When Is It Worth Learning AI? A Conversation with Ashley Faus

By Dan Sanchez · Episode published May 3, 2024

As AI continues to dominate conversations in marketing circles, there’s a critical tension developing between early adopters and more cautious enterprise players. While solopreneurs and small agencies have quickly embraced AI tools with minimal risk,…

This dynamic raises an important question: When is the right time for enterprise teams to adopt AI technologies?

The Enterprise AI Dilemma

For large organizations, AI adoption isn’t just about staying competitive—it’s about balancing innovation with very real risks. Enterprise companies must consider:

Legal liability – We’re already seeing companies face legal challenges when AI makes promises or uses copyrighted material
Regulatory compliance – Terms of service and data usage policies that most people don’t read can create compliance nightmares
System integrity – Introducing unstable technology can break critical business systems
Brand trust – Public-facing AI missteps can damage hard-earned consumer confidence

These concerns explain why many enterprise brands are taking a cautious approach. Just as Disney typically waits 8+ years before adopting new technologies, large organizations can’t afford to experiment with unproven tools when billions in revenue and shareholder value are at stake.

The Opportunity Cost Calculation

One of the most insightful frameworks for thinking about enterprise AI adoption involves opportunity cost. When deciding whether to invest time in AI tools, enterprise leaders should consider:

1. Does the payback period make sense?

If you spend ten hours learning and implementing an AI workflow that saves you one hour per week, you’ll break even after ten weeks. But if you only use that workflow once a month, it might take nearly a year to recoup your investment—by which time the technology may have changed entirely.

2. Is this a template-based task?

Any task that currently relies on templates is likely ripe for AI automation in the near future. If you’re doing repetitive work that follows a predictable pattern (like creating onboarding documents or formatting regular reports), AI can probably help—but the question is whether it’s worth building that automation now.

3. Where does human expertise add the most value?

For experts with 15+ years of experience, the value often lies in tacit knowledge that’s difficult to articulate in prompts. By the time they’ve written detailed enough instructions to get high-quality AI output, they could have completed the task themselves.

The Human Element in AI Adoption

Beyond the technology considerations, enterprise leaders must think carefully about how AI adoption affects their team dynamics:

Skills investment – If you’re coaching team members, does it make more sense to invest that time in helping them master AI tools or in developing their core expertise?
Career development – How does telling employees to “just use AI” impact their professional growth and sense of value?
Knowledge transfer – Is training AI a viable alternative to training your team, or does it create future vulnerabilities?

This human component is often overlooked in AI discussions but could be the most important consideration for enterprise adoption strategies.

Finding the Middle Path

The most effective approach for enterprises likely falls between immediate full adoption and complete avoidance. Here’s a balanced strategy:

Segment AI adoption by risk level

Some organizations are creating policies that distinguish between internal and external use cases. For example, they might use AI for internal brainstorming and planning while keeping all public-facing content fully human-created. This allows experimentation in lower-risk environments.

Focus on augmentation rather than replacement

The most successful enterprise AI implementations enhance human capabilities rather than replace them. Think of AI as a collaborative partner rather than a substitute worker.

Start with process-driven use cases

Look for repetitive workflows that follow clear patterns and have well-defined inputs and outputs. These tend to be the safest starting points for enterprise AI adoption.

The Long View on AI and Employment

Will AI eventually replace marketing jobs? History suggests a more nuanced outcome. When marketing automation platforms first emerged, many predicted they would eliminate marketing positions. Instead, they created entirely new job categories like “marketing automation specialists.”

Similarly, factory automation didn’t eliminate manufacturing jobs overnight—it transformed them. Workers were still needed to operate, maintain, and improve the automated systems.

This pattern will likely repeat with AI. While certain tasks will certainly be automated, new responsibilities will emerge around AI prompt engineering, output verification, and system oversight.

Three Questions for Enterprise Leaders

As you consider your organization’s AI adoption strategy, ask yourself:

What’s the true cost of waiting? Are competitors gaining a meaningful advantage, or is the technology still too immature for your specific use cases?
Where can you experiment safely? Identify low-risk areas where AI failures won’t impact customers or core business operations.
How can you prepare your team? Even if you’re not ready to implement AI widely, how can you build awareness and skills now?

The answers will vary widely based on your industry, regulatory environment, and organizational culture—there’s no one-size-fits-all approach to enterprise AI adoption.

The Path Forward

The tension between early adoption and cautious implementation isn’t going away anytime soon. AI capabilities are advancing rapidly, but organizational readiness evolves more slowly.

Perhaps the most balanced perspective is to recognize that AI is neither a magic bullet nor a passing fad. It’s a powerful tool with genuine potential and real limitations. The enterprises that thrive won’t be those that adopt AI first or last—they’ll be the ones that implement it most thoughtfully.

If you’re interested in learning more about implementing AI marketing strategies in your business at the right pace, I’d love to hear about your experiences and challenges.

[Music]

Ashley Foss I was going to say welcome

back to the show but this is the first

time I think you've been on this show

Even though I've I've interviewed you a

couple of times on various other shows

um but I'm looking forward to this

conversation because we've been going

back and forth now on LinkedIn about Ai

and when it's appropriate to adopt AI as

a team all right that's the conversation

we had I even pulled up your your last

last post where you brought up you

screenshotted a comment that i' on your

you had on one of my posts then you made

a post about it and I think like the

conversation we're simply essentially

having here and this is a conversation

less less than an interview is around

like when should teams adopt AI because

for Enterprise teams it's like if you

adopt it too early you can get burned on

it because the tech isn't quite ready

you lose trust you break systems um

obviously the small teams are doing it

because they have less to lose but

Enterprise teams you got a lot to lose I

mean you're talking about billions of

dollars revenue and trust and

shareholders and government regulations

and you mean shoot we're seeing some

Enterprise companies lose legal battles

right now because the chat prop bought

made promises and it's part of their org

so courts are saying you got to deliver

the product for

free well and the copyright issues too

this is the other thing that's

interesting you know the legal battles

are still playing out with like all the

stuff with the New York Times for

example so the legal landscape hasn't

caught up to the tech landscape and so

it's not even an issue of a chatbot made

promises it's like you don't know if you

put stuff into some of these

models like the underlying terms of

service who's reading that is your

standard marketing coordinator reading

that they're definitely not I don't know

if you saw Chris Pinn recently put

something out he's like do you

understand what you're signing away in

the terms of service and he's like

highlighting it and saying anybody

understand what they sign in the terms

of service no it's we're all signing our

baby and our life away terms of service

agreements with every single company we

work with right I mean I think they even

put out a documentary called like terms

terms or sign away your life or

something like that there's somebody did

a documentary on going deep onto that

and like how tech companies are

essentially like screwing us all over

even though a lot of it obviously won't

hold up in court but like the things

they put in there are so nuts like what

are what are we actually signing when we

do these people have done like exposes

on this but still they're there yeah

yeah it's crazy so yeah so all this to

say it is a timely conversation and I

think it's

interesting for us to have it with me

kind of on the Enterprise side and then

you on more of like the agency solar

preneur like you're building a really

cool product that can do some cool stuff

that's Ai and so I think I think that

Spectrum you know we were we were joking

before we started the record button of

like okay how do we make this spicy like

how spicy are we going to go and I think

acknowledging that there's a spectrum

and you know it's nuanced and it depends

and all that stuff but there's always

Nuance the other reality is again on the

Enterprise side you don't always have

time to have those nuanced

conversations with 500 or a thousand or

10,000 employees and so you end up

starting to get really roughly grained

policies and rules that if you actually

dig into them that's maybe not what

people meant to say but it's it's the

easiest way to not get in a legal battle

or not break all the systems right so I

I do think that it's interesting to

think about how do you how do you take

an incremental approach to this in a

safe way given that you might

potentially put something out there that

affects hundreds of thousands of

customers or tens of thousands of

employees cool so let's set some

precedence here like where where do you

feel personally like AI is going to be 5

10 years from now do you think it's

going to like kind of take over

everything or it's going to be in its

place I think it's going to be in its

place we saw this with marketing

automation platforms like I remember the

first time I saw maretto and I was like

this is how this is the future of

marketing right and everybody said that

HubSpot and maretto and the marketing

automation platforms were going to

completely take over it's going to

eliminate the marketing jobs and instead

what happened is it spawned an entirely

new class of jobs like a maretto

specialist or a HubSpot specialist right

a marketing automation platform

specialist so from my perspective AI is

going to be in its place is it going to

change how we do our jobs yes do we need

to wait to see how it's going to change

our jobs yes and no again when the legal

landscape kind of eventually catches up

yeah that will have some implications

but I think it's going to be in its

place I don't think that we're gon to

end up with no marketers and no writers

and no artists and no graphic design

designers like come on guys humans love

to work we love to create work for

ourselves like we have a lot of we've

had robots join yeah our everyday life

for years and yet we still work 40 to 60

hours a week we like to create for

ourselves like we still have people

working in factories even though

automation's been heavy in factories

since the early 80s right so there's

definitely a precedence there as far as

like Automation and all that kind of

stuff we need more people working the

robots and I guess some of the a lot of

the labor did go overseas but even over

there where they're still fairly

automated making these iPhones you still

have a factory full of hundred like

thousands and tens of thousands of

people working on iPhones right because

they just can't do everything exactly so

there's definitely a precedence I even

like even Disney as Innovative as Disney

is Disney will not like introduce new

tech into their ecosystem until it's

like at least eight years old they're

just like we can't risk bringing in

something new and improved and shiny

until it's at least been around for a

long time so it'll probably be while

before and they they're probably already

me been messing with AI for a long time

but you think they're going to introduce

large language models into stuff they do

heck no it's going to be a while before

Disney actually does because they can't

risk they can't risk something going

wrong exactly exactly so I get it

there's also on the other end a lot of

people are saying that like well if you

don't start now then there's going to be

a gap between you and the ones who do

right because there's this adoption

curve especially when it comes to like

the data you have and the data you're

compiling for it to train on the sooner

you get it training on and improving it

and it learning on how to do whatever

your heck you wanted to do sooner the

better it gets and those are the kind of

conversations people are having it's

like well then there's this like early

adoption thing where if you kind of go

and start moving it along even if it's

rough at first yeah but five years from

now you have a five-year Head Start by

the time it's actually mature or

whatever so but that's a risky game too

but then the question is is if it's

going to be so much better with and some

of this again this is why in one of my

posts I differentiated between the

adoption cycle and the hype cycle yeah a

lot of people are kind of mixing that

and primarily talking about the hype

cycle and you know does AI live up to

the hype well if AI will live up to the

hype in five years is the learning curve

actually going to be easier in five

years so there's some interesting things

too where you know you talk about

digital Natives and why they are so much

faster at picking up technology and it's

because they don't have any preconceived

notions about how it should work and so

if you think about like with the way

computers have evolved right like you

used to have to put a disc into a

computer and so that icon to save being

a dis the reason that that is the icon

is because it used to be like when they

first introduced it that was the way

that they could build the bridge between

physically saving on a disc and saving

it on your computer if you ask digital

natives about that they have no idea why

that icon is what it is right and now

they've grown up in a world where

everything just Auto saves you don't

have to hit the save button it just

Autos saves right so they never actually

had to undo the knowledge of saving to a

physical disc Translating that mentally

into an icon on a screen to a button

that you push right like they didn't

have to do any of that and so there's an

element of it

where I almost

wonder if it's almost like the the

digital natives thing of like AI where

my nieces and nephews are actually going

to be so much better at it like the

thought of me calling out to Siri or the

GW I don't want to say it because it's

going to be like hello can I help you no

you can't help me but

like I that's not fluent for me like we

don't have a bunch of smart home devices

like that and so but for my nieces and

nephews they already know to call out

for the lights or for the music or

whatever so it's I actually I actually

don't know if I totally buy into you're

gonna be five years behind if you don't

start now I'm gonna push back on that so

yeah I after working at a college a lot

of people had told me like oh gen Z so

Tech heavy and I worked with them I'm

like no they're not they know how to

consume it they know how to receive it

they know how to go and engage with it

but they know nothing about how to

actually use it for productivity sake

I'm like I had to train them on how to

actually like use social media not out

of not for personal self but like no

okay let me teach you how to do it for a

business now I will say if they were cre

if they were actually good at being a

Creator they did that that translated

perfectly even if it was like them being

fashion like Guru whatever on Twitter

and Instagram

that knowledge and they built a

following with that that knowledge did

translate so if they were a Creator

because being a Creator is almost like

being a marketer you have to reverse

engineer what the audience wants and

give it to them and cycles and all so

many marketing lessons but most of them

yes they know how to get around Facebook

and Instagram or Tik Tok or whatever the

heck the platform is better but only

from a consumer perspective not from a

work perspective so the interesting

thing that you're pointing out here

which is part of why I don't think AI is

going to replace all of us the

underlying skill is not actually the

tech the underlying skill is the human

connection or putting together an outfit

or yes eliciting an emotion via song or

via images or whatever it is right like

the thing that is actually transferable

is still the core human yes connection

and so I think that is fair that is a

fair push back because I've seen that as

well working with some early career

folks that sense of of you know calendar

management time management inbox

management slack management right like

the thing that is hard about that is not

actually pushing the buttons on slack or

like organizing your channels on slack

or making folders in your inbox the

thing that's hard is managing your

attention and

prioritizing all of the information

that's coming in from all of these

different places that's the actual scale

so that that's a fair that's a fair push

back I still I don't know and we we can

get into this right like I maybe I'm

just using AI the wrong way but I've

been trying to like all right I'm going

to I'm going to test it out right and

I've tried to get chat GPT to like

everybody keep saying oh I love it for

planning trips I love it for like

planning and so I keep trying to get it

to plan I think it's terrible at that

terrible it plans the worst date night

ever for me in my husband I you know

like already had a date night in my head

right and I I actually literally brought

it up to him and I was like hey I have

some ideas of like what we could do you

know whatever and so then I was like

this is a great opportunity for me to

test my chat GPT skills so I was like

okay chat GPT like you know and I put in

a little bit of info about like who we

are and what we like and what you know

and literally said like plan a date

night for today that includes dinner and

an activity and it was like here's

here's three different restaurants you

could try and I'm like I

that's not helpful like I'm not I know

restaurants I could pick a restaurant

right and it's like you don't I I don't

know I don't know what these people are

using it for that's good at planning a

trip or a date night but I think it's

terrible at that I'm like looking for a

conversation ahead in chat GPT recently

I'm like but I have so many it's hard to

find them all I'm like oh gosh I had one

where I threw it a curveball that I

hadn't I didn't know where it would go

yeah but I threw it a parenting question

as I'm good at thinking about marketing

stuff so but I'm like parenting it's

it's it's pretty T I'm like but I I had

a very specific problem that I needed a

a solution for and I could have gone to

Google but I'm like I don't think there

I don't think someone's someone might

have written an article about this but I

think chat GPT can do this

so I have two older kids 10-year-old and

a what 11 she's about to turn 12 and we

have these moments because we homeschool

where they just get overwhelmed and they

run into these growth or fix mindset

issues where they're like I can't do

this I don't like I don't get it and

it's like it's very fixed mindset like

clearly you can get it you just have to

keep working at it you need to choose a

growth mindset but I'm like it it's not

enough for me to tell them hey you have

a fixed mindset let's choose the growth

mindset that's not a bad place to start

but I was like okay chat GPT here's the

situation I can of break down like hey

I'm a parent I'm trying to teach my kids

how to have a better growth mindset

they're running into a fixed mindset

issue where they believe like they can't

do something what is some not something

I can just tell them or review with them

what can I can you give me a process I

can run through them that becomes a

go-to process every time they run into

this specific limiting belief this fixed

mindset and what it gave me this

five-step process I was like yeah this

is fantastic actually I I don't I don't

know where it got it from now maybe if I

did it in perplexity where it actually

CES all its sources like it would have

told me where it got the idea from but

it was it was fantastic and I need to

actually pull it out and print it off

and like start working into my parenting

Rhythm but uh I actually thought it was

pretty good I have seen people like post

videos about what you ran into with date

night kind of like hey let's see what

chatou did for us and then they like go

through a a day in their vacation

they're actually it's like this was

horrible advice like this was a horrible

day what we could have done was yeah I

have seen the vacation or date night

nightmares that J gbt has planned well

it's interesting because as you were

talking about the parenting thing I

thought the punchline was going to be

that like oh it just pulled out like

step one believe in yourself step two

say I believe in myself right like the

platitudes that's why I'm looking for it

if I could pull it

up and the interesting thing is I almost

want to play a game of like AI versus

Ashley because as you were talking about

that there's actually a really

interesting article that Harvard

Business Review wrote years ago at this

point called The Trouble with bright

girls and it actually talks about that

and you know you're probably actually

combating some of this by homeschooling

but the way that the education system is

set up tends to work very well in the

early years for girls compared to boys

because they have to sit down and they

have to be orderly and so they're

constantly praised for being so smart

versus boys since they tend to be more

unruly in high energy they're constantly

told if you would just sit down and

focus if you would just work harder if

you would just try and so the girls are

basically praised for something they're

inher you know quote unquote inherently

good at and the boys are constantly told

to work harder so that by the time they

get in to higher levels of math or

science you know hard things if the

girls can't do it or they it's hard then

they're like well I just can't because

I'm inherently not smart enough versus

the boys are like oh I just have to work

harder right so it's this super

interesting even the language

shift makes a huge difference right in

how you cultivate that growth mindset

versus a fixed mindset so it's

interesting because you know you got

this process and I'm like didn't it did

it just read that article and pull it

from that article like if so good job

chat dpd but like so know would that

have been the top Google search result

if you had Googled it right so there's

some really interesting things that I

think it the thing that it did though

that Google will never be able to do

until it incorporates Ai and it's it's

working on that is that it made it

contextual to the exact specifications I

had yeah right where Google articles

it's going to be kind of off a little

bit then you have to reverse engineer it

in your head to fit the context and

that's that's kind of exciting but how

does this Translate into like business

and Enterprise now like uh Dave Ramsey

which is a big company locally to me

they're embracing AI but they've like

made a policy it's like nothing public

facing will be AI generated because

we're a trust brand yeah and we have too

much at stake to be able to generate AI

stuff without it at least has to pass

through a person 100% Fred but like we

will not like everything will be human

created because we can't afford it um

but they're still playing with it on the

back end and they're using it for you

know like a boss needs to be come up

with a growth plan for something that an

employee gets stuck in so they're just

starting off with chat GPT to kind of

like brainstorm and then be like he it's

pretty good copy paste good yeah you

know so it's like they're using it for

stuff like that all the time I wonder is

are you doing stuff like that in your

job at atlassian yeah so we actually

have atlassian intelligence which runs

across our platform and so we have

access to that internally we've got our

own little playground where you know

it's a safe space basically where we can

put stuffff in we can connect it into

our internal systems so there's actually

some pretty funny things so we on one of

our teams you know slack just rolled out

their AI summaries or whatever and we

have a bunch of Taylor Swift fans on our

team and so somebody jokingly when um

tortured poet's department dropped and

nobody said anything and so she popped

in and it was she was like doing a

wellness check like Dan Ashley are you

okay like we've heard nothing about

tortured poet you know Department yet

and so we were all kind of laughing

we're like well yeah because they're off

listening to the album they're not on

here they haven't formulated their deep

thoughts about it yet and so then the

next day one of our teammates who had

been on vacation was like yeah I'm G to

test out the new AI slack summaries and

it pulled it up and it was like you know

the teammate expressed concern for

Ashley and Dan's well-being about Taylor

Swift the other you know this other

teammate also expressed concern and she

was just like this is the best thing

ever so there's still some limitations

like it's actually it is Handy we have

uh AI summaries at the top so like if

you write you know a big strategy plan

and then you want to generate a summary

for the top of like Executives or if

somebody stumbles on the page then it'll

you can adopt the AI and obviously you

can edit it but you can hit you know

summarize this page and it'll put at the

top we have stuff that's been rolled out

externally so it'll summarize like if

people there's a incident or support

tickets and so if you're the person

who's coming on for your shift for

support it'll do an AI summary of all of

the tickets so you don't have to go

through you know every single comment

that's come up you can get a sense of

where the queue is so we're definitely

incorporating it in that way I think the

hard part is when we think about and

again some of this is like where does

the human stop versus where does the

human start like we've also used it we

wanted to rename a newsletter and so you

know put in a little prompt and have it

just spit out like 30 different names

and of those names like two or three

were actually good and the rest you

throw away but you really only need one

good name you don't actually and so

there's part of it where I I personally

struggle with this because I'm like I

mean only one of these is even

usable right but that's the only you

only need one usable one and a human is

gonna start to tap out at maybe 15 chat

gbt you can just be like another one

another one another one another one yeah

but it it's ability to get better

doesn't it doesn't get better the more

you produce exactly right so so there's

some of that where it's

like I I dealt with this the other day

for myself I was like this is a perfect

example session titles for inbound right

I just ran a poll to say like help me

crowdsource my problem my topic and I

was already starting to think of titles

for these sessions and I was like this

is a perfect thing for chat GPT to help

me with for me to practice my skills so

I went to it and I said you know here's

who you are and and I told it I was like

you're copywriter at Nike and you used

to work at Apple and Ogie so like you're

a boss at this and you know here's the

audience and I said and you've already

come up with these three taglines you

know make the others and so I gave it

what I put in and then obviously hit do

it again and I gave it I was like that

that's interesting I noticed that you

keep asking questions can you restate

these as declarative sentences instead

and it was like yep and in some cases it

tweaked it and in other cases it didn't

right and I I asked it again I was like

these are good but why don't we focus on

alliteration why don't we focus on

rhyming why don't we and so I was

tweaking it and so yes the quality of

the prompts does matter and the quality

of the input matters

but it's just it's just hard because

like I'm actually really good at this

stuff and I have the full context of

exactly what the topic is and by the

time I write out the full context that's

in my head I've already used that

context to come up with five really good

titles already and so like it's not tot

on one hand it's not very

fair that I maybe write this 2,000w page

and AI just has to write two sentences

and it's like well if the two sentences

are bad maybe your thousand words are

bad but at the same time by the time I

have to give it a thousand words to make

it better like I could have just taken a

walk around the block and done it myself

like it's it's a there's still some of

that hard nuance and same thing even the

the support tickets right like how often

do you still have to potentially reach

out to a teammate and say hey do you

have five minutes to just give me a

quick download on this writing is hard

struggle with writing naming is hard

naming is hard like so I think there's

there's some of that too

where if you give it the wrong problem

the assumption that oh well this is hard

for humans but it's easy for

AI is not there's a reason certain

things are hard for humans like the

reason date night is so hard to plan is

because humans are finicky and I

normally like Mexican food but tonight I

want you know Chinese food and it gave

me a Mexican restaurant so it does well

it doesn't know that you want Chinese

food tonight like that's not fair you

know and it's the same thing in

business in some cases like another use

case that we're doing is you know and

again you're going to do it for this

episode you're going to put it through

whatever the AI tool is maybe the One

You're Building it's going to generate

20 clips of whatever we talked about

you're going to pick the top five you're

going to send me three you're going to

keep two back for yourself I'm going to

listen to those three Clips pick one to

promote this episode like that's how

this is going to go what that means is

that 15 of the clips that it generates

are useless is that because we didn't

have anything useful to say or is it

because it couldn't pick up right like

or is it because it couldn't pick up

where the best bits are It's a

combination of both because I do a lot

of those I mean I'm doing I'm generating

Clips multiple times a week for

different clients and I'm having to go

through and pick them out and sometimes

some some episodes because of the person

being interviewed has a higher clipit

and it's very interesting because you

can usually tell just by listening to

them you're like oh this person knows

what they're talking about they're G to

get more Clips because they don't

Meander through they're more concise and

give concise points so you can tell like

how they communicate and what they're

saying is just more clippable and it

would have been the same for a human

whether an AI did it or human did it

they still would have had a high higher

clip rate than normal like a human would

o struggled to get good Clips out of an

out of a someone who just kind of

meandered through and didn't make solid

points wasn't concise didn't have

anything new to say yeah so I have

noticed that but it is getting better at

finding good Clips I don't know its

ability to find higher Clips is is

better and I do notice how they rank

stack them now from like most likely to

be good to least likely to be good

that's generally right yeah yeah well

trting system I'm like I don't know how

it knows which ones are going to be

better but it's I I get less Clips at

the bottom of the pile that's for sure

yeah yeah well and it's so one thing

that's

interesting that we're seeing that is a

combination of obviously the source

material that you put in and the quality

of what you get out but sometimes it's

off by just like 10 seconds yeah that's

right that's pretty frequent that I'm

pushing it 10 seconds one way or the

other yeah and it's like it's it's

almost that sense of I'm GNA again this

conversation for example I already know

that I this is not the smartest

conversation I've had precisely because

I'm so early in my journey on it

compared to conversations we've had in

the past about thought leadership or

about content strategy where I have good

onliners right so if we were to say you

know we'll go back to something that I'm

more familiar with where I would say the

funnel is dead use a playground instead

okay what do you mean by that Ashley

what are the top three things that you

need to think about well you have to

address content depths you have to

address intent based content and you

have to use explicit ctas it's like it

would clip it at just the funnel is dead

what should you do No I gave you the

oneliner a the funnel is dead use a

playground instead and I gave you

content depths intent based content and

explicit ctas why why did you cut it off

at just the first part like

clearly the valuable piece is the second

part and so we've seen that a few times

where or or it'll say you know we're

doing it for products right and it's

like we're going to announce a new

feature and so we put it out there and

it's like and now announcing and then it

like cuts the clip there and I'm like

what are you doing like yeah clearly we

need whatever the announcement is if

it's jira dark mode what tool are you

using so I don't want to be rude we're

we're we're we're working on a couple of

tools I'll I'll DM you separately and I

know of course every this is going to be

the clip where you're gonna be like here

which tools Ashley says she's using I

I'm gonna I'm gonna I'm gonna stand

behind the uh the atlassian policy of

not naming tools that have not been

fully vetted yet again when that's fair

when a large brand like us says we're

using something it's it gets a little

Twitchy so we're still experimenting um

we have seen quality a variety of levels

with a number of tools and now we could

solve that we could just go manually

clip it and just extend it and so

basically the way we're using it is give

me 10 Clips give me a sense for

what's interesting and I can tell within

the first few seconds of like what are

you even talking about no one cares like

discard this or oh this is super

interesting let me listen to the end and

then when they clip if they cut it short

then I can just be like okay I know

exactly where to go and just say extend

it yeah it's this could be an episode

about Clips really fast but I'm gonna

try to steer it back to the Enterprise

because I'm like there's so much I could

say about Clips but yeah yeah we we'll

talk afterwards you'll give me your best

practices and then you'll be some I've

learned about Clips but you talked a lot

about on LinkedIn like the opportunity

cost of learning AI to maximize what you

could be getting out of it now versus

what you could be getting out of what's

currently available right now and

working well you know what's funny about

that is I I feel like nothing's really

working well right now like there's not

like a killer like oh LinkedIn ads are

killing it it's when I go to every

single channel it's like everything's

expensive everything takes a long time

anything that's fast is B is not that

great I feel right now there's no killer

and the economy is kind of like H

struggle I don't mean anybody's being

like Oh yeah we're freaking killing it

right now yeah which right now I'm like

well might as well dig into Ai and make

what what I'm currently doing more

efficient as kind of how I'm seeing

leveraging AI to do do better faster

yeah how do you see the opportunity cost

yeah so like there's the triangle of

good fast or cheap pick two right if

it's G to be good and fast it's going to

be it's not going to be cheap if it's

cheap and fast it's not going to be good

if it's good and cheap it's not going to

be fast right like those things the

point I was actually trying to make was

less about strategies and tactics and

more about

skills so you know I have 15 years of

experience in my craft I'm very good at

what I do and because of that trying to

get someone else to do it is really hard

whether that's a human or a robot and I

know we've had this conversation a

little bit too you're like yeah AI is

kind of like the the interns you have to

break it down and you have to give them

step by step you have to do a Playbook I

actually really love Lov again I know I

keep going back to Chris Penn but like

he's been doing he's been in this world

for like 10 years you know it's like you

were what is it it's like you merely

adopted the darkness and I was born into

it I feel like that's like Chris pin

like you're the you're the adopter and

he's the I was born into it kind of guy

but he was talking about templates and

he said anything that you do with a

template today is an excellent use case

for AI tomorrow and you know where

tomorrow is very near term do a lot of

things with templates because at the the

point where I am the person doing it you

need you need me it can't actually be

done by a template by the time it gets

to me because yeah otherwise you would

have done it already and so I think

that's that's what I'm talking about

with the opportunity cost the work that

I'm doing to me still requires a human

and if I'm the human required to do it

it probably means you need someone who's

got 15 or more years of experience and

like that's a different level of work

and so for me to figure out how to

distill what I just know because I've

been doing this for so long into a set

of written instructions for someone else

to do what I do like that takes a lot of

time and then the question is why would

I invest that time in the robot instead

of in the humans on my team that I'm

supposed to be inv in right like there's

there's also there there's there's some

feeling aspects to it too where I I

actually had a conversation with someone

else who was an early career person and

they were talking to me about some

struggles um with somebody who was more

senior on their team who was supposed to

be giving them feedback and they kept

asking for for feedback and the senior

person said well why don't you just try

it use it with chat GPT I don't have

time just put it into chat GPT and they

were like so

offended and I said well maybe the

delivery was

not right but is it possible that you

could have done that task

without the the more senior person you

were trying to do it with right and and

I think it doesn't feel good if your

manager tells you basically I don't have

time for you I'm going to go train a

robot instead like how does that make

you feel from a career growth standpoint

or a or a job stability standpoint it

doesn't feel great and then now I at

some point I'm still going to have to

teach you something so am I going to

teach you the AI and the answer might be

yes but as we talked about kind of at

the beginning of the conversation with

that learning curve does it make sense

for me who's a bit blind to lead you

who's a bit blind instead of giving you

who doesn't have as differentiated of a

skill set yet because you don't have as

much experience why don't you be the one

to learn this and spread it to the

organization right it's a good growth

opportunity it's a good visibility

opportunity it sets you up well from a

longterm perspective and it minimizes

the opportunity cost of having me do it

when I already have like my my old

school skills are actually still better

than the new school skills right so

there's there's it's a really it's not a

straightforward conversation especially

when you're talking about humans on your

team and what what precedent does that

set about where I invest my time if I

only invested in systems and process and

tools and I don't invest in the humans I

don't know it seems pretty Stark when

you compare it to like giving it to AI

or giving it to people when it could

just be a spectrum a little bit I mean

obviously you don't compare AI to people

it's kind of like oh I'm only giving you

80% today I'm giving 20% to the AI it's

just part of like kind of like you spend

time in Salesforce or HubSpot up a

dashboard so that you can get more out

of it the thing I'd like to know from

you is are there is there anything you

do that's just pretty repetitive I mean

and you walk through the same process

every time you deal with it those are

the opportunities where I find AI can

help usually it's in one of those yeah

like I found that naming naming is a

kind of a weird thing because it is

something you have to do there is a

process to it some people have different

processes but I finally found a book

that I loved from Alexandra Watkins and

she had a fairly particular process that

was very straightforward using

essentially words defining a name and

then finding idioms that those words

were in and then finding the or no it's

like word rhymes with that word idioms

with that rhyme in it and then swapping

back out the original word do that a lot

for the thing you're trying to name

that's one of our approaches and that's

um that's how I came up with like mik

club for one of the podcasts we launch

you know Fight Club you know oh that's

kind of a different feel you know it

takes on a little bit of that feel from

Fight Club but now it's mik Club yeah

right so that's her naming process Chad

GPT is really good at running that

process and it'll get better as it gets

more advanced and GPT 5 comes out and

all that kind of stuff yeah but it's

fully capable shoot I mean an algorithm

can almost run that process it's so it's

so simple it's interesting yeah yeah the

stuff that I that I find to be

repetitive for example but but it's not

exactly that where you could say like

you just need to put in the one like you

have to have the original idea of Fight

Club for example and then you put that

in you you know you say okay here's

you're G to run her process and here it

is right but onboarding documents

especially whenever I'm hiring in

clusters where if I like if I'm hiring

two or three people within a quarter of

each other the onboarding documents are

pretty similar and it's you would think

like oh just copy and paste the previous

onboarding Doc and it's fine right but a

perfect example when I built the apmm

program for atlassian so it was a cohort

of four so I had a joint onboarding plan

for all of them that was you know here's

the alassian business here's some of the

key teams markets Etc and then I had

individual plans for each of them and

the most annoying part of those plans

was all four of them were supposed to

book a one-on-one with each other and so

basically like swapping out the head

shots and the names of the people to be

like Dan Ashley's your teammate Ashley

Dan's your teammate right like I wanted

it to feel personalized to you so I

didn't want you to be

a teammate on there and like and again

this was a couple years ago so I didn't

have access to AI but

like that type of thing of being able to

say or say like if I could put in this

level of person should have one-on ones

with this level of person from these

teams so you know you wouldn't have a VP

meet with every new grad right but you

might have all the new grads meet each

other trying to like map those out for

every single person it's like if I could

just tell

the AI like make this on like tweak this

onboarding plan you know they're still

going to have a c you know nine out of

10 of the people I want them to meet are

the same or they need to meet someone

from every single team match them with

the appropriate level of person given

their level like that would be something

that would be so helpful and then the

other thing which we do have this of

like suggestions

where it'll say at the bottom of a

Confluence page these PE these pages are

frequently read together or like people

who read this page often read this other

page so for an onboarding document that

would be super helpful if it could like

look back at what I've been working on

and see okay all the people who are on

my team have been working on these 10

documents and then basically do a little

write up of like recent projects that

you should know about and then it can

pull in all of those versus me having to

be like all right which of these things

are useful for a new person coming in

because you know I don't want to pull

something from two years ago that's not

helpful like I want to pull the last

quarter of work to kind of get them up

to speed that would be a perfect example

where I think there's

probably ways to do most of this but

again for me to find probably if you're

using co-pilot or something for

Microsoft you guys use

Microsoft we I think we do have I mean

you're kind of big enough that I'm like

you might have your own internal systems

for yeah we have some internal your own

spreadsheet systems and all that stuff

this the thing right like that's the