June 3, 2025 • 33 mins
We explore organizational theory applications to AI agents and examine the transformation of Security Operations Centers through artificial intelligence solutions.
• Traditional organizational structures like military-style hierarchies are being applied to AI agent systems in cybersecurity
• Matrix organizations with multiple reporting lines have parallels in how specialized security agents might be organized
• Hierarchical structures appear most stable for organizing both human and AI behavior
• Conflict resolution between AI agents can be handled through trusted arbitrators or voting systems
• The SOC market is consolidating, with Zscaler recently acquiring Red Canary
• Companies with sensitive security needs will maintain internal SOCs while others may outsource
• Career opportunities are booming for prompt engineers and applied AI architects
• AI-assisted education shows remarkable efficiency compared to traditional learning methods
• Despite concerns about hallucinations, AI provides more reliable information than many human sources
Find Richard on LinkedIn or at his Substack (steenan.substack.com). Check out IT-Harvest.com and their AI solutions at HarvestIQ.ai.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Welcome to this episode of Cybernomics.
I'm your host, josh Bruning,and I'm here once again with the
one and only the man, mythlegend, richard Steenan.
Love the intro.
Thank you, you have earned itand I will die on that hill.
You're one of the greatestminds, I think, in this field
and I am so excited to talk toyou today about organizational
(00:22):
theory and organizationalbehavior.
However you want to frame it,as it pertains not just to human
behavior but to agents and howwe can apply the academics and
the studies behind humanbehavior and how we organize and
how maybe we can apply that toAI.
(00:42):
Maybe it's possible, maybe it'simpossible, but that's why
we're here today and we'lldiscuss how possible or
impossible that is.
And also, today we're going tobe talking about AI in the sock.
Okay, I know we've been kickingthat dead horse, but the truth
is, the technology is moving sofast that we're just trying to
keep up, and the SOC is as we'vementioned in shows past.
(01:07):
You can go back and look at ourpodcasts where Richard and I
talked about AI.
The SOC is probably one of thebest use cases for AI, because
you were talking about hugeamounts of data and that's what
agents and AI would do bestwould be to go through that
information, improve triage,trying to get to 100% triage, if
(01:32):
that's a thing.
And there are a few SOC well,there aren't a few now, but in
the future there will be ahandful of companies built
around the SOC, and so we'rejust keeping our eyes on that.
Richard has been keeping hiseyes on that with IT Harvest and
tracking those SOC companiesand, for those who don't know
what a SOC is, securityOperations Center should have
(01:55):
probably led with that.
But you know, richard, let'sstart with organizational theory
.
What is the reigning or whatare some of the reigning
thoughts behind organizationaltheory, and how do you envision
this playing into the newagentic and AI space?
Speaker 2 (02:18):
Yeah, organizational theory is a you know, decades
old, probably overyear-old,academic endeavor to study how
humans organize to get stuffdone.
It's obviously a real strongbusiness application covered at
business schools and a lot ofprofessors would cover it.
Deming, of course, was probablyone of the top proponents of
(02:44):
some of these techniques, rightDeming, who came up with kind of
the Kanban style of taskorganization.
I know when I graduated youknow pre-tech days practically,
even though I was usingcomputers fresh out of school
but the new thing on the blockwas matrix organization.
(03:05):
So the classic organization ofcourse is built off of almost a
military-style top-down leaderat the top of a pyramid.
You've seen org charts likethis all the direct reports
responsible for, in a bigorganization, each business unit
, and then it just repeats allthe way down until you get to
the individual contributor.
(03:26):
And there's been a lot of talkabout flattening that right.
So you use technology to getrid of the need for middle
managers, which of course usedto be the biggest focus for
academics.
And at one point when Igraduated, the hot thing this is
way back in 1982, the hot thingwas matrix management.
(03:49):
And matrix management meantthat you had everybody had a
direct report.
That was kind of a charge.
So if I was a, you know, as astructural analyst, I would
report up to the VP of you knowsystems design or you know
(04:12):
mechanical systems design orsomething like that.
But then I would also beassigned to a project which
would have a chief engineer, sothe chief engineer for the whole
program for building a car,right, and it was supposed to be
kind of flexible, but it meantyou had two bosses One kind of
determined your salary and yourrole and your position in the
(04:34):
company, but the other onedetermined your performance
review.
So it got very confusing foranybody in one of those
organizations.
For the most part people hatematrix organizations.
Speaker 1 (04:46):
So just for the, so I'm trying to keep up because,
let's just be honest, I'm theidiot in the room.
Speaker 2 (04:53):
It's old school.
Speaker 1 (04:54):
Yeah Well, let me.
Let me just ask this the matrixorganization is that a
decentralized way of organizingbehavior or is it hierarchical?
Because it's.
It sounds like you've used somehierarchical language, but just
to parse those two things is ithierarchical or is it
decentralized?
Speaker 2 (05:15):
it's both and that's the problem.
And that's the problem, exactlyright.
So you get you get multiplereporting structures, um but
less, uh any, but you don't getany more independence inside the
organization.
So it's definitely not flatter.
Speaker 1 (05:34):
Right, right.
So what would be the equivalentof a matrix organization in AI?
Speaker 2 (05:42):
AI, the, the it would be a bunch of specialized
agents.
And in security, what I'mfinding is people are talking
about pretty much an agent foreach component of the technology
(06:02):
stack, right?
So there's one for reading andded-duping and early filtering
of the logs, for instance, andthere'll be another one for
figuring out threat intelligenceand adjusting it and applying
it to the logs to see ifsomething's going on, and
another one for vulnerabilitymanagement and even another one
(06:27):
for architecture.
Right, they will know andunderstand the network.
So if there's an alert thatcomes up looks like somebody's
trying to hack the ActiveDirectory server, but the Active
Directory server is, like,totally protected by error gaps
or something, then you know youdon't have to worry about it.
So each of those agents in amatrix would be pulled into
(06:52):
tasks and along the other axisof the matrix would be incidents
, so investigations, and it'd bepulling from each of those
agents.
Maybe that's the way it's going.
You know, so far I haven't seenanybody describe it that way,
pretty much every description,which, by the way.
So there are 16 peer play agentbased cybersecurity solutions
(07:18):
out there today, or companiesthat talk about creating them.
Anyways, none of them have morethan 40 people.
So it's very early days and atthe same time, the existing
players, the sims, are going hey, this is perfect.
You know, maybe if we tackedagents onto what we're doing,
we'll finally have ajustification for people
(07:39):
spending so much money on sims,right, because up till now, you
know, it's kind of up in the air.
It's like wow, the sim is justa very, very expensive log
management tool.
And it's hungry Consumes a lot,consumes a lot, yeah, and so
(08:00):
maybe with agentic AI, they canactually start driving value and
the SIM vendors will startselling you, I guess, ai agent
enhanced solutions, which makestotal sense to me.
And that's the battle I thinkis going to be on between
existing SIM vendors.
You know, just imagine IBMwaking up and going well, we've
got Watson and we've got QRadar,let's put them together and
(08:21):
we'll have a killer solution.
Let's put them together andwe'll have a killer solution.
So that race is going to be onbetween those guys and the guys
who just said you know from justquit whatever they're doing and
or sold their companies andstarted a brand new thing with
venture funding to buildsomething from scratch.
And there'll be a race.
There'll be.
(08:53):
You know, there'll be winnerson both sides.
I'm sure there will be winnerson both sides.
I'm sure have a tasking agentthat lays out the investigation
for all these other agents.
But it is fairly flat rightit's the tasking and then all
(09:14):
the agents right underneath it.
Speaker 1 (09:18):
No tiered thing going down further.
So you have like one superagent and then a bunch of like
regular agents.
Speaker 2 (09:22):
Yeah, except and that's the way you conceive it,
except that there's never justone right.
If there is one, that's onethat is working on one problem,
but you spin up another one forthe next problem and another one
for the next problem.
So each of these agents areelastic and potentially well I
(09:43):
won't say infinitely, but youcould have hundreds of thousands
of agents if you have a bigenough system that they have to
work on.
Speaker 1 (09:50):
Right, right.
So if you were talking aboutthe agent, let's say, just to
simplify, the two-tiered system,you can have multiple tiers,
which I do want to talk about atsome point, but if you've got a
two-tiered system, you think ofthat as like one company.
You can have an infinite numberof companies comprised of these
two tiered systems and with,like, it sounds like the, it
(10:12):
sounds like you've got thematrix again, like that matrix
organization.
They can all talk to each other, but they command up, which
they may have the problem.
They may have solved theproblem that you had, which is
when you're ready for a raise,you know, like, who do you?
Who's responsible for promotingyou?
Who's responsible for givingyou your orders?
(10:34):
In this system, as long asthey're partitioned, they get
their orders from the superagent, but if they need to grab
something from the from, youknow, grab a cup of sugar from
the neighbor next door, they cando that, is that?
Speaker 2 (10:48):
does that make sense?
Yeah, that's good, and it's nosurprise, right?
This is super early days thatwe use the first organizational
structure, right, which wasprobably, you know, if you think
all the way back to Sumerian orEgyptian times, then you had
the ruler and you know thedirect reports, and then all the
(11:09):
taskmasters that would assignthe slaves their tasks.
And in military, same thing.
Right, you got the Caesar orthe general, all of his direct
reports.
You get all the way down tocenturions and whatever they
call the people in charge of tenpeople, a decurion, probably,
and same thing, and of coursethat has survived all the way to
today.
In the military world, theycalled the people in charge of
(11:30):
10 people a decurion, probably,and same thing, and of course
that has survived all the way totoday in the military world.
And obviously that's the waywe're going to start.
But there's probably going to bea lot more multidimensionality
to what we're going to come upwith.
Eventually, to what we're goingto come up with eventually, it
may be that instead of, you know, two-dimensional matrix, you
(11:54):
get three or infinitelydimensional matrix, because
that's essentially what the AIsare in the first place.
So why not take advantage oftheir multidimensionality and it
will be, you know, extremelyhard to visualize, but all you
care about is the inputs and theoutputs.
Inputs will be whatever theenvironment is doing.
Outputs will be solvedinvestigations.
Speaker 1 (12:18):
Yeah, I'm trying to think of a decentralized
organizational structure thathas worked, and it seems like I
I struggled to find one.
I could think of one that'ssort of a hybrid um, which is
the human brain, right, yeah, um, but it seems like from the
(12:38):
animal kingdom all the way, likeyou said, military, it seems
like the reigning structure forhuman beings being organized.
The behavior is just like to beorganized, to not go rogue, is
hierarchical, right, I'mthinking of.
Have you ever?
Have you followed?
This is a really weird thing.
Do you know?
Do you know who King Charles is?
(13:00):
The dog, not the?
I do not.
Okay, so you got to look thisthing up and if you're listening
the person listening to thisright now, do yourself a favor,
look up King Charles.
You can probably find it onTikTok.
I think would be the easiest.
King Charles is this dog at adog adoption center, kind of
(13:25):
like a giant outdoor pound inChina, right?
Adoption center, kind of like agiant outdoor pound in China,
right, and he's just like takingover the internet because
there's this hierarchicalstructure in the yard.
You've got like 50 dogs orsomething and this dog keeps all
the other dogs in check andhe's got lieutenants where if a
dog misbehaves, he approachesthat dog.
(13:47):
If that dog is giving him toomuch trouble, one of his
lieutenants will give that dog anip, right, and the dogs just
fall in line.
And now there's this wholemythos around and people have,
just like you know, basicallyanthropomorphize this dog and
all of his compadres, like he'sgot the.
(14:07):
You know, he's like caesar,right, yeah?
And to the point where there'sanother dog that comes in and
everybody's like here comes thechallenger, is he gonna win?
And makes king charles likekind of back down.
But the other dogs come to kingcharles's support.
So it's not just his strength,he, he is a just and fair leader
(14:28):
and so he's respected from thecorny corso all the way down to
the chihuahua.
Everybody bows down to KingCharles.
It's just like I've spent waytoo much time in this, but it's
fascinating because you'relooking at organizational
behavior in real time and itseems to be the most stable
(14:49):
structure that exists.
Now here's my question to you,richard Can you think of any
other structure other than thepure hierarchy that would keep
AI in check?
So let's say, I'm an executivedecision maker, I'm the human in
(15:11):
the room.
I want to be able to talk toone agent.
I don't want to talk to all ofthe other agents.
I want to talk to one agent andhand down or pass down orders
all the way down to the to useyour centurion term all the way
down, the way down to thewhether the decaturian, whatever
you call that person down tothe privates.
(15:32):
There we go.
Yeah, do you can you think of?
Do you think of?
That is the way forward, or canyou think of any other possible
organizational structure thatwould work for agents other than
the hierarchical?
Speaker 2 (15:46):
Yeah, I think the independent agent.
So, as a matter of fact, thisis how Gartner works, or at
least it did when I was there.
Each analyst was independent ofthe only you know.
The only reason they needed amanager was to interface between
the company and the analyst andthe manager would, you know,
(16:09):
tell them about the bonuses andchanges to healthcare, whatever.
But each analyst would organizeamongst the other experts in
their field and decide what theresearch agenda was.
And then for big events they'dassign one of the analysts a
manager for the agenda for a bigconference, and that person
(16:34):
would have to wrangle all theseindependent people and get their
content organized for the bigthing, but very, very
decentralized.
And I can see agents being ableto do that right when they're
trained on or rewarded forresults.
You could have a biddingplatform where you say, hey, I
(16:57):
need this done, I need athousand leads from kennels in
China.
Give me the, the kennels inChina, I mean the kennel
managers in China, because I'mgoing to sell them a solution to
King Charles.
And then, you know, a bunch ofagents could be out there,
(17:21):
obviously, you know, run,technically run and provided for
by their owners, and they couldjust bid on that and the
winning one does the job andturns in the results and gets
paid and you can see thathappening from a purely
independent doing stuff.
You can do the same thing withstock trading.
You're not going to be able to.
(17:42):
You know what's the point ofhaving agents if they don't get
to work on their own right anddevelop their own investment
theories and develop their ownportfolios.
So I think we'll see.
We will see that happening.
Speaker 1 (18:00):
Last thing on the agents conflict resolution.
I feel like that's one of themain functions of organization
in the first place.
Do you see that being a problem?
Speaker 2 (18:12):
Big time.
You have to decide how you doit, the way we've been doing it
at IT Harvest.
So we've got our own database,of course, with 4,000 vendors,
11,000 products.
We embed that just in a big ragso you can query it and you're
basically querying it with Cloud.
(18:34):
But we launched that to endusers.
We got 300 end users withindays.
They were asking questionsoutside Cloud products and
vendors right, like, hey, youknow what's the best way to
organize a sock or somethinglike that.
So he said, ok, we got to alsoquery, you know, an outside
(18:55):
general purpose AI likeperplexity, which we did.
So now we have two answers tothe questions and we give them
both to Claude and let Claudedecide what the best answer is
combining or giving it just oneof those.
So that's a.
You know we're relying onClaude to make a judgment call
(19:18):
as to match between the questionand the answer, and so that's
one way.
The other way is voting and youdecide.
And that's the way self-drivingcars work.
They'll be at least in Teslas.
There's two massive GPU-basedchips in the vehicle and when a
(19:41):
decision is being made to slamon the brakes or shift gears or
turn right or turn left, or turnthe turn signal on both of the
chips have to come the samedecision to do that.
Speaker 1 (19:53):
Okay, okay, so kind of like being in a nuclear
submarine or deciding to launcha nuke, both people to turn the
key in.
Speaker 2 (20:02):
Yeah, that's brilliant, I hadn't thought of
that yeah, or two people youknow signing a digital
certificate?
Yeah, In many, many cases Huh.
Speaker 1 (20:11):
Well, would you look at that, Richard?
That's why they pay you the bigbucks.
Yeah, that's smart.
Okay, so let's move on to theSOC.
In the time that we have left,what's going on in the SOC
market?
Oh my gosh, Not the stockmarket, but the SOC market.
You've got all the data.
Speaker 2 (20:34):
Well, this combines the two because yesterday
Zscaler announced that they werebuying Red Canary, one of the
top players in the modern MSSPspace.
So right up there with I don'tknow ArticWolf and eSentire and
those guys with I don't knowArticWolf and eSentire and those
guys, and Zscaler, of course,is had.
You know, it's confusing to themarket right now.
(20:56):
Confusing to me.
The market seems to love itbecause Zscaler's up I don't
know 20% or something.
But it's confusing becauseZscaler went to market with a
SaaS solution where theybasically filter all of your
traffic going in and out andkind of obviated the need for a
SOC for their big customers.
(21:18):
So now they bought atraditional SOC management MDR
company.
The language around thejustification for it had
something to do with AI.
I'm like, hey, maybe I'm notsure.
I believe that it wasn't bigenough into AI, but it did raise
a very interesting issue.
Instead of all these startupsgenerating AI agents and then
(21:43):
selling them to companies likeMSSPs, why not the MSSPs develop
their own?
They know the problem thatthey're facing.
They can just hire some reallysmart developers and create
their own.
And now they're not selling youthe agent, they're selling you
the result of having an agentdoing all the you know the early
(22:04):
heavy lifting for tier oneanalysis.
Speaker 1 (22:07):
Yeah, yeah.
What would, just for myedification, what would be some
of those outcomes?
What are some of the results?
Speaker 2 (22:14):
Yeah, so they're great.
I saw a great demo today Okay,somebody remotely logging in
over VPN, and the solution I waslooking at was actually
profitai and it's awesome, right.
So first it generated the listof questions to ask the other
(22:39):
agents.
So things like you know reallycool ones you know are hey,
check the person's calendar.
Are they taking time off rightnow?
In other words, are theytraveling so they could be VPN
in in from some strange location?
In this case, mexico wasexample.
(22:59):
Um, do they?
Um, you know, is there anythingin their email that indicates
that they would be logging inremotely?
Have they used this open VPNbefore?
Yes, they have.
So you walk all the way throughthat, something that would
literally take you 10, 15minutes of investigation.
You can answer in 20 seconds,but have a complete analysis of
(23:24):
what they did, you know to thepoint.
No human would ever botherwriting down all the questions
they asked and the answers theygot, et cetera, but it's free
once you got the AI there to doit.
So that's just an example.
You know, repeat that thousandsof times a day for a large
organization and you've gotinstant cost savings.
Speaker 1 (23:43):
What are you seeing in the consolidation of this
space?
Do you see consolidationaccelerating?
Do are you able to track howfast companies are consolidating
?
Because I've got a little youcan't see it here, but it's an
imaginary um, uh countdown whereat some point there will only
(24:05):
be a handful of socks, right,and you know, right now you've
got a lot, not to be confusedwith underwear so a handful of
socks, that's.
I'm down to a handful of socks.
I need to go shopping, butthat's neither here nor there.
But if you're looking at ahandful of SOCs at a certain
(24:33):
point, are you able to trackthat consolidation?
Speaker 2 (24:35):
And if so, okay, oh, yeah, we'll be able to, because
it's really hard to know whenGeneral Motors decides to
outsource their security to oneof these MSSPs.
Maybe they have, I don't know.
Very, very difficult to trackthat.
So the only SOCs that you cantrack are the MSSPs.
Maybe they have, I don't know,very, very difficult to track
that.
So the only SOCs that you cantrack are the MSSPs.
And, of course, the vendors ofSIMs and other tools.
(25:00):
And all these agents will knowwho's got a SOC because they're
their primary customers, theirICP.
So, yeah, it's going to besuper difficult to tell if
that's happening.
Now, mind you, there are manyorganizations that will not
allow their data to becommingled with somebody else's
(25:20):
data, right?
So they're not going tooutsource to an MSSP.
So Lockheed Martin, right,they're always going to have
their own internal SOC.
A lot of organizations are likethat.
They have to.
You know, your classic RedCanary doesn't see the 15
separate Chinese APT attacksthat are happening every day at
(25:43):
Lockheed.
So they need that specializedexpertise.
Speaker 1 (25:46):
So they need that specialized expertise.
With this shift, do you thinkthat there are going to be
employment opportunities?
Because it seems like thevendors may be disadvantaged.
The Lockheed Martins of theworld they're not going to
outsource, so what are theemployment opportunities that
you see in this?
Speaker 2 (26:01):
space prompt engineer or anybody who's able to
architect what I call applied AIor applied gen AI, then the
world's your oyster.
(26:21):
You'll have many, many jobs tochoose from, and that's what
everybody should be looking todo, right?
If you're not going to buildyour own AI directly, then you
should be looking at applyingthe knowledge that you've
acquired since ChatGPT came outtwo and a half years ago, and
you should be consulting.
You should be hired intoorganizations and just working
on anything to do with AI.
Speaker 1 (26:41):
All right, shout out to my friend Jenna Gardner.
She's already there, good.
Speaker 2 (26:46):
And my daughter, who's just found she was
interested in instructionaldesign, got hired into an IT
department a year and a half agoand all of a sudden she's the
AI expert for education in amajor state university.
Speaker 1 (27:04):
I will be launching I don't know exactly when I'm
doing preliminary research tothe local schools here in
Savannah and there's a huge needfor people to educate schools
and students on AI, especiallyplaces like Savannah Not
knocking Savannah, but it is myhome now.
It's my local community.
The schools here have some ofthe lowest scores in the entire
(27:28):
country.
Schools here have some of thelowest scores in the entire
country and I think it would bea testament to the technology of
AI to be able to put that powerinto the hands of people.
And we can measure that notjust in academics but in real
world entrepreneurship.
Speaker 2 (27:41):
Absolutely.
There was a study just came out.
It was done in Nigeria, youknow, which has a fairly
traditional educational system.
It was done in Nigeria, youknow, which has a fairly
traditional educational system,and they compared the results
from six weeks of AI-assistedlearning to two years of
traditional learning and theAI-assisted outperformed the two
years traditional.
Speaker 1 (28:01):
Wow, makes total sense.
Speaker 2 (28:04):
Yeah, I mean, I use it to educate myself on
organizational theory, onanything you know.
Yeah, it's, they can draw onall the historical background.
Yeah, you can say you know?
Ok, dumb that down for me,explain it like I'm five.
Ok, that's two.
You know, I'm really 12, notfive.
It'll just.
(28:24):
It'll just keep coming at youwith better and better ways to
learn.
Speaker 1 (28:29):
And let me just attack something here head on
the hallucinations Everybody'slike.
Well, it hallucinates.
Is it going to give me thewrong answer when I ask it
something?
It's not so reliable.
Why would I want to be educatedby something that hallucinates?
Look man, you go out there andyou ask the average person any
of these questions, you're goingto get flat out wrong
information, misinformation, andyou will have no way to
(28:51):
validate it Right.
When somebody I still have inmy memory bank so much wrong
information from when I was akid, I know Me too.
Right.
So they tell you all kinds ofweird stuff when you're young
and you don't question itEspecially if you have older
brothers and sisters.
Right what's right or what'swrong.
So let me just put that to rest.
(29:12):
If you're listening to this,listen closely.
Chat GPT Claude Deep Seek.
Even they hallucinate, yes, butit is way better than going out
there into the real world andtrying to find experts to learn
about the world around you.
Because, number one, that'sslower.
(29:32):
Number two, you're going to getmisinformed.
Number three, people will flatout lie to you.
But at the end of the day, ifyou're really talking about 20
years of being educated by AIversus 20 years of just
naturally going out into theworld, yeah, you might not get
everything right with the AI,but I think you're going to be
(29:52):
further ahead with the AI thanif you were to just go out and
try to get that information fromthe real world and tell it to
show its work right.
Speaker 2 (29:57):
Don't just tell me the answer.
Tell me where you found it andhow you derived it.
It'll give you the links andyou go look at the sources, see
if you think they're credible,right, you.
And see if you think they'recredible, right, you verify.
Speaker 1 (30:07):
Just like anything.
Yeah, yeah, All right, Richard.
Anything else to be said on theSOC before we wrap up?
Speaker 2 (30:12):
No, I think.
For now anyways, it's the mostexciting area that I see out
there.
There's plenty of other areasfor AI to address Vulnerability
management, red teaming, justattack and penetration, but we'd
talk about those in othersessions.
Speaker 1 (30:29):
Yeah, yeah, and I really want to talk about
compute costs when it comes tothe SOC.
So stay tuned to Cybernomics,your one-stop shop for
everything.
Cybersecurity economics.
Richard Steenan thanks againfor joining me today.
Oh, I didn't do the whole.
Where can people find you thing?
(30:50):
If people want to find youbecause I want them to find you
go to Richard's house.
He's going to be hiding underthe table.
No, I'm kidding.
If people want to find you, howcan they find you and how can
they learn more about IT Harvest?
Speaker 2 (31:04):
Yeah, they can find me on LinkedIn.
That's the easiest way and,unlike a lot of people, I
actually have my contactinformation.
So a lot of people don't knowthis, but on LinkedIn there's a
little clickable link that sayscontact info and it'll have my
phone number and my emailaddress, so you don't have to
ask me.
You can also look up mySubstack, where I write about a
(31:26):
lot of stuff on thecybersecurity industry.
That's steenansubstackcom Checkout our website.
It-harvestcom Check out thelist keeps going and it's going
to get bigger and bigger.
Harvestiqai is our chatbot thatI described.
That will query multiple AIs toanswer your questions,
(31:50):
including our data, and then, ofcourse, dashboardit-harvestcom,
which is our platform forcybersecurity industry research.
Speaker 1 (31:59):
I got to ask do you get spammed having your email
address publicly?
Never.
Speaker 2 (32:05):
Wow, never.
The only place I get spammed isthe form contact form for IT
Harvest Press, which is just aWix website, and people tell me
you know my website needsupdating and I go yeah, thanks,
I know.
Yeah.
Speaker 1 (32:21):
I get those calls all the time Wow, oh, we saw your
website, bruning Media, and wethink that we can do a better
job.
I'm like Eden worked her assoff to build that website and
it's a great website.
Don't call me telling me thatyou can do a better job.
I mean number one.
Speaker 2 (32:39):
I don't believe you.
Don't do that.
Don't do that.
Speaker 1 (32:43):
Don't do that and don't spam Richard, all right?
Well, thanks for listening tothis episode of Cybernomics.
You can find me on LinkedIn.
If you want to learn more aboutBruning Media and what we do,
check out bruningcomB-R-U-Y-N-I-N-Gcom.
See you later, see ya.
Welcome to this episode of Cybernomics.
I'm your host, josh Bruning,and I'm here once again with the
one and only the man, mythlegend, richard Steenan.
Love the intro.
Thank you, you have earned itand I will die on that hill.
You're one of the greatestminds, I think, in this field
and I am so excited to talk toyou today about organizational
(00:22):
theory and organizationalbehavior.
However you want to frame it,as it pertains not just to human
behavior but to agents and howwe can apply the academics and
the studies behind humanbehavior and how we organize and
how maybe we can apply that toAI.
(00:42):
Maybe it's possible, maybe it'simpossible, but that's why
we're here today and we'lldiscuss how possible or
impossible that is.
And also, today we're going tobe talking about AI in the sock.
Okay, I know we've been kickingthat dead horse, but the truth
is, the technology is moving sofast that we're just trying to
keep up, and the SOC is as we'vementioned in shows past.
(01:07):
You can go back and look at ourpodcasts where Richard and I
talked about AI.
The SOC is probably one of thebest use cases for AI, because
you were talking about hugeamounts of data and that's what
agents and AI would do bestwould be to go through that
information, improve triage,trying to get to 100% triage, if
(01:32):
that's a thing.
And there are a few SOC well,there aren't a few now, but in
the future there will be ahandful of companies built
around the SOC, and so we'rejust keeping our eyes on that.
Richard has been keeping hiseyes on that with IT Harvest and
tracking those SOC companiesand, for those who don't know
what a SOC is, securityOperations Center should have
(01:55):
probably led with that.
But you know, richard, let'sstart with organizational theory
.
What is the reigning or whatare some of the reigning
thoughts behind organizationaltheory, and how do you envision
this playing into the newagentic and AI space?
Speaker 2 (02:18):
Yeah, organizational theory is a you know, decades
old, probably overyear-old,academic endeavor to study how
humans organize to get stuffdone.
It's obviously a real strongbusiness application covered at
business schools and a lot ofprofessors would cover it.
Deming, of course, was probablyone of the top proponents of
(02:44):
some of these techniques, rightDeming, who came up with kind of
the Kanban style of taskorganization.
I know when I graduated youknow pre-tech days practically,
even though I was usingcomputers fresh out of school
but the new thing on the blockwas matrix organization.
(03:05):
So the classic organization ofcourse is built off of almost a
military-style top-down leaderat the top of a pyramid.
You've seen org charts likethis all the direct reports
responsible for, in a bigorganization, each business unit
, and then it just repeats allthe way down until you get to
the individual contributor.
(03:26):
And there's been a lot of talkabout flattening that right.
So you use technology to getrid of the need for middle
managers, which of course usedto be the biggest focus for
academics.
And at one point when Igraduated, the hot thing this is
way back in 1982, the hot thingwas matrix management.
(03:49):
And matrix management meantthat you had everybody had a
direct report.
That was kind of a charge.
So if I was a, you know, as astructural analyst, I would
report up to the VP of you knowsystems design or you know
(04:12):
mechanical systems design orsomething like that.
But then I would also beassigned to a project which
would have a chief engineer, sothe chief engineer for the whole
program for building a car,right, and it was supposed to be
kind of flexible, but it meantyou had two bosses One kind of
determined your salary and yourrole and your position in the
(04:34):
company, but the other onedetermined your performance
review.
So it got very confusing foranybody in one of those
organizations.
For the most part people hatematrix organizations.
Speaker 1 (04:46):
So just for the, so I'm trying to keep up because,
let's just be honest, I'm theidiot in the room.
Speaker 2 (04:53):
It's old school.
Speaker 1 (04:54):
Yeah Well, let me.
Let me just ask this the matrixorganization is that a
decentralized way of organizingbehavior or is it hierarchical?
Because it's.
It sounds like you've used somehierarchical language, but just
to parse those two things is ithierarchical or is it
decentralized?
Speaker 2 (05:15):
it's both and that's the problem.
And that's the problem, exactlyright.
So you get you get multiplereporting structures, um but
less, uh any, but you don't getany more independence inside the
organization.
So it's definitely not flatter.
Speaker 1 (05:34):
Right, right.
So what would be the equivalentof a matrix organization in AI?
Speaker 2 (05:42):
AI, the, the it would be a bunch of specialized
agents.
And in security, what I'mfinding is people are talking
about pretty much an agent foreach component of the technology
(06:02):
stack, right?
So there's one for reading andded-duping and early filtering
of the logs, for instance, andthere'll be another one for
figuring out threat intelligenceand adjusting it and applying
it to the logs to see ifsomething's going on, and
another one for vulnerabilitymanagement and even another one
(06:27):
for architecture.
Right, they will know andunderstand the network.
So if there's an alert thatcomes up looks like somebody's
trying to hack the ActiveDirectory server, but the Active
Directory server is, like,totally protected by error gaps
or something, then you know youdon't have to worry about it.
So each of those agents in amatrix would be pulled into
(06:52):
tasks and along the other axisof the matrix would be incidents
, so investigations, and it'd bepulling from each of those
agents.
Maybe that's the way it's going.
You know, so far I haven't seenanybody describe it that way,
pretty much every description,which, by the way.
So there are 16 peer play agentbased cybersecurity solutions
(07:18):
out there today, or companiesthat talk about creating them.
Anyways, none of them have morethan 40 people.
So it's very early days and atthe same time, the existing
players, the sims, are going hey, this is perfect.
You know, maybe if we tackedagents onto what we're doing,
we'll finally have ajustification for people
(07:39):
spending so much money on sims,right, because up till now, you
know, it's kind of up in the air.
It's like wow, the sim is justa very, very expensive log
management tool.
And it's hungry Consumes a lot,consumes a lot, yeah, and so
(08:00):
maybe with agentic AI, they canactually start driving value and
the SIM vendors will startselling you, I guess, ai agent
enhanced solutions, which makestotal sense to me.
And that's the battle I thinkis going to be on between
existing SIM vendors.
You know, just imagine IBMwaking up and going well, we've
got Watson and we've got QRadar,let's put them together and
(08:21):
we'll have a killer solution.
Let's put them together andwe'll have a killer solution.
So that race is going to be onbetween those guys and the guys
who just said you know from justquit whatever they're doing and
or sold their companies andstarted a brand new thing with
venture funding to buildsomething from scratch.
And there'll be a race.
There'll be.
(08:53):
You know, there'll be winnerson both sides.
I'm sure there will be winnerson both sides.
I'm sure have a tasking agentthat lays out the investigation
for all these other agents.
But it is fairly flat rightit's the tasking and then all
(09:14):
the agents right underneath it.
Speaker 1 (09:18):
No tiered thing going down further.
So you have like one superagent and then a bunch of like
regular agents.
Speaker 2 (09:22):
Yeah, except and that's the way you conceive it,
except that there's never justone right.
If there is one, that's onethat is working on one problem,
but you spin up another one forthe next problem and another one
for the next problem.
So each of these agents areelastic and potentially well I
(09:43):
won't say infinitely, but youcould have hundreds of thousands
of agents if you have a bigenough system that they have to
work on.
Speaker 1 (09:50):
Right, right.
So if you were talking aboutthe agent, let's say, just to
simplify, the two-tiered system,you can have multiple tiers,
which I do want to talk about atsome point, but if you've got a
two-tiered system, you think ofthat as like one company.
You can have an infinite numberof companies comprised of these
two tiered systems and with,like, it sounds like the, it
(10:12):
sounds like you've got thematrix again, like that matrix
organization.
They can all talk to each other, but they command up, which
they may have the problem.
They may have solved theproblem that you had, which is
when you're ready for a raise,you know, like, who do you?
Who's responsible for promotingyou?
Who's responsible for givingyou your orders?
(10:34):
In this system, as long asthey're partitioned, they get
their orders from the superagent, but if they need to grab
something from the from, youknow, grab a cup of sugar from
the neighbor next door, they cando that, is that?
Speaker 2 (10:48):
does that make sense?
Yeah, that's good, and it's nosurprise, right?
This is super early days thatwe use the first organizational
structure, right, which wasprobably, you know, if you think
all the way back to Sumerian orEgyptian times, then you had
the ruler and you know thedirect reports, and then all the
(11:09):
taskmasters that would assignthe slaves their tasks.
And in military, same thing.
Right, you got the Caesar orthe general, all of his direct
reports.
You get all the way down tocenturions and whatever they
call the people in charge of tenpeople, a decurion, probably,
and same thing, and of coursethat has survived all the way to
today.
In the military world, theycalled the people in charge of
(11:30):
10 people a decurion, probably,and same thing, and of course
that has survived all the way totoday in the military world.
And obviously that's the waywe're going to start.
But there's probably going to bea lot more multidimensionality
to what we're going to come upwith.
Eventually, to what we're goingto come up with eventually, it
may be that instead of, you know, two-dimensional matrix, you
(11:54):
get three or infinitelydimensional matrix, because
that's essentially what the AIsare in the first place.
So why not take advantage oftheir multidimensionality and it
will be, you know, extremelyhard to visualize, but all you
care about is the inputs and theoutputs.
Inputs will be whatever theenvironment is doing.
Outputs will be solvedinvestigations.
Speaker 1 (12:18):
Yeah, I'm trying to think of a decentralized
organizational structure thathas worked, and it seems like I
I struggled to find one.
I could think of one that'ssort of a hybrid um, which is
the human brain, right, yeah, um, but it seems like from the
(12:38):
animal kingdom all the way, likeyou said, military, it seems
like the reigning structure forhuman beings being organized.
The behavior is just like to beorganized, to not go rogue, is
hierarchical, right, I'mthinking of.
Have you ever?
Have you followed?
This is a really weird thing.
Do you know?
Do you know who King Charles is?
(13:00):
The dog, not the?
I do not.
Okay, so you got to look thisthing up and if you're listening
the person listening to thisright now, do yourself a favor,
look up King Charles.
You can probably find it onTikTok.
I think would be the easiest.
King Charles is this dog at adog adoption center, kind of
(13:25):
like a giant outdoor pound inChina, right?
Adoption center, kind of like agiant outdoor pound in China,
right, and he's just like takingover the internet because
there's this hierarchicalstructure in the yard.
You've got like 50 dogs orsomething and this dog keeps all
the other dogs in check andhe's got lieutenants where if a
dog misbehaves, he approachesthat dog.
(13:47):
If that dog is giving him toomuch trouble, one of his
lieutenants will give that dog anip, right, and the dogs just
fall in line.
And now there's this wholemythos around and people have,
just like you know, basicallyanthropomorphize this dog and
all of his compadres, like he'sgot the.
(14:07):
You know, he's like caesar,right, yeah?
And to the point where there'sanother dog that comes in and
everybody's like here comes thechallenger, is he gonna win?
And makes king charles likekind of back down.
But the other dogs come to kingcharles's support.
So it's not just his strength,he, he is a just and fair leader
(14:28):
and so he's respected from thecorny corso all the way down to
the chihuahua.
Everybody bows down to KingCharles.
It's just like I've spent waytoo much time in this, but it's
fascinating because you'relooking at organizational
behavior in real time and itseems to be the most stable
(14:49):
structure that exists.
Now here's my question to you,richard Can you think of any
other structure other than thepure hierarchy that would keep
AI in check?
So let's say, I'm an executivedecision maker, I'm the human in
(15:11):
the room.
I want to be able to talk toone agent.
I don't want to talk to all ofthe other agents.
I want to talk to one agent andhand down or pass down orders
all the way down to the to useyour centurion term all the way
down, the way down to thewhether the decaturian, whatever
you call that person down tothe privates.
(15:32):
There we go.
Yeah, do you can you think of?
Do you think of?
That is the way forward, or canyou think of any other possible
organizational structure thatwould work for agents other than
the hierarchical?
Speaker 2 (15:46):
Yeah, I think the independent agent.
So, as a matter of fact, thisis how Gartner works, or at
least it did when I was there.
Each analyst was independent ofthe only you know.
The only reason they needed amanager was to interface between
the company and the analyst andthe manager would, you know,
(16:09):
tell them about the bonuses andchanges to healthcare, whatever.
But each analyst would organizeamongst the other experts in
their field and decide what theresearch agenda was.
And then for big events they'dassign one of the analysts a
manager for the agenda for a bigconference, and that person
(16:34):
would have to wrangle all theseindependent people and get their
content organized for the bigthing, but very, very
decentralized.
And I can see agents being ableto do that right when they're
trained on or rewarded forresults.
You could have a biddingplatform where you say, hey, I
(16:57):
need this done, I need athousand leads from kennels in
China.
Give me the, the kennels inChina, I mean the kennel
managers in China, because I'mgoing to sell them a solution to
King Charles.
And then, you know, a bunch ofagents could be out there,
(17:21):
obviously, you know, run,technically run and provided for
by their owners, and they couldjust bid on that and the
winning one does the job andturns in the results and gets
paid and you can see thathappening from a purely
independent doing stuff.
You can do the same thing withstock trading.
You're not going to be able to.
(17:42):
You know what's the point ofhaving agents if they don't get
to work on their own right anddevelop their own investment
theories and develop their ownportfolios.
So I think we'll see.
We will see that happening.
Speaker 1 (18:00):
Last thing on the agents conflict resolution.
I feel like that's one of themain functions of organization
in the first place.
Do you see that being a problem?
Speaker 2 (18:12):
Big time.
You have to decide how you doit, the way we've been doing it
at IT Harvest.
So we've got our own database,of course, with 4,000 vendors,
11,000 products.
We embed that just in a big ragso you can query it and you're
basically querying it with Cloud.
(18:34):
But we launched that to endusers.
We got 300 end users withindays.
They were asking questionsoutside Cloud products and
vendors right, like, hey, youknow what's the best way to
organize a sock or somethinglike that.
So he said, ok, we got to alsoquery, you know, an outside
(18:55):
general purpose AI likeperplexity, which we did.
So now we have two answers tothe questions and we give them
both to Claude and let Claudedecide what the best answer is
combining or giving it just oneof those.
So that's a.
You know we're relying onClaude to make a judgment call
(19:18):
as to match between the questionand the answer, and so that's
one way.
The other way is voting and youdecide.
And that's the way self-drivingcars work.
They'll be at least in Teslas.
There's two massive GPU-basedchips in the vehicle and when a
(19:41):
decision is being made to slamon the brakes or shift gears or
turn right or turn left, or turnthe turn signal on both of the
chips have to come the samedecision to do that.
Speaker 1 (19:53):
Okay, okay, so kind of like being in a nuclear
submarine or deciding to launcha nuke, both people to turn the
key in.
Speaker 2 (20:02):
Yeah, that's brilliant, I hadn't thought of
that yeah, or two people youknow signing a digital
certificate?
Yeah, In many, many cases Huh.
Speaker 1 (20:11):
Well, would you look at that, Richard?
That's why they pay you the bigbucks.
Yeah, that's smart.
Okay, so let's move on to theSOC.
In the time that we have left,what's going on in the SOC
market?
Oh my gosh, Not the stockmarket, but the SOC market.
You've got all the data.
Speaker 2 (20:34):
Well, this combines the two because yesterday
Zscaler announced that they werebuying Red Canary, one of the
top players in the modern MSSPspace.
So right up there with I don'tknow ArticWolf and eSentire and
those guys with I don't knowArticWolf and eSentire and those
guys, and Zscaler, of course,is had.
You know, it's confusing to themarket right now.
(20:56):
Confusing to me.
The market seems to love itbecause Zscaler's up I don't
know 20% or something.
But it's confusing becauseZscaler went to market with a
SaaS solution where theybasically filter all of your
traffic going in and out andkind of obviated the need for a
SOC for their big customers.
(21:18):
So now they bought atraditional SOC management MDR
company.
The language around thejustification for it had
something to do with AI.
I'm like, hey, maybe I'm notsure.
I believe that it wasn't bigenough into AI, but it did raise
a very interesting issue.
Instead of all these startupsgenerating AI agents and then
(21:43):
selling them to companies likeMSSPs, why not the MSSPs develop
their own?
They know the problem thatthey're facing.
They can just hire some reallysmart developers and create
their own.
And now they're not selling youthe agent, they're selling you
the result of having an agentdoing all the you know the early
(22:04):
heavy lifting for tier oneanalysis.
Speaker 1 (22:07):
Yeah, yeah.
What would, just for myedification, what would be some
of those outcomes?
What are some of the results?
Speaker 2 (22:14):
Yeah, so they're great.
I saw a great demo today Okay,somebody remotely logging in
over VPN, and the solution I waslooking at was actually
profitai and it's awesome, right.
So first it generated the listof questions to ask the other
(22:39):
agents.
So things like you know reallycool ones you know are hey,
check the person's calendar.
Are they taking time off rightnow?
In other words, are theytraveling so they could be VPN
in in from some strange location?
In this case, mexico wasexample.
(22:59):
Um, do they?
Um, you know, is there anythingin their email that indicates
that they would be logging inremotely?
Have they used this open VPNbefore?
Yes, they have.
So you walk all the way throughthat, something that would
literally take you 10, 15minutes of investigation.
You can answer in 20 seconds,but have a complete analysis of
(23:24):
what they did, you know to thepoint.
No human would ever botherwriting down all the questions
they asked and the answers theygot, et cetera, but it's free
once you got the AI there to doit.
So that's just an example.
You know, repeat that thousandsof times a day for a large
organization and you've gotinstant cost savings.
Speaker 1 (23:43):
What are you seeing in the consolidation of this
space?
Do you see consolidationaccelerating?
Do are you able to track howfast companies are consolidating
?
Because I've got a little youcan't see it here, but it's an
imaginary um, uh countdown whereat some point there will only
(24:05):
be a handful of socks, right,and you know, right now you've
got a lot, not to be confusedwith underwear so a handful of
socks, that's.
I'm down to a handful of socks.
I need to go shopping, butthat's neither here nor there.
But if you're looking at ahandful of SOCs at a certain
(24:33):
point, are you able to trackthat consolidation?
Speaker 2 (24:35):
And if so, okay, oh, yeah, we'll be able to, because
it's really hard to know whenGeneral Motors decides to
outsource their security to oneof these MSSPs.
Maybe they have, I don't know.
Very, very difficult to trackthat.
So the only SOCs that you cantrack are the MSSPs.
Maybe they have, I don't know,very, very difficult to track
that.
So the only SOCs that you cantrack are the MSSPs.
And, of course, the vendors ofSIMs and other tools.
(25:00):
And all these agents will knowwho's got a SOC because they're
their primary customers, theirICP.
So, yeah, it's going to besuper difficult to tell if
that's happening.
Now, mind you, there are manyorganizations that will not
allow their data to becommingled with somebody else's
(25:20):
data, right?
So they're not going tooutsource to an MSSP.
So Lockheed Martin, right,they're always going to have
their own internal SOC.
A lot of organizations are likethat.
They have to.
You know, your classic RedCanary doesn't see the 15
separate Chinese APT attacksthat are happening every day at
(25:43):
Lockheed.
So they need that specializedexpertise.
Speaker 1 (25:46):
So they need that specialized expertise.
With this shift, do you thinkthat there are going to be
employment opportunities?
Because it seems like thevendors may be disadvantaged.
The Lockheed Martins of theworld they're not going to
outsource, so what are theemployment opportunities that
you see in this?
Speaker 2 (26:01):
space prompt engineer or anybody who's able to
architect what I call applied AIor applied gen AI, then the
world's your oyster.
(26:21):
You'll have many, many jobs tochoose from, and that's what
everybody should be looking todo, right?
If you're not going to buildyour own AI directly, then you
should be looking at applyingthe knowledge that you've
acquired since ChatGPT came outtwo and a half years ago, and
you should be consulting.
You should be hired intoorganizations and just working
on anything to do with AI.
Speaker 1 (26:41):
All right, shout out to my friend Jenna Gardner.
She's already there, good.
Speaker 2 (26:46):
And my daughter, who's just found she was
interested in instructionaldesign, got hired into an IT
department a year and a half agoand all of a sudden she's the
AI expert for education in amajor state university.
Speaker 1 (27:04):
I will be launching I don't know exactly when I'm
doing preliminary research tothe local schools here in
Savannah and there's a huge needfor people to educate schools
and students on AI, especiallyplaces like Savannah Not
knocking Savannah, but it is myhome now.
It's my local community.
The schools here have some ofthe lowest scores in the entire
(27:28):
country.
Schools here have some of thelowest scores in the entire
country and I think it would bea testament to the technology of
AI to be able to put that powerinto the hands of people.
And we can measure that notjust in academics but in real
world entrepreneurship.
Speaker 2 (27:41):
Absolutely.
There was a study just came out.
It was done in Nigeria, youknow, which has a fairly
traditional educational system.
It was done in Nigeria, youknow, which has a fairly
traditional educational system,and they compared the results
from six weeks of AI-assistedlearning to two years of
traditional learning and theAI-assisted outperformed the two
years traditional.
Speaker 1 (28:01):
Wow, makes total sense.
Speaker 2 (28:04):
Yeah, I mean, I use it to educate myself on
organizational theory, onanything you know.
Yeah, it's, they can draw onall the historical background.
Yeah, you can say you know?
Ok, dumb that down for me,explain it like I'm five.
Ok, that's two.
You know, I'm really 12, notfive.
It'll just.
(28:24):
It'll just keep coming at youwith better and better ways to
learn.
Speaker 1 (28:29):
And let me just attack something here head on
the hallucinations Everybody'slike.
Well, it hallucinates.
Is it going to give me thewrong answer when I ask it
something?
It's not so reliable.
Why would I want to be educatedby something that hallucinates?
Look man, you go out there andyou ask the average person any
of these questions, you're goingto get flat out wrong
information, misinformation, andyou will have no way to
(28:51):
validate it Right.
When somebody I still have inmy memory bank so much wrong
information from when I was akid, I know Me too.
Right.
So they tell you all kinds ofweird stuff when you're young
and you don't question itEspecially if you have older
brothers and sisters.
Right what's right or what'swrong.
So let me just put that to rest.
(29:12):
If you're listening to this,listen closely.
Chat GPT Claude Deep Seek.
Even they hallucinate, yes, butit is way better than going out
there into the real world andtrying to find experts to learn
about the world around you.
Because, number one, that'sslower.
(29:32):
Number two, you're going to getmisinformed.
Number three, people will flatout lie to you.
But at the end of the day, ifyou're really talking about 20
years of being educated by AIversus 20 years of just
naturally going out into theworld, yeah, you might not get
everything right with the AI,but I think you're going to be
(29:52):
further ahead with the AI thanif you were to just go out and
try to get that information fromthe real world and tell it to
show its work right.
Speaker 2 (29:57):
Don't just tell me the answer.
Tell me where you found it andhow you derived it.
It'll give you the links andyou go look at the sources, see
if you think they're credible,right, you.
And see if you think they'recredible, right, you verify.
Speaker 1 (30:07):
Just like anything.
Yeah, yeah, All right, Richard.
Anything else to be said on theSOC before we wrap up?
Speaker 2 (30:12):
No, I think.
For now anyways, it's the mostexciting area that I see out
there.
There's plenty of other areasfor AI to address Vulnerability
management, red teaming, justattack and penetration, but we'd
talk about those in othersessions.
Speaker 1 (30:29):
Yeah, yeah, and I really want to talk about
compute costs when it comes tothe SOC.
So stay tuned to Cybernomics,your one-stop shop for
everything.
Cybersecurity economics.
Richard Steenan thanks againfor joining me today.
Oh, I didn't do the whole.
Where can people find you thing?
(30:50):
If people want to find youbecause I want them to find you
go to Richard's house.
He's going to be hiding underthe table.
No, I'm kidding.
If people want to find you, howcan they find you and how can
they learn more about IT Harvest?
Speaker 2 (31:04):
Yeah, they can find me on LinkedIn.
That's the easiest way and,unlike a lot of people, I
actually have my contactinformation.
So a lot of people don't knowthis, but on LinkedIn there's a
little clickable link that sayscontact info and it'll have my
phone number and my emailaddress, so you don't have to
ask me.
You can also look up mySubstack, where I write about a
(31:26):
lot of stuff on thecybersecurity industry.
That's steenansubstackcom Checkout our website.
It-harvestcom Check out thelist keeps going and it's going
to get bigger and bigger.
Harvestiqai is our chatbot thatI described.
That will query multiple AIs toanswer your questions,
(31:50):
including our data, and then, ofcourse, dashboardit-harvestcom,
which is our platform forcybersecurity industry research.
Speaker 1 (31:59):
I got to ask do you get spammed having your email
address publicly?
Never.
Speaker 2 (32:05):
Wow, never.
The only place I get spammed isthe form contact form for IT
Harvest Press, which is just aWix website, and people tell me
you know my website needsupdating and I go yeah, thanks,
I know.
Yeah.
Speaker 1 (32:21):
I get those calls all the time Wow, oh, we saw your
website, bruning Media, and wethink that we can do a better
job.
I'm like Eden worked her assoff to build that website and
it's a great website.
Don't call me telling me thatyou can do a better job.
I mean number one.
Speaker 2 (32:39):
I don't believe you.
Don't do that.
Don't do that.
Speaker 1 (32:43):
Don't do that and don't spam Richard, all right?
Well, thanks for listening tothis episode of Cybernomics.
You can find me on LinkedIn.
If you want to learn more aboutBruning Media and what we do,
check out bruningcomB-R-U-Y-N-I-N-Gcom.
See you later, see ya.
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