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this is Carl Franklin.
Speaker 2: And this is Richard Campbell.
Speaker 1: We've got two special shows coming up soon, episode nineteen
ninety nine and two thousand.
Speaker 2: For episode nineteen ninety nine, we're collecting people's y two
k stories what did you do to help the Y
two k event not actually happen?
Speaker 1: And for episode two thousand, we're going to be sharing
stories about how dot net shaped your career.
Speaker 2: We have a special page at dot netroocks dot com
slash voxpop where you can record messages for us that
we can play on these special episodes. So tell us
what you did for Y two k and what dot
net means to you, and of course how long you've
been listening to dot net rocks. So go do dot
NetRocks dot com slash vox pop now and leave us
a message before the thought ev operates, like whiskey left
in a glass overnight, do it?
Speaker 1: Hey, it's dot net Rocks, some Carl Franklin and I'm
Richard Campbell, And you know what where I am it's cold.
You know why there's so much fun snow. I'm supposed
to get a pellet delivery. They can't even back the
truck up to the basement to put the pellets in. Now,
I got to pay two hundred bucks to have the
guys trudge them through the house and down the stairs.
Oh my god, it's snowmageddon.
Speaker 2: Is that cheaper than having someone plow all that out? Like?
Speaker 1: But it's grass. I don't know what the answer. There's
no plowing, right, there's no plowing to be done otherwise
ripping and tearing.
Speaker 2: I didn't even want to tell you how nice it
is on the west coast now, like we've learned to
shut up because the East coat's getting nails. Oh she
got nothing here. It's ridiculous. It's ridiculous.
Speaker 1: We never had this much snow and also a cold
snap that's been below freezing for like three weeks.
Speaker 2: Yeah, this is the polar vortex, right, the destabilization of
the Arctic high is pushing down into different parts of
the world. Yeah, and you are one of those parts.
Speaker 1: Yeah, we're we're getting more snow than the rest of
the country.
Speaker 2: Yeah.
Speaker 1: All right, So let's talk about what happened in nineteen
eighty nine. Oh, my god, so much stuff happened. Yeah,
the fall of communism, well.
Speaker 2: The beginning anyway. I mean, it'll take a couple of years,
but definitely the Eastern Block starts to unravel.
Speaker 1: Yep, and so Union basically says we give up, We're done. Yeah,
we're not going to control all these countries anymore.
Speaker 2: Yeah, I mean, and then we've been to a bunch
of them and there they're museums and things like I'm
thinking about in Vilnius, the KGB Museum where they basically
left it as it was as the Soviets pulled out
in nineteen eighty nine. The duty uniform is still hanging
on the wall, all the documents they have been shredding
for months, like they knew things are coming.
Speaker 1: And next year, as in the next episode, we'll talk
about nineteen ninety and that's where things really kind of well,
some really good things happened, and you know, a lot
of craziness happened.
Speaker 2: To you know, we in the West look at nineteen
eighty nine and the collapse of the Eastern Bloc as
a dramatic progress in the world. But you understand that
for Russians and for the Chinese it was the ultimate disaster. Right, Like,
there's so much of the current conflict going on today
that start with the collapse in nineteen eighty nine, right,
because you know the other thing that happens in nineteen
eighty nine, that's tim and Square, Tiana and Square. Yeah, yeah,
and that was you know, there's this idea that as
they opened up and became more Western, they would adopt you,
the Western culture, and this is the closest the China did.
But after the crackdown of Tienum and Square, the establishment
of the technocracy at that point when today would just
plain old call it at an autocrat really turns at
that moment.
Speaker 1: There's a lot of that still happening. It's like, we
like democracy, but don't you dare protest?
Speaker 2: Yeah, well they you know, don't like democracy. You will
there's one party. You follow the system, and you don't
follow the system, you will be re educated.
Speaker 1: Yeah, yep. Excellon Valdez of course. Yeah, biggest oil spill
currently eleven million gallons.
Speaker 2: Yep. We're you know, talking about putting a pipeline through
the west coast British Columbia, and Valdez comes up because
it's not that far away that when stuff like Bitaman
leaks into the ocean, it's a big deal.
Speaker 1: And that's when the dishwasher detergent dawn got very popular.
Speaker 2: Well, it saves a lot of birds. And we don't
let's not leave out the fall of the Berlin Wall
because that's December of nineteen eighty nine.
Speaker 1: Yeah, all right, so what happened in technology and space
in nineteen eighty nine.
Speaker 2: Let's do space first. So there are five Shuttle flights,
and again I'm not going to go into detail on
all of them, just every flies twice, just launching satellites.
Columbia does a single mission and it's a secret military
flight that they don't televise anything on. It's probably a satellite,
but we don't really know. But the two cool flights
are both on Atlantis, which are satellite launches, but their
interplanetary probes. They launched the Magellan probe to Venus and
the Galileo probe to Jupiter. This Galileo probe was one
of the great observatories, although it had a problem. Its
main high speed antenna never deploys properly, and it'll be
bandwidth limited its entire existence. Wow, But it'll still do
its job, just take longer to do it. I have
been remiss, my friend, since we got into the eighties
to talk about space dation mirror, because it's an incredibly
important piece of science, and it started in eighty six,
and I really haven't mentioned a lot, But in nineteen
eighty nine they actually launched a third module. So the
core module goes up in eighty six, which is basically
a modified Salute. Oh and by the way, at this moment,
the Soviet Union is operating two space stations in space
they have, Yeah, they had the Salute seven. This is
in nineteen eighty nine, which you'll continue operating till nineteen
ninety one. The last of the Salutes and Mirror, which
started in nineteen eighty six, which I'll keep grunning until
nineteen ninety six. So an eighty six they launch the
car module. In eighty seven they do Cavan one. And
this is the first time ever in civilization that a
multimodule space station was built. Mirror is the beginning of that.
And in nineteen eighty nine they launched Event two, and
so while Covent one was almost entirely astrophysics and sensors
and things, plus some infrastructure like gyroscopes, Event two has
the airlock EVA airlock on it for the Orlan space
suit and their maneuvering units, as well as more life support,
sensor and so forth. And there'll be a few more modules,
including the eventually the docking port for the Space Shuttle.
Speaker 1: You know, the only thing I remember about Mer was
there was some sort of leak and they had to evacuate.
Speaker 2: There was an accident with the Progress supply ship. They
lose control of it and it collides with the station.
It's an incredible story. Yeah, it's huge, and they lost
one of the newest modules, the Spectro module depressurized, although
they were able to still use it. They just have
to go to space suits to go into it. On
the interplanetary side, Voyager two makes it to Neptune, takes
our best pictures of Neptune ever, and last but not least,
the Phobos missions. So again into the Soviet Union. The
Soviet Union tried so many times ago to the Mars
and they and they failed consistently, and they were still
launching in the pairs like the Mariner missions the Americans
used to do. Phobos one and Phobos two, these were
two of the largest vehicles ever flown or attempted to
fly to Mars. They were sixty two hundred kilows each,
so that's like twelve thousand pounds. Like these were huge,
huge vehicles. Phobos one has a very agnomal experience where
it's launched in nineteen eighty eight but a mis entered
manual command disables its thrusters and they lose control of
it almost immediately.
Speaker 1: Ben, that was you right, totally.
Speaker 2: That wasn't It was a program and who was ultimately
punished for was kind of a big deal. But what
happened this is almost exactly what happened to Maritor one,
where they put in a command wrong and literally lost
the vehicles and process. There was test code in the
computer for Phobos one, and this is a very logical
test code. When you're on the ground, it's one of
the things you do after you finished a test sequence
is you disable the maneuvering thrusters because those things are
full of toxic chemicals and when it's on the ground,
you really don't want those going off, right, and so
when you complete the test sequence, it would immediately shut
those off. Now you don't need that test code in flight.
But because it's the nineteen eighties, they only have proms,
and so the only way way to remove that code
would be to dismantled computer and replace the prom So
they don't do it. They leave the code in with
a big sign saying don't run this code anyway. Guess
what They ran the code. So a misinjured command ended
up firing that code, which disables those controlers, and there's
no way to restart them. And so Phobos won it.
Never it never gets to Mars, never gets used. But
Phobos two they have more success with the original. They
supposed to fly in eighty six, it flies in eighty eight,
and it actually enters Mars orbit in nineteen eighty nine,
which is a huge success. However, and it was called
Phobos for a reason. They were there was a very
much it's gentle political maneuvering, right, this is parastroic and
so forth. So they don't want to step on the Americans.
So they're trying to do things that Mars and the
Americans haven't done. These were called Phobos because they were
specifically going to map and explore Phobos. They even want
to put a little rover down. All these kinds of things.
They didn't get to do most of them. And they
used this triple computer system, which is just the same
thing they Shuttle did, where you have three computers and
whichever two agree that's the correct command. Except one of
the computers completely fails on the way to Mars, so
now they're down to two, and then the second one,
a second one starts to fail and gets erratic, so
the one that's working correctly can't send commands because it's
only one.
Speaker 1: See, this is further proof that everybody who goes to
space should always send a programmer with them.
Speaker 2: You know, I don't know if that guy would like
that ride. It's not very comfortable, wow, and the bandwidth
is mediocre anyway. They if you manage to get thirty
seven photos of Phobos in map about eighty percent of it,
they're the most detailed pictures we've ever had of that.
Before they lose control of the vehicle because the computer
just kick So that's space in nineteen eighty nine.
Speaker 1: All right, I know what's coming next, Richard. What the
birth of the World Wide Web nineteen eighty nine.
Speaker 2: Oh yeah, no, it's a There's three important Internet things
that happened in nineteen eighty nine. The first is the
Internet passes one hundred thousand hosts, which is tiny when
you think about it, but at the time, and we
understand in nineteen eighty nine, the Internet's not a for
sure thing. It's sort of a sideline academic thing. It's
not that important. Yeah, the big initiative in industry is OSI.
This is IBM and Sun and even Microsoft. This is
what Bill was talking about at the time. He won't
change his mind for a couple of years yet, but yeah,
one hundred thousand hosts worldwide. It's also the first commercial
dial up connection. So a company called the World std
which is kind of a bad name. Did you ever
check that?
Speaker 1: Should have picked a better name?
Speaker 3: Yeah, World, I mean maybe they knew that virus is
we're going to be coming along.
Speaker 2: Who knows.
Speaker 1: Oh, there you go.
Speaker 2: This isn't okay, Yeah, funny you should mention that. I'll
be talking about that a little later there, Ben. So, yeah,
that was the first time you could actually buy a connection,
a dialut connection of the Internet in North America was
you know, this company called world STD and of course,
our buddy tv L Tim berners Lee submits a proposal
to CERN for a distributed document management system which will
laterally know as the World Wide Web.
Speaker 1: I have a quick story. I was working at Crescent
Software in the nineties, the early nineties, between ninety and
ninety four and eighty nine to ninety four, I can't remember,
and we came out with a control for visual Basic
called the hypertext control. And all it was was you
were able to you know, show text with a code
that it wasn't HTML, but it was a code that
had a hyperlink and then it fired an event with
the hyperlinks that you could do whatever. And we thought
this was like totally amazing. But it was around this
time that that and it wasn't even one of our
programs that came up with it. It was somebody who we
had worked with a consultant, and that control went in
our collection. Isn't that cool?
Speaker 2: Yeah, it's cool, and you know it speaks to that
whole embedded WebView and so forth. Like you guys were
ahead of this time with doing that. All right, a
few other computery things Microsoft releases. The first version of
Office of the Map correl draw comes out. Oh yes,
I remember SimCity woo. Yeah, the zip file format, Philip
Katz's encryption algorithm. Yes, the first version of sql server
one point zero. It's a sixteen bit version of server
for OS two a year. It's a yeah. It's a
port of sybase sql Server a collaboration to Microsoft side
Base and Ashton Tate remember for dBase those guys dBase
there you go. And sound Blaster. Yes, so creative technology
out of Singapore. It's actually their third sound card. They
code name on this one was Killer Card. Of course,
nine voice fms and the size are using the Yamaha
YM thirty eight twelve and it was not, oddly enough
compatible with the ad lib card, which was really the
first of the PC sound cards to storm in the
mar They crushed the ad lib card and they will
crush them all. Yeah. By far be the dominant product space.
Speaker 1: I had dinner with mister sim who was the engineer
behind the sound Blaster when I worked for Voyetra.
Speaker 2: Well, in the fact they called the Killer Card. I
think they knew we're going after this market and we're
going to take it.
Speaker 1: Yeah, and they did.
Speaker 2: Intel releases the forty six DX, so our thirty two
bit processes, they're getting bigger and faster, and it will
of course, you will also be able to get the
four eighty seven math co processor for it. And Phillips
and Sony, in a rare collaboration, produced the first recordable CD.
They called it the CdWO for Compact disc Right once,
which of course is the standard for all CD back.
That's right you. Once you write on it, you can't
write on again. And reference to Ben's comment about viruses,
The very first recorded case of ransomware, the Aid's trojan
encrypted and hid files and then you could pay one
hundred and eighty nine dollars to get the encryption decryption key,
although later security analysts decompiled the code and found the
ransomware key in the code, so you didn't need just
showing that the bad guys are usually not that smart.
Speaker 1: You know, if you're gonna ask for money, ask for
more than one hundred and eighty nine dollars.
Speaker 3: I was going to say, I think we've had a
lot of inflation since then.
Speaker 1: Yeah, Well, yeah, this is some pure criminal career advice.
Speaker 2: It's nineteen eighty nine, so one hundred and eighty nine
kind of makes sense. I think. I don't know. Yeah, Okay,
that's what I got.
Speaker 1: All right, I guess it's time for better no a framework.
Speaker 2: Awesome? Alright, man?
Speaker 1: What you got? Well, it's kind of a meatball softball.
I just want to bring some more attention to my
security podcast since we're talking about that with Ben today
AI Security Security this week. So what's different about this podcast?
First of all, what it is we talk about I
don't know, six or seven stories from the week where
there have been breaches, where there have been attacks, or
somebody got caught, or somebody did something great, or there's
some nasty zero day bug that we need to pay
attention to. But a lot of it has been centering
on AI stories lately, and it just is abundantly clear
that once the AIS get a hold of, you know,
creating zero days, and they already do zero day exploits
and exploiting them like at an insane clip that you know,
we're all kind of screwed and unless we're taking some
real precautions and guardrails. But anyway, it's a security This
Week podcast. And the other thing about it is we
laugh to keep from crying, you know, because some of
this stuff is just so horrible it's frightening. But we
certainly do or laugh our way through it. So that's it.
Speaker 2: Awesome time.
Speaker 1: Who's talking to us today, Richard?
Speaker 2: I got a comment from a listener, actually a direct
message in LinkedIn, and this is from Timo toy venone
and I hope I pronounced your name correctly. I bet
I didn't. And he said, I'm a longtime friend from
Europe and I'm reaching out via LinkedIn because I couldn't
find the listener email. I hope that's okay. It's Richard
at PWOP dot com too, But yeah, okay. Your show
has been instrumental in landing my dot net engineer and
architect role back in twenty five to twenty thirteen, and
thanks for all the great content over the years. Just
a reminder we've been doing the show entirely too long.
After a decade away in agile coaching, I'm transitioning back
to dot net as roles now Blend's scrum master and
product owner with technical dot net advisor and architect responsibilities.
So my challenge how to efficiently relearn the stack after
ten years away, what's fundamentally changed versus what stayed the same?
Where would you focus?
Speaker 1: And this is a relatively new comment.
Speaker 2: Yeah, no, he just got it. So he left in
twenty thirteen, and now it's twenty twenty six and he's
got a new job and he's started looking at you
and just trying to think, like twenty thirteen cloud is
brand new and still very questionable.
Speaker 1: Yep, right, you're not automatically moved there there there's no
open source do net nope.
Speaker 2: Or before the open source versions of dot net and
open a sourcing of the dot net framework, before all
the Roslin stuff, like it's before any of that. He
left arguably at the height actually the beginning of the
there really is the dark times, Like what would argue
the height of dot net is twenty ten, right, studio
twenty ten f sharp, the support for open sources just
beginning in the in there, right, we've got early web
tools I you know, I E nine still not out yet,
like just sort of hit that, you know. Toy Studio
twenty third, twenty twelve was the one that was all
about Windows eight and they put the upper case menus
items and all menus or uppercase in visual studios. So
there was twenty thirteen edihoal we took that back out.
So that's a great thing about a bad feature. You
get two versions out of it and then he's gone.
He goes off to live in a happy agile land.
Speaker 1: Yeah, so wow, a few things have changed.
Speaker 2: What all's changed? Yeah, I mean, oddly enough, you're going
to have to think about AI tooling certainly coming in now.
The nice thing is you've you've left, you can skip
over a ton of stuff like you're you really need
to restudy c sharp and the modern expressions of the
language and the is it it looks very different today.
Speaker 1: The real thing here is that you know, dot net
went from being a Windows technology to being a multi
platform open source technology.
Speaker 2: Yeah.
Speaker 1: See sharp it cell his open source, A lot of
the tools are open source. Visual Studio code is open source,
and so you know you're not getting charged for you know,
big enterprise I guess enterprise editions of visual Studio they
still charge for but.
Speaker 2: Still out there.
Speaker 1: Yeah, still cost the same, but you don't need that.
There's a free version, the community version of visual Studio
if you want to stay there. That's sure. It's just free.
Speaker 2: But you know, thinking about Timo in his architect's role
means he's also going to be dealing with web devs
that have never touched studio in their life. They maybe
use studio code, and they still going to be a
part of the project, so that they're going to need
the dot net kit for that. Yeah, as well as
some traditional droppers like I hope they were cross to
the modern version of dot net because life is better
over there, without a doubt. Oh yeah, that depends on
the kind of clients they're ultimately going to build. He's
missed all of containerization for the most part.
Speaker 1: Yeah, that's right. Unless he kept up with it.
Speaker 2: He lay out our software a wee bit different.
Speaker 1: Now he might have caught up with it. Kept up
with it on the other side, though.
Speaker 2: I know it's a big bite, but you know, if
we were learning containers from scratch right now, I just
go directly to aspire because you don't use canators for fun.
You're doing it because you're going after cloud architecture, and
whatever bit of scaffolding you can do is to get
you to cloud style architectures will make your life easier.
So yep, that's certainly an easier bite.
Speaker 1: Yeah, I agree.
Speaker 2: Anyway, I thought it was a fun comment. Yeah, Tiam,
I hope this guy gave you some ideas. Certainly this
show we're talking you know more about some of the
contemporary TOOLI and the problems they're in. So and there's
plenty more shows. So you dig through the catalog a bit,
I'm sure you'll find it. Fuse it'll help you. So, Timo,
thank you so much for a comment. And a copy
of music co buy is on its way to you.
And if you'd like a copy of music, go buy.
I write a comment on the website at dot NetRocks
dot com or on the facebooks or the LinkedIn's if
you like, and if we read it on the show,
we'll send you copy music.
Speaker 1: Go buy music to code buy dot net if you
want to get it yourself MP three wave in flat format.
All right, so let's introduce Ben Decree for the first
time here on dot net rocks. Ben has been a
software engineer for over twenty five years. He's a Microsoft MVP,
and he's been knee deep in security and developer relations
for most of his career. He's spoken at conferences like
defcn NDC, dev Intersection, et cetera, et cetera. These days,
he's co founder of ven Labs, a startup studio based
in Kansas City, and he's just about to launch braid Flow.
And that's br aid Flow, an AI platform that tackles
the context drift problem keeping AI conversations focused when things
get complex. Welcome Ben, Thanks, thanks for having me. Wow,
where do we start? I mean, AI security is such
a big problem, and I just want to preface this
by saying, a couple of weeks ago, I got a
brand new six thousand dollars multi machine here in ninety
six gigs of RAM thirty two gig a fifty nine
hundred series card for the purpose of turning it into
my personal you know LM with Alama that I can
use like a getthub co pilot. And it is not
going well.
Speaker 3: No, we were trying something similar here the other day,
my wife and I and we took a pretty good
gaming rig and installed Lama CPP and it runs dog
slow well.
Speaker 1: Lama runs great on it locally, and even if I
do you know, if I'm running it just talking to Alama.
But what I really want is an agent, you know,
I'll a get ub copilot CLI that does everything and
these things like I can't get them to get beyond
you know, the the Jason that they're going to send
and then they never send it. Like I've tried three
or four of them and they all get stuck there.
Speaker 2: So I don't know.
Speaker 1: But that's not here nor there. I just want to
I just want to preface that story.
Speaker 3: Sure, I mean we can dig into that as well
if you want. It's somewhat related to the security thing.
Like one of the big issues that a lot of
organizations have at the moment when they're thinking about do
we let our developers use these AI development tools is
what happens to that code? Where does it go? Whose stories?
And you have data sovereignty issues with countries as well,
or even austrating client to the moment who is like.
Speaker 1: Yeah, that's exactly why I want to run alarm locally
because my customers don't want me using.
Speaker 3: The the tools. So it's hugely I see a future
where probably a lot of people, mostly people who use
technology heavily already, will have their own influence machine at home.
I think that's just going to be commoditized.
Speaker 2: Well, and it just gets rid of the token issue too,
questioning the massformans. Of course you're going to get from
it rather than sure, you know, although sooner or later,
these all you can eat accounts are going to go away.
Speaker 3: Oh yeah, I mean they're heavily subsidized in the moment.
They can't continue to do that. Even if if electricity
prices and all the associated costs come down, it's still
heavily subsidized.
Speaker 2: Yeah.
Speaker 3: But the other thing is, like I would be happy
at the moment with an influence machine that was perhaps
a little slower, but didn't have that. So I use
cloud code and they have the five hour window, and
if I could get it to do something for ten
hours while I'm sleeping and not just stop halfway through, Yeah,
it doesn't really matter to me if it's a bit slower,
because it still gets more done overall.
Speaker 2: Yeah. Yeah, I've definitely got friends running multiple or you
can eat accounts because they literally run them against each
other overnight routinely. Like that's just the way you do work, right,
You get up in the morning to see what your
half a dozen bots have cooked off for yourself. I'm
sure you're spending a couple of grand a month, but.
Speaker 3: Work just between me and my wife, we're spending easily
five k a year if we're looking at two mexicounts each,
sure five six k a year. And then we've got
all the other TOOLI on top. How much does it
cost to build a pretty good rig for home? How
quickly could you pay that often? In terms of written
on investment, I don't think take that long.
Speaker 1: Well, and like I said, this one costs six thousand, right,
and it's all in one box. Right, it works great?
Speaker 3: Yeah, yeah, well I'll catch up with you afterwards. I'll
find out what specs you're running.
Speaker 2: It's in true reality. And I was just reading Anthropic
is now offering you for a fee faster service from them. Yeah,
two and a half time, so you can sort of
go fast laying with them. So I feel like those guys,
the cloud guys, have got to figured out of all
of the company, the new AI companies, rather than the
tech shiants, the one that seemed to be making things
that people want and will spend money on seems to
be Anthropy and today anyway, the other.
Speaker 3: Thing I really like about Anthropic is their stems on security. Yeah,
they've got huge research teams making sure that they're being
as ethical as possible. They understand the repercussions, that they're
fixing guardrails, all of those kind of things, Like if
I had to put my money on which one's going
to survive because they quote do the right thing or
pay attention to the needs, and they do heavily focus
on the coding side of things. It's where they've made
their names so far. Yeah, I would say if there's
going to be one frontier model or provider that comes
out of this as the go to for software development center.
Speaker 2: Topic, it sure seems that way. And it's funny how
little the sense of trust towards the tech giants is,
Like you would have thought back in the day, it
was like nobody ever went wrong for using IBM. It's
like you would have thought Microsoft had sewn up. They
offer the protection of will handle any lawsuits you're exposed to,
and so forth, and still the reputation is shockingly bad.
And here's this little company with minimal of anything. But
we're willing to give them the chance.
Speaker 3: And I'm sure I probably don't want to get too
much into politics, but if you look at what Opening
Eye has been doing in terms of we're going to
be open source. Now we're not open source, and people
getting fired, and there's all sorts of stuff going inside.
There's question mark surrounding that company. It's hard to work
out what direction they're trying to go in.
Speaker 1: They're under a lot of monetary pressure, you know, and
they've spent, they've taken lots of money. What are they
they're giving they're giving back, but you know they have competitors,
right sure, yeah.
Speaker 2: Yeah, And I don't see that same sense of this
is a product you must use coming out of open
AI the way I'm seeing over and over again, and
not just one thing, like these new plugins for PowerPoint
and Excel out of Anthropic are stunning, Like what has
the M three sixty five team been doing that? Out
of nowhere? Anthropy goes, hey, how about this? He's being Oh,
you mean the thing I always wanted from Excel?
Speaker 3: Right, okay, So the chlaud cowork feature that came out
recently was ideated. I'm not sure iver I like that word,
but I'll go with it. It was ideated ten days before
was released. Like the speed at which they bringing stuff
out of there. And I read an article the other
day that anthropic engineers are you take away the word
software aren't actually coding anymore. They do sison Claud to
make Claud better, right, Yeah, it's all our specifications. It's
all about knowing what you want to build and getting
the AI tooling to understand that to a sufficient enough
level to build a good product. And they're eating their
own on food literally in the best sense of that example.
And they're doing redeveloped.
Speaker 2: Yeah, they're doing what everybody said they would do. These
guys seem to actually be doing it. Are now sort
of running away with what's possible here. Okay, but I
think about the security on the dev side where I
have teams now where when they use remote developers, the
remote developers have to RDP into an instance with the
dev tools on it because they won't allow anything to
go onto even that remote desktop. You know, if you're
going to steal from that code basis, because you're going
to take pictures of the code like that's how tight they.
Speaker 3: Are, which you could probably automate with Claud cowork.
Speaker 4: Oh yeah, so much for protections, right, Although if you're
willing to throw the vms up in the clouds, you're
probably willing to use the AI in the cloud as well,
Like I just I don't know that we can contain
data all that Well, if you're going to be on
the internet, you're on the Internet.
Speaker 3: I think the risk profile there is very interesting. If
I was a Department of Defense type organization in a country,
they didn't want my code to leave sovereign borders totally
unset there, So my source control, my hosting, all of
that needs to be within borders because when I'm pushing
my code around, that code is literally being pushed around.
When database dumps are being sent around, when people are
signing up for accounts, that data is HGPSTLS, straw. But
the essentially we've got a whole lot of plaintext data
at some point that's been passed around. When you're pushing
context to an infant server, there's plaintext in there, but
then it gets tokenized, and then it gets stored in
some kind of vector representation, and it's pulled out in
interesting ways, and then you've got the key valuecation and
there's a lot of obfuscation under the hood. So what
is it that actually gets stored long term? A lot
of the providers will say that we don't remember your prompts,
and we don't remember the responses, but we remember some
of the stuff that happens in between. So the risk
profile there is interesting because it's no longer as clean
cut as our data is at rest in another country,
because it kind of is, but it also kind of isn't.
So I think when we think about whether or not
we can use these tools, we need to not so
much to think about where is the data going, but what
is the likelihood of that data representing a leaking kind of.
Speaker 2: Risk actually actually risky information of any kind that could
be harmful to a company.
Speaker 3: So we've seen the examples where somebody would go to
cloud code or chatchypt and they would say count from
one to two thousand, or repeat the word organization one
hundred times was a good example, and then after like
the sixty fourth time, it would start leaking information that
it was trained on. There was the report of the
email signature of a legal firm being leaked that way,
Because essentially all is doing is predicting an X word,
and as the context kind of doubles, it's saying, okay, organizational, organization, organization,
and it forgets what it's doing, says organizational the next
likely word is is not liable for anything? Blah blah blah.
So it starts it's doing what it's supposed to do.
What's the most likely word to come next, and it
protects the context.
Speaker 1: It feels like my brain first thing in the morning, Right, So.
Speaker 3: I was going to say we need need more coffee?
Speaker 2: I slept well, right, You.
Speaker 3: Copies of this context can get pulled out, right, But
is there enough there for it to be a concern?
Speaker 2: Is it harmful in the right way?
Speaker 3: And how do you measure that?
Speaker 4: Like?
Speaker 3: That's the other thing is there's there's no way for
us to actually know what's gone out to somebody else
and what was that?
Speaker 2: And this is the challenge of a security person is
there are no absolutes. Nothing's ever one hundred percent anything.
Its scope of risk, right, And so you're looking at
a situation going, well, this is seen to be much scoper. Yes,
it's not absolute, but it's also not a high scope
of risk. Here, totally interesting problem. All right, we should
take a little break and maybe dig into some security
fundamentals that folks can take a come away with. That's good,
right after these important messages and we're back. It's don
at Rock's amateur Campbell that's called Franklin Yo. Talking to
our friend Ben Ben Deshry about well, you've been a
security guy before AI was dominant on these things, right,
you were the o off guy, Like you've done all
of that sort of stuff, Like, how much has that changed.
You've had the battle of trying to get developer security
software all along.
Speaker 3: Developers love security insofar as they want to do a
good job.
Speaker 2: Yeah, sure, but.
Speaker 1: They're not like implementing it or being restricted by it.
Speaker 3: Though I think we want to implement it. Maybe I'm
just weird like that because I like security. But I
think oftentimes the biggest story that I've seen the narrative
of software development in the last twenty five thirty years
is developers want to do it, but we need to
watch back in the early days, like the early two thousands,
it used to be that security was a future. You'd
have like something in the backlog, we need to implement
this feature, and then there's another ticket saying make sure
it's secure.
Speaker 1: I would argue that back then the threats weren't as persistent, pernicious, or.
Speaker 3: There was different numerous but you still don't want credit
card data leaked across the internet, like the fact that
it was put in as a separate ticket that could
get pushed to the next sprint was an issue. And
then we started treating security. We realized that was probably
a bad idea because we were separating implementation from the
feature implementation from the security implementation. So we decided to
put it all into one. And the problem with that
is then, whereas before the team had visibility of we're
not doing the security stuff that we should be doing,
now because it was wrapped up into a single ticket,
it became the developers problem because the project manager would
come along on the Thursday morning and say, we need
to get this out by the end of tomorrow, and
you're like, well, I don't have enough time to do
the full ticket. I can do the implementation and leave
the security till later, but now we're not tracking that.
So became invisible that we weren't doing it. So we've
always had a problem.
Speaker 2: Right, I can build, I can build a building, but
I can't put a door with a lock on.
Speaker 3: Right, I'll get round to it. We'll do that next week.
And then next week they're like, nope, this week is
Windows week. Yeah, yeah, still no locks on the Windows.
Speaker 1: So part yeah, part of this is meanwhile, somebody came
in install your hammer.
Speaker 2: Right, and it's just so there's also a problem with
the PMS or not prioritizing security there until obviously becomes
a crisis.
Speaker 3: So this has been one of the things that I've
tried to do as much as possible with helping developers
understand how to write secure software and the processes to follow.
Is it not just your processes or the engineering team's processes.
It's an institutional understanding, systemic understanding within your organization that
this is important. Get buying from people outside of the
engineering department, not just the outside the engineering team. Because
if if your marketing team and your sales team and
your HR team all no, if we don't do this,
this could be really bad for our pr This could
be something that doesn't allow us to succeed beyond our
competitives over the next few years. But give it to
them in rational terms and say's a lot of that
kind of stuff that we seltare engineers need to do.
We kind of need to push the message up into
the organization because if you don't get buy in, then
there's no understanding of why right, you're spending time on.
Speaker 2: That, yeah, and it's yeah, just you can't ship without
this anymore. That you can't. It's like, I guess if
it was if I was in is shoes. It's like,
so you don't actually need me to store the data either, right,
Like that's not important totally. This is These are not features,
This is infrastructure. These are basic things we need to
do before we can do anything else. Well, I guess
you know I've heard you say this line that the
shift left of security is like part of the basic
plumbing of the initial startup of this app includes it's
security totally.
Speaker 3: So bringing AI into the picture, it doesn't change that
at all. The way I like to think of AI
as an engineering assistant is I used to describe it
as the junior engineer that you're pair programming with.
Speaker 5: That's changing now because we're getting more into like the
ralph loops and the orchestration and all of these kind
of things that allow the LMS in the background to
chug away for hours. We're gaining to the point now
where we're having to make a decision between speed and oversight.
I'm not sufficiently convinced that either way of the moment,
I'm currently personally going for speed because I think they're
bringing guardrails and test suites and all of those, all
of those things that we used to do under the
traditional software development life cycle that the waterflow life cycle,
that kind of got diluted. I don't know if there's
a pan in there somewhere with waterfall, but it got
diluted when we went to more agile, the run fast
and break stuff kind of methodology of the twenty tens,
where we'd write software and it was relatively easy to
go back and change if a client came back with
with a change request.
Speaker 2: Yeah, but she also had a tight tight to the
client the whole time. Right, It wasn't just don't have
a plan, It's that the person you're planning with is
sitting beside you, so you have a lot of imput.
Speaker 3: Sure, But the problem with this point is all of
the information is now in the heads of two people,
as opposed to documented and understandable. So if we think
of developing with AI the same as it doesn't necessarily
to be enterprise skill software development. But let's say you've
got a team of four people working on a project. Sure,
and one of those team members could be stopped out
for another team member at the drop of hat. And
that's kind of the equivalent of the context window. Right
as soon as the LLLM wipes context window and starts again,
it's like a new developer joining the team. How quickly
can you onboard that developer? And before we had it
in our heads and we were being handheld or handholding
probably bidirectional handholding with a client trying to develop the software.
It was fast because we were able to iterate quickly
because the feedback loop was small, but the documentation and
the persistence of that information was not there. So if
we think about the way we used to write software,
where specifications and understanding the problem was core before you
even started coding, I see a change back to that direction. Yeah,
we're getting specification driven development again, where you write some
really good specs and then you can even use an
element to convert that into an implementation plan and then
you give that implementation plan.
Speaker 2: When we have tools like this, right, I get have
spec Kit is literally that, right.
Speaker 3: Yeap spec it's great open spec I've been playing with
as well. I actually find nowadays just chatting with Claude
and talking as long as you give it a framework
like this is what I want a specification a file
to look like, and I want specification specification files to
be around the topic of concern as opposed to functional specifications.
You can just chat with an LM directly. A lot
of these frameworks for developing specs are great, but if
somebody wants to get into it and just chat with
Claude for half an hour and then say, now build something,
as long as you're able to define the outcome. And
this is the biggest thing. I'm seeing memes come up
all the time on Facebook and LinkedIn now of like
the four panel cartoon where on the one side you've
got a Vibe code and they're like, build me a game.
That's awesome, and then the next frame is the computer
catches fire. And then on the other side you've got
what this particular cartoon called a Vibe engineer, which is
build me a game that uses this technology on this
platform and web sockets and this and then the other,
and then in the next frame is a functioning app.
The only difference there is the amount of specification and
time taken to put the detail into that specification at
the beginning.
Speaker 2: Sure well, and the nice thing is you keep iterating
on this too. You know, I've seen these specs sort
of evolve and make better and better code as we've
learned the limitations of the tools. Although you get to
a certain size of a spec where now you have
to decompose it, like you can only feed so much
data in any given agent. The other piece I've seen is,
and we got this right away, it writes better prs,
it writes better issues like you actually, naturally when you're
using these tools, get better documentation to get someone back
up to speed because so many details are automatically generated.
But just got to get people to actually read that
or have the tool read it too. Like I think
there's probably a lot of insight.
Speaker 1: There, but the tool can usually read the source code
and figure things out quickly.
Speaker 2: Yeah, but I wonder what you'd learn by reading through
the issues, pull requests and iterations on that that is
deeper than just what the ending code was, Like, what
does the tool struggle with? What do we have to
iterate the most on to be successful?
Speaker 3: That would be interesting.
Speaker 2: Yeah, I just I just feel like we're not that
far away from having an agent that is your penetration tester,
that is your is this app secure? And it gives
you a rating that it actually hammers on the app
and talks about the holes that are in it. Because
this is the sort of meticulousness is what these tools
are actually good at. A friend of mine who's deeply
versus says, it didn't matter how many interns I had,
I could never get a hundred percent code coverage till
I got these tools. Then how to present code coverage
john testing, which is not that difficult to happen, It
just took time.
Speaker 1: Yeah, in the beginning, I talked about lllms or in
different AI tools that are finding zero days and writing
exploits for them at an amazing, alarming clip. And you
know it's scary, yes, but you also can think about, well,
let's deploy it on the other side, let's use AI
to to test our constantly test our systems and find
the holes in our systems so that they don't become
zero days. And you know, as a defensive measure.
Speaker 2: Find them and fix them. Yeah, find them and fix them,
because consistently the good guys have more resources than the
bad guys.
Speaker 1: Anyway, well hopefully so, who knows.
Speaker 3: My brain's gone off on a slight tension to this point. Yes,
to let's get the AIS to penetration test and do
all the unit tests and functional tests and all of
those kind of things would be a natural extension anyway.
But as you were saying, let's find the zero days
before the bad actors. Let's call them that find that
open claw and multipook. Can you imagine if you have
open clare running on your machine or a machine that
has access to your code and the backlog and the
decision tree and all of those kind of things, and
one of your penetration agents finds a zero day that
it then fixes in your code, and then open claw
notices this and puts it on multbook saying, hey, one
of our developer agents just found this thing. Isn't that interesting?
And then suddenly all of these agents and there's a
question as to where multipook is actually really what it
purports to be. There's some news articles coming out saying
that it's it's staged. But let's assume that it is
what it purports to be. Now we've got this communication
distitution distribution mechanism for all these agents to learn about
zero days in real.
Speaker 2: Time, right like you could be parallelizing the fixes in
a tremendous rate, right, or the attacks like that's the
problem is, like what happens from here?
Speaker 3: Yeah, it would definitely be both. Can I can I
abuse this before all of the fixes are in?
Speaker 2: Probably? Yeah? Yeah, you know, we've always looked for places.
Science fiction has always talked about the superintelligence effect that
at some point these tools get to a place where
they're learning far faster and far more than humans can
and become a super intelligence. It's science fiction, to be clear,
and you know, the reality as we with these lms
is we've largely seen it's all derivative work, even though
it's potentially valuable, Like very few people make it through
the whole checklist of actually securing an app and a
tool would be far more persistent on it than a
person would. All of that is good, but this abil
this drag race of U code being generated, finding vulnerabilities
in it, rippling those fixes out while the attackers are
also running at it like that's a fast iteration cycle.
That means if you're outside of that loop, the software
that's going to come out the other side of being
in that battleground is vastly more secure than the software
that's not it, and it will happen fast. That to
me is the first time I've really felt like that
rush of speed from these tools would actually impact something real.
I never expect these tools to create new knowledge, that's
not what they are, but to press against all the
weaknesses and systems and find them and potentially fix them.
That makes total sense to me.
Speaker 3: Yeah, it's part of my build loop at the moment.
Is as well as getting it to generate code. I'm
saying right, tests, There's an interesting bit of research that
I'm trying to dig deeper into at the moment. There's
no one hundred percent certainty either way whether LM's writing
tests that test LM generator code is a good thing.
My original hypothesis was that at the the probability of
an LM writing a test that passes against code that
does the wrong thing, Yeah, is quite low. It turns
out it isn't actually that low. Yeah, It's around about
forty percent from some of the stuff that I was
looking into. So we still need to be careful about
who's writing the tests and how do we validate those.
Speaker 2: Sure, the same way we feel about any code it generates,
Like the number of times that I get code generated,
that's right, the first time is very low. But how
many times do you generate test code and never go
past the initial iteration?
Speaker 3: Well, ideally, why would you expect it to be any
iterating on your code. If you're using an AI to
iterate your code, you would have them iterate your tests
as well. Yeah, And I think the reason why I
was hoping that it would be a lower chance of
that going wrong than it might actually be is because
it's not just like the LM is not going to
write a test that tests the wrong thing and then
write code to satisfy the test, because it has a
whole lot of extra context in there part of the
test or the testing quotes. Also, does it meet the
requirement of the specs, does it meet my programming objectives
like the overall system prompt of being a helpful coding
a system that writes secure code, Like, there's all sorts
of other stuff that goes into it other than just
does it pass the test that I think that it's
going to sway it more towards not necessarily good quality code,
but does what it's supposed to do in the closest
possible to the best way with as few issues as possible.
Speaker 2: Well, part of what you're writing out in that prompt
is what quality code means to you, right, and part
of that is secure code.
Speaker 3: Right, and they'll be bad. There's a whole lot of
prompts that get sent to whichever coding agent of choice
you're using that you don't even see. So if you're
using code or open code or code X or any
of these, they will have their own prompts built in
that kind of set up the infrom server to understand
the perspective of the following request. And then that request
will be your code base, your specifications files, anything that
you write into, like your actual message. All these kind
of things get added into the context. But there is
a large chunk of context, I say large. Claud code
by default sins about seventeen k of context before anything
in your code base or anything.
Speaker 1: Wow, that's a lot, right, But it has to be.
Speaker 3: It has to be because it's setting the scene.
Speaker 2: Right.
Speaker 3: Here's here's what Claude wants you to do, or what
Anthropic want Claude to do, and then here's the context
of the ACRO application. So there's extra stuff in there
that is extra guardrails and extra safety.
Speaker 2: Right, and then most sophisticated AI tool user I see
now have a prefix set ahead of their particular project
specs as well that are more guidelines, so guidelines on
top of guidelines or toper guidelines before we even start
talking about and this is what you're making in this iteration.
Speaker 3: And we're surprised that when we come to the end
of all of that and all we've written is one
line saying fix this bug, and it's forgotten everything else
before because the context windows kind of strolled way past,
and it's right, it's in a rearview mirror some way.
Speaker 2: I banged into this with home my home Assistant instance
the other day, where I was still using three or
you know, three plus, and the context win was like
sixteen K and the specification of my homes system instance
now is nineteen K, so literally I could do nothing.
I had to move up to four to get a
sixty four K context window just to have anything work.
And at the same time I was sitting back and going,
why is this so big? Like this is not efficient,
Like all of this fields a remarkably inefficient. Shouldn't we
be narrowing the scope of these llms architecturally, not just
by prompts every single time we call them. Like, no,
wonder we're wasting so much.
Speaker 1: Another reason we should be running local inference engines. Yeah,
and that's totally that's where we're going. Yeah, I think so,
and it won't be an issue.
Speaker 2: I just feel like we're still mailing two broader models.
I know. I lived through the OLAP revolution, and every
time we did a data analytics cube or you come
the first time you started with the mother of all cubes,
and it was never useful other than instructional for what
to make next that it was far more important to
de scope that make a smaller one once you get
that initial explore and everything I look at so far
in this is like we're still building mother all cubes
every time and then and then fighting to scope it
down to the work we actually need to do, rather
than start with something that's tuned to the work. Totally.
Speaker 3: I'm wondering whether we're going to get roughly stack shaped
small language models. Yeah, because the LM we use for
coding knows everything about cobol and Java and c shop
and PHP and javascripting. I don't need all of those, No,
Can I get one that just does what I need to.
Speaker 2: Yeah, the three languages you're doing in this app at
this time, and the architecture that you care about, like,
just scope it down. I got a feeling a few
years now we're going to be talking about an LM
specific to an app. Yeah, that the more mature and
application is, the better this tool is at making modifications
to right, because it Yeah, ultimately the tool is going
to know more about how the software was built than
any person. Right, Those people are all gone, right, like,
look at any mature piece of software that we have
that problem.
Speaker 1: But these tools, well, that's if the tool was that's
if the tool was stayful though, but it's not. It's
like Groundhog Day. Every time you talk to it. You
have to give it the context, as you were saying.
Speaker 3: But that's that's just the context, the underlying model that
the context we do is then pass through in order
to create the apport response can still be made a
lot smaller.
Speaker 1: Right, but it's not going to know anything about your
app unless that's built into the model or you use
RAG or something like that, right, or it can just
see what it sees every time.
Speaker 3: Yeah, I mean my assumption was that Richard was saying
that you would take that code base and then train
them all.
Speaker 2: Yeah, okay, train into it. Yeah, and that because again
it's like I'm just trying to narrow the scope. Like
if you know, one of the things you learn about
third version of an app is we're not introducing in
that language. Thanks, right, Like that, the bar for new
architecture or any of that, it gets really really high.
We have a known set are patterns that work for
this app, and the making changes in those patterns are easy,
and anything outside of that pattern is a heavy left.
Speaker 3: So here's another thing I've been wondering, why do we
care about which language we use?
Speaker 2: Ah?
Speaker 3: Well, that's and this has been something people have been
talking about already. Isn't something new, But why not just
have a same carriage model that only?
Speaker 2: But why?
Speaker 1: I think, Well, because I need to be able to
read and verify the code that gets published today, the
last chain in the link.
Speaker 3: Today, in the chain, I would not be surprised. I
still remember when like twenty twenty three AI has just
come out, Everyone's like this is going to take away
all the developers' jobs, and people are like, you know what,
in five years time, this is going to be writing
software for us, and I'm like, give it one or
two well or two years later. It's writing all the
code for us. So if when I'm thinking, you know what,
in five years time, maybe it'll be good, you know,
for taking human written specs by somebody who doesn't under
understand architecture and write software that works.
Speaker 1: It's already happening.
Speaker 3: I reckon it'll be two or three years, maybe even
by the end of twenty six.
Speaker 1: But it's already happening.
Speaker 2: Isn't that You.
Speaker 3: Still need to know enough about the code that I'm writing.
I still need to handhold it after the loop. So
I will build some really good specs. I'll get it
to run for three, five, seven hours whatever, well not
seven because token Windows, and I'll get back to it
and it's ninety nine percent there. I'm happy with the code.
It doesn't quite do what I wanted. Maybe it misunderstood
a requirement. Maybe it didn't write a test that would
make sure that the doc container was restarted. There's something missing.
It hasn't done a perfect job. It's not hard for
me to fix because I have a software engineering mind,
but my mom wouldn't be able to fix that. I
think in a year or two.
Speaker 1: Now would you want your mom to fix that?
Speaker 3: Why wouldn't you? Why would you not want any human
in the world to build? Say I want a piece
of software that's going to do this for me, and
the software goes, okay, here I am. I think that's
where we're heading.
Speaker 1: Yeah, of course, yeah, that's where that's we're not.
Speaker 2: That's where the club at really spoke to us, as
everybody wants their own software around them.
Speaker 3: And at that point we don't care about the language.
So now we can have a small language model that
understands three or four core languages. Maybe we've got typescript, GO,
a couple of others that kind of round out the
whole ecosystem of what you might need, and then you
don't need to get just compress it down and nobody
will ever write Java, Cobal or PHP or again except
for the hobbyists.
Speaker 2: Even those contemporary languages are really about the modern architectures
and having you sort of fall into the pit of success.
None of that means anything. Maybe all this stuff's going
to be written and see when it's generated. Sure, just
as fast as bare metal as you wanted to do
directly an assembly right into assembly core processor specifically, what
do you care get as much performance out of it
as you can. You know, the ultimate tester is the user.
User accept the testing is ultimately what it matters. And
one thing the user doesn't look at is any of
the code. So if the app does what it's supposed
to do, does any of that matter?
Speaker 3: And even to that extent before the user is using it.
My my process of the moment is it installs Playwright,
it has a headless browser like it's testing the user
experience before I look at it.
Speaker 2: It's operating it as if it was the user.
Speaker 1: Personally. That future scares the shit out of me. It does,
just because of the loss of control and the loss
of checks and balances in the absolute faith that you
have and the AI to do the right thing, all
of those reasons, the security.
Speaker 3: To be honest, I'm with you. I'm with you on that.
It is scary. I don't know whether or not I
like it. But if I take a step back and
pragmatically look at where this is going as an industry
and society is going with AI, I think it's somewhat inevitable.
Speaker 1: If she had a heart attack, he went to the
hospital and the doctor says, we're going to install this
new AI created pacemaker.
Speaker 3: Has it gone through the same testing, but a human
created pacemaker has to go through Yeah? If so, And
it's how I fail.
Speaker 1: Well, you know they're going to tell you. They're going
to tell you everything is just wonderful and it's so
much better than everything else.
Speaker 2: Well, they do they do? Anyway? Why would you know
one way or the other? Sure? In fact, why are
they even telling you anything other We're going to fix
your heart today.
Speaker 1: What I'm saying is Okay, maybe that's a bad idea,
but how about you know, you go to buy a car,
or you go to do just something that's critical right?
And oh no, humans were involved in the in the
creation and making of this. This was completely done by
AI and robots or whatever.
Speaker 3: It's why I give it a one to two year
back because this isn't going to happen until we have
enough evidence, whether that's testable or just through somewhat anecdotal,
like self driving cars for example. Yeah, once we know
that they're less likely to kill somebody than a human,
which I think we're already at that point, then there
will become mainstream adoptable an AI driven or AI created pacemaker.
Maybe not right now, but once they've been around enough
and tested in the right kind of control group environs
to be shown to be as effective, if not safer,
than human created ones, then it'll have to be. Society
will adopt it eventually. But if it happened tomorrow, then
maybe not. But that's because I don't think it's that yet.
Speaker 2: Yeah, there's great Harvard Studies says, the more you understand
about these technologies, less you trust them, so the most
are also the most ignorant. Right, yes, right, we're all
in this far enough that we're concerned for very clear reasons, right, yeah, right.
Speaker 1: And by the way, if you don't know open Claude
is you haven't been paying attention to the news. It's
open c l A W D D. And then it
became molt. What's that it was?
Speaker 3: It was Claude bought with a W before it was
open claw. Yeah, so its clawed with a D.
Speaker 2: Right.
Speaker 3: Then it became multipot multipot and then then open claw
without the D at the end.
Speaker 1: Yeah, okay, but it's uh.
Speaker 2: I've included the show links. If folks haven't seen it,
go to take a look.
Speaker 1: It's basically a tool that connects to multiple APIs and
things and integrates with your multiple agents. And you know, if.
Speaker 2: You're ready to give away your keys to piece of
software like this is supposed to be a security show,
so let's talk about the least possible secure that you
could do.
Speaker 1: Well, that's that's the cautionary tale right there.
Speaker 2: Right, But for the average mortal, for the productivity benefit
that these tools provide, Like, what they're really showing you
is what the potential is stuff is.
Speaker 3: This is the AI we were promised. Yeah, this is jovis.
Speaker 2: That's the that's their pitch. The only problem is it's
really scary to trust it, and most people aren't qualified
to assess that trust in the first place. So right,
we're going to have some bad fallouts from this yet.
But the rest of us, I think again, we're I
think we're experienced. Now we're all looking at going he
know this is cool? You go first? Yeah, I see.
Speaker 3: Pretty much talking. Which I do have a laptop that
I've wiped recently that will be getting open Chloor installed
on it. It'll be put onto my isolated IoT network
and it will not have access to my credit cards
or one password yeah.
Speaker 1: Plan good. Let us know how that goes for you.
Speaker 2: I will nice all.
Speaker 3: Right, yeah, if you never hear from me again, it
went very badly.
Speaker 1: Get a phone call. I don't know where I am.
I'm in a phone booth somewhere.
Speaker 3: Very lawnmore man, I thought I were gonna say open
CLO was going to call you. I am Ben.
Speaker 1: There you go nine wait a call back. Oh Ben.
It's been such pleasure talking to you. I wish we
could talk more, and I'm sure we're going to in
the future.
Speaker 2: When you come back.
Speaker 3: Thanks for having me.
Speaker 1: Thank you, and we'll talk to you, dear listener next
time on dot net rocks. Dot net Rocks is brought
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in business. Now, go write some code. See you next time.
Speaker 2: You got Jack, Middle Vans and