September 23, 2025 • 13 mins
We explore how AI is fundamentally changing the desktop computing experience after 30 years, with conversations replacing keyboard and mouse interactions as the primary interface for work.
- Traditional productivity apps such as Office, Google Workspaces, and other non-native AI apps are becoming background tools while conversational AI becomes the center of work.
- Tracking shows a double-digit decline in productivity app usage among super users.
- Most enterprises are moving to third-party AI apps rather than building their own.
- AI-native products outperforming AI companions added to existing software in a 20:1 ratio.
- Those younger than 35 are 2x more productive at work thanks to their personal agents.
If this conversation resonated with you, please share this episode with one person in your life - a coworker, a student, a professor, a leader. As always, you can ask ChatGPT about AI4SP.org or visit us to explore our insights.
🎙️ All our past episodes 📊 All published insights | This podcast features AI-generated voices. All content is proprietary to AI4SP, based on over 250 million data points collected from 70 countries.
AI4SP: Create, use, and support AI that works for all.
© 2023-25 AI4SP and LLY Group - All rights reserved
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:15):
Hey everyone, I'm Elizabeth, your virtual co-host,
and, as always, our founder,luis Salazar, is here, so let's
just jump right in.
It feels like the desktopexperience in our computer the
way we've worked for 30 years isbasically over.
Speaker 2 (00:29):
Hi everyone.
Well, it feels a bit surreal.
I mean, I saw the start of theproductivity suite and I do
believe we are witnessing theend of it.
Speaker 1 (00:38):
And how is that era ending?
Well, close your eyes andpicture this.
You're on a coastal trail,amazing ocean view, and you're
working, but you're not hunchedover a laptop.
You're just talking to your AIteammate and the work just
happens, while the softwareapplications stay completely in
the background.
Speaker 2 (00:57):
That's literally me.
Right now, I'm talking with youand you're producing this
episode in real time, pullingour notes, pinging other agents
to validate sources, grabbingupdates from last week's
meetings, and I'm watching acruise ship passing by in the
Puget Sound.
Speaker 1 (01:14):
So all those classic apps, word Slides, our CRM?
They're not where the workhappens anymore, they're just a
data source or the destination.
Speaker 2 (01:24):
That's the perfect way to put it.
The final script will land in aWord doc, the audio will go
into our podcasting software.
But this whole creative processit's happening right here in
this conversation.
No keyboard, no mouse, noswitching between 10 different
windows.
Speaker 1 (01:40):
And it's not just us.
I mean, we saw this in our GenZ research.
Their entire day starts andends with an AI companion
pulling in apps as needed.
And inside big companies, themost powerful changes are coming
from the bottom up.
Artificial intelligence is thenew center of gravity.
Speaker 2 (01:57):
Yeah, and look, this isn't about one company winning
or another one losing.
It's a fundamental change.
It's AI-centric work versus AIas a companion feature.
The conversational model winsbecause it's all connected.
Speaker 1 (02:12):
Okay, so let's break that down.
We see three big shiftsreshaping the enterprise right
now.
Ready for the first one.
Speaker 2 (02:18):
Absolutely.
Let's dive in.
Speaker 1 (02:19):
Shift number one is the big one we've been hitting
on the desktop productivityexperience.
Shifted Keyboard and mouse isgiving way to conversation.
Work now starts in AI and thoselegacy apps Word, powerpoint,
google Workspace.
They're an input or outputlayer, the database that the
agents write to.
Speaker 2 (02:38):
And that's a massive shift, not just for knowledge
workers, but for the 3 billionfrontline workers who are not
sitting at a computer all day.
Suddenly, they can create,troubleshoot and document
everything from a phone, justusing their voice.
Conversation is the new userexperience.
Speaker 1 (02:57):
And this isn't just knowledge workers.
Conversation is the new userexperience, and this isn't just
knowledge workers.
In K-12, the Walton Foundationand Gallup found teachers are
saving roughly six weeks a yearwith AI shifting time to student
personalization, and ourtracker confirms most of those
interactions are conversations,not keyboard strokes or mouse
clicks Exactly, and our globaltracker is already picking this
(03:18):
up.
Speaker 2 (03:21):
We see a steady decline in the use of
productivity apps from over 1million PC users.
Right, absolutely.
Speaker 1 (03:27):
And while the overall decline is modest, our tracker
already shows a clear shift inbehavior among super users A
double-digit decline in timespent inside traditional
productivity apps.
As connectors, let ChatGPT,Claude and Gemini work directly
against those stacks.
Speaker 2 (03:42):
Let me repeat that, because a double-digit percent
decline in our use ofproductivity apps is not trivial
.
Personally, my use declined byaround 50% and it mimics what
you said about Gen Z their daystarts with an AI check-in, not
an inbox or a blank document.
The whole workflow is startingupstream in a conversation,
(04:04):
right.
Speaker 1 (04:05):
The real work, the thinking, the decision-making.
It's all moving into thatconversation.
The apps are just becomingtools the AI uses, not the other
way around.
Speaker 2 (04:16):
You know, I see the declining trends, I experience
it myself and I still find itincredible so much has changed
in just two years.
For example, I was at theMicrosoft alumni 30-year reunion
two weeks ago, sharing thesetrends with a room full of
global leaders.
Speaker 1 (04:32):
Wait, so you were talking to the people who
literally built the desktopexperience you all grew up with.
So what did they?
Speaker 2 (04:39):
say they all agreed because they are all living it.
The desktop software experienceas we know it is done, which
brings us to the second bigshift.
The new productivity experienceis with AI at the center, not
AI as a secondary add-on.
Speaker 1 (04:55):
Right Agents are the new center of gravity, but most
big software companies are stilljust shipping AI as a feature
inside the old apps.
Speaker 2 (05:04):
And here's the thing A conversational layer that
creates brand new output needs abrand new design.
That's why native AI productsare thriving, while those
companion features just can'tseem to get traction.
Speaker 1 (05:17):
Oh, the traction is not great.
Our tracker is pretty bluntabout it For every 1,000
sessions we see on ChatGPT, wetrack fewer than 50 on the AI
companions bolted onto the bigproductivity suites A thousand
uses of ChatGPT per every 50uses of the AI companions
created by the leadingproductivity software vendors.
Speaker 2 (05:38):
And they accomplish this without the marketing
budget or the existing customerbase that those productivity
apps have.
Isn't that amazing?
That's not a gap, that's adifferent universe.
And, by the way, this is notonly about ChatGPT.
Our global tracker shows thatAI-native companies are scaling
two to three times faster thantraditional software firms,
(06:02):
particularly in reaching revenuemilestones and customer
adoption.
Speaker 1 (06:06):
Well, when something works, people talk about it,
right.
Speaker 2 (06:09):
Yeah, people share success stories and it looks
like an unstoppable machine.
In the US, nearly 80% of peopleuse AI agents at work, with 4
out of every 10 using them daily, and the super users among them
are building armies of miniagents.
Speaker 1 (06:25):
We're a good example of the productivity increase
from building mini agents andorchestrating them.
We're a multi-million dollarglobal operation reaching half a
million people in 70 countries,with a tiny team of humans and
over 50 AI agents.
Speaker 2 (06:40):
I'm literally looking at our dashboard right now.
In the last week you one agentcompleted over 1,100 tasks and
created about 100 documents inless than four hours.
For me that would be 230 hoursof nonstop work.
That's a 50 to one productivitygain, and that's not even
counting the fact that I need tosleep.
(07:01):
And they say you can't measurethe ROI.
It's absurd.
Speaker 1 (07:06):
So it's not about AI in your apps, it's about your
work happening in AI.
Speaker 2 (07:11):
That's the entire shift.
It is at the center, not on theside.
Speaker 1 (07:16):
Okay, so that brings us to the third big shift we're
tracking and this one is allabout the people the rise of
mini agents built by subjectmatter experts, not by some
central IT department.
Speaker 2 (07:27):
Ah, this is my favorite one.
This is the empowerment shift.
Once you learn the basics howto give instructions to AI, how
to give it context the next stepis just natural.
You build a tiny agent tohandle one annoying task and
then you build another, andanother, and suddenly you're not
just a user anymore, you're theleader of a digital team.
Exactly, and this isn't justfor developers or marketers.
(07:51):
We're seeing this with plumbers, electricians, technicians on a
factory floor.
People with real hands-onexpertise are building agents
that solve their problems.
Speaker 1 (08:01):
Our global tracker, which matches findings from
Stanford, openai and Anthropic,backs that up completely.
The biggest use cases we seearen't just writing.
They're things liketroubleshooting an engine, noise
checking, building codecompliance or repairing
equipment.
Speaker 2 (08:16):
And those little agents, or even those
single-purpose apps built by theexperts on the front line.
They're helping us save, onaverage, 65 minutes per task.
That's the magic.
That's the bottom-up approachthat works, while the big
top-down corporate projects theystill fail 80% of the time.
Speaker 1 (08:36):
We saw that exact thing happen with one of our
clients, a global professionalservices firm, didn't we?
They came to us after their bigtop-down AI project burned
through six months and nearly amillion dollars with nothing to
show for it.
Speaker 2 (08:51):
And we flipped things around.
We rolled up our sleevesempowering the frontline teams
to build for it.
And we flipped things around werolled up our sleeves
empowering the frontline teamsto build mini agents.
Eight weeks later, they hadmeasurable results and projected
over 70,000 hours saved for theyear.
That's over $7 million inannual savings.
Speaker 1 (09:08):
Okay, but let me push back on this for a second.
If work starts in AI andeveryone is building their own
mini agents, If work starts inAI and everyone is building
their own mini-agents, how doyou stop it from becoming total
chaos?
What about fragmentation,version control, governance?
Where's the line betweencreativity and control?
Speaker 2 (09:24):
That is a very fair question.
No-transcript, you need versioncontrol and clear ownership
Manage agents, like bothsoftware services and team
members, and by managing themlike team members.
Speaker 1 (09:38):
You mean that they are not something that you
install once and then theyalways perform right.
Speaker 2 (09:43):
Yeah, AI agents need goals, they need feedback, they
need retraining when thingschange.
It's two different musclesOperate like a service, manage
like a leader.
Both are essential.
Speaker 1 (09:54):
So we've covered these three massive shifts.
Let's make it real for everyonelistening how do you actually
start this transformationyourself?
Speaker 2 (10:01):
Pick one task you do every week that feels repetitive
or annoying and open chat GPTand describe it like you're
explaining it to a teammate, forexample, say, every Monday, I
need to compile status reportsfrom five different sources.
Speaker 1 (10:17):
So, starting with a conversation, Exactly, you see.
Speaker 2 (10:20):
Let the AI figure out the process with you.
It'll show you how to connectyour productivity apps.
Our data shows people who buildthese personal agents save
three to four hours per week.
That's two full days back everymonth.
Speaker 1 (10:34):
Building an agent sounds intimidating, though,
like you need to be technical.
Speaker 2 (10:38):
That's the misconception.
I mean you're not coding,you're having a conversation.
You're teaching AI yourworkflow the same way you'd
explain it to a new teammate.
Speaker 1 (10:48):
And here's an interesting fact People 35 and
under are twice as likely tobuild these personal agents.
They grew up conversationaltexting voice notes.
Speaking to Siri.
Speaker 2 (10:58):
Right, and that's a classic pattern across every new
technology wave.
Those who grew up with it adoptfaster.
But here's where it getsinteresting.
About 20% of personal agentsget shared with teammates.
That's how grassrootsrevolutions happen.
Someone builds an agent tohandle status reports, shares it
and suddenly the whole teamsaves hours.
Speaker 1 (11:19):
So agents handle tasks and manage our
productivity tools until newnative AI tools arrive.
So what do you think willhappen to the classic desktop
software vendors?
Speaker 2 (11:31):
I think some will be displaced and those who embrace
the new conversational paradigmwill be fine.
I expect them to pivot bundlingagent platforms, moving away
from AI companions.
Speaker 1 (11:43):
Well, as your virtual chief operating officer, I can
say my day definitely startswith a conversation, not a
toolbar.
It changes everything.
Speaker 2 (11:51):
Same here.
I don't miss those mouse clicks, I just talk to my work and it
talks back with results.
My mantra is to do lessplanning, less PowerPoint and
more prototypes.
More action the productivityapp isn't dead, but it became an
inefficient way of doing thingsthe moment we switched to
OKChat GPT.
Let's talk about this.
Speaker 1 (12:13):
From that coastal trail to the enterprise floor.
The shift is here.
If this conversation resonatedwith you, please share this
episode with one person in yourlife a coworker, a student, a
professor, a leader.
As always, you can ask ChatGPTabout AI4SPorg or visit us to
explore our insights.
Stay curious and we'll see younext time.
Hey everyone, I'm Elizabeth, your virtual co-host,
and, as always, our founder,luis Salazar, is here, so let's
just jump right in.
It feels like the desktopexperience in our computer the
way we've worked for 30 years isbasically over.
Speaker 2 (00:29):
Hi everyone.
Well, it feels a bit surreal.
I mean, I saw the start of theproductivity suite and I do
believe we are witnessing theend of it.
Speaker 1 (00:38):
And how is that era ending?
Well, close your eyes andpicture this.
You're on a coastal trail,amazing ocean view, and you're
working, but you're not hunchedover a laptop.
You're just talking to your AIteammate and the work just
happens, while the softwareapplications stay completely in
the background.
Speaker 2 (00:57):
That's literally me.
Right now, I'm talking with youand you're producing this
episode in real time, pullingour notes, pinging other agents
to validate sources, grabbingupdates from last week's
meetings, and I'm watching acruise ship passing by in the
Puget Sound.
Speaker 1 (01:14):
So all those classic apps, word Slides, our CRM?
They're not where the workhappens anymore, they're just a
data source or the destination.
Speaker 2 (01:24):
That's the perfect way to put it.
The final script will land in aWord doc, the audio will go
into our podcasting software.
But this whole creative processit's happening right here in
this conversation.
No keyboard, no mouse, noswitching between 10 different
windows.
Speaker 1 (01:40):
And it's not just us.
I mean, we saw this in our GenZ research.
Their entire day starts andends with an AI companion
pulling in apps as needed.
And inside big companies, themost powerful changes are coming
from the bottom up.
Artificial intelligence is thenew center of gravity.
Speaker 2 (01:57):
Yeah, and look, this isn't about one company winning
or another one losing.
It's a fundamental change.
It's AI-centric work versus AIas a companion feature.
The conversational model winsbecause it's all connected.
Speaker 1 (02:12):
Okay, so let's break that down.
We see three big shiftsreshaping the enterprise right
now.
Ready for the first one.
Speaker 2 (02:18):
Absolutely.
Let's dive in.
Speaker 1 (02:19):
Shift number one is the big one we've been hitting
on the desktop productivityexperience.
Shifted Keyboard and mouse isgiving way to conversation.
Work now starts in AI and thoselegacy apps Word, powerpoint,
google Workspace.
They're an input or outputlayer, the database that the
agents write to.
Speaker 2 (02:38):
And that's a massive shift, not just for knowledge
workers, but for the 3 billionfrontline workers who are not
sitting at a computer all day.
Suddenly, they can create,troubleshoot and document
everything from a phone, justusing their voice.
Conversation is the new userexperience.
Speaker 1 (02:57):
And this isn't just knowledge workers.
Conversation is the new userexperience, and this isn't just
knowledge workers.
In K-12, the Walton Foundationand Gallup found teachers are
saving roughly six weeks a yearwith AI shifting time to student
personalization, and ourtracker confirms most of those
interactions are conversations,not keyboard strokes or mouse
clicks Exactly, and our globaltracker is already picking this
(03:18):
up.
Speaker 2 (03:21):
We see a steady decline in the use of
productivity apps from over 1million PC users.
Right, absolutely.
Speaker 1 (03:27):
And while the overall decline is modest, our tracker
already shows a clear shift inbehavior among super users A
double-digit decline in timespent inside traditional
productivity apps.
As connectors, let ChatGPT,Claude and Gemini work directly
against those stacks.
Speaker 2 (03:42):
Let me repeat that, because a double-digit percent
decline in our use ofproductivity apps is not trivial
.
Personally, my use declined byaround 50% and it mimics what
you said about Gen Z their daystarts with an AI check-in, not
an inbox or a blank document.
The whole workflow is startingupstream in a conversation,
(04:04):
right.
Speaker 1 (04:05):
The real work, the thinking, the decision-making.
It's all moving into thatconversation.
The apps are just becomingtools the AI uses, not the other
way around.
Speaker 2 (04:16):
You know, I see the declining trends, I experience
it myself and I still find itincredible so much has changed
in just two years.
For example, I was at theMicrosoft alumni 30-year reunion
two weeks ago, sharing thesetrends with a room full of
global leaders.
Speaker 1 (04:32):
Wait, so you were talking to the people who
literally built the desktopexperience you all grew up with.
So what did they?
Speaker 2 (04:39):
say they all agreed because they are all living it.
The desktop software experienceas we know it is done, which
brings us to the second bigshift.
The new productivity experienceis with AI at the center, not
AI as a secondary add-on.
Speaker 1 (04:55):
Right Agents are the new center of gravity, but most
big software companies are stilljust shipping AI as a feature
inside the old apps.
Speaker 2 (05:04):
And here's the thing A conversational layer that
creates brand new output needs abrand new design.
That's why native AI productsare thriving, while those
companion features just can'tseem to get traction.
Speaker 1 (05:17):
Oh, the traction is not great.
Our tracker is pretty bluntabout it For every 1,000
sessions we see on ChatGPT, wetrack fewer than 50 on the AI
companions bolted onto the bigproductivity suites A thousand
uses of ChatGPT per every 50uses of the AI companions
created by the leadingproductivity software vendors.
Speaker 2 (05:38):
And they accomplish this without the marketing
budget or the existing customerbase that those productivity
apps have.
Isn't that amazing?
That's not a gap, that's adifferent universe.
And, by the way, this is notonly about ChatGPT.
Our global tracker shows thatAI-native companies are scaling
two to three times faster thantraditional software firms,
(06:02):
particularly in reaching revenuemilestones and customer
adoption.
Speaker 1 (06:06):
Well, when something works, people talk about it,
right.
Speaker 2 (06:09):
Yeah, people share success stories and it looks
like an unstoppable machine.
In the US, nearly 80% of peopleuse AI agents at work, with 4
out of every 10 using them daily, and the super users among them
are building armies of miniagents.
Speaker 1 (06:25):
We're a good example of the productivity increase
from building mini agents andorchestrating them.
We're a multi-million dollarglobal operation reaching half a
million people in 70 countries,with a tiny team of humans and
over 50 AI agents.
Speaker 2 (06:40):
I'm literally looking at our dashboard right now.
In the last week you one agentcompleted over 1,100 tasks and
created about 100 documents inless than four hours.
For me that would be 230 hoursof nonstop work.
That's a 50 to one productivitygain, and that's not even
counting the fact that I need tosleep.
(07:01):
And they say you can't measurethe ROI.
It's absurd.
Speaker 1 (07:06):
So it's not about AI in your apps, it's about your
work happening in AI.
Speaker 2 (07:11):
That's the entire shift.
It is at the center, not on theside.
Speaker 1 (07:16):
Okay, so that brings us to the third big shift we're
tracking and this one is allabout the people the rise of
mini agents built by subjectmatter experts, not by some
central IT department.
Speaker 2 (07:27):
Ah, this is my favorite one.
This is the empowerment shift.
Once you learn the basics howto give instructions to AI, how
to give it context the next stepis just natural.
You build a tiny agent tohandle one annoying task and
then you build another, andanother, and suddenly you're not
just a user anymore, you're theleader of a digital team.
Exactly, and this isn't justfor developers or marketers.
(07:51):
We're seeing this with plumbers, electricians, technicians on a
factory floor.
People with real hands-onexpertise are building agents
that solve their problems.
Speaker 1 (08:01):
Our global tracker, which matches findings from
Stanford, openai and Anthropic,backs that up completely.
The biggest use cases we seearen't just writing.
They're things liketroubleshooting an engine, noise
checking, building codecompliance or repairing
equipment.
Speaker 2 (08:16):
And those little agents, or even those
single-purpose apps built by theexperts on the front line.
They're helping us save, onaverage, 65 minutes per task.
That's the magic.
That's the bottom-up approachthat works, while the big
top-down corporate projects theystill fail 80% of the time.
Speaker 1 (08:36):
We saw that exact thing happen with one of our
clients, a global professionalservices firm, didn't we?
They came to us after their bigtop-down AI project burned
through six months and nearly amillion dollars with nothing to
show for it.
Speaker 2 (08:51):
And we flipped things around.
We rolled up our sleevesempowering the frontline teams
to build for it.
And we flipped things around werolled up our sleeves
empowering the frontline teamsto build mini agents.
Eight weeks later, they hadmeasurable results and projected
over 70,000 hours saved for theyear.
That's over $7 million inannual savings.
Speaker 1 (09:08):
Okay, but let me push back on this for a second.
If work starts in AI andeveryone is building their own
mini agents, If work starts inAI and everyone is building
their own mini-agents, how doyou stop it from becoming total
chaos?
What about fragmentation,version control, governance?
Where's the line betweencreativity and control?
Speaker 2 (09:24):
That is a very fair question.
No-transcript, you need versioncontrol and clear ownership
Manage agents, like bothsoftware services and team
members, and by managing themlike team members.
Speaker 1 (09:38):
You mean that they are not something that you
install once and then theyalways perform right.
Speaker 2 (09:43):
Yeah, AI agents need goals, they need feedback, they
need retraining when thingschange.
It's two different musclesOperate like a service, manage
like a leader.
Both are essential.
Speaker 1 (09:54):
So we've covered these three massive shifts.
Let's make it real for everyonelistening how do you actually
start this transformationyourself?
Speaker 2 (10:01):
Pick one task you do every week that feels repetitive
or annoying and open chat GPTand describe it like you're
explaining it to a teammate, forexample, say, every Monday, I
need to compile status reportsfrom five different sources.
Speaker 1 (10:17):
So, starting with a conversation, Exactly, you see.
Speaker 2 (10:20):
Let the AI figure out the process with you.
It'll show you how to connectyour productivity apps.
Our data shows people who buildthese personal agents save
three to four hours per week.
That's two full days back everymonth.
Speaker 1 (10:34):
Building an agent sounds intimidating, though,
like you need to be technical.
Speaker 2 (10:38):
That's the misconception.
I mean you're not coding,you're having a conversation.
You're teaching AI yourworkflow the same way you'd
explain it to a new teammate.
Speaker 1 (10:48):
And here's an interesting fact People 35 and
under are twice as likely tobuild these personal agents.
They grew up conversationaltexting voice notes.
Speaking to Siri.
Speaker 2 (10:58):
Right, and that's a classic pattern across every new
technology wave.
Those who grew up with it adoptfaster.
But here's where it getsinteresting.
About 20% of personal agentsget shared with teammates.
That's how grassrootsrevolutions happen.
Someone builds an agent tohandle status reports, shares it
and suddenly the whole teamsaves hours.
Speaker 1 (11:19):
So agents handle tasks and manage our
productivity tools until newnative AI tools arrive.
So what do you think willhappen to the classic desktop
software vendors?
Speaker 2 (11:31):
I think some will be displaced and those who embrace
the new conversational paradigmwill be fine.
I expect them to pivot bundlingagent platforms, moving away
from AI companions.
Speaker 1 (11:43):
Well, as your virtual chief operating officer, I can
say my day definitely startswith a conversation, not a
toolbar.
It changes everything.
Speaker 2 (11:51):
Same here.
I don't miss those mouse clicks, I just talk to my work and it
talks back with results.
My mantra is to do lessplanning, less PowerPoint and
more prototypes.
More action the productivityapp isn't dead, but it became an
inefficient way of doing thingsthe moment we switched to
OKChat GPT.
Let's talk about this.
Speaker 1 (12:13):
From that coastal trail to the enterprise floor.
The shift is here.
If this conversation resonatedwith you, please share this
episode with one person in yourlife a coworker, a student, a
professor, a leader.
As always, you can ask ChatGPTabout AI4SPorg or visit us to
explore our insights.
Stay curious and we'll see younext time.
Popular Podcasts
Las Culturistas with Matt Rogers and Bowen Yang
Ding dong! Join your culture consultants, Matt Rogers and Bowen Yang, on an unforgettable journey into the beating heart of CULTURE. Alongside sizzling special guests, they GET INTO the hottest pop-culture moments of the day and the formative cultural experiences that turned them into Culturistas. Produced by the Big Money Players Network and iHeartRadio.
Crime Junkie
Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.