the overwhelming acceptance.
What I used to see a couple of years back was that marketers would be a bit skeptical.
And I think I understand the reason.
Over the last decade or so, there had been over-promises in terms of content marketing
space, especially a lot of AI or technology tools promising things which would rather
turn out to be not at least as much as the claims would be.
The initial skepticism was probably justified, but I think by now everybody knows that AI
in content marketing is here to stay and that content marketers of all types, of all sizes
in every niche and every industry would use it.
So that's like the one biggest change I would point out.
What I'm particularly interested in and looking to get into the discussion with you is how
AI sits alongside the latest developments that we've seen in search engine optimisation,
such as Google's helpful content update, which now tells us that you've got to be writing
high quality, helpful content for humans.
And obviously that's got to be done in conjunction with the EAT guidelines as well.
So in that context, in the modern contemporary 2023 content marketing landscape, tell us
how does Longshot work?
I would kind of start from the point of view of content marketers who would be interested
in SEOs.
The answer is likely more direct for those kind of content marketing folks.
The impact on SEO and merely by using AI content was kind of either overblown or was kind of
in some sense a lot of confusions around it and they have gone.
And there are two main reasons for that.
One is that people have understood that or at least learned some tricks of the trade,
like where exactly, how should they use it?
And second thing is that, for example, Google has taken a very open position that initially
there was some kind of confusion around it, but now it was pretty clear that they're not
after AI content, so to speak.
And we are also seeing that specific sort of, you know, ask or other behavior in our customers
or in our users.
So I guess get lesser less confusions with respect to will this AI content not rank or
will that be penalized?
I think that is pretty much negligible.
People have seen that just because AI, the impact was not there in the sense that if
the content was bad, the content did not resonate with the overall domain, etc.
Of course, there may be an SEO sort of downside or there'll be an impact, but not merely because
it was an AI content per se.
Another reason is that we are seeing like, you know, both tools making like my own tool,
we try to, for example, you know, create sophisticated enough workflows so that we tend to create
as much human-like on brand content as possible.
Plus, the AI technology itself has improved.
It has itself become less synthetic over the time.
So I think it's a culmination of many factors.
So I would say unless if you're trying to abuse it, if you're trying to create bulk
content without any oversight and with like a primarily spammy intent, you should watch
it, watch out.
But beyond that, it's reasonable to accept that if the content is good, you're good.
Google's position on that is very clear.
They've said that they won't punish you as long as it is helpful to the readers.
So you touched on your tool there.
Many people listening won't have tried Longshot.
Tell us about it.
So Longshot, I mean, as Martin already, you mentioned that it is a content suite of products.
We observe content marketers and a variety of workflows, primarily long-form content.
That's why the name and we basically try to solve the problem, which was rather confusing
for serious content teams.
For example, think like hallucination, factuality, etc.
So if you're creating content for, let's say a brand, so you would not want content which
would be very generic, would have factual inaccuracies or would hallucinate.
So in order to do that, we developed the workflows, which would try to fix that by a variety of
methods.
So the product is a combination of many features and that had to be the case because there's
no one single use case by content teams.
They do a variety of jobs and there's a field which keeps on evolving.
Therefore, we have to also cater it.
So today, if you go to Longshot, you would be able to write really complex and long content
with an extremely guided approach.
Let's say you want to create a listicle article and you can upload or give inputs your own
context, your own personality, the brand voice, things of that nature.
And then you can guide it along the way and finally optimize.
When I say optimize, it's not just SEO, it's a thing like plagiarism and readability.
So we try to be at a space where it's an overall assistant to a content team.
And then of course, if there are interventions required, there are also features for that.
For example, you can send it to a team review within the product and a lot of people do
that.
Pack their team members, et cetera, et cetera.
That's our goal and we are of course progressing towards that goal.
You were one of the first out of the traps in the industry to really focus on reliable
content.
You spoke a moment ago about inaccuracies and hallucinations and you launched Fact GPT
as it was originally called.
I don't know if the feature is still called Fact GPT now, but you were one of the first
out of the traps with that.
Tell us what was it that you saw in the industry that led you to go down that route?
Fact GPT is a feature inside Longshot.
It is still called Fact GPT.
And of course the feature has since grown to do many other things.
So basically as the name says, we realized that the generic AI tools, including chat
GPTs, et cetera, were really good in creating high quality content styles, but they did
not do that well when it comes to two, three things.
For example, if you want to produce something which is very recent or if you want to upload
your own context, you have an applethora of data, you want to sort of give it to the AI.
This was not easy.
I wouldn't say that it was impossible, but for a content team, there's a lot of work
to be done and a lot of things under the hood.
So we decided to solve this problem just to summarize if you want to make sure the content
is either recent or you want to give your own context or if you want to just focus your
content on some specific websites.
Let's say you trust 10 websites for a specific type of news, a specific type of content.
You want to base your content only on these 10, let's say.
So what do you do?
So those are the kind of things which Fact GPT attempted to solve, still solves.
And we were of course motivated primarily by our users asked that they wanted a method
to do that.
They would initially what we saw that they were producing a generic draft and then they're
in some sense updating the recent fact, right?
So they were doing it in two parts and we thought can't we combine this?
So this was the primary motivation.
We eventually arrived at something which did work and it has been growing since then.
Since then it has grown to be much more sophisticated.
It can handle lots of varieties of data and much more context.
And thanks to both my team's work as well as upgradation of the AI itself, which we
also leverage.
So it's basically the technology itself has evolved and the product therefore has also
evolved.
You mentioned the AI has evolved.
You've built a tool which has connections to external APIs and you've built your own
products on top and you've also developed your own products behind the scenes.
Can you talk to us about bringing the product together and the models that you're using
and how you go about choosing whether to develop your own model or application or integrating
into something that already exists?
I would say it's been an interesting scenario.
The reason is that we leverage AI technologies like OpenAI and now we also leverage others.
For example, Claude Coher, many other open source fine-tuned llamas, et cetera, and some
homegrown ones.
What really happened is that when we were developing it, or I'm basically summarizing
the whole two and a half years journey, we were developing and testing and seeing is
it okay or is it good for our users.
The technologies for whom we were customers were also learning along the way.
So OpenAI of the world and Coher's and Claude's of the world have actually also improved thanks
to their users, including me.
We were, for example, I remember we had lots of deep dives, we still do, with the OpenAI
teams, Claude teams, et cetera.
In that sense, we kind of became a front for these technologies to also go.
It was pretty symbiotic that way.
To answer your question specifically about what models to choose, this was based on both
external tests and internal tests.
We would go back to the research literature, seeing which model performed best, but we
will also do that testing on our own sample.
As our user base grew, we knew where to test, what to test for, where are these issues which
come.
So today when we test, we do not just believe in the openly available benchmarks.
All the AI APIs which we develop, they would have to undergo some kind of testing process
and they will publish these testing process.
They're okay, this did plain X, Y, Z, et cetera.
So that would be a good signal, not the complete signal.
Why?
Because your own specific type of user behavior might differ.
So these testing platforms kind of look at general behavior.
We wanted for our type of users, right?
And we by now had extremely sophisticated testing sets for that.
So we do that.
We have been doing that.
This is actually a pretty ongoing and a very real process.
This is the primary motivator, which AI technologies to use where.
Also I'd like to point out that today in long shot and by proxy, I can also say in many
tools, there's no single sort of AI technology behind a feature.
There is generally a chaining, right?
So for example, you would use, you're not just depend on, for example, GPT-4, you'll
do GPT-4, but for rack pipelines, for example, you would do like embedding search for that.
You will either have something homegrown or, you know, so generally that's like a pipeline
of a small or big AI technologies.
So which has gone right to the user behavior and this is going to grow more sophisticated.
Now with GPT marketplace launched and I think co-pilot side things coming soon, we will
see it more and more.
This chaining of entire things and we are being extremely sophisticated over it.
So excited to see what part we will play with this.
You mentioned there embeddings and embedding searches, and you also mentioned Co-Hare.
Co-Hare is one of the most highly regarded models for search and embeddings.
Is that how you're deploying that within your workflows?
Great.
Co-Hare also we use at few places, not everywhere.
So Co-Hare, as you already said, Co-Hare is pretty highly regarded, but among their set
of AI technologies, some are better than others.
So they have something called Co-Hare reranker.
So now what this reranker does is that if you, let's say, so you already mentioned FAC
GPT, which is a feature where you would upload or link to a lot of data and we'll process
it.
Co-Hare is used somewhere there also.
Does a good job at which document we should look at first or what is that order.
So those kinds of things Co-Hare has done pretty well.
So we use that in Co-Hare.
As I said, this keeps on changing.
If we are speaking two weeks from now, I might have a different answer.
That's really how the nature of the game is.
Absolutely.
It was less than 24 hours ago that Clawed 2.1 was announced with the 200k context window
and improvements and hallucination reduction and all the rest of it.
So yeah, an ever moving landscape.
Ever moving.
For sure.
So just to take it back to the content marketing piece then, you've clearly been working with
lots of customers in all sorts of segments.
Last time we spoke, I know you were working with journalists and news teams, marketing
departments with education teams.
I mean, you name it.
I think you were just about across it.
What learnings could you impart to our listeners about how to think about deploying AI tools
within the content marketing workflow?
First of all, I'll give you the answers which we are more clear on because this is also
something which is bound to be a bit opinionated.
But something which is less opinionated, I would say that if your content style or the
kind of content you're writing has sensitive to a few things, for example, you are in FinTech
or you could be in compliance, legal, areas like that.
So you have to, by definition, make sure that this veracity and hallucination are checked.
That's maybe the first thing you should do.
The style and the creativity is maybe take a backseat here.
Therefore, for example, if you are picking a tool, I mean, I would do whatever tool it
is.
So make sure that it's that prioritized.
And similarly, then there are lots of use cases.
We see that just after that, there are some other guidelines.
Let's say we have teams which say that they want specific guidelines to be met.
It could start from that they should have a specific tonality of the kind of content
they have previously read.
Now, so just understand that this is a bit complex because it's not like they know a
name for this tonality.
Let's say if I say write in the way how Martin has read.
It's of course hard for anyone who has not read Martin to understand.
So we have to, we do not have luxury to just know by if you just mention all the same.
The style has to be in some sense discovered.
So this sometimes this becomes important for teens who are very careful about brand voice.
And then I, as I said about brand guidelines, so guidelines, example guidelines could be
that for example, that they don't want abbreviations or they don't want any sort of names which
or any legal technologies to be shared or things like that.
So now the point is that if these kinds of things you can always do by hand, right, as
traditionally has been done.
But when you're selecting, just see that is that prioritized or not.
So I think that could be the kind of answer.
I'm pretty different.
The reason is that we also tend to attract such users more because of course, just if
you are interested to just write the content, right.
If you have some quick idea and write a tweet, then I think that's a pretty co-ordination.
You don't have to even use any tool.
You just go on.
I think Bing's and Google's of the world would solve it for you.
Right.
So there, but it depends on the sophistication and sensitivity or curiosity.
On the flip side, I would say that if you other things which are like, which also matter,
which we see, for example, we cater primarily in English, sometimes also in, I mean, in
few major languages.
And the reason being that some other languages like Arabic and even Hindi, right.
Indian languages are a bit hard to tame.
I mean, now it is improving.
What I'm seeing is that there are dedicated tools coming for languages.
Maybe that will grow.
So that also kind of factors in.
So I think there are a few angles one which has to be vigilant about.
You've also introduced within the tool and you referenced this earlier, the more collaborative
the team based features.
Is there anything there that you think teams need to consider?
One thing personally that I'm very keen on at the moment is pushing just the basic AI
literacy.
What are the models?
What are the limitations of the models?
What is a hallucination?
Things like that.
And so any other considerations that teams or leaders of teams and businesses might want
to consider when deploying AI technologies in marketing?
Yeah.
So that's a good question.
I'm not sure if I have a direct answer to that.
I think part of it is that I'm actually surprised and very impressed that content team leaders,
content heads of content, they are themselves pretty much on, it might not have been the
case a year back, but now they are themselves dated at least to a great extent on a lot
in some sense in context of AI literacy.
I think they are catching up fast.
I'm not sure if as a tool we have a part to play there, but that kind of thing has happened
post-ChatGPT.
I think people start to take it very seriously.
Everybody and thanks in part to influencers, they did hype the thing, but then everybody
and their mother decided to give it a shot.
So that basically became like a, you know, when a lot of people did it for the FOMO,
right?
That they have to understand what's going on.
So in no less part to all the constant drama, which generally open AI surrounds themselves
with, including the recent one.
So in India, for example, there is a world cup going on, right?
So I was seeing the chat, a parallel chat between two things, right?
The world cup, the cricket world cup that is, and the open AI, right?
At least in the tech interested community, which was unprecedented.
So yeah, I would say that a lot of evangelism has happened because of marketing and a lot
of public understanding already.
I think it would as any other technology, right?
I think it would be in terms of what has to be, what should be prioritized and what should
not be prioritized.
That has to be also solved, I think, apart from the marketing language.
I'm not sure what do I have to, what would my role or at least product role would be
there.
I think that would be in some educators role.
But one thing I would definitely say, any new technology, of course, adds to confusion.
But if you compare it to a few other technologies, which has happened in the past, things like
blockchain and all, it is still much less confusing.
I would say things are much more straightforward.
You can see for yourself it is working.
For example, in a blockchain world, right?
It's not trivial for anybody to just start playing with it, but here you can do it.
So you can in some sense see for yourself.
So because of that very nature of things, I think the education has become much easier.
Users can get value from it immediately.
The time to value is very, very quick, isn't it?
And like you say, there's no technical requirement.
I can ask ChatGPT to write me a tweet about a topic and it will do it.
And that's great.
I say on the flip side, an NFT, I can buy a JPEG of a monkey.
So what?
Right?
Where's the value there?
Not that I'm dumping on the NFT and blockchain community.
I would never do that.
You mentioned there the open AI drama.
Are you confident that your board are not going to sack you and then rehire you in four
days?
Yeah, I hope not.
And the reason is that we don't have that kind of board, right?
Which would have such a drastic disagreement.
I think this is really one of them.
This happens once in 30, 40 years, maybe like last time it happened was Steve Jobs, right?
I don't think that founders or CEOs start doubting their boards.
So mostly this will be one off.
Yeah, hopefully.
I think it does go to show the value of having a good board though, an experienced board
for sure.
Yeah, but I would definitely add this actually taught a lot of us and it's not like this.
We were all prepared that no matter how big or how influential a particular, let's say,
company becomes, our job is not to just entirely depend on open AI's of the world, right?
Either by leveraging other elements or by using our homegrown versions, by fine tuning
open sources, et cetera.
But that is definitely what a general lesson for a builder in this space would be.
So that I would definitely, in some sense, I would update my, this is something we already
had a bit of careful about, but this kind of, I updated the sort of seriousness of this.
I saw several people on threads at the weekend saying that they were switching over their
open AI APIs and applying to the Microsoft Azure models.
So they could just do a light replacement.
They felt much more confident using it through Azure than open AI given the drama.
Whether that's warranted or not, I don't know, but I agree.
I think this gives developers cause for concern and to be aware of the over-reliance on one's
supplier for sure.
Looking ahead to the AI landscape, things are changing rapidly.
We've seen in the two and a half years that your product has been on the market, things
have evolved quickly and the interest in the space has obviously gone through the roof
in the past 12 months.
Fast forward 12, 24 months, where do you see the space heading?
What's next for us?
Yeah.
This is something which I just had an opportunity to speak on just a few days back.
So it was not exactly about content marketing, but it was content management system, which
also has extraordinarily like overlap, right?
So I would base the answer from there and whatever I learned there.
So I would say that there are some really interesting trends which has come up, right?
So the role of content would not be, would drastically change in the sense that, so what
does, for example, what, how does a marketer treat content?
Content is but a medium to inform your users, right?
Things like that.
So it's like you are putting some piece out there, somebody's reading it, understanding
a few things or getting evangelized or stuff like that, right?
So this whole philosophy might be updated.
For example, this might sound futuristic.
When we say futuristic, it might be like six words on the line, right?
So whatever you are reading a blog and the blog updates itself on the real time, right?
Based on what your signals are.
I'm not saying that you have to chat everything and ask because sometimes when you try to
ask, you don't know what to ask.
You don't know what you don't know, right?
But it's like taking cues of your sort of past historical data and what have you liked,
where are your eye balls on things like that, right?
So you would probably see a scenario where maybe like there'll be a draft content, but
beyond that is truly personalized, right, with respect to this is, you know, I was also
astonished when I kind of learned, but some people are taking this seriously, right?
So you know, CMS of the world are trying to update themselves, what if this happens?
What will their role be?
How will you store the content, right?
Or those kind of things.
Second thing I would say is that I think in order to truly stand out, two types of context
would matter.
Your context as in the reader's context, which I already touched upon in the last point,
as well as the brand context.
It always used to matter.
You have to, people would be interested in the messaging you have, et cetera, et cetera.
It still works like that.
But then I think it will go much deeper.
I would not be surprised if every medium to large companies, when they use an AI tool,
either a tool or AI directly, they have fine tuned it or adapted their use case.
So the genericness will be taken care of.
We just were in talks with one big media player and they had guidelines like this, for example.
So both, they are like a media company and when they would talk about any person, right?
Depending on what kind of content it is, they would shun away from writing anything negative,
right?
But at the same time, they also have to present the facts.
So let's say somebody did cram it, right?
All those things, it's a bit hard to capture today, right?
And so we were trying to see what do you really mean?
It's hard for users or humans to tell what they mean, but rather than show what they
mean.
And the last point I would like to say is this.
I would also say that there'll be innovations on how users interact with all this, but maybe
there is something which is completely unthought of in terms of how people interact with the
AI first content tool.
It can be something which we have not even arrived.
So I think even designers have a role to play here because maybe the true value of AI is
not hidden in the better model, but it might be hidden in the time.
Like how do users interact with AI?
So for example, chatgbt surprised everyone, including OpenAI.
We're on record saying this.
What comes after chatgbt?
What is the next surprise?
And I am confident that this will happen.
And content marketing is a world where you see the first innovations, right?
Because there are huge and very horizontal landscape, right?
So this will definitely be one of the first areas to both get experimented upon as well
as, you know, absorb it.
Cathy Kozakov, the chief decision scientist at Google who recently left, she wrote earlier
this year, a blog post that said the latest AI revolution is not an AI revolution.
It's a design revolution.
Yeah.
And it was all about the user interface.
And so I 100% agree with that.
It was fascinating to see how getting a large language model into an interface, just like
WhatsApp suddenly changed the appetite and demand for these technologies.
Hey, who knows?
Maybe the next frontier for content marketing is the humane wearable and we'll all be creating
content through that kind of interface.
Yeah.
That's a dystopian idea.
Let's see.
I'm not judging.
I'm not fully sold on that as a concept just yet.
Let's look ahead for Longshot.
What are you working on?
What can you give us a peek behind the curtain on?
So, so in Longshot, you know, what we are very bullish on the one aspect which we are
convinced will be the next creation is the brand voice thing.
Brand voice, our definitions also changed.
We used to think that it's just the style of tonality, but it has actually evolved to
multiple guidelines, rules, and the space keeps evolving.
And of course, we now, we are actually working on a way that the most complex or the even
most tracked, the most vague sort of, you know, ask can also be in some sense accepted
by the voice.
Like there is a feature or there is like a section of Longshot which is called auto blog
workflows wherein we try to create blogs in nearly, I would not say 100% automated fashion,
but nearly automated fashion.
Like this is also proved to be valuable.
So rather than creating one generic template, we tend to give like a lot of popular templates.
For example, listicles and some types of blog, let's say FinTech blog would have a slightly
different style and things like that.
But then what if you don't even find all that?
What if you have a style of your own or context of your own and then you want to create your
own pattern?
So that all those things are working on.
I would also say finally that we have seen a lot of interest in APIs.
A lot of people, especially larger companies for whatever reasons, they want to use kind
of solutions we offer, but maybe in their own CMSs, in their own environment.
So for that we had already brought up APIs which are used by lots of companies now, but
this is also going to be an increased focus.
So you don't have to depend on using Longshot, right?
You can actually plug Longshot's APIs in your own systems and it will work like in C2.
So those are the two, three main areas.
We would be focusing on and for the readers who are interested, I don't intend to, as
I said, be very focused on too much Longshot.
You can see for yourself.
If anybody's interested, you can just go to Longshot, get a free trial and I'll be happy
to hear your feedback of any type.
It is his own, you know, or critiques or praise, whatever, you know, bring it on.
I would encourage people to check it out.
I've been a long time user.
I've seen the product evolve a fair amount over the past couple of years and looking
forward to seeing where it heads.
So actually building some tools with the API, getting that integrated into some of my own
workflows as well.
How do you feel about the future of content marketing and AI?
What can you leave us with before we say goodbye?
So I would say that I think if there are still folks who are skeptical of AI technologies,
I think you should embrace it.
I think the issue is that it will replace the job is overblown and it will.
The point is that replacing job can be seen as a welcome change to get on to new things,
right?
In the sense that even in this very space, content marketing has never been a space which
was set in stone, right?
Every year it will go to any of these subject to changes, right?
So I think, are you, and the reason I'm bringing it up is that we had the fair amount of such
interaction previously.
It has gone drastically down now.
So my appeal would be to embrace it and buy by your own expertise with the products like
us will also improve, right?
So that's the whole point.
If there are some legit concerns which product builders like ourselves have missed out so
far, this is our opportunity to embrace them.
Fantastic and optimistic and call to arms for content marketers to embrace AI.
If people are interested in getting started with Longshot, they can check it out.
It's longshot.ai and you get access to the full suite of tools via there.
Thank you very much for joining me today.
Thanks a lot, Martin.
So it was a lovely talk and hope to exchange notes soon in future.
Fantastic.
Cheers, bye.
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