Episode Transcript
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Speaker 1 (00:00):
This is the Art of
Network Engineering, where
technology meets the human sideof IT.
Whether you're scaling networks, solving problems or shaping
your career, we've got theinsights, stories and tips to
keep you ahead in theever-evolving world of
networking.
Welcome to the Art of NetworkEngineering podcast.
In this episode, we're pullingback the curtain on one of the
most transformative forces intechnology.
(00:20):
You might have heard about itartificial intelligence, ai.
Ai isn't just helping usoptimize networks.
It's redefining how wetroubleshoot, secure, scale and
even think about infrastructure.
And it's not stopping therefolks, from smarter home
assistants to predicting networkoutages before they happen, ai
is touching just about everyarea of our lives.
Oh, and full disclosure, thisintro was written with AI.
(00:42):
I'm reading it off the screen.
So if it starts recommending, Idate a Roomba blame the
algorithm.
Joining me today is ourresident AI expert, the man who
can explain neural networksfaster than you can say chatbot,
jeff Clark.
What's up, jeff?
Speaker 2 (00:56):
Not too much.
I feel like the AI wrote insome praise that I maybe didn't
deserve on that.
I wouldn't call myself an AIexpert.
I would totally call myself anAI enthusiast, though.
Speaker 1 (01:07):
That was so weird.
I've never read an intro.
I tripped over it a bunch oftimes and kept screwing up and
if you ever wondered how muchI'm prepared and reading off of
notes for the show, it's zero,because I can't even read a
one-paragraph intro.
So in this episode, jeff had afantastic idea I so in this
episode Jeff had a fantasticidea.
I guess we talked about AIbefore Jeff.
Speaker 2 (01:28):
Well, we talk about a
lot of things on different
episodes and AI.
You can barely get through 10minutes without me bringing up
AI two or three times, becausethere's just a bunch of stuff
happening in that field that I'mreally excited about.
So, yeah, we talked about it ina previous episode and one of
the things we had talked aboutwas how much I was using it and
(01:48):
how you were starting to use it.
And then what kind of sparkedthe idea for what we're doing
right now, which is differentthan the typical A1 podcast, is
this one's more visual Like're.
We're kind of we're doing a bitof a show and tell here and um,
it's because there's a lot ofstuff we talk about like, oh,
(02:10):
I'd love to see that sometime,or oh, that you know I should
learn how to do that.
Or I would love to learn topush that out, to get and I
figured with these show and tellepisodes they.
It may make sense to do more ofa visual one on this.
I don't want to take away fromthe longer form podcast, but
maybe these are little sidejourneys doing that.
So I thought I'd show you how Iwas using AI.
You and I were talking earlierabout some of the ways you're
(02:30):
doing it, so I figured we'd justhave a good conversation.
Maybe share our screens a bit,show what we're doing, Because
every time I talk to someoneelse who's an AI enthusiast, I
learn a new trick that I wasn'tdoing before, and so I thought
I'd share what I'm learning andhopefully you have some stuff
you can share with me.
Speaker 1 (02:48):
That sounds really
cool.
So, yeah, good, call out forthe audio only listeners.
I will do my best to keep youin mind, because we get way more
audio downloads than we doYouTube views, so I will try to
visually.
You know what is it?
What do they call it?
Theater of the mind.
I will try to paint a picturewith my eloquent words on what
(03:10):
we're doing, but if you'relistening to this and it sounds
compelling and you think youmight want to watch it, you can
watch this on our YouTubechannel.
It's at Handle Art of NetEng.
And right before we started thepodcast, jeff and I were talking
about kind of my and we can.
So Jeff's going to show us somecool stuff.
I think the idea of the showwas hey man, I do all this
(03:31):
really cool stuff with AI.
I'd like to show it sometime.
So that's what we're going totry here little different format
for the show, so bear with us,but I think it'll be cool.
And something else I sharedwith Jeff I am a person who,
when AI first popped, I was notexcited about AI.
I was intimidated about AI andI thought that it was going to
(03:52):
be overall, not additive tohumans.
But, you know, do things thatwere nefarious and bad and you
know, whatever Right.
And that's not too differentthan my automation journey,
which again I mean Jeff and I.
When did we work together?
10 years ago, 15 years ago?
It feels like forever ago.
Speaker 2 (04:10):
Oh yeah, I know.
Speaker 1 (04:11):
We worked together in
another life, right, and you
were automating.
Then I didn't even think aboutautomating, but for years I had
been saying I don't likeautomation, I don't want to be a
coder, I don't want to do thisstuff, they're going to take our
jobs, blah, blah, blah.
And here's why I'm telling thisshort little anecdote is
recently the world of AI.
So I've been dabbling in AI andI've been dabbling a little bit
(04:34):
in Python, just barely.
But something happened to merecently where these two worlds
kind of converged and all of asudden I have this fire lit in
me like oh my God, because Irealized what I can do with the
help of AI.
And the tooling has gotten sofar now that I won't get into
the details, but I was sharingwith Jeff earlier that I'm
(04:54):
working on building a SaaSproduct Me Okay, developer, andy
.
Well, great.
But here's the interesting thingand it sounds crazy.
So I had Erica Dietrich on herenot too long ago and we were
knocking on the vibe coders andlike you don't understand code
and all this stuff and listen, Ifeel that you need to
understand coding to write code.
(05:15):
However, I listened to thisDiary of a CEO podcast that I
can link to in this show, but hehad some AI experts on and some
entrepreneurs and that I canlink to in this show, but he had
some AI experts on and someentrepreneurs and they were
talking about how you can promptChatGPT on an idea, something
you want to build.
You can have it code for you.
Then you can go to thisplatform called Replit and I
think for 20 or 25 bucks a monththey also have their own LLM
(05:37):
that you can talk to and it'llcode for you.
But I can talk to the machine,tell it what I want, the.
I can talk to the machine, tellit what I want.
The machine will create thecode, build it, deploy it for me
, show it to me and we can justiterate from there.
So we've gotten to a point thathas gotten me so excited,
because I have an idea and Idon't have tens of millions of
(05:58):
dollars in VC funding and a teamof 30 developers to build this
thing, which is what you alwaysneeded forever.
So again a couple years ago,I'm like, oh my God, ai is going
to destroy everything.
And now I'm like, oh my God, Ithink AI is going to allow me to
build a SaaS product withoutalmost any coding knowledge.
So that's a long way to say Iam really excited and a little
(06:18):
nervous for all this AI stuffgoing on, but Jeff has some
really cool, I think, use casesand we're just going to get into
, I guess, how, jeff, you use AI, maybe in your daily life,
maybe in your job.
I could share a couple ofthings, if we like.
So where do you want to starton this AI show of?
These are things you can do inyour everyday life and or job,
(06:38):
and how you can leverage AI tomake it better easier.
Speaker 2 (06:46):
Is that kind of a
good framing, yeah, I, I mean.
So what I don't want to do is Idon't want this to have to have
to be too stodgy and how tohave to follow a format.
Um, what I, what I did is Icame up with, uh, really, three
ideas that I wanted to you, andit's kind of based around you,
because this is kind of a let'shopefully teach andy something,
and so what I wanted to do iskind of cover the three
(07:06):
essentially jobs that I see thatyou have, the first one being
our podcaster right, yeah, thepodcast.
The second one being you workin marketing and something like
that for Nokia.
And then the third thing isreally you're still a network
engineer.
I mean, at heart, and at leastin what your background is,
(07:28):
you're a network engineer.
So I wanted to show some of thestuff that I'm doing just in
networking to make all of thatwork for me.
And now you have primarily beenworking.
You said Replit and JetGPT.
Are those the two things you'reusing right now for AI tools,
or what do you primarily use?
Jetgpt?
Are those the two things you'reusing right now for AI tools?
Chatgpt?
Speaker 1 (07:46):
is the only thing
I've been using.
I do pay for whatever thepremium is.
I haven't used Replit yet, butthat's kind of my next step is
to go in there and mess around.
But basically, chatgpt, Istarted with the free one and I
started to see its value and I'mlike, oh, wow, this is actually
, you know.
I again to frame this correctlylike if I was writing a paper or
I mean, I'm in marketing now,like I am not going in to chat
(08:07):
GPT and say, do my job for meand then taking what it gives me
and then going, oh, here, let'spublish that and you give me
money for that.
But why I really like chat GPTis it's an incredible like
brainstorming idea.
Like if I need a title forsomething you know, give me
tight, I can give it a blog thatI've written and say, hey,
generate you know a list ofcompelling titles, right.
Or for the podcast, like hey,because, listen, we're 160
(08:30):
something episodes in five yearsin.
And like 160, said I don't wantto say I'm running out of ideas
, but it's seen, it feels hardernow than it was in the
beginning when we were atepisode one.
So something I'll do is like,hey, look at all the episodes
we've done.
So I'll go to ChatGPT just forinspiration, ideas,
brainstorming, so that's kind ofhow I've been using it.
Speaker 2 (08:51):
Yeah Well, why don't
we do this then?
Since you know ChatGPT, we'llend with that and I'll show you
some of the stuff I'm doing inthere, but what I wanted to do
was introduce you to a new toolthat, for me, has really, really
been taking off, which isNotebook LM.
I don't know if you've seenthis before.
You've probably certainly seensome stuff on YouTube or heard
(09:12):
these podcasts, that podcaststhat Notebook LM can put out.
Have you heard about thisproduct at all?
Speaker 1 (09:19):
I have not Tell me
about it, okay.
Speaker 2 (09:20):
So what Notebook LM
does is it allows you to put in
a bunch of sources.
So in this case, for example, Igrabbed the last, I don't know.
Let me see 50 differentepisodes.
I think you can do like 60different sources in this.
You might be higher by now, butI can basically put in a bunch
of different sources and create,say, a notebook about that, and
(09:43):
then I can do really coolthings with that, like create a
mind map.
So out of the last 50 episodes,I clicked on this mind map
button and it created a mind maphere that shows some of the
core things that we've talkedabout in different episodes.
So under core networking stuff,we talked about DNS, ntp, ipv6,
and then useless, which isfunny.
(10:04):
Which is funny because thesewill probably bring up some of
the episodes that these wereabout.
This one I recognize fromFirewalls or Our Friends In here
.
We talked a little bit aboutedge and perimeter and internet
connectivity.
So this is taking the last 50episodes that I popped in here
and it created this really coolmind map.
And then if I wanted to divedeeper into maybe what we talked
(10:28):
about under that topic, so ifwe got into edge, perimeter, I
can click on that, and whatthat's going to do is it's going
to create a summary of what inall of these different resources
so, whether they're in thiscase, I've done YouTube videos,
but they could be YouTube videos, they could be PDFs, they could
(10:48):
be your blog posts it's goingto put together a comprehensive
list of any time we've reallytalked about perimeter edge
security, so, and then each oneof these you'll notice there's a
reference so I can click onthis.
That reference is going to showme oh, this is going to take us
to this video.
It won't actually play thevideo in here, but it'll show me
(11:10):
which video we were talkingabout this in.
It'll give me a summary of thevideo.
It's a really, really cool wayto take a ton of information
that you've got from maybe abunch of different sources and
bring it into one thing.
Speaker 1 (11:22):
I have a comment to
make.
So I love mind maps because Idon't know if I'm a visual
learner or if I just love.
You know I like to see stuff,so mind maps I'm a big fan of.
So for those listening Jeff'stool he trained, so I guess
you're training it right, thestuff you fed it Like.
Here's your information that Iwould like you to focus on.
Yeah, exactly I information thatI would like you to focus on.
(11:43):
Yeah, exactly, I love that whenyou click mind map, it gave.
So what did it give?
It gave all the topics you goback to it.
Yeah, so, network engineering,concepts and careers.
So is that just the overall?
Because what I was thinking asyou were doing this is part of
what you do, part of what I tryto do as a content creator.
I don't want to keep doingcontent that people like which
sounds fine to say, but likeokay, well, so no.
(12:04):
Like which sounds fine to say,but like okay, well, so no, no,
no.
So I like to talk about thingsthat I think are relevant in the
industry, that people are goingthrough, that are going to help
the listener.
But there's also the beast youhave to feed of like well, how
can we get more people to listen?
How can we get more peopleengaged If we're not reaching a
wider audience?
You know it's more people thatwe could help.
So what I've, what I've tried todo in the past, is you look at
the episodes that have done.
(12:24):
Well, you know, if we get 2000downloads an episode and then
one gets 5,000, huh, you try tofigure out, like well, what is
it about that content thatresonated so deeply with the
audience, and can we do more ofthat, Because I'd like to give
people more of what they enjoy?
Um, even if so, as you'rewalking through this, I'm like
huh, I wonder if I could plugour statistics from our host,
(12:48):
the hosting thing, but if it hasall the transcripts and then it
has all the episodes, and thenI can look at the metrics and
then show me what is in commonacross our best performing
episodes.
Speaker 2 (13:09):
So, anyway, I know
that's not what we're doing here
, but what an amazingapplication of this technology
to help me do something thatI've been struggling to do.
I'll show you another example.
You actually brought up EricaDietrich earlier.
So what I'm going to do is,rather than coming in here and
putting in resources, sometimeswhen you're trying to research
something, you don't know whatresources you want to put in.
So Notebook LM lets you put indiscovery stuff.
So in this case and I havealready copied and pasted her
(13:30):
information or copied herinformation here so in this case
I want to research Erica, right?
So maybe she's going to be aguest on the show.
I want to know what's Ericabeen doing.
I'm also going to give it kindof her handle so I know how I
might recognize her on theinternet.
And Erica is a good examplebecause she puts out content on
the internet.
So there's going to be somegood stuff about her.
But again, I want to bring inresources that I know are good.
(13:51):
So I'm doing a discovery.
So it's going out to theinternet and it's looking for
stuff that she's produced, stuffthat she's been in.
So here's some stuff whereyou're chatting with Erica
Dietrich talking about developerstuff.
So I'm going to go ahead andI'm going to import these
resources I could go to.
Let's go find her.
Speaker 1 (14:12):
I'm of course,
interested if her A1 episode is
in there, and I think I did seeit in their developers.
Speaker 2 (14:17):
It might be, I didn't
even look.
Speaker 1 (14:19):
I pulled in.
Yeah, I saw so let's grab this.
Speaker 2 (14:22):
I'm going to throw
this in as a resource that we
might want to use, so I'll addthat that's going to be a link
for a website, so we'll put thisin here and then, as I'm doing
some research on Erica, I'm justgoing to go ahead and hit that
mind map button.
I have no idea what it's goingto generate, but, again, this is
while I'm trying to do someresearch on Erica.
(14:43):
I want to get to know a littlebit more about what she's doing
and where she's been at.
So here we've got this mind map.
It's put up.
Developers should attendsecurity conferences.
Inside of this we've gotbridging the gap between
innovation and security.
So these are all recent topicsthat I know she's going to be
knowledgeable on.
I can dive a little deeper intothese and lack of security,
(15:05):
development and training.
So there must have been somestuff she was talking about on
that.
A lot of people never tookcourses, unaware of good courses
.
No time, okay, these are allsome things that when I'm
interviewing her, I might wantto know about.
Maybe I want to know, I don'tknow learn secure coding, best
practice.
All right, let's see what elsewe have over here.
Developer versus networkengineer.
(15:26):
This looks like something fromour podcast.
Ah, the divide and the riftbetween network engineers.
So, again, I can now startdiving into these things that
she has already contributed tothe internet, and then I can
start learning more about Ericaby diving into one of these
topics.
But the other nice thing is Ican now do what I call having a
(15:47):
conversation with thesedocuments.
So, yeah, this is the summary ofwhat I was clicking out of the
mind map, but if I wanted to, Icould just kind of start from
scratch here and say, write up abrief I don't know introduction
of Erica for an upcomingpodcast.
(16:08):
Make it two paragraphs.
So it's going to write twoparagraph max, but it's going to
be pulling from all of thisstuff.
So it's not like I just went inand I had to come up with a
bunch of stuff on her.
It's going in and it's pullingto the end.
Today our guest is EricaDietrich, known online as
whatever.
She found all this stuff.
She's a developer advocatespecializing in security,
recently worked at cisco,basically a lot of the stuff
(16:30):
that we even talked about.
The podcast, but it was able topull all of this right from
these resources and what'sreally cool about this?
Is that unlike, uh, if I wereto just go to google, or even if
I were to just go to chat GPTand just get a request?
Speaker 1 (16:43):
I've been using chat
GPT like this, so what's the
advantage of this?
Speaker 2 (16:48):
So the advantage of
this is kind of I think we
talked a little bit before thisthat you're starting to do
custom GPTs, which we'll talkabout in a minute here.
But essentially I'm giving it alimited amount of data rather
than giving it the wholeinternet, because AI gives you
better results if you give it alimited scope of information to
(17:10):
deal with.
Speaker 1 (17:11):
That's news to me.
That is very importantinformation.
Speaker 2 (17:18):
And it kind of makes
sense because, let's say I were
to say, hey, andy, tell mewhat's been going on.
It's a really broad question.
But if I were to turn to youand say, andy, I'd love to know
what's going on with your kids.
What are they doing in sportsthese days?
I've now given you a directionthat now you can really go down
and you can give me a lot moredetails.
On something more specific, aiworks the same way.
(17:40):
If I can give it a set amountof data to pull from, it's going
to give me the best detailsfrom that data.
It's not just going to bewilly-nilly pulling information
from everywhere, so it means Ican also pick and choose sources
, like I was doing some researchearlier on some of Fortinet's
products that are somewhat newto me, and one of the resources
(18:02):
I found was Reddit.
I'm like, okay, that's foranother day.
I don't want Reddit to be my.
It's not going to be my sourceof truth, but maybe anything
from Fortinet's webpage I wouldconsider a source of truth
Anything from Gardner, anythingfrom you know, whatever I can
look at those sources and saythese are reputable sources.
So that's what I think theadvantage of this is over at
(18:23):
ChatGPT is that it lets mecreate a notebook with just the
sources I want.
The other place that's reallycool is it can work with your
own documents.
So I can go into Google Docsand I can look at my own folders
here, because this is a Googleproduct.
So back in the day, tech TipTuesday I used to do a podcast
(18:44):
called Tech Tip Tuesday.
So these are all of my podcastepisodes and scripts that I had
written.
So I could bring all of thesein and I'm not going to yeah, I
could add all these in here asresources, then start
interacting with old episodes ofTech Tip Tuesday from back in
2011.
So I would have all these asresources to pull from back in
(19:07):
2011.
So I would have all theseresources to pull from and so I
could say things like give me alist of topics covered already
in the podcast.
So that's going to look throughhere.
It's going to find me a list oftopics.
It's going to generate thatstuff and again, I'm working
from my own content.
So it's the kind of thing that,let's say, you have a bunch of
PDFs on a product that you guyshave over there at Nokia, or
(19:29):
you've just got a bunch of whitepapers, which are an absolute
nightmare to read.
You can put all of this stuffin here and start pulling it in.
Look at this Back in 2011,.
Stuff that was important to mewas nightnightcom, mailchimp,
memolane.
Qr codes were a brand new thingback then, so it's kind of a
(19:51):
fun way to look back down memorylane on, in my case here, old
stuff that was in my documents.
Speaker 1 (19:57):
So would this be
similar to?
I know you said we'll get intoit later, but would this be
similar to training in customGPT, where you constrain?
I don't really understand howthis stuff's working, but when I
create a custom GPT I give itspecific set of information.
This seems kind of similar,right.
Speaker 2 (20:14):
It is not similar,
it's identical.
It's exactly what I'm doing.
Speaker 1 (20:17):
When I create a
custom GPT, it doesn't go out to
the world and pull ineverything, it's just using what
I feed it.
Does that sound right?
Speaker 2 (20:23):
Correct.
And then within the custom GPTyou can.
You know we'll talk aboutcustom GPTs in a minute here,
but you can absolutely go abunch of different directions,
like telling it specifically tosearch the web and specifically
search certain sites.
Speaker 1 (20:36):
But it seems similar
to this where you just here's
what I want you to look atconstrain yourself to this and
to your point.
I've gotten much better resultsin certain situations with a
custom GPT than I do with thegeneral model you mentioned work
for both of us.
So just a quick aside have youso you're in the security space
for Fortinet?
Has the I don't want to say theintroduction of AI, because
(20:59):
we're past that but has AIchanged your job or your scope
of work job or your scope ofwork, or have you like, for me,
I have to learn about ai,networking and inferencing and
training and back end andlossless and rocky like, just to
be able to have conversationslike.
Oh yes, I know these things, wecan talk about this.
My, my buddy, phil gervasi um,gave me this book, machine
(21:20):
learning for network engineers,and yeah, and which I've been.
You know I started a while backand then haven't gotten back
into it, but I think it's themath and the logic behind how
these systems work.
I don't know if I need to gothat deep, but again, I'm
somebody who wants to understanda little bit of what's
happening under the hood.
So I'm just curious from asecurity perspective.
Does AI present your verticalany different challenges, or
(21:42):
you're not really having to dealwith it yet?
Speaker 2 (21:44):
So the biggest
challenge we have right now is
around how we make sure thatpeople are not feeding AI
information that they shouldn'tbe feeding to it, and a lot of
that comes down to what we callDLP or data loss prevention, and
it's all about, hey, how do wemake sure that proprietary
information isn't being sharedor isn't being used to train
(22:10):
some AI somewhere?
And that is part of the problemwith this.
I mean, you've been workingwith the AI long enough now that
you know that you can havewhole conversations with that.
I mean, the amount of stuffthat ChatGPT knows about me, I
don't know.
Have you ever asked ChatGPTwhat it knows about you?
Speaker 1 (22:27):
I haven't yet, but
maybe I should.
Maybe not on an episode.
I don't know what's going tocome up, come back.
Speaker 2 (22:34):
I don't know.
I'm gutsy.
This is a lot.
We can cut it out if we need to.
Here we go.
Based in Depard, new Jersey.
You're into technology, audiobooks, scripting, building
things like html, javascriptsites, ios applications, ubuntu
servers, docker containers.
Talks about projects that I'mworking on.
Some of my preferences, like Ilike concise, clear answers.
(22:55):
Uh, talks about my personal.
I'm 46, got a son named logan,a wife named sharon.
Wow, I didn't realize it knewsome of this.
Um, I planned trips with my momand my daughter and I mean, if
this is just a brief summary ofstuff it just pulled out, but
this is all stuff that I've fedin the past.
So, to answer your question,the real scary part is, if I'm
(23:17):
feeding this thing, thisinformation and I'm security
conscious what are people whodon't necessarily think about
security giving it?
Are they copying and pastingcustomer information?
Like?
That's one of the things in ourtrainings right now.
We are all over making sure thatyou can't be copying and
pasting proprietary Fortinetstuff that's not supposed to be
(23:39):
out there to the public.
Be really cautious withanything that has customer data
in it.
Make sure that you eitherobfuscate that data or we have
some of our own internal AItools.
That's the big thing that Ithink, as a security
professional is concerned.
And then the real concern forme is that AI like you talked
(24:00):
about programming and scriptingAI makes it super easy to learn
how to hack something.
I mean, if you ever really wantto just learn to be an ethical
hacker, go into ChadGBT, tell it.
You're studying to be anethical hacker, you're using a
tool like Kali Linux and help melearn information about my own
network and it'll tell you howto hack your own stuff.
It's impressive and scary.
Speaker 1 (24:19):
Isn't that
interesting and that's the world
that we're in right now, andit's this double-edged sword.
I've gone in and asked it tohelp me, double-edged sword.
I've gone in and asked it tohelp me excuse me, with maybe a
problem I'm having or achallenge, and just have a
conversation with it, and it'sextremely helpful.
I'm trying to hack into thatwork or deal with a personal
challenge or learn sometechnology.
I remember you said, way backwhen, when we had an episode
(24:40):
that prepped for you, saying,hey, I don't know anything about
you know, whatever it wasAnsible, teach me Ansible.
And you said, in an hour youhad, you know, you were like you
were running a playbook, sothat's, that's helpful
information.
And just thought about thesecurity stuff.
I mean the same, the same withme, with with work.
You know, if it's, if it'ssomething that shouldn't be
public, we do have internal AItools, so that's nice and I'll
(25:01):
leverage those.
And then if I'm writingsomething a little more generic
or just trying to troubleshootor brainstorm, rather, um, you
know, I'll use it, but you haveto be careful.
The first story I rememberhearing was I forget what
company it was, but it was aginormous company and I think
they were uploading their code.
It was like proprietary patentpending whatever code and they
uploaded it to chat gpt for help, and then it just became part
(25:22):
of public domain and I thinklike somebody else grabbed it
right.
So, yeah, anything that you putin there, I guess, becomes
available to anyone using thetool.
Is that accurate?
Speaker 2 (25:33):
No, but it is being
used to train the tool, so what
does that mean?
Speaker 1 (25:38):
Train it on data?
Does it stay there forever?
Now it knows what you taught it.
Speaker 2 (25:44):
So let's give it as
an example.
Let's say that I have access asa developer to internal code
here at fortinet.
I don't, but yeah, let's sayfor argument's sake that I did.
And so I'm in chad gbt and I'mgiving it all this information,
saying here's the uh, you know,here's the new commands and
here's, here's the back-end codefor this.
Um, that ai model is nowlearning that this is
(26:07):
information that couldpotentially be helpful to
someone who's working onFortinet stuff.
And so when I'm saying I'mtraining an AI model, I mean
it's like if you post somethingto the internet to some degree,
it's not that it's necessarilypublic, but it's that it could
potentially be available,because this AI doesn't
understand that that'sproprietary code, right?
(26:27):
It doesn't understand thatthat's proprietary code, right?
It doesn't know that that wasproprietary code.
So I put this in here and nowsomeone asks for you know, hey,
can you give me a snippet ofFortinet's blah, blah, blah, how
to do this, and maybe it sharesthe future code that isn't out
yet, right?
That is the kind of thing thatcompanies are afraid of.
I don't know that in the worldwe have a bunch of examples of
that yet, but it's the thing.
(26:49):
That's the fear right, you knowit's what security
professionals are the mostnervous about is you're putting
this stuff out there.
I mean, it's the same thingthat's true of.
You know you're putting stuffinto a cloud environment.
If you're not careful in howyou secure that cloud
environment, that cloud couldbecome publicly accessible.
That cloud environment, thatcloud could become publicly
(27:09):
accessible.
So it's not that I put thisstuff in and you can just go and
say, hey, jeff has a son namedLogan, because Chad GPT knows
about it, but you are feeding itinto somebody else's data set
and you don't know what they'regoing to do with that.
So that's it Anyway.
So this is Notebook LM.
It's one of these that you kindof it's totally worth playing
with.
But the other piece, it is free.
(27:30):
There's some stuff you get withthe paid version, that is, I do
pay for the paid version.
What I've done is I've agreedin my own brain to put up to $50
a month into AI tools, and thatmeans I sometimes cancel
something and I'll try somethingelse, but that's my number
right 50 bucks.
So I'll pay for.
I pay for chat gpt and then Ipay for google's uh tool set,
(27:54):
which includes gemini, whichwe'll talk about in another
second here notebook lm, a bunchof other ai tools, that they
actually have some really coolthings.
Uh, in, let's go, gemini.
Speaker 1 (28:06):
I think I know the
answer to this, but why did you
decide to spend money everymonth on AI tools?
Speaker 2 (28:12):
So before the podcast
, we were talking about whether
we think AI will take our jobs.
I think AI could take the jobsof people who don't know AI.
Right, I certainly think thatpeople with knowledge of how AI
works and how to use AI aregoing to be more desirable
employees than people who don'tknow it in the future.
(28:32):
So I look at it in the same wayI had to learn OSPF, or that I
had to learn BGP.
These are important aspectsthat I just feel are important
to learn.
So, for me, playing with the AItools today is an investment in
what I think is going to benext year or the year after or
the year after I don't know sobut I just I feel like
(28:56):
understanding how thistechnology works right now.
I really genuinely feel likewe're in the beginning stages of
a huge, huge boom that's goingto be as big as the internet's
been in terms of impact to ourlives.
Speaker 1 (29:09):
And the speed it's
moving is like nothing you've
ever seen.
Yep, exactly right.
Yeah, that's.
I think that that's a goodphilosophy.
Yeah, I think that that's agood philosophy.
And just to put an ending tothat thought at least for me, or
my addition to that thought isthat in a capitalist system
where we always have to showgrowth and that's hard and blah,
blah, blah, and if I'm asoftware company and I have 50
(29:31):
devs, finish the thought, right,If I could have one dev.
So you said something earlierwhich I thought was compelling.
I don't know if it was on theshow or before, but using ai,
you feel like you have a smallstaff working for you.
Right, like your, your, yourefforts have been multiplied, I
think it's kind of how you putit right, like, and I feel the
same way I can get more done.
So again, as someone running acompany trying to reduce, uh,
(29:55):
what would it be, you know?
overhead right now my overheadso that I can increase revenue,
so I can make Wall Streethappier.
Whatever right Stockholders,the board, what happens?
This is why Andy was scared ofAI in the beginning.
I'm not even going to touch it.
What's going to happen to the49 developers that we don't need
anymore?
And extrapolate that number out, because one person can do the
(30:16):
job of 50 by using the AI?
Ai will do it.
The person that knows code willlook through it to make sure it
didn't do anything extremelystupid before they test and
deploy.
You know what I mean.
Like that's the future for me.
Speaker 2 (30:26):
I hear you, but I
think the difference, at least
for me, is I look at it from theperspective of.
The only reason companies tendto let employees go is because
they don't have enough work tokeep that employee going.
Right, the company is notproducing enough that that
employee is useful.
I feel like when you have let'ssay that you're a business with
10 employees and now all 10 ofyour employees can do the work
(30:51):
of 100 employees, well, thatmeans that your business is now
producing 100 employees worth ofstuff.
Right?
It's not that you don't have toget rid of your 10 employees.
Speaker 1 (31:02):
There's not people,
you're not going to hire that
might need a job.
Speaker 2 (31:05):
I mean again I'm
saying what's the?
Speaker 1 (31:07):
ramp up to get there.
I'm being the old guy yellingat class, the doom and gloom guy
.
I mean I get it.
And so, to circle back to yourpoint, you need to learn these
AI tools, and you need to learnthem yesterday because it seems
like there's potential for a lotof disruption and a lot of
places, and the differencebetween the have and the have
nots will probably be those whoknow the tooling, know how to
(31:30):
use them, know how to leveragethem.
If there's a job with twodifferent, you know, with two
candidates, and one person knowshow to use these tools that
make you crazy efficient and oneperson doesn't, which is why
I'm reading a machine machinelearning book because, like, I
would like to be part of thehabs.
Speaker 2 (31:44):
Okay, so cool I think
some jobs will go, but I also
think it's going to create someother jobs.
But yeah, absolutely.
Like I don't know the last timeyou called comcast for tech
support, but I'll tell you, I'drather be talking to an ai um as
a former comcast people guywho's been with your hands on
doing this stuff, no, no, no.
Speaker 1 (32:05):
What I'm going to say
is who's been with verizon
fires for eight years and wouldnever go back.
I know exactly what you'resaying.
Speaker 2 (32:13):
Yeah, yeah I mean,
that's true of anything, right,
you get, you get a bunch ofpeople in there that are kind of
your level one engineers, andit's rough, but AI figures a lot
of that.
But going back to this tool,notebook, lm, google tool yeah,
this is just another piece ofGoogle's.
I was just going to bring thisone up.
In terms of other tools Irecommend checking out.
Speaker 1 (32:33):
What are the suite of
Google AI tools that you use?
I guess Notepad LM is one ofthem.
Yep, of Google AI tools thatyou use, I guess Notepad LM is
one of them.
Do they have a homepage of?
Speaker 2 (32:42):
all their stuff, yes
and no, it's a little bit
disparate.
Notebook LM is this Notebook LM?
And then Google AI Studios isreally exciting because this one
I can do things like share myscreen with it and then ask it
for help on things Like hey, I'mtrying to get this to work,
what do I do?
And it and then ask it for helpon things like hey, I'm trying
to get this to work, what do Ido?
(33:02):
And it will walk me through me.
It's, it's literally walked methrough solving stuff on my own
products because I had to sharemy screen.
I'm like, listen, I'm on my ownFortiGate here and I can't
figure out what's going on.
And then it's like, oh, clickover here and click on that.
It's impressive.
It's like doing a screen share,uh, with with tech support.
So check out Google AI Studios.
Speaker 1 (33:20):
So, if you're working
in tech, if you're human in
tech, right now Gemini's comingfor you.
I'm not trying to be doom andgloom.
I'm amazed at this stuff andI'm also like, oh my God, that's
what a whole lot of people do.
But this is better.
This is probably better thanthem.
No, knock on them Like it'sjust because AI has become or is
(33:40):
becoming smarter than us, right?
I think that's the inflectionpoint, like uh-oh, right,
rewards.
So, okay, we're in Gemini.
This is Google AI Studios.
Speaker 2 (33:49):
Yep.
So now we're back to Gemini.
Gemini is like ChatGPT, butthere's a feature in both
ChatGPT and in Gemini that Ireally like, and it's called
Canvas mode.
So earlier before we started, Iwent in here and all I did was
I popped into Gemini and I saidI helped me build a unique,
interactive HTML and Java singlefile website that can serve as
(34:12):
a digital resume.
And then I said here'sinformation from my LinkedIn
profile to get you started.
Then also search the web for myjob description from previous
jobs and put some of it together.
Right, that's all I gave it.
And then I gave it.
I literally copied and pastedthe entire LinkedIn webpage.
So I mean it includes thingslike following and people I
follow, and I mean it's stuffthat I don't need.
(34:32):
But I was like, yeah, let's seeif I can figure it out.
And here's what it gave me.
It gave me I'm going to goahead and pop this out to a full
screen here, because it'sinsanely better than anything I
could create and it did this inabout two minutes, maybe three
minutes.
It put together a full website.
Here's my About Me section, mysuperpowers, making complex
(34:53):
technologies easy to understand,blah, blah, blah.
Then it came down here and itdid.
Something I didn't even thinkabout was if you look on my
linkedin page, it says Itranslate geek into english.
Right, because it's part ofwhat I do as an se is I take
technology stuff.
I sometimes have to break itdown into plain english for
people who maybe aren't astechnical.
Well, it put in this really coolgeek translator and when it did
(35:15):
it, initially I could only do acouple of things because it was
.
I would be like I'd put inFortinet and it would give me
the description I'd put inFortinet because it was very
programmatic.
But then it asked me.
It says would you like to useour API to make this geek
translator better?
And I was like yes, please.
So it now lets me put insomething like if I put in ZTNA
(35:37):
and there's still some stuff towork out here, like notice,
that's not very easy to read,but I put in ZTNA and it does a
great job, it translates us intoa single paragraph translation
stuff, which is awesome.
So it means I can build awebsite.
That was essentially my resumeand it could make this easy for
people to see and then it doessome little interactive stuff
(35:58):
down here.
Again, that was the entireprompt I gave.
It was what I showed you here.
But what's cool about thisCanvas mode is that I can look
at the code here as it createsit, and then I can preview what
it creates.
It'll do the same thing inPython.
It'll do the same thing in Bashand all these other programming
languages.
It'll let me see the code hereand work with it.
Speaker 1 (36:20):
That's amazing, cause
I I built a website for myself
and by built I mean justfollowed the templates, and I
think it was Squarespace and itdoesn't look anywhere near as
slick and cool as what this onedid for you Like I, I really
it's not perfect, it's not it'snot amazing, but it's it.
I really.
It's not perfect, it's notamazing.
(36:40):
It's better than I could do.
It's different If you're tryingto do a digital portfolio or a
digital resume.
I mean even the fact I'vealways loved your.
I Translate Geek into English.
I've heard you say that foreverand the fact that it added an
actual translator is just.
I loved it I would have neverthought of that.
It's really awesome.
Speaker 2 (36:56):
It was not something
that jumped out at me as an idea
that I'd even put on thewebpage, but now I'm like,
absolutely, I do that.
Then I tie it in with withtheir API stuff, and.
But what I like about it wasjust the ability to kind of go
back and forth between the code,and here's what the code looks
like at the end, and, yeah, itlets me build out something and
then be able to see it happenlive mode.
If I'm doing some writing inchat GPT, so we're back to chat
(37:19):
GPT, something you already know.
But if I go to write code andI'm going to say canvas, well, I
said Canva, give me an overviewof Canva.
All right, let me start fromscratch, because I just screwed
that up.
And I'm going to say canvas,we'll just do this.
We'll go into their canvas mode, which is Writer Code.
(37:41):
I'm going to say help me writean email to Andy telling him how
great he is, and what this isgoing to do is it's going to go
into a side-by-side writing mode, and so it starts doing this,
and what I can now do, though,is, if I'm writing a long thing,
I can be, like just in thisparagraph here, a little more
crazy, flowery, whatever,doesn't matter about the
(38:02):
spelling, and so what it's doingis, in this mode, it's only
changing that paragraph.
I can come in here and be like,oh, you know what, this is
really good for the people whoare listening.
Speaker 1 (38:11):
It says hello, andy.
I just needed to pause theuniverse for a second to shout
from the east top.
So truly, magnificently,intergalactically, great.
You are sorry, I just had toread the first sentence.
That's amazing.
I I have never received aletter like this and it would
make my day, week, month, life,probably.
This is so nice.
Be nice to someone, folks.
Speaker 2 (38:29):
This is so nice but
in this canvas mode, here's the
other really cool thing is thatnow this is also a regular
writing tool, so I can say thisis some other cool stuff about
you.
And then I'm going to come downhere and I'm going to say drop
a new line and I'm going to sayAskChatGPT and Art of Network
(38:50):
Engineering.
Speaker 1 (38:51):
You know, I don't
think I've ever used Canvas mode
.
I think I've tried.
Speaker 2 (38:53):
I haven't either
until recently.
Speaker 1 (38:55):
I think I have a
blocker like Privacy Badger or
something that I think blocks itfrom working.
So I think I have to disable itand mess around with it,
because this looks really cool.
So why do they call it Canvas?
Because it's just a workingcanvas of what you're working on
and then you can kind ofhighlight things, tell it to
change things, and it's kind oflike a paint canvas.
Speaker 2 (39:12):
Yeah, I don't know,
that's my guess.
Speaker 1 (39:17):
But that's how
functionality is right.
Yes, you're kind of just goingin and you're not having to give
it a prompt and watch itrewrite the whole paragraph over
again.
You can just tell it hey, thislittle thing here, do something
different.
Speaker 2 (39:26):
Yeah exactly so you
can have it rewrite.
So, for example, if I'm writingan email to someone, it's maybe
a long paragraph, or maybeyou're rewriting the intro to A1
.
You know the intro to A1, youknow you're like, oh, we need to
rewrite this thing.
You can come in here and thenjust manipulate the pieces you
want and then again, I can, youknow, start typing in my own
(39:48):
stuff in here, you know, andthen we're kind of working
together rather than with thetraditional way you work with
chat, dbt, it's.
It spits out information.
You ask it to change something,it spits out the same
information again.
The difference between this modeand Canvas mode is that I can
work I mean, it's a livingdocument rather than question
answer, question answer kind ofthing Compelling.
Yeah, so we've kind of talkedabout how it helps with the
(40:11):
podcast.
I showed you the interactiveresume.
But the other area where andthis kind of goes back to what
you were talking about withprogramming, but I've been using
ChadGBT for is stuff like thisyou know I'm building out, you
know, a lot of times I'mbuilding out in my labs and I
just need a base configuration.
I need to get, you know, thesethree boxes set up with the
(40:33):
minimum configuration for me toget to the gui on them.
So things I can do with chatgbt is I can grab a screenshot
of this and say help me build abase forti gate configuration
I'm just impressed you're stillusing gns3 I also use a, even g.
I've got them all diagram.
Ask me any questions.
(40:53):
You need to, and I want to dothis in canvas mode, so so I've
given it a picture.
Speaker 1 (40:58):
Why are you selecting
canvas mode?
Speaker 2 (41:01):
Because I want it to
ask me here and I want it to
spit out the code over here.
So this is the other piecewhere canvas mode can work.
Okay, right.
So step one IP address.
I need to confirm the IPaddress for each FortiGate.
So I'm going to say, for portone, I want to use the site ID
plus 100 in the fourth octet,see if that gives it enough
(41:24):
information.
So that should be 1092.201.101for branch one, 102 for branch
two, 103 for branch three.
Okay, this could all completelyfail on me here.
Great, so here it goes.
It's telling me okay, here'ssome assumptions.
And again, this is somethingyou've never configured at
FortiGate that I'm aware of.
So notice what this has done.
Is it looked at my diagramwhich, if we go back over here,
(41:47):
1092-201.1.
That's my gateway.
It was able to say, oh, that'sa slash 24.
And then all I said was in thefourth octet, I want to take the
site ID, which in this casewould be branch 1, branch 2,
branch 3.
And it was able to figure outthe 1092.201.101 is what I want
for branch 1.
And then it even gave port 2 a1.1.
(42:07):
And there it is.
It's already called a branch 1LAN.
Here's the step for branch 2.
Here's the step for branch 3.
And I can tell you just bylooking at this it's 100%
correct.
And now it's asking me hey, doI want to use the .1 Pladivall
gateway?
We're going to say yep, so nowit's going to put in my routing
information into all three ofthose configurations.
Speaker 1 (42:25):
So for anyone still
listening to the audio version
of this podcast, and I can'timagine there's anybody left.
But this is really compellingthat the picture that you fed at
the chat GPT was a very genericright, like a little cloud on
the top with a slash 24, threedevices down below a firewall
and it's spitting out beautifulFortiGate configs that Jeff says
(42:48):
are 100% accurate.
I mean, this is what I used todo to generate configs is I
would try to find other routersin the enterprise and steal
their configs and change the IPs.
You know what I mean.
Speaker 2 (42:58):
So this is really
amazing well, it lets me come in
.
I mean, I've even taken it totake configurations from one
device and convert them toanother, right, so I can say, oh
, can you take this thing from acisco asa and convert it to a
40k?
And it's not perfect, right,because it's.
I mean, it's yeah, it's justokay, but it it is far better
(43:20):
than I would have done figuringit out initially.
And so what ends up happeningis this is where I'm working
with it to get that stuff done.
And I'm just going to say itasks me what DNS?
Dns is fine, so it'll pop inthe basic stuff, pop saying
again it's going to do all mybasic routing, it's going to
build my ports, it's going tobuild the DNS configurations,
build the dns configurations and, uh, I'll have a working
(43:40):
configuration that I can popinto each of those three
fortigates and at least get intothe gui.
Afterward.
I said no on that, I just wantthis thing to finish.
Um, so this is the kind ofstuff that you can do in the
canvas mode because, like I said, it spits out actual working
code.
Uh, do you want to say the hostname for each?
Good grief, it's 20 questions.
I did ask it to ask me anyquestions.
Speaker 1 (43:57):
It needed to build
the base configs, but um, I have
no problem with that, right,You're having a conversation
with the agent and it's givingyou what you need.
I mean, if it didn't ask youthese questions, the config
probably would be less accurate,right?
So it's not necessarily a badthing.
Speaker 2 (44:12):
Well, yeah, because
all I did was I gave it a
picture, and so it's like allright, well great, here's the
stuff I need to know to reallymake this good.
And so here's what it's goingto build.
It's going to build interfaceswith static IPs.
It's going to build a defaultroute.
It's going to build a LAN toWAN policy, so it's anything
coming in on the LAN interface.
And then it's going to changethe host name, and no, I don't
want to change any SNMP stuff.
Speaker 1 (44:31):
It's doing a hell of
a lot better job than I would do
in creating a 40-gb config.
It's doing it pretty darn quick.
Speaker 2 (44:41):
Yep, and then I can
work with and literally copy and
paste.
So that's some of the stuff onthe network engineering side
that I use this for, and then ifI really wanted to go crazy, I
could say I may want to do this100 more times in the future.
Build me a script and it'llbuild out a script with the
correct props.
Speaker 1 (45:00):
I just had my brain
either just did something weird
or made a little connection.
But so you know, this is codegen, like you're generating
configs, like to me this lookslike the magic is that you gave
it a picture and it figured allthis out.
But would you ever use this,instead of something like
Ansible, to generate configs?
Speaker 2 (45:18):
Um, for, for the lab
stuff, like I'm doing right now.
Speaker 1 (45:23):
Absolutely.
You see where I'm going withthis.
Is this better than Ansible?
Is it similar?
Is it generating?
You know what I'm saying?
You're generating configs here.
I mean, I guess this isn'tautomation.
Speaker 2 (45:34):
No, but you missed
the last part I just did, which
was I took it and I said write ascript.
Now I said, yeah, I may want todo this 100 more times in the
future.
Well, may want to do this 100more times in the future.
Speaker 1 (45:42):
Well, it's what
prompted me to say Ansible when
you said I want to do this 100more times.
Now that you're repeating this,is this basically Ansible?
Speaker 2 (45:49):
It is an Ansible.
So if you think about whatAnsible is, Ansible is just
doing that.
It's taking the same, it'staking variables and it's
putting them into aconfiguration.
Speaker 1 (46:00):
What I see this doing
is Ansible, does so that's what
I'm getting at is like wow, Imean, I don't know if you use
this instead of Ansible, I don'tknow.
This seems to have moreintelligence and more
flexibility.
Speaker 2 (46:11):
So I would use this
to build the Ansible stuff,
because in the end, let's saythat I want to build a
configuration that's consistentacross everything.
What Ansible is going to do is,now that I've defined these are
my prompts my site ID, my LANIP, my subnet mask and my host
name.
That's what it's going toprompt me for.
It's going to prompt me for allthose things, and then it's
done.
I don't have to have this wholeconversation with it, but it
(46:35):
built out this Ansible scriptfor me now.
So this is the kind of stuffthat I think that if we really
get focused in on AI and wereally spend some time learning
it we're engineers, we like tofigure stuff out Most of these
things aren't going to beperfect, but they're going to
get us a heck of a lot furtherthan we could have on our own,
(46:56):
and it lets us expand ourknowledge at a ridiculously fast
pace.
Speaker 1 (46:57):
So how long do you
think it would have taken you to
write this line by line, byhand?
Speaker 2 (47:01):
The actual base
configuration for these?
Yeah, line by line by hand.
Uh, the actual baseconfiguration for these?
Yeah, well, I mean, I knowthese base configurations like
off of the top of my head, so Icould, you know, I probably
would have written a base configfor all three of those in maybe
10 minutes, right, which soundslike that's really fast.
But again, all I'm doing is I'mputting in a static ip, I'm
putting in this stuff, but whatI wouldn't have been able to do
(47:22):
in that same 10 minutes is thencreate an Ansible playbook
that's repeatable 100 times, andthat's what I was able to do
with this.
I was able to create a Pythonscript or an Ansible playbook
that, based off of the firstthree things I built, said I
want to do it 100 times.
Now, that's where I was able toget to beyond the thing that
(47:42):
maybe it took just as long as Idid to do those three, but now
this is a repeatable task ahundred times or a thousand
times or whatever.
Speaker 1 (47:50):
And you've said that
before with automation like it
might take me just as long, butnow I can do it a number of
times.
Speaker 2 (47:55):
Yeah, and it's not
just about doing it a bunch of
times.
Sometimes it's about it beingconsistent across those.
So what I don't want to do?
I feel like I've covered abunch of things in here.
I don't want to keep going onand on and on about the AI stuff
, because I feel like I'vecovered enough that maybe give
people a bite.
There's probably a million moretopics we could talk about.
What are your thoughts?
(48:17):
Did you learn anything new?
Is this a lot of stuff you'vealready seen?
Speaker 1 (48:20):
I think this is
fascinating.
I was taking notes along theway, so we started out with
notebook lm, which just the mindmap tool alone I think is worth
.
Whatever this thing you knowwould charge me.
Um, the fact that it, you canfeed it, you know specific data,
which again you can do a jetgpt, but like just when you hit
that mind map and it visualizesall the data and you can keep
(48:41):
digging in and I I found thatsuper compelling.
Um, I think that gemini screenshare is like next level, yeah,
uh, star trek stuff.
Like here's my screen.
Let me show you a thing andlike how can it just look at
your screen and solve yourproblems?
But here we are, like thatunbelievable, it doesn't seem
real.
Like is that real?
But it's happening?
(49:01):
Um, I mean, because you know,we're like 40 something year old
guys.
I mean we grew up at a timebefore the internet, before
computers at home, like so to gofrom that context and
background to like I show thismagic computer, my screen, and
it solves problems for me, likeoh my god, it's just amazing to
me according to chad gpt, I'm 46, which apparently is accurate.
Speaker 2 (49:22):
Um, I like the canvas
mode and chad gpt.
Speaker 1 (49:23):
I've been using and
paying for chad gpt I'm 46,
which apparently is accurate.
Um, I like the canvas mode andchat gpt.
I've been using and paying forjet gpt for at least a year or
two and I I didn't.
I've seen it try to show mecanvas mode and then it wouldn't
work and I'd fight with it butI didn't realize the
functionality.
So what you showed me in there,I really really like um to be
able to kind of change anditerate and expand certain
little sections.
Um, because that's I'mgenerally waiting for it to
(49:46):
finish, giving it a differentprompt.
It regenerates everything in adifferent version, which I like
the canvas mode much better.
And the fact that you gave chatgpt a very simple picture of
three, six, seven, eight, youknow, little squares on the
screen.
It generated base configs for,uh, you know, fortinet devices
and to your, as far as you cantell, they're accurate 100, like
(50:07):
holy crap.
That's amazing.
And then you had to make youansible playbooks like I.
Just again, I I'm amazed.
I'm the old guy who grew upwithout any technology and here
we are just talking toartificial intelligence and
having to doing just some of themost amazing things.
I.
I love the time that we're,that we're in right now yeah.
Speaker 2 (50:26):
I'm with you as long
as we can all keep our jobs.
Speaker 1 (50:30):
Yeah, yeah, and
listen, it's not that in tech.
I mean, I've joked about itbefore, but it happened with
automation for me.
Sure, I avoided it until it wasa requirement, right.
I wouldn't recommend that.
And I wouldn't avoid AI in thetooling until it was a
requirement, right.
I wouldn't recommend that.
And I wouldn't avoid AI in thetooling until it's a requirement
and you can't get a job withoutit.
Speaker 2 (50:49):
So get in now, while
we're all new and nobody's an
expert and the other thing Iwill say, going back to the AI
and the professionals that areusing it, is I can have AI write
me a pretty decent program, butit's only decent from my
perspective.
Who couldn't write that programat all?
My brother, who's a programmer.
He writes incredible thingswith ChatGPT or with any of the
(51:13):
AI tool or with some of the AItools that he's doing.
That I couldn't even fathomwriting because he's an expert
in that field already, and sohe's taking his expertise and he
knows how to talk to that AI asthough it was a professional
and ask it to do things, becausehe understands the parameters
that it could deal with.
He understands things that itcan do that I didn't even know
(51:33):
it could do, because it's whathe does.
So I think, in the end, ai Ilook at it as more of a
companion than a replacement forme and, like I said, they're
like having a bunch of littleassistants that do things I ask
them to do, and so I'm kind ofthe orchestrator there.
Is it going to change what myjob looks like in the long run?
Yeah, is it going to cost me myjob?
(51:54):
Hopefully not.
I'm sure there's going to beplenty of other things I can
figure out how to do, but Idon't know.
I'm having a good time alongthe way.
Speaker 1 (52:00):
I just want a robot
that's AI powered, that can mow
my lawn, clean my pool, cleanthe house.
I mean, I don't know if I'lllive long enough to see it, but
I've seen some really cool stuffin robotics.
Now they're applying thisintelligence to you're taking it
from your screen right in thiscode and now applying it to the
physical world.
I think that that's reallycompelling.
Speaker 2 (52:19):
Where's your next
episode?
Speaker 1 (52:26):
Jeff, next episode.
Jeff, it's always a pleasure.
Thank you for the education.
I really like this idea.
I'm hoping that we can do, uh,more of this jumping in with um,
what do we call it was it?
It wasn't whiteboard wednesday,it was show and tell, I don't
know.
We got to come up with somekind of help for what do you
want to call it?
We'll do it right now allpeople.
Speaker 2 (52:39):
I mean show and tells
, whiteboard, whiteboard
wednesday, that's actually areally good, it's not a bad name
at all.
Speaker 1 (52:45):
It was your idea, was
it, did I?
Speaker 2 (52:47):
throw that out there.
Probably got it from ChatGPT.
Speaker 1 (52:51):
Yeah, all right, so
we'll go with White Bar
Wednesday for now, but I'mhoping to do more of these.
So you brought up a reallygreat point on the show is we'll
talk about stuff and somebodywill say something cool and I'm
like, oh, I wish we had time toget into that and show it, and
it gives us so much content thatwe can create.
And we've wanted to do moretechnical, more show and tell
stuff on the show for years andit just, uh, it hasn't happened
(53:12):
for a number of reasons.
So this might be, you know, thepoint that we can start to put
some more of this content out,the fact that you're here, that
you're willing to do this andteach us stuff, when we can find
some other stuff.
We were talking about maybebringing William or somebody to
do, like you know, andy's firstgit push and because we did a
git episode.
So I really like this idea.
I'd like to keep it going and,um, you know, continue helping
people learn.
So I learned a lot of coolstuff today.
(53:34):
Um, thank you so much for yourtime and teaching us um, for all
things.
Art of net eng.
You can go to our link treeforward slash.
Art of net eng all kinds ofcool stuff in there, including
our Discord server.
It's all about the journey,where you can go in and join and
hang out.
Jeff is in there as FortiJeff.
If you have any questions foranyone, you can go in and ask
questions.
We were just having today a chatin the general chat about iBGP
(53:56):
versus eBGP and why you wouldneed it and local pref.
I I mean we geeked out on bgptoday in the discord server.
I know that that probablysounds terrible for some of you,
but I love bgp and I think Iknow it well.
But, uh, you talk to somepeople in there and you're like,
oh, there's very much I do notknow.
So, um, it's a great communityof wonderful people.
Um, we also have a lot ofmoderators in there, which
(54:19):
they're pretty low-key and youwouldn't know they were
moderating.
But, um, thank you to thosefolks who, uh, do a great job at
kind of keeping the riffraffand nonsense down.
If anybody shows up and startstrying to sell you crypto,
they're gone pretty quick.
So, um, check it out.
Uh, linktree forward slash.
Art of dead edge.
I'm jeff.
Thanks so much.
This was awesome.
I can't wait to do more andwe'll catch you next time on the
(54:39):
art of network engineeringpodcast.
Hey, if you like what you heardtoday, please subscribe to our
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(55:00):
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