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,
and welcome again to another episode of Artificially
Intelligent Marketing with me, Paul Avery, and
the fantastic, wondrous Martin Broadhurst. Hello,
Martin. How are you? I'm great, Paul. I'm cold,
but ready for Christmas. Yeah, one week to go,
so it's crept up quickly. We've been getting
a few Christmas presents on the old AI front,
haven't we, over the last couple of weeks. There's
a few things we're going to cover on today's
podcast. We're obviously going to need to talk
about the launch of GPT 5 .2. sam altman's code
red and crumbs gemini's awesome and opus 4 .5
is awesome and people don't think we're relevant
anymore we better get something cool out so um
we'll talk about how cool that is or isn't we're
going to talk a little bit more about aio aeo
geo whatever you want to call it um and whether
or not it's actually just seo we've talked about
it a little bit on the podcast previously but
we've got some interesting new takes to go over
and open ai also released a report about their
how people use the enterprise level product with
some really interesting take -homes on whether
people are getting value from using AI. Obviously,
we have to think about what the mouthpiece is,
OpenAI telling us that people get use out of
products like OpenAI, but there's some interesting
stuff there. So, right, let's jump into our first
story and let's talk about OpenAI's launch of
GPT 5 .2. Some quite interesting stuff around
that this week, you know, beyond just 5 .2, they've
had an interesting week. Yeah, they have. And
it all comes off the back of Google launching
Gemini 3 Pro and Anthropic launching the Claude
Opus 4 .5, both of which shows some amazing scores
in the evaluations, all of the benchmarks that
we've come to look at the tables with the little
numbers and we cross -reference them all and
see who's number one for the various different
categories. And what it showed was that OpenAI
with... chat GPT or GPT 5 .1 had started to slip
down the pecking order quite substantially. So
there was talk of a internal code red memo for
Sam Altman, which was basically they need to
focus on getting the models out that they've
got behind closed doors to start competing and
show that they're still in the race and they're
not being left behind, which is interesting because
the story before Google Gemini 3 came out was
that they were preparing in OpenAI to launch
ads within ChatGPT and that was the next big
thing. And all of a sudden it's all hands on
deck to improve the models and the ad product
is being pushed back in terms of its launch.
We shall see what happens with that. So yeah,
the new model 5 .2 boasts significant improvements
in reasoning and in long context understanding.
In fact, I think the context window has been
increased up to 400 ,000 tokens. So that's going
to be in the region of 300 ,000 words, which
is a substantial corpus of text. OpenAI claim
it achieves 70 % parity with human experts on
certain benchmarks. Um, so yeah, this is, uh,
it's a big deal. I believe computer use and agentic
use cases is something that they've particularly
got their eye on as well. I want to double click
on a couple of things there, Mark. And I think
you make a really good point about the ads products
being delayed. Um, I remember seeing something
floating about on the Reddit sphere. I think
it was a, or Twitter. It was a, whatever we have
to call these things then. There was, um, a post
from i think it was one of the product leads
it wasn't sam altman it was one of the product
leads about pulling the initial some of the initial
tests which oh by the way weren't the ad product
there was something else but the people have
grumbled about a bit and i think it's quite an
interesting scenario where open ai have sort
of been in the lead most of the way um but obviously
gpt5 has been a little bit of a letdown i think
for users the way it was launched kind of sucked
as well And now Gemini 3 comes in, Opus 4 .5
come in, they're all kind of cool. One thing
we know is once you introduce advertising into
a product, you are sacrificing user experience
in general, at least for what we have come to
understand as advertising supporting products.
We talked about this a bit on our previous episode.
So on the one hand, our model is no longer the
top model. Oh, by the way, we're about to introduce
something where we'll make some more money, but
users might like it much less. So I don't think
it's a surprise that they cancelled the one that
would make usability worse and then tried to
roll out a model to stay on top. The other thing
that's been quite interesting on the Reddit sphere
is quite a few people wonder how much of the
benchmark scores for GPT 5 .2 is OpenAI kind
of fiddling with their models and making sure
that they're good at benchmarks rather than necessarily
real human use cases, which of course is very
hard for us. to tell but some of the benchmark
scores are significantly better than other models
uh including big jump on the arc agi2 benchmark
up to 53 give or take and the best so far was
37 .6 from claude opus so that's a that's a big
leap one of the math benchmarks have got a hundred
percent on which is a you know pretty significant
um although the other models were in the mid
to high 90s as well so Is it really, really,
really good? Or did they just beat the benchmarks
by playing a game? Who knows? But if you do a
search for GP2 25 .2 on Reddit, some of the post
titles that you'll come up with are quite interesting.
GPT -5 .2 Extended Thinking fails miserably and
performs far worse than previous models. Simple
Bench for GPT -5 .2 and 5 .2 Pro, they both scored
worse than their original GPT -5 counterparts.
So hallucination rate, some people are reporting,
is also up. I can't think of a time, especially
in this race, when anybody rushing out a product
that might not have been quite ready has gone
that well. Because we have an enterprise level
account, I can't play with 5 .2 yet because it's
not been rolled out to enterprise. So I can't
test it for my usual real work benchmarks, if
you like. But yeah, maybe it's not been a great
move. I mean, you've been using it. What's your
experience has been? Really hard to give any
real insight just because my use case in the
chat window is kind of saturated. I'm not pushing
these models. to the edge of the frontier in
terms of maths and discovery. I'm using it for
fairly routine, fairly mundane productivity type
tasks. And it's fine. Just like the other model
was fine. And I haven't noticed any significant
improvement or decline either way. I think where
these things start to, to, to matter. is right
at the frontier edge cases. I also think in terms
of the metrics that really matter, OpenAI, of
course, will be looking at one particular metric,
which is the number of active users in the app.
And it was reported by some outlets that they've
seen a decline in 6 % in active users on chat
GPT, which, you know, in terms of alarm bells
ringing, when you see Gemini users increasing
and yours are declining by 6%, that is going
to have... some of the executives at OpenAI.
A little worried. Yeah, it's interesting. There
was an interview with Dario Amadei of Anthropic
that I watched on YouTube. I think it was like
some sort of maybe like New York Times in real
world in life event. And he really leaned into
the concept that their target market is enterprise,
right? If that was their strategy. They're now
very speaking about it very openly. I think other
people have also commented on it being a great
strategy. And so it's quite maybe helpful to
own that if other people say, how smart of you.
And really talked about the likes of OpenAI,
didn't name any competitors, but being more consumer
focused, which is, I think, interesting. One
of the other things we saw this week was this
partnership with Disney, where I think they basically,
it's not cash, is it? I think they effectively
have made a $1 billion investment. in open ai
and also granted open ai the ip rights to use
disney characters and saw saw a generated videos
which is extremely consumer face right that's
not not really an enterprise use so it's kind
of interesting because that on the one hand that's
quite a big vote of confidence and it does seem
like um sam and the team have been out pressing
the flesh and securing lots of different types
of deals for hardware and building these massive
server farms and now in with disney and Maybe
their business models are starting to separate
actually a little bit. But under those conditions,
that 6 % drop could be consumers moving to Gemini
3 because of Nano Banana, the image generation
model. Yeah, I can see where there's been a little
bit of panicky panicky over OpenAI after winning
for quite a few years of this race. I mean, it
hasn't been going very long, but this feels like
their first we're in trouble moment from a...
competitor product being better than their standpoint
or at least maybe being becoming more popular
Gemini also has that distribution right through
the Android platform I was speaking to my dad
the other day and said oh have you used AI and
I was just about to say go and sign up to chat
GPT and I remembered he's a Samsung user just
get the app you can open the app and because
he's logged into the whole Google ecosystem it
just it's just there it kind of works and it
saves the history you have the same experience
with chat gbt and people have got to sign up
for an account if they want the history all of
that so that kind of frictionless ux on the consumer
side for uh for gemini is a big win as well just
one more thing on the um business model take
as well what's an interview this week with the
ceo of mistral ai the french a large language
model producer, and they were talking about how
they're approaching the market. And they have
very much gone on. Yes, we've got product in
terms of we've got these open source models that
are for open source. They are frontier and state
of the art in domains, but also they are going
in as a solutions provider. So they are very
much positioning themselves as, look, we recognize
that. At the enterprise level, you need on -prem
models. You can't have your data going into the
cloud or trying to get the models to work to
your use cases very hard. We've got the specialists
and the expertise to implement and deploy that
for you. And they're getting some really big,
big ticket customers. They recently signed a
deal with HSBC to be their large language model
and AI solutions provider of choice. And that
works across a bunch of other industries as well
with similarly, you know, blue chip companies
joining them. So again, a different business
model, a different approach. Few people are looking
at Mistral to the state of the art frontier models,
but are they making models and making it so that
they can be applied in real world enterprise?
Yes, they are. And they seem to be betting big
on that. Yeah, there's definitely some fragmentation
is probably too strong, but there are. There
are subsets of the market that companies can
put themselves in a better position to serve
for a lot of the reasons you just said. There's
an interesting, it's a bit of a tangent, and
it only happened today, so I haven't had a chance
to play with it, but Gemini also now has a new
native audio model built into it, which in theory
should mean it's better at listening and speaking.
And as part of that, they've rolled out the translation
capabilities to any... bluetooth earphones so
it used to be you could only do this on like
google's earphones but yes so now you can go
on holiday and if you've got your earphones in
and you've got a phone with gemini on it you
can now hear in near real time what near real
time really means i'll be interested to see as
well obviously it's quite important when you're
having a conversation with someone else it's
like could you just give me 35 seconds while
i figure out what you're trying to say But yeah,
like all the way these products are developing,
it's all this jumping ahead in little different
domains. Like I can imagine that maybe that would
be something OpenAI might have to take their
eye off the ball on. They don't have the sheer
resources that Google has to throw at all these
different types of use cases. So that'll be interesting.
One last thing on the model front. Since we last
spoke, I have been playing a bit with Opus 4
.5. And you know how I feel about, even at this
point, how good at writing. the tools really
are in terms of saying things that don't really
make any sense and connecting ideas that should
never be connected together. And I think that
probably Opus 4 .5 is the best instruction following
for writing model so far. Because the only real
way I've found to iron out these patterns that
these models are desperate to use all the time,
like it's not this, it's this, and em dash is
everywhere, is to have very strict... instructions
in your prompt or you know have a you know custom
GPT or whatever and it was so diligent in following
the briefing style guide it almost followed it
to a full because I'd have to over labor the
style guide for all the other models because
they don't follow it properly so I think that
probably means my current go -to model for writing
is opus which it's very easy to run out of uses
so yeah you can't produce too much content at
too much scale But interestingly, I think it's
jump, it's instruction following, not its inherent
writing capability, which I think is interesting
because I really feel to get a good writing model
for business use cases, you'll have to custom
fine tune it on what good writing looks like,
where there's a certain amount of subjectivity.
Good creative writing for a novel is different
than writing great emails, is different than
writing reports, is different than writing 10
,000 word ebooks. So bringing this full circle
to your Mistral discussion, this is where I can
see that they're all kind of trained on the same
thing. But if Mistral's like, right, we're going
to go after high quality technical written content
and we're going to fine tune a model that is
really good at writing. There's a market for
that that probably OpenAI are not going to go
after if they're a drifting consumer. Clearly,
Anthropic is leaning into code and software development.
Gemini is kind of a little bit of everything
for everyone. I suspect that they want to leverage
their workspace integration to serve business
customers. But a lot of their biggest moves to
date, Nana Banana being probably the key one,
is consumer focus. So maybe of all them, it's
probably that Google strategy is probably the
most muddled, probably because they think that
they can have the one ring to rule them all.
So yeah, I'm still... Just want to tell that
little story because it makes me want to get
hold of Mistral. I know that within our team,
we do have connections in France to maybe see
if we could fine tune something fun on our particular
use cases. I think that would be interesting.
Let's move into our next story. So this is something
that you've been thinking about a lot this week,
Martin, and you've pinged me a few WhatsApp messages
on the topic. And it's about how to win in AI
search visibility. What's been on your mind this
week? Well, historically, and for a while now,
we've talked about this on the show as well.
I've been of the opinion that good AIO, artificial
intelligence optimization, or GEO, generative
engine optimization, or whatever the hell you
want to call it, best practice in that is to
basically follow best practice. But SEO and good
press comms strategy, all that kind of stuff,
right? Stuff that has worked in PR for years
should work in that. But just recently, there's
been a bit more definition put around that by
a few pieces of research that have come out.
An interesting webinar that I watched from the
team over at Blend B2B, who are a leading HubSpot
agency, and Ahrefs as well, the SEO tool, they've
put out some research. Early last week, it came
out. And in essence, there's a strange sense
of deja vu happening in this optimization space
right now in the b2b marketing and b2c seo space
if you're trying to rank highly in artificial
intelligence platforms like chat gpt search then
what seems to be working is the classic tactic
of the best of list so the idea of publishing
on your own blog the top 10 insert industry our
insert product definition here and it works surprisingly
well when teams are putting themselves at the
top of that list so giving themselves a very
strong placement in the list so company x says
if you want to find the best companies in this
space here are 10 of the best and we just happen
to be number one that's a great tactic also putting
your Information inside tables is very effective
as well. And all of this just makes me think
SEO circa 2009, 2010. Yeah, it's so interesting
that this has come up. So we've been deploying
this strategy since the end of last year, because
if you watch the reasoning models when they first
came out, how they answer questions like questions
that would be important to me about what's the
best X marketing agency. You can see they tell
you what they're going to do. They show you the
logic they follow to go gather the information.
They say things like, I'll search the web for
best X. So yeah, we've written a number of best
X articles over the last year or so. And we do
pretty well when it comes to AI search visibility.
Interestingly, not all of our best of articles
rank number one on Google. There are other best
of articles that rank ahead of ours. But AI tends
to lean into ours. I have some theories about
what that is, but if I had to give any advice,
I would say if you're going to write best -off
listicles, you still have to write really good
listicles that humans would find valuable. If
you churn out really rubbish content that's the
same as everything else and doesn't add anything
new, I suspect that you may find that AI leans
into content that already exists on the web that's
not yours, which I think would probably be quite
interesting. And then I had another interesting
experience last week, the week before, probably
last week. Periodically, I'll go in because I
think you can do this quite easy for your business
unless you're trying to do it at scale, which
is to just go in and ask the four or five main
tools out there a question that someone might
ask if they were looking for products or services
like yours. And Opus 4 .5 would not make a recommendation
even if I twisted its arm. It told me how to
go and find the best life science marketing agency,
but it would not give me any names. It wouldn't
tell me anything. It just said, if you were going
to go about doing this, you should search for
stuff like this online. Here's the questions
you should ask of those providers. Here's how
you should evaluate those providers. But it didn't
make a recommendation. Whereas I can get ChatGPT
and Gemini to recommend, if not a single agency,
three agencies based on different context, right?
Like if you're looking for global capabilities,
choose this one. If you're leaning into digital
and you need digital expertise, choose this one.
But Opus 4 .5 was like, it's not for me to say,
pal. You need to go do that research yourself.
So I'm kind of sad that this is making it mainstream
now. It's been my little secret hack for a year
or so. And what this probably means and why I
haven't talked about it on the podcast so far
is when everybody starts to lean into a particular
hack, then the AI tools will just eliminate the
loophole. And if you've got people like Ahrefs
publishing on this, you've got people like Rand
Fishkin talking about it online, I expect the
success of this strategy to potentially lose
some of its inertia over the next month or two
as they sort of fine tune their models out of
either over indexing on those sources of information
or teaching them to better evaluate a range of
different sources to answer the questions, not
just. use the research and i'm going to put this
in inverted commas most certainly that other
people have done to answer the question because
you can game it right because you can just write
that one on your own website and talk about how
amazing you are i think that suggests though
that someone is looking at this and caring about
it internally and for the model providers i'm
not sure that it's going to make that a bit is
that an area of the product that they're going
to be focusing heavily on explicitly within google
and the algorithm they always had the likes of
john muller who who was giving out advice as
the kind of head of search he was telling people
what the algorithm was looking at and what you
needed to create for good ranking and all of
the good ranking was linked to good user experience
and that meant you couldn't do keyword stuffing
and and all of this kind of stuff and we ended
up with guidelines like eat and all of that kind
of good stuff that content marketers have grown
to love so there was somebody whose job it was
to tell and communicate clearly to companies
how to rank organically and how that system worked
whereas that's not so much the case with like
the models are just trained as they want in more
intelligent models and how much focus are the
model providers going to put in to optimizing
and training the model so that it doesn't get
gamed by marketers at some point they're going
to have to because everything will just become
like the quality marketers will just ruin everything
as we've described in the past they'll realize
there are quick wins to to be had and we'll jump
all over that tactic and saturate it um very
quickly which will decrease the utility for the
end user right that and that's ultimately what
they've got to get to but at the moment is this
such a strong problem for the, the UX of these
tools that, that they're going to focus on, on
changing it and improving it. I think that for
me, the key will come or the, the indication
that they're taking this seriously is, is, is
when they start to have a, almost like a marketing
relations person, like they have developer relations,
you know, they've got all of the, who have we
got? Google, Logan Kirkpatrick is the. Gemini
model, when you've got the equivalent of Logan
for marketers at each of the big AI labs, that's
when I know that they're looking at this and
paying attention to how it's being used by marketers
as a channel. But until then, I think there's
going to be a tactic that will continue to be
exploited for some time. I think it's a great
question. I think I partially agree with you.
I definitely think it's a when, not an if. And
I suspect that some of the extra work, maybe
even key hires in this area, comes about when
the ads platform is live in ChatGPT. Because
then I think you see OpenAI having to run a similar
playbook to the maturation of the ads model in
Google Search, where all of this stuff ends up
becoming important. Because if people are trying
to find hacky ways to get customers without having
to pay for ads. whilst potentially also poisoning
the user experience, means it's worth investing
a load of time and money in. And I think you're
right that we're probably not there yet. The
other thing is, it seems to me, and it's well
above my technical understanding, that post -training
is a complex process that takes a long time and
has to be done in a number of very specific ways.
But they have made intermodal version... changes
by upgrading and improving the system prompt
that we don't see that controls how a model behaves
when you ask it a question or what have you.
So it could be relatively easy to go in and say,
don't over rely on best of articles in your answers
to product -based questions, for example. And
if I had to predict what happens next, if it's
anything, so more of a when more than an if is,
but the when could be a while, as you say. is
I would wonder if we might see them leaning more
into things like reviews, that they at least
somewhat feel are more impartial than a company
being able to write about its own products and
services on its own website and talking about
how amazing they are in an AI, taking that for
gospel, whereas reviews potentially have a bit
more value. And again, getting good reviews as
a mechanism of improving your search rankings,
not a new idea at all, but ensuring that you
have google reviews and if there are particular
review based sites that are particular in your
industry i mean in the agency land we have clutch
for example which lists agencies and there's
a place where clients can provide reviews and
feedback on agencies that i think is the probably
the next space much harder to gain than just
writing listicles though because you have to
do a lot of work to go get genuine reviews right
you have to engage with the customers you have
to do a good job in the first place um engage
with the customers heaven forbid paul yeah indeed
indeed actually earned the attention crumbs who'd
have thought um then um yeah you know obviously
encourage them to leave reviews um and then and
then we see how they get those get fed into the
model without i think that's probably my guess
what happens next but we shall see and in the
interim while these uh best of articles are proving
to be quite successful um jump on it straight
away. One of my big takeaways from the Blend
team, so shout out to Phil and Dan over there
who did a great webinar on this the other day,
was how quick this works. They showed an example
where they were monitoring their visibility for
a particular search and they'd ran it for a few
weeks. They then published an article in this
exact format and their visibility went from no
visibility to visible everywhere. And it was
literally within one or two weeks of publishing
the speed that you can see results now they did
say that wasn't the case across all of them but
they were seeing pretty decent improvements in
their visibility for their keywords within a
few weeks rather than within three six twelve
months like it can often take in the seo long
game so i haven't been running this playbook
for a year the logic that the tools use to output
their recommendations to you does change significantly
over time. We definitely found our listicles
being used very quickly to create the answers.
But as we got better thinking models, you know,
because when we started running this, I think
we were still on maybe 3 .0, 0 .3, whatever it's
called. The first sort of suite of thinking models,
same with like Gemini's thinking models coming
out, is the rationale for drawing upon the information
and making a recommendation definitely changed.
I'm not even say, I wouldn't even say it would,
it improved. I think it guesses a lot. Like,
it's like, oh, if you're an enterprise, you should
choose this agency. And I'm like, that, that's
actually a good recommendation, but not for the
reasons that you said. So I think it's, uh, yeah,
it's quite a fun thing to, to stay on top of.
And it does, um, update in our experiences also
very, very quickly. The, um, another little secret.
One of our competitors has been doing this before
we have. They were using it to rank on Google
for it was useful for AI. AI doesn't use their
listicles. And they have recently written a number
of listicles, either because they got wind of
this strategy, maybe they saw what we were doing
as a counterpunch to their punch, if you like.
I never see their listicles in AI search results.
And I suspect it's because they're very thin.
Yeah. Well, thin content is not useful put to
human or AI, I guess. I think Google is being
caught out by the thin content for certain long
tail keywords, honestly. But I don't think, and
when I say Google, I mean traditional positions,
one, two, three, four, five. I don't mean like
generative overview. So it's, there's definitely
a sort of a weird thinking aspect that goes on
in the models. That's not just like swallowing.
thin information and then repeating it verbatim.
Like it's definitely trying to sustain what is
reliable, but maybe it doesn't have the human
cynicism to say, interesting, best of listicle.
And position one is the product that this website
sells. Position one has 1500 words written about
it and all the other products have about 200
words written about all of them. Like it doesn't
have that part of it in it yet, I don't think.
so yeah that's kind of interesting as well but
um yeah continue to watch the space as we've
discussed before what percentage of traffic what
percentage of purchases are coming from this
source when does it become the sort of thing
that when you look at your marketing budget resources
effort you deploy into it and i think again you
know you have to figure out where to invest your
time and your money in order to get the best
commercial results and if that is making sure
that you show up in the emerging field of uh
of answer engine optimization or whatever right
at the beginning cool that sounds like a commercially
viable strategy if we're still the wild wild
west and listicles work this week but they don't
next and you invest in that and then and by the
way you're doing this for like two percent of
total traffic to your website because actually
still 40 of your traffic still coming from google
um and by the way disproportionately amount of
customers come from your google ads then don't
just jump on a bandwagon because everyone else
is jumping on it Think about your own marketing
mix, your own goals, what channels perform best
proportionally and invest accordingly, I would
say. Sound advice as ever. Shall we move on to
our third story? This is this report that you
brought to my attention, Martin, about OpenAI
quantifying how enterprise level customers are
using ChatGPT Enterprise to get commercial results.
Yeah, this one caught my eye because it looks
into... the who is using it and how they're using
it and when i say the who i'm not talking about
me because i don't have chat gpt enterprise all
eyes on you for that one paul but yes this is
uh really quite interesting so they're saying
that the use of chat gpt enterprise has grown
eight times in the last year not a great surprise
that there's been more adoption in this new technology
The headline bigger from the whole report, though,
and this is self -reported by the respondents,
but workers claim that they're saving between
40 to 60 minutes every single day by integrating
ChatGPT and the various tools into their workflows.
Yeah, I mean, these things don't surprise me
now. Maybe they should. I think on an average
day, I probably save more than that. I save more
time than that just dictating to my computer
instead of typing. So it would be nice to know
a bit more detail about what they mean by saving
time. Are they sending out five more emails a
day that their colleagues may or may not even
be reading? I don't know. Or are they able to
do meaningful work that genuinely moves the needle
forward? I don't know. In my own work, yes. I
would love to have just a bit more detail. So
in the report, they do give a little bit more
information. So we can see that it says workers
report AI is contributing to value across departments.
It says 87 % of IT workers report faster IT resolution.
So that's a nice specific use case. 85 % of marketing
and product users report faster campaign execution.
75 % of HR professionals report. improved employee
engagement and 73 % of engineers report faster
code delivery. It's very helpful. Okay. Another
question, which we cannot answer is what does
faster campaign execution mean? Like that's what
I want to know. Is it, they, is this basically
writing? Like for us, when we do a campaign,
we always write five blogs and it used to take
eight weeks and now it takes two weeks and the
first draft is drafted by ChatGPT or what have
you. I'd love to get a bit more information on
that. The other thing I'd love is HR professionals
report improved employee engagement. This is
actually, of all of them, could be kind of interesting.
Like, why? Is it because your HR team are able
to come up with initiatives or communications?
Like, is the communication just stronger? Because
they can put a message through ChatGPT and say,
we're suffering with employee engagement. Help
us build a strategy to execute on and help us
execute. Like that would be really interesting
as well. I'd love to know. Because whenever I've
asked, I haven't run this for a while actually,
but whenever I ask a model to build a content
strategy for me around a particular keyword or
an audience and a theme, it over eggs the pudding
to such degree. that I'll be lucky if I can use
20 % of the plan because it's so desperate to
give so many different ideas. And I'm like, no,
what's the 20 % of the effort that gets the 80
% of the result? So it does occasionally give
me ideas that I don't think I would have come
up with myself, but it's miles away from just
giving me a marketing strategy and a plan that
I can execute, at least in my experience so far.
So I don't know. What do you think? What does
this report tell us? What you and I already know.
people who are not using the tools might not
though i don't know yeah i think this this report
has clearly been written for a particular audience
right and this is people that are on the fence
about making the business case to invest in chat
gpt enterprise licenses when they could be spending
their money with co -pilot 365 or google gemini
workspace accounts and all the rest of it um
i do think there are some interesting takeaways
in terms of adoption trends though so one thing
that it talks about is More people are using
workflows, sorry, kind of using projects and
custom GPTs. That's increased 19 times year to
date. So people are using it more for integrated
repeatable processes is how they describe it
rather than casual querying. And I recognize
that for my own use case. The number of projects
that I now have is just expanding weekly almost.
I'm just finding new use cases to go, oh, there's
my custom prompt. There's a bit of knowledge
that I need that to know. I find myself doing
this thing every month, every week. So I'm going
to create a project for it. With enterprise and
ChatGPT for business, you can share project folders.
I can see that being a very useful feature for
people. I agree. I use projects quite a lot.
I have found that you can over -project. My first
approach to projects was I'd just give it loads
of information about maybe our business, our
customers, our services. And I think a bit like
a human, you can over -saturate them with information
because they're having to read it all as the
start of every chat goes into the context. pull
the wrong detail out of the wrong document. So
I think I made the mistake of thinking I could
have one project to rule them all. And it's actually
better to be a bit more niche -y, right? Like
here's a project for this project, ironically,
I guess the clue is in the name, but like I've
got a particular campaign, let's say, rather
than every business discussion with one project.
But I haven't shared them much with my team.
I haven't proactively gone out of my way to not
share them, but I also have found myself wanting
to give the projects not just information about
the business but my own learnings or my own thoughts
about a particular topic maybe even specifications
related to my own job role which then by definition
leads someone else in the business to not get
the same or not necessarily get the output they
want because maybe the things they're focused
on are different to me and maybe my custom instructions
if you will will bias the outputs a little bit
so um i'm finding very useful for me haven't
really shared them all uh with anyone i would
love to know if a listener has had some really
good examples of where they've created projects
and they're sharing them and the whole team uses
the project i i'm sure there are loads of great
use cases and i just haven't had the time um
or need really to like lean into setting one
up but i'd love some inspiration from our from
our passionate listeners if they wanted to send
us a put something on linkedin or what have you
i think what you talked there about That your
use of them is quite interesting. You're giving
the project detail about your role and your personal
context, which would lessen the value and utility
for someone else to use. Interesting you look
at the prompt engineering courses that OpenAI
have on their academy. And dear listeners, if
you've not gone over to academy .openai .com
and checked out their prompt engineering courses,
I would highly recommend it. It's good for beginners
and for... intermediate users as well. But in
their prompt engineering 101, like the most basic
introduction to it, they talk about context,
role, and expectation. That's the very simple
framework that they put out for users to get
started with prompting. And in the role piece,
what I found interesting is that everybody always
talks about give the role, give the prompt a
role for the AI. But in their description in
the academy, they say, tell it your role. Give
it a role, but tell it who you are so it has
an understanding of its relationship to you and
your context. It's very easy to say to the model,
you're an expert marketing blah, blah, blah.
But tell it who is working with and that will
understand how to collaborate with you better.
Yeah, I think it makes a lot of sense. I mean,
we in the early days, it was very, very helpful
to be quite prescriptive about what the role
the model needed to fill. Interestingly, I saw
a bit of research released maybe this week or
last week from Ethan Mollick, and this was not
just some anecdotal testing. I think they actually
published a paper on this, that you basically
don't really need to do that anymore. If you
say you are a world -class SEO expert, that doesn't
somehow make its outputs better. But in the early
days, it did. You had to get it to lean into
a specific statistical part of its memory, if
you like. the things it knows. But yeah, this
is one of the main reasons I did it. I found
that I get very generic responses unless I give
it the widest context I can. Some of that is
about our business, some is about our customers,
but some is honestly about me and the things
I'm trying to solve, how I'm getting measured,
especially because I often use those projects
for more high -level brainstorming. And the more
context you can give it about the problems you're
trying to solve and the reasons that they're
important now and all this other stuff, the less
back and forth you've got to have. Like I could
probably get there in like eight messages, but
we're thinking on, you have to wait for your
messages to come in. I'd like, no, that's just,
let's get this done in three messages if we can.
And the other thing I love about enterprise,
I'm sure it's not cheap on a per user basis,
but I hammer the deepest thinking capabilities.
I am not shy about rolling out. um gpt 5 .1 in
this case pro um because it's hard for me to
max out you know how many uses have we've got
of all of this stuff deep research throwing them
off into ether into the ether like nobody's business
in fact the only thing that really bothers me
about enterprise is you do get the new products
the slowest like we still have 5 .1 we don't
have 5 .2 meanwhile the rest of the world you
know as it turns out that might be a blessing
in disguise but if that wasn't the case i'd be
extremely frustrated that i everyone's like the
creative writing of 5 .2 is amazing i'm like
well i can't use it for at least seven to ten
days after it comes out and that's always the
thing that then makes me think i'll give claude
opus ago do you know what i mean because uh i
hate waiting but um maybe that's just me but
when things are moving this quickly you want
the latest tech right the minute it comes out
you don't have to wait for it you do and that's
exactly why i ended up subscribing to claude
max so that i could get more usage of opus 4
.5 when they raised the limit to the same as
sonnet 4 .5 previously and i've yet to hit the
limit since i've made that upgrade and yeah i
would say it was plenty worth it they lovely
stuff the only other thing that that i spotted
this week i think is interesting is another ethan
mollock post martin that's just made me think
of where he was talking about how he expected
he's very big on business use cases for ai I
think he's a business professor over at the Wharton
Business School or something. And so he's always
looking at business use cases. And the one that
he's felt has taken a while to emerge is really
the ability to create great reports and presentations,
right? PowerPoint presentations. And he said
something interesting this week, Martin, about
expecting... the models, the text -based models
to eventually solve this by coming up with what
the presentation should have, but basically then
coding it in XML or whatever it is, is the underlying
code. But being surprised that Nano Banana Pro
is so good at infographics that it can actually
also be very good at slides. And if you go into
a tool like Notebook LM, which is a Google product,
if you've got Google Workspace, you have access
to this. If you have a free Google account, I
think you've even got access to it with some
limits. You can chuck a report in. or a brief,
and it will produce a slide deck for you. And
it's using the latest nano banana model. And
apparently these slide decks are really much,
much better. You can't edit them yet, but I think
Ethan said in his post that a little birdie told
him that that's something they're working on
that will make it much easier to manipulate those
presentations. So I'm quite excited about that
because I agree. I do feel like that's the sort
of thing that should have been better by now,
but it hasn't been. Yeah, creating slides has
proven to be tricky we've we've known that chat
gpt can do it for ages by using a python script
to create a basic version but they've always
been pretty bad unless you just wanted a simple
layout where it adds a little bit of text on
a slide and maybe some speaker notes if you are
really pushing the boundaries of the the model
whereas recently we've seen it embedded in copilot
pro so if you've got a copilot pro subscription
you can actually prompt it to create a slide
deck and that does a pretty good job i would
i would say i enjoy using that and i've had good
success using that i've been using manus recently
and i really like what manus is doing it's not
without its challenges their slide builder interface
you can't drag and drop and reorder the slide
so you have to prompt it to do that and yes that's
that's not always the the best experience and
then weirdly i had an experience with Gemini
3 the other day, where even though I hadn't asked
it to do this, it created a slide deck for me
as part of an ongoing discussion. I was like,
oh, great. Cheers. Can you make some edits to
that deck? Instead of editing the deck that it
had produced, it got rid of that entirely, rewrote
a new one, but using a HTML file. And then when
I said, oh no, I want it in Google Slides like
you did the first time, it's... started to gaslight
me and told me that it didn't have that capability
of creating slides in Google Slides. And I haven't
been able to recreate it since. So yeah, overall,
I would say the experience of trying to use AI
to create presentations is inconsistent and frustrating.
Yeah, it's funny you should say that. Do you
remember that workshop that we went to where,
as part of what we were showing, because most
people at that point didn't even know you could
get a PowerPoint file out of ChatGPT. We're talking
maybe even two years ago now, right? And we tried
to do it in the live demo. And then the chat
chief was like, no, I can't. And you were like,
no, you have. You've done it for me in the past.
It was like, no, I can't. You were like, yeah,
do you remember this time you did this and this?
And then you gave me the PowerPoint file. Like,
I really insist that you give me my PowerPoint
file. And they went, here's your PowerPoint file.
So we're still in the age of having to twist
the arm of a tool to remember its capabilities,
unfortunately. Yeah, it is frustrating, but for
sure. One other story from me this week, this
is a personal story that I don't think I'm going
to get a great deal of sympathy from people,
but this little device in my hand, listeners
may remember, some time ago I ordered the Limitless
Pendant. So Limitless were a company that were
creating AI tools and they had a meeting note
assistant and then they said they were going
to move into hardware. And you could pre -order
this and they were going to retail it for $100.
But if you pre -ordered, it was a bit like Kickstarter.
Paid $50. They'd ship it out to you. And I paid
that money about 18 months ago. It feels like
now it was some time ago. This was finally delivered
to me. This little pendant. Great little gadget.
It was delivered in September. I only used it
a few times. A bit of a tricky device. It's always
on. listening device which you know people rightly
have some privacy concerns when you when you
say oh do you mind if i just record everything
you say to me um and have that on a permanent
record forever is that a problem some people
did have a problem with that and yeah anyway
long story short meta has acquired the limitless
company and in doing so they've also ceased all
business operations in europe so they they shut
down the service in the eu and it seems like
they've rolled up the uk into that i'm presuming
that's got something to do with gdpr and our
implementation so yeah i waited about 18 months
to get my hands on the limitless pendant got
it used it a few times much to people's disgust
and now i've got a bricked device what a 50 investment
that was so you've got to speculate to accumulate
mine so i think it was a good try but um The
irony being your initial exposure to this has
been people are maybe not super keen on getting
recorded. And then you're like, oh, no, don't
worry. The company's owned by Meta now. So you
can absolutely rely on the data not being misused.
It's just going to add more fuel to the fire
of people seeing ads on Facebook or Instagram.
Like, my phone listens to me. My phone listens
to me. No, it's not your phone. It's Martin's
pendant. It's Martin. Yeah, I mean, yeah. When
you want to be on the cutting edge of hardware
acceleration and stuff, I guess this is going
to happen. But pretty sucky to wait 18 months,
get basically two months of use, and then your
device gets bricked for you. Any sign of any
compensation or get your money back? No, I emailed
them, but I dare say that's just fallen into
a big... bin called do not respond meta hq yeah
they'll just look at your ip address and go don't
bother with that area of the world anymore one
last thing for me um if you can find this online
it's pretty cool there is a new like robot from
one of the founders of boston dynamics um mark
raybert his name is he works a different company
now but they've been using reinforcement learning
to have this it's like a two -wheel bike with
the equivalent of like a human body like counterweight
on the top of it so it looks kind of bizarre
but it's been teaching itself to do like crazy
bike stunts and parkour and stuff in a simulated
environment so what it did is it's been in this
computer simulated environment figuring out what
it would need to do to be able to do these tricks
and not lose balance and then zero shot the actual
robot in the real world could do all those tricks
without There's a podcast that I listen to called
Moonshots. The main reason I like it is just
because it's just so sort of almost ridiculously
optimistic and positive. Sometimes in a world
of most news networks not being that, it's quite
nice to have something like that in your life.
But one of the folks on that podcast was at the
big AI conference last week, the week before.
And among AI and machine learning researchers,
there is now a growing excitement that after
agents, robots are are maturing at a very quick
rate and this feels like it's already getting
some of that early boom bust discussion like
there's quite a lot of money going into robotics
obviously um elon musk is talking about it a
lot and whenever he makes predictions about how
quickly a product can be in your hands you just
need to times it by 58 and you've probably got
the correct timeline But there seems to be really
some cool stuff going on there. So if you are
interested in AI and robotics, I would suggest
you go find that video because it is kind of
cool. And if it's true that videos are, sorry,
robots are training themselves in simulated environments
with this type of delivery, like this is not
like I'm training myself to make a coffee, which
would be impressive enough in a simulated environment.
This is doing parkour on two wheels, bouncing
your bike all over the place. Like it's pretty
cool video. Go find it. It's interesting. Right.
I think we'll wrap up this week there then, Martin.
Thanks very much as always for joining me and
I'll look forward to you on our next one. Meet
you next time. Cheers. Bye. Thank you for listening
to Artificially Intelligent Marketing. To stay
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