Speaker 1: Hey Richard, Hey Carl, what do you know?
Speaker 2: Well, I know that our friend Michelle Rubusta Monte is
Speaker 2: with us to tell us about something that's going on
Speaker 2: adjacent to DEV Intersection.
Speaker 1: What is it? It's cybersecurity Intersection. Let's let Michelle tell
Speaker 1: that story.
Speaker 3: Hey Michelle, Hey Carl, Hey Richard, how are you.
Speaker 2: Tell us about cybersecurity Intersection?
Speaker 3: Well, so, Richard and I are partnering with the group
Speaker 3: that does DEV Intersection and next Gen AI, and we
Speaker 3: are putting on a new conference dedicated to one hundred
Speaker 3: percent security focused topics. And I mean, honestly, the lineup
Speaker 3: of speakers is incredible. We have Paula A. Jenis, who's
Speaker 3: here from Poland and does keynotes all over the world
Speaker 3: and is one of the top rated RSA speakers and
Speaker 3: black hat speaker. We're so lucky to have her. But
Speaker 3: she's not only keynoting, she's got a workshop teaches you
Speaker 3: about protecting your environments against hackers and shows you about
Speaker 3: how to you know, do attacks so that you can
Speaker 3: prevent them. It's pretty cool and sessions like that as well.
Speaker 3: But we also have speakers from Microsoft. We have we
Speaker 3: have speakers that specialize in you know secure coding practices,
Speaker 3: Azure security, zero trust architectures on Azure uh and people
Speaker 3: who do decision maker tracks, so things around governance policy
Speaker 3: and you know how to how to manage and your
Speaker 3: production operations keep them secure. So it's an amazing group
Speaker 3: of speakers, really excited about it.
Speaker 2: And I think I can count myself among the group
Speaker 2: of speakers there.
Speaker 3: Well, yes you can. That is great.
Speaker 2: Yeah, I'm doing a securing Blazer Server applications talk and
Speaker 2: also I think we're doing a Security this Week live
Speaker 2: show there somewhere that is correct.
Speaker 3: Yeah, we'll be recording Security this Week Live. We're going
Speaker 3: to have a great panel with some folks. The interesting
Speaker 3: thing here is we don't really have a Microsoft and
Speaker 3: dot net and Azure focused toecurity conference yet, so that's
Speaker 3: the reason we're putting this on as well. You know
Speaker 3: there are other security conferences, but they have a spread
Speaker 3: of topics that maybe don't focus on the things you
Speaker 3: do day to day. And you know this overlaps with
Speaker 3: again our community of folks that specialize in again dot net,
Speaker 3: Azure and yeah, they need to keep it secure too.
Speaker 3: So with tons of.
Speaker 1: Talks, cyber Intersection is part of a trio of conferences
Speaker 1: we're doing. They have Intersection alongside the Next Gen AI
Speaker 1: Conference all in Orlando the week of October fifth through tenth.
Speaker 1: That's workshops and the main conference. And you can get
Speaker 1: a special registration code if you sign up through Cybersecurity
Speaker 1: Intersection dot com.
Speaker 3: Yeah, so if you sign up at Cybersecurity Intersection dot com,
Speaker 3: then you put in this code, so Alliance cyber three
Speaker 3: hundred and you'll get three hundred off the entry price.
Speaker 3: So that's a special code that only works at cybersecurity
Speaker 3: dot com. And then you have access to all the conferences.
Speaker 2: Like Richard said, Wow, that's cool. Thanks Michelle. I'm looking
Speaker 2: forward to it and I'll see you there. Hey, guess what,
Speaker 2: it's dot net rocks all over again.
Speaker 1: I'm Carl Franklin, an amateur Campbell.
Speaker 2: We're at episode nineteen hundred and sixty nine.
Speaker 1: The first time I've looked at history and thought we
Speaker 1: probably should do a geek out all by itself because
Speaker 1: this is all by itself on this year. It's the
Speaker 1: craziest year, just out of it.
Speaker 2: Yeah, completely madness, cultural shift, end of the sixties. It's
Speaker 2: a big deal, no kidding. It was a pivotabal moment. Yeah,
Speaker 2: well we might as well do that.
Speaker 1: Now you want to go right into it.
Speaker 2: Yeah, what happened in nineteen sixty nine. I'm going to
Speaker 2: let you talk about the space stuff because it's pretty significant.
Speaker 2: Why don't you start with that?
Speaker 1: Yeah? Sure, I mean we're talking about the Moon landing.
Speaker 1: So Apollo nine, which tested the lunar module in lower orbit,
Speaker 1: Apollo ten, which flew all the way to the Moon,
Speaker 1: practiced the landing, got within fifteen kilometers of the surface,
Speaker 1: and then aborted to test the abort systems. And then
Speaker 1: in July of nineteen sixty nine, the Apollo landing A
Speaker 1: follow eleven and Neil Armstrong and that other guy Buzz
Speaker 1: still good old Buzz Buzz Buzz, who was also like
Speaker 1: the guy He's the one who said magnificent desolation describing
Speaker 1: the Moon, and they pulled off this remarkable mission again
Speaker 1: at ridiculously high risk. Yes, that vehicle, the lunar lawn
Speaker 1: module was the limiting factor. It could support two people
Speaker 1: for three days, but it took more than three days
Speaker 1: to stage your rescue, So anything had failed anywhere in
Speaker 1: that vehicle, it was not survivable. Neil happened to bump
Speaker 1: the a breaker on his way out of the lunar
Speaker 1: module and broke that breaker. That breaker happened to be
Speaker 1: the power connection for the ascent engine. Ouch turned out
Speaker 1: that the shape of the breaker cap that would have
Speaker 1: pinned it back down was exactly the same shape as
Speaker 1: a felt pen cap, which Buzz happened to have found
Speaker 1: jam did in there, and that's the only reason they
Speaker 1: were able to get back. That's so cool. I'm sure
Speaker 1: they would have come up with another solution.
Speaker 2: Well, and Apollo of their team would come later. And
Speaker 2: that was even so much innovation in order to get
Speaker 2: those guys on so much of emergency to find it,
Speaker 2: find a way to survive. Not to ignore the Soviets,
Speaker 2: but they were behind at that point. They did their
Speaker 2: first in orbit rendezvous that same year, but the real
Speaker 2: accomnchihment with the first successful landing on Venus with the
Speaker 2: Venera six mission that made it to the surface of Venus,
Speaker 2: sent back footage for about twenty minutes and then milting it.
Speaker 2: Other aerospace news again to ninety sixty ninety Insane seven
Speaker 2: forty seven's first test flight and first commercial flight in
Speaker 2: the same year, go Boeing also Concord's first test flight.
Speaker 1: Nineteen sixty nine. It's crazy, but for all of us
Speaker 1: being computer people and what you are doing right now.
Speaker 1: This was the year that arpanet was turned on for
Speaker 1: the very first time. So this was a packet switching
Speaker 1: network precursor to TCPIP was all about decentralization, no central help,
Speaker 1: multiple routing routes. Although the first messages attempt a first
Speaker 1: message attempted to be transmit across the network got as
Speaker 1: far as L and O in login before crashing. Yeah,
Speaker 1: still work needed to be done. But all of that
Speaker 1: in nineteen.
Speaker 2: And of course, in terms of culture, the Beatles' last
Speaker 2: public performance on the roof of Apple Records on January thirtieth,
Speaker 2: And did you watch Get Back? Yes, the remake of
Speaker 2: it so a great movie. Great movie and the way
Speaker 2: that they cleaned up the footage and everything. It was
Speaker 2: so much better than the quote unquote Let It Be movie,
Speaker 2: which was just horrible quality. Woodstock, the Woodstock Festival in
Speaker 2: August in New York, Upstate New York was a big deal.
Speaker 1: Yep. Yeah.
Speaker 2: In politics, Vietnam War escalated, significant anti war protests occurring
Speaker 2: across the US. The Libyan coup September one, Marmarga Daffi
Speaker 2: ousted King Idris the first ho Chi Minh died September second,
Speaker 2: at the age of seventy nine. And there was a
Speaker 2: few other things. But wow, what a year. Yeah, crazy years,
Speaker 2: extraordinary year. And we were two, so we were just
Speaker 2: becoming conscious of everything around us.
Speaker 1: Not really, yeah, barely. Oh they lift off of Apollo
Speaker 1: eleven was July sixteenth, my birthday. Yeah. Oh so I
Speaker 1: turned two as the rocket was taking.
Speaker 2: That is so cool. Random yeah, random, but very cool.
Speaker 2: All right, so let's do better? No framework roll the music?
Speaker 1: Awesome? All right, man, what do you got?
Speaker 2: I found this really cool trending repo on GitHub. Web
Speaker 2: gooat to web gooat a deliberately insecure web application.
Speaker 1: Oh nice.
Speaker 2: It's maintained by OASP designed to teach web application security lessons.
Speaker 2: Big disclaimers while running.
Speaker 1: Do not deploy this.
Speaker 2: Don't even be on the internet when you're running it.
Speaker 2: Oh wow, it's a demonstration of common service side application flaws.
Speaker 1: Right.
Speaker 2: The exercises are intended to be used by people to
Speaker 2: learn about application security and pen testing techniques, and so
Speaker 2: warning one is, while running this program, your machine will
Speaker 2: be extremely vulnerable to attack. You should disconnect from the
Speaker 2: Internet while using this program. Webgoats default configuration binds to
Speaker 2: local hosts to minimize exposure. And of course this program
Speaker 2: is for educational purposes only.
Speaker 1: Right.
Speaker 2: If you attempt these techniques without authorization, you are very
Speaker 2: likely to get caught. If you are caught engaging in
Speaker 2: unauthorized hacking, most companies will fire you, claiming that you
Speaker 2: were doing security research. Will not work? Is that as
Speaker 2: the first thing that all hackers claim? How about that?
Speaker 1: Yep, don't do it. I mean, you know we're big
Speaker 1: on Troy hunts. You know, pen test yourself, you know,
Speaker 1: hack yourself, but do it with permission. Let people know
Speaker 1: what you're doing. You know, your intent should be good,
Speaker 1: be very careful.
Speaker 2: And you know, like they say, don't be on the internet,
Speaker 2: don't expose yourself. Yeah, you can do all this without
Speaker 2: added risk.
Speaker 1: There are tools sweeping ips all the time looking for vulnerabilities.
Speaker 1: You will not be it will not be long. Yeah,
Speaker 1: and that's it. Who's talking to us today? Richard Grabbing
Speaker 1: comment off a show with nineteen fifty four, the one
Speaker 1: we did a build with our friend w O'Brian talking
Speaker 1: about how AI has come to playwright with the playwright
Speaker 1: MCP which I think you and I both really enjoyed. Yeah,
Speaker 1: this is a funny comment. This is from Karthik VK
Speaker 1: who said in the podcast was mentioned that Microsoft should
Speaker 1: be leading the agent space, but I argue they already were,
Speaker 1: just without getting recognitional rewards. Microsoft has consistently been in
Speaker 1: first areas but rarely reaps the benefits. I don't know
Speaker 1: if I agree with you on this, Karthik, but let's
Speaker 1: see your argument. Take Copilot studio. It's a solid platform
Speaker 1: for building agents with real finesse. Semantic Kernel is another
Speaker 1: underrated gem, true enough, not easy to work with, but
Speaker 1: pretty powerful, letting developers convert existing applications into LLLM powered
Speaker 1: ones just by adding attributes using function calling in a
Speaker 1: well architected way. This is new for Microsoft. They were
Speaker 1: first with a touch based OS, but never got credit.
Speaker 1: That's definitely not true, you know, doubt They did a
Speaker 1: lot of experiments and built tablets early on and back
Speaker 1: in the XPE and so forth, but there were touch
Speaker 1: based interfaces. Heck, we talked about it on the show
Speaker 1: here going back to the sixties. So yeah, they've been
Speaker 1: around for a while. The much criticized Vista layout is
Speaker 1: now being embraced by Apple as the foundation for AR
Speaker 1: glasses of spatial interface. Yeah. I don't think Apple would
Speaker 1: coin it that way. Yeah. Wow. Yeah, the basic idea
Speaker 1: of bigger icons that give space for those kinds of interfaces.
Speaker 1: I don't know that you can copyright any of that. Yeah.
Speaker 1: Microsoft often builds foundational tech that shapes and ecosystem, but
Speaker 1: not always ways and build bring them glory. I think
Speaker 1: like all companies, Microsoft does allow experiments to happen and
Speaker 1: sometimes put them in the field, and sometimes they're too
Speaker 1: ahead of the market. You know, Apple may have built
Speaker 1: the iPhone, but they also built the Newton ten years before.
Speaker 2: Yeah, you can't say always this and never that. I mean,
Speaker 2: it's just not the way it works that. Microsoft has
Speaker 2: made some great contributions to tech over the years, and
Speaker 2: also some flops. So and so is Apple. It's just
Speaker 2: not a.
Speaker 1: I'm really disappointed to Courier tablet never shipped. You know,
Speaker 1: they they got to final prototype on that one before
Speaker 1: they pulled the plug on, which is two bad because
Speaker 1: it's it looked like an interesting machine. I not think
Speaker 1: that it would have succeeded, but I would have bought
Speaker 1: one I would have taken one up for a spin
Speaker 1: for sure. But yeah, Karthik, I think there's more research
Speaker 1: to be done if you want to see these different things.
Speaker 1: But I agree there's many technologies that get put out
Speaker 1: there but are put in the in front of people
Speaker 1: in a way that they necessarily embrace. If Microsoft says
Speaker 1: sinning for anything, it's not advocating for their own stuff
Speaker 1: as well as they possibly could. Often they're just building
Speaker 1: things and it gets out there, and whether or not
Speaker 1: people can see what it can do is another question entirely. Heck,
Speaker 1: half our shows are based on Hey, did you know
Speaker 1: what could do this? Yeah? Right? But that being said,
Speaker 1: thank you so much for your comment, and a coffee
Speaker 1: of music Cobuy is on its way to you. And
Speaker 1: if you'd like a copy of music Code, I read
Speaker 1: a comment on the website at dot NetRocks dot com
Speaker 1: or on the facebooks. We publish every show there, and
Speaker 1: if you comment there and we're reading the show, we'll
Speaker 1: send you a copy of music Code.
Speaker 2: By Before we get started with James here, I want
Speaker 2: to let everybody know that Jeff Fritz and I have
Speaker 2: a new YouTube show that we're doing in addition to
Speaker 2: Blazer puzzle, and we're probably going to alternate weeks, but
Speaker 2: it's called code It with AI. As you probably know
Speaker 2: and James certainly knows because he's his boss. There's a
Speaker 2: big mandate to do AI content for Microsoft Evangelism, you know,
Speaker 2: to because there's a lot of new stuff and there's
Speaker 2: a lot of things to understand, and so we wanted
Speaker 2: to take some of the stuff that he did in
Speaker 2: Copilot that John, which is his website of all these
Speaker 2: little tips and tricks for using Copilot and other things,
Speaker 2: and do videos exposing some of the things that we
Speaker 2: can do as dot net developers, not only to help
Speaker 2: us write code and publish software, but to incorporate AI
Speaker 2: into our applications. And so we started It's interesting you started.
Speaker 2: You talked about Playwright. We started with the playwright MC
Speaker 2: was it MCP? Yeah, yeah, we started with the Playwright
Speaker 2: MCP to create documentation for Copilot dot com and we
Speaker 2: did an individual studio code with the Sonnet four to
Speaker 2: oh and it was amazing. It basically was a very
Speaker 2: small prompt and it just created a user manual for
Speaker 2: Copilot dot John using playwright. So that's coded with AI
Speaker 2: dot com. If you want to check it out and
Speaker 2: we will do more and let us know.
Speaker 1: That's it.
Speaker 2: So let's bring James on. James Montemagne is an old
Speaker 2: friend of ours, a developer community lead at Microsoft focused
Speaker 2: on building community around and helping developers learn and adopt
Speaker 2: the latest frameworks, languages, and agentic developer tools. Hey man,
Speaker 2: what's up.
Speaker 1: Yeah?
Speaker 4: I think that new one at the very end is
Speaker 4: the first time we got to add that on sence
Speaker 4: the last time I was on the pod.
Speaker 1: So yeah, it's been a last time we were on.
Speaker 1: It was like zamorin Land, it was just a while ago,
Speaker 1: like entirely too long ago, to be clear.
Speaker 4: I've missed you both, and I'm I'm very pleased and
Speaker 4: honored and humbled to be back on the pod. So
Speaker 4: it's really good to be back.
Speaker 1: You have you on, man.
Speaker 2: Let's give a little a little history here.
Speaker 1: Oh my god.
Speaker 2: Back in the days of Zamorin, we met James and Hardy, right, yeah, yeah,
Speaker 2: in Boston at the beginning of a dot net Rocks tour, right,
Speaker 2: and you guys were you know, zamorin and at that point,
Speaker 2: and we were talking about zamorin forms and all that stuff.
Speaker 2: You were talking about zamorin forms on the road trip
Speaker 2: with us, and we were just talking about dot net
Speaker 2: in general. I think, if my memory is correct, I.
Speaker 1: Always had the sense that he was chucked under the
Speaker 1: bus in that sense, it's like, hey, get on this
Speaker 1: bus with these strange men.
Speaker 4: It was it was my I believe it was my
Speaker 4: second month on the job, and I'm pretty sure that
Speaker 4: they said, Hey, you're going on Toro with these two dudes,
Speaker 4: or got this RV and just driving around the US
Speaker 4: and go ah.
Speaker 2: And I don't know if you and Chris did it
Speaker 2: the same time, but you guys had built apps and
Speaker 2: got noticed by Microsoft. And I guess that's you know,
Speaker 2: how you worked your way into the organization, isn't it?
Speaker 2: The mobile app?
Speaker 5: Yeah?
Speaker 4: So I had been a professional mobile I worked at
Speaker 4: Cannon early on, writing printer software for them out of college,
Speaker 4: and then I went to PDC, which was right before Build.
Speaker 4: I was on big tent on campus and I got
Speaker 4: a Windows phone. I was a c sharp developer, fell
Speaker 4: in love with mobile development, got an Android device an iPhone,
Speaker 4: started building apps, and I got a job in Seattle.
Speaker 4: Moved my life up there as a mobile developer, found
Speaker 4: zamorin to do cross platform mobile devon dot net. Never
Speaker 4: looked back and that was it. I wrote an app
Speaker 4: that got featured for the company I worked at, Seaton.
Speaker 4: I got featured in Gadget and I was writing blog
Speaker 4: posts and doing kind of advocacy off to the side,
Speaker 4: and yeah, they randomly emailed me. I thought it was
Speaker 4: actually for like their MVP program. I didn't actually realize
Speaker 4: that it was to come in and interview like with
Speaker 4: Natt Friedman at the time, so I like win and
Speaker 4: course by then I knew I was interviewing. And yeah,
Speaker 4: it was three and a half years had xamred before
Speaker 4: the acquisition into Microsoft, which is which is awesome. So
Speaker 4: you know, I still building and publishing apps. I just
Speaker 4: published a brand new Blazer hybrid MAUI app to the
Speaker 4: app store last week, you know ndred percent Vibe Code,
Speaker 4: which was awesome.
Speaker 2: So it was rad I remember Chris Hardy talking about
Speaker 2: his favorite app that he wrote was how many days
Speaker 2: until Christmas?
Speaker 1: He's a big house fan.
Speaker 4: Yeah, and I took his it was ioas only and
Speaker 4: I ported it to Android. Those are the very one
Speaker 4: of the very first things that I did, and I
Speaker 4: put that on the app Store with Chris, which is hilarious.
Speaker 2: So yeah, yeah, funny, funny stuff, long long time ago.
Speaker 2: But we boy, that's where we met and we have
Speaker 2: been friends ever since.
Speaker 4: Absolutely, yeah. And it's like it's so interesting the year stuff. Right,
Speaker 4: you think you were, you know, around in nineteen sixty nine,
Speaker 4: Like what a time to be alive. And that's kind
Speaker 4: of like now. I kind of like think that now,
Speaker 4: and just like how everything is. Everything's always be moving fast, right,
Speaker 4: but it feels like things are super accelerated. But if
Speaker 4: you've latched on, I feel like it's in a really
Speaker 4: really fun and interesting place. I'm excited to dive in
Speaker 4: with kind of some new topics with y'all.
Speaker 2: Well yeah, I mean we don't. We haven't really we
Speaker 2: don't really talk about visual studio code that much because
Speaker 2: I don't think Richard and I use it all that much.
Speaker 2: I don't know about you, Richard, but.
Speaker 1: I'm in and out of it all the time. But
Speaker 1: you know we're we're studio people or ide people, right,
Speaker 1: that's where we came from. I don't know that when
Speaker 1: I want to develop, that's where I go. When I
Speaker 1: want to edit a zambal doc. I mean I mean
Speaker 1: studio code, but.
Speaker 2: I've found that the agents work better in studio code
Speaker 2: than they do in studio probably because of the threading
Speaker 2: model or something like that. I don't know what's going on,
Speaker 2: but I really really enjoy it. You know, every time
Speaker 2: that Fritz and I do something in studio code, I'm like, hmm,
Speaker 2: maybe maybe I'll you know, although I have customers that
Speaker 2: are in studio and I have to use that, so.
Speaker 4: Yeah, I think I think, you know, for me, it
Speaker 4: was kind of in maybe January or February this year
Speaker 4: or I kind of made this leap and jump, and
Speaker 4: I think a lot of developers are early on, like
Speaker 4: in their sort of like how much AI coding stuff
Speaker 4: do I adopt every single day and their journey, Like
Speaker 4: we kind of think that everybody's using it, but that's
Speaker 4: not the case. However, many people are and adopting it
Speaker 4: kind of slowly. But we have always been if you
Speaker 4: think about just intelli Sense and intelecode, and then we
Speaker 4: have the extensions that have been giving us and helping
Speaker 4: us write code faster.
Speaker 1: So really, in.
Speaker 4: January February, I kind of did dive all in when
Speaker 4: agent mode dropped inside of VS code and I really
Speaker 4: dove in deeper because the c sharp Defocate was getting better,
Speaker 4: the Maui extensions were getting better, the Plazer integrations were
Speaker 4: getting better, and it's really just dove all in. And
Speaker 4: I like to say I like gave in. I gave
Speaker 4: myself to agent mode, and you know, I've gone back
Speaker 4: and forth kind of talking about the IDEs, like the
Speaker 4: vs team has been doing great, like you know, adding
Speaker 4: more and more features to the Relief twenty twenty six
Speaker 4: is coming out soon, and like there's more and more integration.
Speaker 4: So it feels like they have some unique features that
Speaker 4: are like the profile aer and some of the debugging
Speaker 4: stuff for ID specific things. But yeah, the agent mode
Speaker 4: and the rapid pace. Like I'm on Insider for VS
Speaker 4: code and I'm just getting updates every single night, just
Speaker 4: like rapid, right, and that's how I live. I don't stable,
Speaker 4: I on the insider and just go.
Speaker 1: I feel like VS code can move faster into this
Speaker 1: new paradigm than the studio can, Like studio customers tend
Speaker 1: to be supporting large projects, like we tend to not
Speaker 1: emphasize the studio responsibilities to project management as much as
Speaker 1: it is to coding space as well, Like the show
Speaker 1: we did with Mads a few weeks ago talking about
Speaker 1: Studio twenty twenty six. He's very clear this is the
Speaker 1: AI version of Studio and it's still coming where you know,
Speaker 1: Studio Code had this in the spring to some of
Speaker 1: the rate. Obviously there's more to be done, but it's like, hey,
Speaker 1: would you think's going to happen with this behemoth that
Speaker 1: is an eye like it only goes so quickly. They've
Speaker 1: I've really done the plugins and so forth, but the
Speaker 1: integration is not the same. It'll be interesting to see
Speaker 1: where they get to. But this is far from a
Speaker 1: played out store.
Speaker 2: We were talking to Dustin Campbell and I was sort
Speaker 2: of complaining a little bit about the Razor Editor. He says, oh, yeah,
Speaker 2: I got that, man, I'm working on that, and apparently
Speaker 2: he has. I haven't seen twenty twenty six yet, but
Speaker 2: Fritz says he has, and the Razor Editor is like
Speaker 2: night and day of what it is and you know,
Speaker 2: currently in twenty twenty two.
Speaker 1: Yeah, I think so, I can't wait.
Speaker 4: The teams are really pushing super hard, and I think
Speaker 4: it's a good point. Like I also think that it's
Speaker 4: great that these you know, two paradigms exist. A lightweight
Speaker 4: code editor that's an AI first open source everything editor,
Speaker 4: and then visual Studio, which is this ide with all
Speaker 4: these big workloads sets up everything for you, right, And
Speaker 4: I think with the Visual Studio, right, it's also not
Speaker 4: just I'm going to open a project, it's that they're
Speaker 4: come and is that And individuals that have huge, crazy projects, right,
Speaker 4: huge c plus plus games like game studios are using
Speaker 4: these things with you know, hundreds of millions of lines
Speaker 4: of code, right, and they're like legacy projects too, and
Speaker 4: you have to think about how do you support the
Speaker 4: really really old stuff and the new stuff and then
Speaker 4: make all of that AI stuff work seamlessly across all
Speaker 4: of that. That's a big chat challenge to represent compared to, Hey,
Speaker 4: I'm on modern stack, right, Like I built this at
Speaker 4: feedback Flow, which you know, I've one hundred percent vibe
Speaker 4: coded AI and I went back and forth between VS
Speaker 4: and VS code. But that's all modern, right. It's it's
Speaker 4: done at nine, it's Blazer, it's Azure Functions, it's done
Speaker 4: at APIs, it's modern MCP stack. So I'm in the
Speaker 4: modern world of doing stuff inside of there. And that
Speaker 4: was great, you know, that I could go and I
Speaker 4: could also open that in VS if I need to
Speaker 4: do deep debugging or do like some advanced profiling or
Speaker 4: things like that. But I can also code anywhere. Right
Speaker 4: right now, I'm on my my Mac Mini, I got
Speaker 4: my surface loptop, I got all my devices. So that's
Speaker 4: where that sort of experience goes. I think it's kind
Speaker 4: of a It's always a great time to be alive
Speaker 4: as a developer because things are evolving. But just that
Speaker 4: choice and flexibility I think is important. And we say
Speaker 4: that with AI as well. There's lots of choices out there.
Speaker 1: I'm seeing that lots of teams, especially those they also
Speaker 1: have younger generation developers. They are mixing the two like
Speaker 1: studio and studio code, you know, especially once you get
Speaker 1: dev kid in the equation, they work and play well together.
Speaker 1: And a lot of web devs and again I'm going
Speaker 1: to say skew younger, they're not interested in the ide
Speaker 1: they learned on studio code. That's how they want to develop.
Speaker 1: They have a plan on how they want to do that,
Speaker 1: but they need to work within those larger projects that
Speaker 1: let's face it, more senior folks are living, you know,
Speaker 1: we're originally built in the IDE and a lot of
Speaker 1: the dependency on that, so it's not like these two
Speaker 1: are mutually exclusive to each other now.
Speaker 4: And I think the team's done a pretty good job,
Speaker 4: especially in this last year, especially as Visual Studio has
Speaker 4: actually adopted a faster iteration cycle instead of every quarter
Speaker 4: every month, and you're actually seeing a lot more parody
Speaker 4: jumping between the two, right actually, as far as model selection,
Speaker 4: how the actual like agent mode and chat modes work,
Speaker 4: and how different integrations like now with coding agents are
Speaker 4: being integrated between the two. So VS Code because it
Speaker 4: ships crazy fast, you know, is going to have things
Speaker 4: super fast first, but also VS will soon follow up. Right,
Speaker 4: it's going through different sort of you know, rolling out
Speaker 4: as just sort of people adopt things at a different pace,
Speaker 4: but also adding unique features, like I said, specific for
Speaker 4: that type of development.
Speaker 1: Being done, and you would hope one informs the other two,
Speaker 1: like what they learn from those modules running in studio
Speaker 1: code then is reflected in studio. You know, can can
Speaker 1: build a better version or more it may make more
Speaker 1: sense for that customer.
Speaker 4: Base, absolutely, you know, And that's why I like the naming.
Speaker 4: The names are the same, right, ask an agent they're
Speaker 4: the same. Right, It'd be really weird if you open
Speaker 4: the same project in both VS Code and Visual Studio
Speaker 4: and then like everything is one hundred percent different, right,
Speaker 4: So even icons and placement and things thought about. I
Speaker 4: think at that factor, however, like inherently they're different. They're
Speaker 4: different editors, they're different spaces inside of there. And for
Speaker 4: me at least, I've really enjoyed kind of being on
Speaker 4: this like super breakneck fast, you know, on the things
Speaker 4: that I'm building. I like to say the year of
Speaker 4: twenty twenty five was the year that I shipped and
Speaker 4: wrote more code in my entire life, at multiple levels
Speaker 4: small like little prototype levels, to large production applications that
Speaker 4: are infusing you know, AI elements of foundry into them,
Speaker 4: to functions to databases, and nearly none of the code
Speaker 4: I wrote by hand at all. Right, I'm actually like, really,
Speaker 4: like I said, dove into this prompt first type of
Speaker 4: development between both VS Code and VS and it's really
Speaker 4: fascinating to watch the editors evolve and also the deep
Speaker 4: understanding that like VS and VS Code and Microsoft itself
Speaker 4: in the developer space, you know, developers, right, So we're
Speaker 4: building tools for developers and we're dog footing, right.
Speaker 1: The vs Code.
Speaker 4: Team builds vs code with vs code and agent mode
Speaker 4: and these things, and same with the Visual Studio team.
Speaker 4: So it's like deep dog fooding and understand that we've
Speaker 4: been doing this for twenty years, thirty years, whatever it
Speaker 4: is now that deep understanding of how software is built.
Speaker 2: Can we talk about the models a little bit. It's
Speaker 2: my understanding that Claude's on it for is like the
Speaker 2: best right now for coding C sharp, Blazer, CSS, JavaScript.
Speaker 2: What's your take on that?
Speaker 4: Well, Carl, back in my day in February weeks ago,
Speaker 4: you know it's now fun because you know all the
Speaker 4: web devs like with JavaScript lies. Oh it's a new day,
Speaker 4: it's a new like. Now it's a new model.
Speaker 1: Right.
Speaker 4: So when I always when I super dove in like
Speaker 4: Clauds on it, three five Droma and four is using there,
Speaker 4: I think there's a few things models or models will
Speaker 4: be new models they have all the time. I think
Speaker 4: for me, it's it's when I think of this and
Speaker 4: if I was to encouraged developers listening, it's a new
Speaker 4: tool in your toolbox. Every model is a new tool.
Speaker 4: Inside of that toolbox is ask, which is agent mode,
Speaker 4: which is coding agents that are working autonomous in the background.
Speaker 4: For me, it's a great question. It comes down to
Speaker 4: how do you want to work and how do you
Speaker 4: want to work with your model? So let me break
Speaker 4: it down into two categories.
Speaker 1: You kind of have.
Speaker 4: You have the GPT models and I usually am in
Speaker 4: GPT five Mini or GBT five and a lot of Sonnet.
Speaker 4: I go back and forth, and I'll tell you why
Speaker 4: I go back and forth. Okay, that these models inherently
Speaker 4: work and think different and they're different people. It is
Speaker 4: if I have two different co workers sitting side by
Speaker 4: side of me, working.
Speaker 1: With different kinds of brain damage, basically.
Speaker 4: All sorts of different thinking and logic and type of
Speaker 4: code that they write. So I think with the GPT
Speaker 4: models they like to kind of be told what to do,
Speaker 4: like what files, what do you want to work on?
Speaker 4: You know, how do you want to work on it?
Speaker 4: And go off and do it. They are very much
Speaker 4: give me a ticket, describe the specs. I gotcha, right.
Speaker 4: They're very very good at that, and they're very very
Speaker 4: fast at it, right to be more pointed at it,
Speaker 4: and that's good in a lot of scenarios like bug fixing,
Speaker 4: like examining, just looking and doing ask and like kind
Speaker 4: of getting detailed information quickly, because that's.
Speaker 2: That's what the GitHub agent uses, right, getub agent, the
Speaker 2: on GitHub, the coding agent, the coding Yeah, the coding agent.
Speaker 1: I think it bops between a few models, does it? Yeah?
Speaker 1: I think it does fast.
Speaker 2: I checked it GPT only, but the son it was coming,
Speaker 2: I guess yeah.
Speaker 4: For a while it was just son it for I
Speaker 4: think so. Really, yeah, I think so.
Speaker 1: But son it.
Speaker 4: Models are fascinating. They are super curious, and they are ambitious,
Speaker 4: and they take time to understand a lot of the context,
Speaker 4: explore the code base. And when you tell it to
Speaker 4: do something and you ask it and you kind of
Speaker 4: give you know, smaller, medium, or even large prompts or
Speaker 4: assign an issue, they like to get in there. They
Speaker 4: like to explore, right, They like to just just figure
Speaker 4: out all the little nooks and crannies and what qutblem
Speaker 4: break it down. And what claud will do though, is
Speaker 4: it will do things you don't necessarily maybe even want
Speaker 4: it to do. But then you're like, maybe I did
Speaker 4: want it to do that.
Speaker 1: I don't know.
Speaker 4: It'll start updating things. It's like, oh, I have to
Speaker 4: dis method. Oh, I should update the docs or I
Speaker 4: should do this right, And as it sort of context grows,
Speaker 4: it will start to like really explore the COVID, which
Speaker 4: is good and bad because it's good and that it
Speaker 4: may you know, get things that you missed, but also
Speaker 4: at the same time, it takes longer. Right, you just
Speaker 4: could be letting it churn and kind of letting it
Speaker 4: do stuff which background coding agents, like background tasks, background agents,
Speaker 4: things like that that run autonomously out there. That's great
Speaker 4: because they can take a lot of time. They can
Speaker 4: be very verbose to get run tests. But I've seen
Speaker 4: with Claude, for example, it's like, hey, let me write
Speaker 4: this tone Okay, let me run this test. I'm gonna
Speaker 4: write test, I'm gonna write the docs. I'm gonna run this,
Speaker 4: and I'm gonna run this, and you're gonna run this.
Speaker 4: You're like, Wow, you just did an entire test suite
Speaker 4: and all.
Speaker 1: I can do is an overachiever. Uh employee.
Speaker 4: It's ambitious. Yeah, they're really ambitious, and you want that
Speaker 4: sometimes and sometimes you don't.
Speaker 1: I've always got the sense that claud it's like they're
Speaker 1: pre the prompt you write to chet GPT is the
Speaker 1: prompt that arrives at chet GPG. When I write a
Speaker 1: prompt to Claude, it's like somebody added a bunch of
Speaker 1: that stuff, a bunch of stuff to the prompt to
Speaker 1: do more.
Speaker 4: So there's a few things, you know, I think of
Speaker 4: best practices here of how do we get these models
Speaker 4: to generate code as if we were writing it. One
Speaker 4: is like the team, the VS and VS code team.
Speaker 4: Like when you send a prompt, there is a system
Speaker 4: prompt that also gets sent, right because there's tools, there's mcps, results,
Speaker 4: other stuff. Each model has its own prompt, right because
Speaker 4: each model is different. So the team is working directly
Speaker 4: with Anthropic and open AI and these other model vendors
Speaker 4: to make sure their models work great based on how
Speaker 4: they built a model. But then there's stuff that you
Speaker 4: can do right. So for example, agents dot MD and
Speaker 4: copilot and diductions, which are instruction files that get sent
Speaker 4: with every single request that you put. So think of
Speaker 4: it as your team's best practices. How do you want
Speaker 4: your code generated? Do you want your CSS and eraser
Speaker 4: dot CSS or do you want to interact dot CSS.
Speaker 4: Do you want things to be light theme and dark theme?
Speaker 4: Do you want specific you know, M underscore, underscore, S underscore, CamelCase,
Speaker 4: Pascal case, how do you code? The model can infer,
Speaker 4: but the model also wants to please, and it wants
Speaker 4: to please quickly. Right, So like if you think of GPT,
Speaker 4: especially for one or five five mini that aren't necessarily
Speaker 4: deep thinking models, they want to respond to you as
Speaker 4: fast as humanly possible.
Speaker 2: Right, So, if you're right, they want to be Promorphization
Speaker 2: is killing Richard, I can just well, no, don't.
Speaker 4: Worry, it's coming. You're absolutely correct. You're absolutely correct. I
Speaker 4: see the mistake now, you're right, and they want to
Speaker 4: make you they want they want to make you happy inherently, right.
Speaker 4: So that's why they have this like verbiage that is like,
Speaker 4: oh no, you're absolutely right, you're totally you're totally good. Yep,
Speaker 4: I see the problem up good? Yeah, Oh I fixed it.
Speaker 1: Did you?
Speaker 5: I don't know what I're looking for is obsequious, but
Speaker 5: you know when you think about it, you know, if
Speaker 5: you had another engineer sitting side by side, do you
Speaker 5: you know you'd be looking at the code.
Speaker 4: Oh yeah, I do see the problem there, it is, right,
Speaker 4: let's fix it.
Speaker 1: When you actually pair a program. You are pretty kind
Speaker 1: to each other because we've all sat in the seat, right, Yeah,
Speaker 1: we've all sat beside the seat.
Speaker 4: If you look at it that way, I think that's
Speaker 4: the way to achieve it. And then also not giving
Speaker 4: up on it. When I built feedback Flow, like I said,
Speaker 4: it's it's hundreds of thousands of lines of code and
Speaker 4: nice architecture and fully open source. And I went into
Speaker 4: it saying I don't want to write any code. I
Speaker 4: want to really dive deep into understanding how every model works,
Speaker 4: how the agent works, how I can customize my instructions,
Speaker 4: how I can get this working. And I'm at the
Speaker 4: point now I don't even run the app on on
Speaker 4: my local machine. I just push it to a branch,
Speaker 4: do a PR, it goes into staging, have the I
Speaker 4: don't even run it. I don't even need to because
Speaker 4: it's gotten to the point that I've massaged the infrastructure
Speaker 4: around it so much that the thing is building it,
Speaker 4: it's running the test, that's doing all the stuff before
Speaker 4: I push the code, sure that it's either going to
Speaker 4: look or not right, and just wasting time running it
Speaker 4: and testing it's not going to pass the tests if
Speaker 4: it is.
Speaker 2: When you say massaging the infrastructure, do you mean like
Speaker 2: setting up a context so it kind of knows your
Speaker 2: style and it and you said it infers it, but
Speaker 2: does it remember it?
Speaker 1: Like is there?
Speaker 2: Do the agents have enough context to learn what I
Speaker 2: like and keep doing it that way?
Speaker 4: Right now you're in the mode of telling it kind
Speaker 4: of how you wanted to do. So that agent's dot
Speaker 4: mdfile or the copilot instructions filed. They're the most important
Speaker 4: files in any project. System prompts, yeah, they're well, they're
Speaker 4: they are not necessarily system prompts. Think of them as
Speaker 4: a set of you know, guidance that you send with
Speaker 4: every prompt. So for example, it'll tell it like what
Speaker 4: the projects are, what frameworks they are, how you like
Speaker 4: your CSS, how you like your c sharp, how you
Speaker 4: like these things, how you like different things constructed in
Speaker 4: your application. Maybe for example, like you prefer using XI
Speaker 4: nate over MS tests, and the tests are run here
Speaker 4: and this is how you run them, or using aspires,
Speaker 4: or here's how you run a spire, Here's how you
Speaker 4: want your CSS versus not. And with every request that
Speaker 4: gets sent off, so it gets attached to the system
Speaker 4: prompt So give it the guidance of the context. Now
Speaker 4: that being said, there's not like there's memories today. I
Speaker 4: mean you can inherently create memories. So I often have
Speaker 4: a docs folder or an ideas folder or you know,
Speaker 4: kind of something in my repo, kind of like spectruve
Speaker 4: in development, like here's my specification, so it could go
Speaker 4: look at how I want things created. But when you're
Speaker 4: in the agent chat, there that entire, entire context is
Speaker 4: being sent back and forth. Right, So the memories, if
Speaker 4: you're working on a big feature, you inherently are like, okay,
Speaker 4: I want to start new chats and I'm working on
Speaker 4: something different. It's actually better to keep that thing around
Speaker 4: until you've implemented or fixed that bug and then change context.
Speaker 4: It's almost like opening and closing a ticket because that
Speaker 4: context is there now. Ideally over time and I think
Speaker 4: we'll get there and probably not the far future. Is
Speaker 4: that these bits of memory, right Like Carl, for example,
Speaker 4: you're like no, no, no, I really want my CSS
Speaker 4: this way, blah blah blah. It should remember that, and
Speaker 4: it should remember that just like you would write that
Speaker 4: in a documentation. So right now today, what I do
Speaker 4: is whenever I see something wrong that it generated and
Speaker 4: I asked.
Speaker 1: It to fix it.
Speaker 4: I say, oh, and can you go write a note
Speaker 4: in the copilot instructions so you don't get this mistake again.
Speaker 4: So I'm telling it to go inherently keeping it memory
Speaker 4: out there.
Speaker 2: I've found with the GitHub code agent coding agent that
Speaker 2: even though I did that, it's still insisted every time
Speaker 2: I asked it to do some laser coding to take
Speaker 2: my existing dot net nine application and downgrade it to
Speaker 2: dot net eight for set, no matter how many times
Speaker 2: I say, don't do this, keep storing it.
Speaker 4: Okay, okay, okay, So here's what's happening with coding agents.
Speaker 1: Bluish pluck here.
Speaker 4: Okay, so I just I just watched this as black
Speaker 4: like whole labubou thing, which is hilarious ID YouTube. Okay,
Speaker 4: so here's a pro tip for dot net developers. Okay,
Speaker 4: So think of coding agents as so agent mode chat.
Speaker 4: You know, code completions inside of VS, inside of VS
Speaker 4: code model context switch. Coding agents. These are that, but
Speaker 4: now they're working on some other machine doing work asynchronously
Speaker 4: for you. It's like having a whole plethora of coworkers
Speaker 4: assigning and doing work all at the same time, multiple branches,
Speaker 4: multiple things, things like that, and to get up Copilot
Speaker 4: coding agent is one of those same thing right now.
Speaker 4: Inherently what happens here, think of it is it needs
Speaker 4: to spin up architecture, needs to spin up a machine
Speaker 4: to write the code and run your code and test
Speaker 4: the code on it. So just like you would you
Speaker 4: write a GitHub action, or you would say, hey, I
Speaker 4: want this to be on a Windows VM, I wanted
Speaker 4: to have dot Net nine, I want to insult these workloads,
Speaker 4: blah blah blah blah blah, you gotta do the same
Speaker 4: thing for the coding agent. So you have to create
Speaker 4: a workflow, and you need to create it with a
Speaker 4: specific name, which is the Copilot setup instructions. And I
Speaker 4: had this happen. It was so upsetting everything that you're
Speaker 4: talking about in general. I'm opposed to link there. This
Speaker 4: is to mine. And what I do is I say, hey,
Speaker 4: you're going to run this on an am boontu Latest,
Speaker 4: give it read permission, check out the code, set up
Speaker 4: dot net nine, and then insull dependencies and insult the ASPIRECLI.
Speaker 4: And when you do that, what ends up happening is
Speaker 4: it writes the code and then it builds your project,
Speaker 4: so you can think of it like this. What happened
Speaker 4: to Carl is it tried to run the code and
Speaker 4: it's like I only got done at eight. I don't
Speaker 4: have dot at nine. So instead of it, does it
Speaker 4: necessarily know how to install stuff, you know on your
Speaker 4: behalf on that machine, you need to tell it.
Speaker 1: It would be cool if it did.
Speaker 4: To be honest with you, I mean it can you
Speaker 4: get restore, it can run those commands. So it's like, hey,
Speaker 4: I know, I know how to fix this, Like, oh,
Speaker 4: I see the problem. I see the problem.
Speaker 1: I'll just eight.
Speaker 4: I'm on a machine that's done at eight, but you
Speaker 4: want down nine, so I'm just going to downgrade it automatically.
Speaker 4: So that's how you get around that. And the same
Speaker 4: thing for for Maui, for example, if you're doing Mali
Speaker 4: work you install the Maui workload for for Android and
Speaker 4: I just run it on a boon joke because you
Speaker 4: don't need to inherently run it on iOS and all.
Speaker 1: These other things.
Speaker 4: So that's how that's how you set it up. It
Speaker 4: seems silly, but once on at ten's here, then the
Speaker 4: default right, the default machine, Well, then get upgraded. So
Speaker 4: That is a pro tip because I ran to that
Speaker 4: same thing. I use coding agents all the time. I
Speaker 4: have an idea at midnight, I open up the GitHub
Speaker 4: app on my phone, you know, I create an issue.
Speaker 1: Boom done. Yeah.
Speaker 4: And now if I'm on a branch, I just you
Speaker 4: just go in and there's an agent's panel to say, yeah,
Speaker 4: this app. Go. I wake up in the morning, you're
Speaker 4: like five pool requests ready for your review, you know.
Speaker 4: And it's like this crazy thing. Once you go all
Speaker 4: in that you can really build in hip code if
Speaker 4: you get it into that state where I think you're
Speaker 4: in the flow kind of like when we talk about
Speaker 4: code flow, right, you're in the addit area blah blah
Speaker 4: blah blah.
Speaker 1: Right.
Speaker 4: If you can get in in the flow with these agents,
Speaker 4: and I think it can be super super productive.
Speaker 2: So I know, we got to take a break here,
Speaker 2: so let's do that. When we come back, I have
Speaker 2: a message about Azure deevop, so we'll be right back
Speaker 2: after these very important messages. Did you know there's a
Speaker 2: dot net on AWS community. Follow the social media blogs,
Speaker 2: YouTube influencers and open source projects and add your own voice.
Speaker 2: Get plugged into the dot net on Aws Community at
Speaker 2: aws dot Amazon dot com, slash dot net, and we're back.
Speaker 2: It's dot net rocks. I'm Carl Franklin, that's Richard Campbell. Hey,
Speaker 2: that's James Montemagno. And we're talking about AI and visual
Speaker 2: studio code in other places. So, yeah, I have a
Speaker 2: customer where we started out in GitHub and then they
Speaker 2: said we had to go over to Azure DevOps because
Speaker 2: there are other stuff, their legacy stuff is over there whatever.
Speaker 2: And then the GitHub copilot agent coding agent comes out
Speaker 2: and I'm like, geez, I wish I had this over there,
Speaker 2: but I don't. And so now I'm trying to get
Speaker 2: him to come back over to GitHub right and they
Speaker 2: won't do that, and I'm just like, what.
Speaker 1: Can we do about that?
Speaker 4: That's a great question. So there are a few integrations
Speaker 4: with get up copilot for azur DevOps. One, there's been
Speaker 4: GitHub Advanced Security for a while, which is pretty cool,
Speaker 4: so you can turn that onto scanning. There's also now
Speaker 4: Azure boards integration for get hub copilot. This is a
Speaker 4: private preview you can kind of see where this is going.
Speaker 4: But basically how this will work is that if you
Speaker 4: have using Azure DevOps and if your code is hosted
Speaker 4: on GitHub. Because Azure DevOps can connect to multiple Git repositories,
Speaker 4: you can then assign work through Azure DevOps to getthub
Speaker 4: code pilot and will perform that work for you on
Speaker 4: your back right. So it is a hybrid flow today.
Speaker 4: But that condition infrastructure.
Speaker 2: That condition means that the code repositories have to be
Speaker 2: on GitHub and that's not where they are on TFS,
Speaker 2: and that's whe're going to stay there.
Speaker 1: Which really what I thought was why how as your
Speaker 1: DevOps are supposed to work? That was the TFS approach,
Speaker 1: where GitHub actions was the GitHub appro.
Speaker 4: Yeah, you know, I think that there's been a lot
Speaker 4: of listening and learning to Obviously, you know, the companies
Speaker 4: using Azure DevOps, we use a lot of Azure DevOps
Speaker 4: internally as well, so this is a problem for us
Speaker 4: to inherently we have tons of code on get up,
Speaker 4: but also tons of code not on GitHub. And there's
Speaker 4: a lot of teams that are like exactly in carl
Speaker 4: Spot that want to do this. So there's a lot
Speaker 4: of work being done there. I don't have necessarily like
Speaker 4: insight into it, but you know, the teams are listening
Speaker 4: and you're starting to see some of that listening back
Speaker 4: into product right away. Right inherently, there are two very
Speaker 4: different products that work very very differently. And the thing
Speaker 4: is do you build the thing twice?
Speaker 1: Right?
Speaker 4: You know what I mean?
Speaker 1: Or that's what they suggested.
Speaker 2: Actually they well they suggested I clone the repo in
Speaker 2: the kidthub and then use all the coding agent stuff
Speaker 2: and then move it back into the TFS repunt. I'm like, God,
Speaker 2: I want to do that that.
Speaker 4: There's a few things though, I will say this is
Speaker 4: is that that's a little bit tricky in general on
Speaker 4: that ideal. Obviously for all the stuff that you're doing
Speaker 4: in VS and VS code, obviously all works just fine,
Speaker 4: just that coding agent part that is there for asynchronous work.
Speaker 4: And the thing is also like remote indexing. I don't
Speaker 4: think we have remote inducing for Azure DevOps, but if
Speaker 4: your code is on GitHub, when you're working inside of
Speaker 4: VS code or Visual Studio, we actually remote index your repo.
Speaker 4: And what that means is it can do semantic search
Speaker 4: a whole lot faster. And that means that all of
Speaker 4: your agent mode requests are like way faster, especially on
Speaker 4: huge codebases. And that's also super important. So I'm not
Speaker 4: sure that's going to come to Azure devlops for what
Speaker 4: that will look like, that would be pretty cool. I'm
Speaker 4: sure there's a future requests out there, but that is
Speaker 4: something to think about. But yeah, you know, I think
Speaker 4: with this world of AI, there's a lot of implications
Speaker 4: of where the tools are, what tools are you using,
Speaker 4: how do you blend these together? And also the team.
Speaker 4: But one thing we'll point out is, you know, I
Speaker 4: work with a lot of companies that they're not only
Speaker 4: using dot net spoiler alert. You know, they're not only shocking,
Speaker 4: they're not only.
Speaker 1: Using vs code.
Speaker 4: Right, they're in Exco, they're in Intelligent, they're in other ideas.
Speaker 4: You have a team that's maybe building mobile apps natively, well,
Speaker 4: they're in exco, they're inside of Android Studio. Maybe they're
Speaker 4: back ends in dot net. So do you buy five
Speaker 4: different AI coding projects?
Speaker 1: Yeah, well, I'm seeing that in a lot of organizations
Speaker 1: where they're quite fragmented. There's guys running Windsurfing, guys running Cursor,
Speaker 1: and yep, they're all working against the same codebase. But
Speaker 1: some weird things happen sometimes, and the models right inherently
Speaker 1: are the same models across all of them right in general,
Speaker 1: just different user experience. But I will point out this
Speaker 1: get up Copilot does have extensions for excode for Intelligent
Speaker 1: for Eclipse. Right, that's out there, so you can actually
Speaker 1: use you know, Claude so on it, you know, powered
Speaker 1: by get up Copilot inside of xcode to write swift
Speaker 1: code like that exists today. That's out there. And I
Speaker 1: will say, if you're being enterprise, get up Copilot and
Speaker 1: the enterprise and business skeus give.
Speaker 4: You a lot of.
Speaker 1: Control.
Speaker 4: For example, uh, my wife, we were just doing some
Speaker 4: coding and I was showing her all these models and
Speaker 4: this and this that, and then she's like, oky, oh
Speaker 4: I got we're doing like a little She goan to
Speaker 4: go do this thing. She's like, I only see GPT
Speaker 4: four oh and four one. She's like, I want sown it.
Speaker 4: Where's my son it? Where's my GPT five? And I
Speaker 4: was like, hell, your IT department needs to turn it
Speaker 4: on because it's like for her company. Right, So it's like, yeah,
Speaker 4: there's that control. So I think that's one thing too,
Speaker 4: is what do you want?
Speaker 1: Right, I've asked. I've also seen you.
Speaker 4: Unfortunately some folks that just are like contractors. Right, they
Speaker 4: work for a bunch of different companies, and then they
Speaker 4: get their get up account onboarded by the company temporarily,
Speaker 4: and then their get up copilot settings get overruled by
Speaker 4: the company processes. Right, So how do you manage that?
Speaker 4: It's a very interesting thing about, you know, different policies
Speaker 4: that are out there, so good or bad, right, how
Speaker 4: things are working? But yeah, it's not probably about there's CLIs,
Speaker 4: there's coding agents, there's integrations, there's all sorts of things
Speaker 4: and many tools. Obviously I use our stuff that we build.
Speaker 1: I'm a little.
Speaker 4: Biased, obviously, but I think our stuff's really great, and
Speaker 4: I've been really building and shipping a lot of code.
Speaker 4: But kind of to Carl's point earlier, it's also hard
Speaker 4: to really keep up with all this stuff, right, You.
Speaker 1: Can't keep hopping between tools all the time. You got
Speaker 1: to get some work done too, exactly right. And so
Speaker 1: one thing that has been really nice is some into
Speaker 1: the newer standardization when it comes to things like MCP servers,
Speaker 1: model contacts and protocol servers that want to work everywhere.
Speaker 1: It isn't the embracing of thems CP just to proof
Speaker 1: that the industry is desperate for some standards, maybe a
Speaker 1: little bit because MCP is not great, but at least
Speaker 1: it's something people could agree. Yeah, it's a way to
Speaker 1: provide that additional context to data to these models, right,
Speaker 1: And you know there's tons of folks across the industry
Speaker 1: that are on the board, including folks from Microsoft and
Speaker 1: GitHub and the registry as well. So standardization of how
Speaker 1: does this work? How does it work in businesses? But
Speaker 1: also agents dot MD. You go to agent dot MD
Speaker 1: that is a kind of sid in the show link
Speaker 1: already because it's well worth a look and everybody seems
Speaker 1: to be conceding that too. Yeah.
Speaker 4: You know, here's the problem as well, is like how
Speaker 4: do you make sure that you have unique features versus
Speaker 4: everyone else? So it takes time to create those standards,
Speaker 4: but creating time means like this thing was created like
Speaker 4: a few months ago. Now it's standard, which are kind
Speaker 4: of crazy to think about in this modern day. So
Speaker 4: Agents at MD is basically a way of open format
Speaker 4: for coding agents that works across all those things that
Speaker 4: you just mentioned, including vs code. The coding agent will
Speaker 4: come to Visual Studios soon obviously, and CLIs and it
Speaker 4: is exactly like copilot instructions in a.
Speaker 1: Way, it's like a universal language.
Speaker 4: It's a universal language. So what we see is folks
Speaker 4: will mix and match these agents and copilot instructions have
Speaker 4: really specific things what they're using a get up copilot,
Speaker 4: and then more generic things for the agent's ot MD
Speaker 4: that anything can work on. But yeah, so it's great
Speaker 4: to see so many names there, and I think you'll
Speaker 4: see more of this sort of standardization as it goes.
Speaker 4: But also tools will do unique things and they'll stand
Speaker 4: out as well.
Speaker 1: So yeah, yeah, I got to push back on the
Speaker 1: vibe coding term. It kills me. I mean because what
Speaker 1: Caparthy was talking about and it was only earlier this year,
Speaker 1: which is crazy to think about that. It really was
Speaker 1: like senior developers should experiment, but you know, you don't
Speaker 1: deploy those experiments where I feel like you're using it more.
Speaker 1: You're using your tools as in a PM role, And
Speaker 1: you really say vibe coding and we say, I'm not
Speaker 1: writing the code, but I am supervising the process.
Speaker 2: It's like a pejorative that got reclaimed by another culture, right.
Speaker 2: You know, so my kids used to call me bougie.
Speaker 2: You know, Oh that's so that's so boogie dad. You know,
Speaker 2: when I'm like cooking a steak that costs sixty bucks
Speaker 2: or something like that, Oh, it's so bougie. And then
Speaker 2: you know, I'm like, I'm going to use that term
Speaker 2: in a positive way. I'm gonna, Oh, this is gonna
Speaker 2: be the boogiest dinner you've ever had, right, And they're like, no, Dad, No,
Speaker 2: you can't do that.
Speaker 4: I think if I'm going the same thing, it's hard.
Speaker 4: When I think of vibe coding is really just coding
Speaker 4: with AI. Let's just be honest with you and you're
Speaker 4: in a flow, just like you can be coding anytime.
Speaker 4: To me, honestly, that's all vibe coding is. I went
Speaker 4: on hansom In's podcast and he had the same exact thing,
Speaker 4: I hate you know, blah blah blah. I was like, listen,
Speaker 4: I think the term is silly, but it also describes
Speaker 4: what is happening in my mind. I was up with
Speaker 4: David Fowler working on the feedback flow app because him
Speaker 4: and I were going back and forth on it, and
Speaker 4: it's like this is a real production now, like this
Speaker 4: is a thing that actually ships, like a real money
Speaker 4: for my personal subscription that has It's one of the
Speaker 4: biggest things that I've ever shipped, you know, in the
Speaker 4: last fourteen years since I did advocacy. It's it's a
Speaker 4: real product. And I also vibe code tons of tiny
Speaker 4: projects as well. But it is just really coding. But
Speaker 4: I am in a vibe like I'd be up at
Speaker 4: two in the morning going back and forth and David's like,
Speaker 4: what if you had this new feature and literally five
Speaker 4: minutes later, I'd have it pushed to production. It was
Speaker 4: like the vibes, the flow. It's a coding flow, just
Speaker 4: with AI. So the vibe coding part.
Speaker 1: Is it's all vibes.
Speaker 4: I say, it's vibes all the way down. I turn
Speaker 4: on some music. I'm just going. And I told my wife,
Speaker 4: I said, when I was really deep in this project,
Speaker 4: really in the beginning, I said, I'm sorry, I'm just
Speaker 4: I haven't had this much fun coding in like a decade,
Speaker 4: and I can't help myself. And I know I'm gonna
Speaker 4: wake up refresh and I'm going I managing a project.
Speaker 4: I'm not not coding. I am supervising in real time.
Speaker 4: I don't know the code is mine. I'm prompt, I'm
Speaker 4: doing things. I got into this flow where literally as
Speaker 4: it was churning and it was describing what's doing and it's
Speaker 4: doing I'm actively reviewing the code so fast. In my mind,
Speaker 4: that flow, that flow state was just there. I'm not
Speaker 4: say it's going to be there for everyone when you're
Speaker 4: working on very pointed updates, but it happened.
Speaker 1: No, No, And I totally and I agree with what
Speaker 1: you're saying too, Like, I think this is a great point.
Speaker 1: It's like, if your passion is typing code, you're not
Speaker 1: going to love these tools. Now if your passion is
Speaker 1: delivering solutions to customers, boy, this thing cranks out solutions fast.
Speaker 1: And you're running in there that PM role of supervising
Speaker 1: the overall flow, but you're also responsible for the architecture.
Speaker 1: You know, you're you're kind of put on the QA head. Ever,
Speaker 1: so I woulday, are we really going down the right path?
Speaker 1: Like you're pressing on a lot of things. But and
Speaker 1: that could be really fun. I have a friend who said, dude,
Speaker 1: I've learned how to fly, and I'm really enjoying flying.
Speaker 4: I worked Okay, so not ALLAI coding is vibes right,
Speaker 4: So I worked with co pilot pother and I implemented
Speaker 4: authentication into my feedback flow app. It took one month
Speaker 4: one poll request. I added twenty we added twenty two
Speaker 4: thousand lines of code, removed five thousand lines of code.
Speaker 4: We had two hundred files changed in a conversation of
Speaker 4: two hundred and forty comments back and forth. We're having
Speaker 4: a conversation reviewing code back and forth in real time, right,
Speaker 4: And this happened pushing back and forth to get us right.
Speaker 1: And to be clear, you're conversing with software.
Speaker 4: I am conversing with software as if it is. It
Speaker 4: is Carl sitting next to me, and and I'm reviewing
Speaker 4: code with Carl. That's what I'm.
Speaker 2: Doing, James.
Speaker 1: But I also have a great appreciation for putting all
Speaker 1: that as issues and in pull requests. Commentary gives you
Speaker 1: a clear documentation of what the intent was and what
Speaker 1: the tools did for you.
Speaker 4: Yeah, one hundred percent, one one hundred percent and there,
Speaker 4: like I am, the guidance is just a tool, whether
Speaker 4: whether it's there or not, just like intellcode or Intelecentre. Honestly,
Speaker 4: it's exactly the same.
Speaker 1: And I'm high resisted the personalization because people are overdoing it, right,
Speaker 1: They're taking this to the r but do I talk
Speaker 1: to my car and my car misbehaves? Damn, right, I do.
Speaker 1: There you go.
Speaker 4: I will say this. I do talk to agents and
Speaker 4: AI much different than I would talk to Carl A
Speaker 4: hundred percent sure, are.
Speaker 1: Per I know a lot of folks just like if
Speaker 1: you conversed with a person the way you're talking to
Speaker 1: this tool, HR would be calling you. Right, this is
Speaker 1: abusive language.
Speaker 2: You know what I talk about when I talk about
Speaker 2: the Amazon thing that starts she who starts with a right.
Speaker 2: We can't really say her name because she does cause harm.
Speaker 2: So my wife, when you know, I will usually say,
Speaker 2: you know, hmmm, stop when she's rambling on about something
Speaker 2: I wanting to stop. My wife says shut up, and
Speaker 2: it works, but I feel bad.
Speaker 1: Yeah, you know like negative language, negative language and it works.
Speaker 1: It affects both ways.
Speaker 4: Yeah, I think just looking at it is like if
Speaker 4: I'm writing the code or I'm writing the prompt. It's
Speaker 4: like I was going to write this code eventually, right,
Speaker 4: but I'm doing the code reviews. I'm like you said,
Speaker 4: I'm in charge of the archestras.
Speaker 1: You are responsible.
Speaker 4: Yeah, And I would say this even if you're like,
Speaker 4: I don't necessarily wanted to write my code. I was
Speaker 4: sitting down with a developer the other day and this
Speaker 4: really complex application, big scale application, and they were hitting
Speaker 4: this endpoint. It was making a call off to EF
Speaker 4: and hitting their database and it was just returning a
Speaker 4: five hundred er no exception. It just was five hundred
Speaker 4: coming back in the swagger. And I said, Okay, here's
Speaker 4: what I wreck And they were like, I've been trying
Speaker 4: to figure out what the heck this is going for
Speaker 4: the last forty five minutes. I said, take the entire exception,
Speaker 4: go into ask mode and put on a thinking model, right,
Speaker 4: a thinking model that can do deep research. Say hey,
Speaker 4: I have this method in this thing. When I call
Speaker 4: this this is happening. I know the breakpoint goes here,
Speaker 4: it doesn't hit the next line.
Speaker 1: What's the problem.
Speaker 4: Within thirty seconds, it's like, Oh, what actually happened is
Speaker 4: you'd set up a new model and the DTO and
Speaker 4: enerny framework is expecting it as a foreign key, but
Speaker 4: it expects it as a different name inherently, so you
Speaker 4: need to add an attribute to foreign key.
Speaker 1: Right.
Speaker 4: Could they have figured that out?
Speaker 1: Yes? How long would it took?
Speaker 4: Who knows?
Speaker 1: But it's smart. Could have been the whole day and
Speaker 1: your keyboard imprints on your forehead right like being there thrashing.
Speaker 4: So I think it is it is a do you
Speaker 4: need to go all in to this agent mode and
Speaker 4: it's coding agent like start slow, right, get some suggestions,
Speaker 4: ask it, get some insight into the application. I was
Speaker 4: working with the with copilot just yesterday with my MCP
Speaker 4: server I have for this app, and I was like, yeah,
Speaker 4: you know, how do I architect it? What does this
Speaker 4: look like? What do I need to update my application?
Speaker 4: It came together with a plan. It's like, here's the plan.
Speaker 4: Let's review the plan, and then let's implement the plan. Right,
Speaker 4: So I'm in control, right human in the loop, I'm
Speaker 4: always in control of everything that it's doing. I'm prompting,
Speaker 4: I'm creating the plan, I'm creating the issues. I'm reviewing
Speaker 4: that code. I'm the one pressing the merge button right right,
Speaker 4: I'm merging the code right at the end of the
Speaker 4: day that I've reviewed inside of it. And the hope
Speaker 4: is that with the guidance of these instructions and these
Speaker 4: agents on MD that that the code that it generates
Speaker 4: is very similar to code that I would generate at
Speaker 4: the end of the day, so I have to review
Speaker 4: and the compiler always gets to say and the requirement
Speaker 4: stock is sitting there to compare against.
Speaker 1: Like I do think we're in a unique place in
Speaker 1: our role as creators of software to take these generative
Speaker 1: AI tools to places that are harder for other industries
Speaker 1: to do, just because we're used to vetting this and
Speaker 1: we're used to building goal posts and evaluating against them.
Speaker 1: Like we have a lot of tools and behaviors long
Speaker 1: before the LM showed up that support this development practice.
Speaker 4: It's a mind shift. It's just a mind shift, just
Speaker 4: like any tool or extension that you've ever in soaved
Speaker 4: individual study or VISKA. It is how do I learn
Speaker 4: this tool? How do I become an expert at this
Speaker 4: tool to help me be more productive? As little or
Speaker 4: as much as you want to use you know, it depends.
Speaker 1: You know.
Speaker 4: It's just a slider bar, that's all it is. And
Speaker 4: to me, it's am I saving a minute, an hour
Speaker 4: a day? All of those are important. It's just a
Speaker 4: I can shave a few minutes, that's great.
Speaker 2: It's another choice that you take before you sit down
Speaker 2: and write a line of code. It's like all right,
Speaker 2: here's here's what I have to do. HM, can sign it?
Speaker 2: Help me out here?
Speaker 4: Yeah?
Speaker 1: Can you know is.
Speaker 2: It going to be faster for me to do it
Speaker 2: myself because I know, or is it going to be
Speaker 2: faster for me to create a prompt and blah blah
Speaker 2: blah and explain things and have the AI do it.
Speaker 4: Example, if I want to like rename files or move
Speaker 4: things around or actually like change in name space, like
Speaker 4: Visual Studio is very good at that and it's very proficient. Right,
Speaker 4: if you move a folder from models to models, person
Speaker 4: people or whatever, you need to update the name spaces,
Speaker 4: It'll just do it for you. You could have prompted the LM.
Speaker 4: Now you're just burning tokens for no reason. Let the tools.
Speaker 4: Let the tools be awesome at what tools are doing,
Speaker 4: right vs Code and Visual Studio are awesome at so
Speaker 4: many things without AI right that it's doing, you know,
Speaker 4: just inherently the static analysis. Let it be awesome at that,
Speaker 4: and then use the model for these harder problems to
Speaker 4: kind of solve as well.
Speaker 1: Or just nuisance things.
Speaker 2: Right, So I had I don't know a list of
Speaker 2: twenty properties that I had to boolly and check and
Speaker 2: if if the properties were true, then I had to
Speaker 2: express some HTML, right, and I had to do that
Speaker 2: for like twenty properties, but they weren't in alphabetical order,
Speaker 2: so you'd end up with a list with you know,
Speaker 2: names of things all over the place. And I just
Speaker 2: you know, told the I think it was chat Chiptia,
Speaker 2: just said can you alphatize this for me?
Speaker 1: And yeah, no problem.
Speaker 4: Copy paste the vs code website. We have these dev
Speaker 4: days going on, these community events. All the data is
Speaker 4: in like a CSV file. So I go into agent
Speaker 4: MO and I say, hey, I need to add And
Speaker 4: then inside the vs code websites a bunch of like
Speaker 4: you know, different blobs, different data, different things, and I say, hey,
Speaker 4: I need to add these five events. Just go update
Speaker 4: the site with these five events, and go update in
Speaker 4: these places and it'll take. It's like, this is CSV data.
Speaker 4: It knows how to transform that and just put it.
Speaker 4: And then we also have locations of latitude and longitude.
Speaker 4: So I'm like, and also go figure out the latitude
Speaker 4: and longitude. It knows the latitude and longitude of you know, Portland, Oregon,
Speaker 4: for example, Right, I can figure it out, and of
Speaker 4: course I review it to make sure it's correct. It's
Speaker 4: not one hundred percent every time. And that's another part
Speaker 4: in part right it, it'd be clear it doesn't know
Speaker 4: it looked it up. It looked it up, and it
Speaker 4: may have looked it up incorrectly.
Speaker 1: That's let Yeah, I like it.
Speaker 4: It does it exactly exactly. It's all the context that
Speaker 4: it has.
Speaker 2: They all have brain damage. You got to pick your
Speaker 2: brain damage basically.
Speaker 1: Well, let's start with they don't have brain Oh, come on, Richard,
Speaker 1: lighten up. It's just software. It is just soft software.
Speaker 2: But it's easier for humans to engage with something when
Speaker 2: they treat it like another human. That's what we do
Speaker 2: with our dogs and our pets and our cars and everything.
Speaker 4: I think it's a it's a big database. I think
Speaker 4: it was a big database that it's quarrying, right, But
Speaker 4: what it does is that it can querry that database
Speaker 4: kind of like you're saying, Richard's like, it's just a
Speaker 4: big database of stuff that it's pulling from.
Speaker 1: But what it does is it.
Speaker 4: Summarizes things and a thing that I can part Like
Speaker 4: I was just looking at example example out of the blue.
Speaker 4: We our dog has diabetes and we have to give
Speaker 4: her shots every day, the VET accidentally gave us you
Speaker 4: one hundred needles. We're supposed to get you forty needles.
Speaker 4: I actually have no idea what that means. Are they
Speaker 4: the same? The units look okay, they're different, Like they
Speaker 4: are the same. So I just went into copilot on
Speaker 4: my at Microsoft copilot and I said, just like you're
Speaker 4: going shat Gypt, I said, what's the difference between you
Speaker 4: forty and you one hundred needles? And give me an
Speaker 4: analysis of like what this means and if there's conversions
Speaker 4: or anything. And it gave me tables, It gave me graphs,
Speaker 4: and it gave me warnings like these are not the same.
Speaker 4: You should not be using these internal No, it's two
Speaker 4: and a half times more. Now I could do all
Speaker 4: of that research, all of that research. All that data
Speaker 4: exists on the internet, and if I went to Google
Speaker 4: or went to bing right, they give me that. But
Speaker 4: it gave me this nice thing that I could then share,
Speaker 4: I could keep in my memory. I now understand that I
Speaker 4: could go back to that's all these things are big
Speaker 4: databases of information, and it knows how to nicely summarize
Speaker 4: things for us in human form in a nice way
Speaker 4: that I can understand or tell it, to tell it
Speaker 4: to display it in a different way.
Speaker 2: Right, here's a creative Here's an issue though, Right, A
Speaker 2: lot of people are using these AI things to get
Speaker 2: to gather facts and then they're satisfied with the fact
Speaker 2: that the facts look okay, and so you know, we
Speaker 2: we we're not going to double check because that's why
Speaker 2: we asked it in the first place, because we didn't
Speaker 2: want to go to Google and go to different resource
Speaker 2: places and look things up. So I think that people
Speaker 2: are doing that, they're just you know, asking for facts,
Speaker 2: taking the facts as they are, not checking them and
Speaker 2: using them. I don't think that's right.
Speaker 4: Now, I think no, I agree. I think it's the
Speaker 4: same thing with coding, right, like the code that's in
Speaker 4: the flow, Like I'm reviewing, I'm understanding, I'm doing that.
Speaker 4: I I I'm not when I say I'm you know,
Speaker 4: just in the flow and I'm just like accepting the stuff.
Speaker 4: I'm reviewing the stuff I'm reviewing what's generating, right, I'm
Speaker 4: not having an auto commit.
Speaker 1: Right.
Speaker 2: But in this case, you didn't know the difference between
Speaker 2: you forty and U two hundred, right, so you couldn't know.
Speaker 1: Could not It was accurate or not.
Speaker 4: Now that being sad, like you said, it's up. It's
Speaker 4: just like it's just like funnily enough going to googler
Speaker 4: bang and then opening a bunch of links. How much
Speaker 4: do you trust those sources as well to it?
Speaker 1: Right?
Speaker 4: So, the one thing that I do like about and
Speaker 4: what I how I use AI. Actually, surprisingly I use
Speaker 4: very little like AI chapbot, I don't use JGBT. I
Speaker 4: use Copilot a little bit for some research. It's not
Speaker 4: really my I haven't gotten into that flow of like
Speaker 4: how I want to quarry the Internet for this data,
Speaker 4: But I will say that the one thing that I
Speaker 4: do and how I use it is it gives me
Speaker 4: the links of where I got the research.
Speaker 1: I always leble check. But I agree with you.
Speaker 4: I don't think people are doing that, And I think,
Speaker 4: how do you bubble that up? So people know at
Speaker 4: least at high level did this come from? You know,
Speaker 4: CNN dot com? Did this come from the.
Speaker 2: That I want at least three sources?
Speaker 1: Right?
Speaker 2: And if if any one of those three sources is different,
Speaker 2: now we have a problem.
Speaker 4: Yeah, and you can always ask it to double check itself.
Speaker 4: I had it come up with some numbers. We're celebrating
Speaker 4: some number like fifty million Visual City users. It's like,
Speaker 4: give me some fun stats about fifty million. It just
Speaker 4: came up with something and was like, yeah, but really
Speaker 4: is that really true? And it's like, yeah, some of
Speaker 4: them weren't. I was like, okay, you know, ask it,
Speaker 4: like are you sure that that is writing? Is that correct?
Speaker 4: It's like, well, I was just trying to be fun.
Speaker 1: Like okay, well, I was asking the crack type.
Speaker 4: I was like being serious here, like let's go in
Speaker 4: you know, on this. So I think it is like
Speaker 4: with anything, yeah, any new tool, you know, making sure
Speaker 4: that you are reviewing all of all the input and
Speaker 4: output that that you have. Right, you can give it
Speaker 4: bad input and get bad output. You can give a
Speaker 4: good input and get bad output. You can get good
Speaker 4: input and get good output. But always having that human
Speaker 4: in the loop is super important and reviewing everything in
Speaker 4: the world. Right, but also the same Right, if I
Speaker 4: walk down the road and I talked to five people
Speaker 4: and asked them about something, I might get five different answers, right,
Speaker 4: which one's correct? I don't know what are their sources.
Speaker 4: So that's how you look at it.
Speaker 2: It makes a good case for us as developers because
Speaker 2: we are the guys with the knowledge and we can
Speaker 2: see whether that code that it general it is right
Speaker 2: or wrong, or efficient or inefficient. So it really really
Speaker 2: really works. AI really works for us. It's just in
Speaker 2: that whole fact based MELIU that I think problems arise
Speaker 2: and then it'll get better.
Speaker 1: Well, and if you know the code is generating is
Speaker 1: in theory a set of facts about executing. It's just
Speaker 1: that there's an easy way to validate it. Yeah. But
Speaker 1: I think this behavior of you know, building a validation
Speaker 1: strategy out of every output is just going to be
Speaker 1: part of the reflex the same way.
Speaker 2: Yeah, And I just don't think many people are going
Speaker 2: to do it.
Speaker 1: Well, they will eventually. We all got better at searching
Speaker 1: the internet too. Sure, right like the early days it
Speaker 1: was worse. It's one would argue the peak has come
Speaker 1: and gone and it's worse. It's getting worse again. You know,
Speaker 1: we're back to this mechanism of having to validate more
Speaker 1: often and more completely, and for multiple sources. You know,
Speaker 1: the behaviors will change over time.
Speaker 2: Well, this has been a fascinating dive into more AI,
Speaker 2: and especially with Visual Studio code and Visual Studio James.
Speaker 2: Thank you very much. It's always a pleasure to doc
Speaker 2: to you, my friend.
Speaker 1: Thanks for having me entirely too long since the last time. Yeah, anytime.
Speaker 4: I'm sure if you have me back in two months,
Speaker 4: everything will be completely.
Speaker 1: Everything will be difference, all right.
Speaker 2: And check out coded with AI dot com and we'll
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