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Speaker 1: NetRocks dot com. Hey, and welcome back to dot net rocks.
Speaker 1: I'm Carl Franklin, an amateur camp This is episode number
Speaker 1: two thousand and five. Here we are, so, I guess
Speaker 1: we should start with what happened in two thousand and five?
Speaker 2: You want to start? Where do you want to go?
Speaker 2: I got a bunch of weird things.
Speaker 1: Yeah, I'll save all the good stuff for you. But
Speaker 1: there's some, you know, not so good things that happen
Speaker 1: in two thousand and five, like Hurricane Katrina. Oh right, yeah,
Speaker 1: I was down in New Orleans after Katrina for jazz
Speaker 1: Fest and Robert Plant and what's her name? Alison Krause
Speaker 1: came out and did when the levee.
Speaker 2: Breaks a little on the nose but okay.
Speaker 1: And also I remember going to a bar where they
Speaker 1: said it was a makeshift hospital during Katrina and on
Speaker 1: the you know, people would lay on the bar and
Speaker 1: doctors would come in and work on them. Sure, all right,
Speaker 1: Iraq war, bad war? In Iraqi elections. John Paul the
Speaker 1: Second died in two thousand and five. Pope Benedict became
Speaker 1: Pope Well. German Cardinal Joseph Ratzinger became Pope Benedict, and
Speaker 1: he was a sixteen.
Speaker 2: He was a close confident of John Paul's.
Speaker 1: I recall, yeah, the London July seven terrorist bombings.
Speaker 3: MS.
Speaker 1: Were you around when that happened.
Speaker 3: I was in London when that happened. I was Yeah,
Speaker 3: that hit very close to home. Well glad you're still here. Yeah,
Speaker 3: me too.
Speaker 1: Sodom Hussein's trial begin, Well, we know how that'll go. Yeah,
Speaker 1: we know. The spoiler alert didn't go well for him.
Speaker 1: Terry Schiavo the right to Die case. Remember the legal
Speaker 1: and ethical battle over removing the feeding tubes from Terry's chabo. Yeah, yeah,
Speaker 1: national debate about end of life decisions, government intervention, family rights.
Speaker 1: Record breaking Atlantic hurricane season, not just Katrina, but Rita Wilma,
Speaker 1: just one of the worst hurricane seasons. UH Israel withdrew
Speaker 1: from Gaza. Things were looking up.
Speaker 2: There, we're gonna be elections only one.
Speaker 1: Yeah, and Angela Merkle became Chancellor of Germany, first female
Speaker 1: chamer beginning a leadership era that would shape European politics
Speaker 1: for more than fifteen years. Some honorable mentions. Michael Jackson
Speaker 1: was acquitted, Prince Charles married Camilla Parker Bowels. French and
Speaker 1: Dutch rejection of the EU Constitution. Let's talk bad about
Speaker 1: the French and.
Speaker 2: The Dutch, right Arguably the moment the E that's the
Speaker 2: moment the EU broke.
Speaker 1: Yeah, in Pakistan there was an earthquake that killed tens
Speaker 1: of thousands of people. In high oil and gasoline prices worldwide,
Speaker 1: I'm not so sure that they were as high as
Speaker 1: they are now. I don't know, probably not. Yeah.
Speaker 2: No.
Speaker 3: Also, I got married in two thousand and five. Yeah,
Speaker 3: ah wow, which nearly made it to twenty years. Yeah,
Speaker 3: but you know, most of them were good and it
Speaker 3: was it's amicably dissolved, good, good, good.
Speaker 2: Some lovely progeny. As I recall, I do have two.
Speaker 3: I have two of the most amazing kids anybody could
Speaker 3: hope for. Yeah, that's just apps. I mean, they are special,
Speaker 3: they are and yeah, I'll never say that, but my
Speaker 3: kids are awesome, all right.
Speaker 1: So Top ten grossing movies from two thousand and five.
Speaker 1: Number ten Hitch, number nine, Batman Begins, so many Batman's,
Speaker 1: I'm Batman, Charlie and the Chocolate Factory, Mister and Missus Smith, Madagascar,
Speaker 1: King Kong War, The World's The Chronicles of Narnia, Lying
Speaker 1: the Witch and the Wardrobe, Number two, Star Wars Episode three,
Speaker 1: Revenge of the Sith, and number one Harry Potter and
Speaker 1: the Goblet of Fire, grossing eight hundred and ninety five
Speaker 1: point nine million dollars.
Speaker 3: I'll see. If I could only keep one of those,
Speaker 3: I'd go with Madagascar like that one was a great
Speaker 3: Winds just killed.
Speaker 1: Yeah, yeah. Richard, Space and Tech, I guess this was
Speaker 1: a pretty good year for space. Huh.
Speaker 2: Well, uh, this is the year that Airbus reveals the
Speaker 2: A three eighty find the building an airplane bigger than
Speaker 2: seven forty seven, and they kind of botched it because, actually, music,
Speaker 2: they'll take far longer to build than planned. Deep down,
Speaker 2: if you're into aeronautics, they had they knew, they expected
Speaker 2: that they would build stretch versions of the A three eighty, right,
Speaker 2: they only ever built the one model the eight, but
Speaker 2: they were planning on building stretch models, and so in
Speaker 2: anticipation of that, they overbuilt the wing so that it
Speaker 2: would be able to handle the stretch versions, and that
Speaker 2: there are for by making the main version, the initial
Speaker 2: version less efficient than it could be. Okay, that, combined
Speaker 2: with the general failure of spoken hub flying systems, this
Speaker 2: method of using big airports that everybody flies into and
Speaker 2: everybody flies out of, meant the A three eighty was
Speaker 2: the wrong airplane for modern times. And so build a
Speaker 2: less than two hundred of them, and then they'll shut
Speaker 2: on the line and it'll be a major financial loser.
Speaker 3: For air US.
Speaker 1: I don't remember any of that. I just Airbus built
Speaker 1: other planes since then, right, Oh yeah, No.
Speaker 2: Arguably the A three twenty is the most successful airplane
Speaker 2: out there. You know, he's neck connect with the seven
Speaker 2: thirty seven. But I can go nuts on aerospace, as
Speaker 2: you well know. Yeah, let's keep going on, I would argue.
Speaker 2: One of the most interesting things happened this year. The
Speaker 2: year was the DARPA Grand Challenge. This was the beginning
Speaker 2: of automated driving, and when Stanford's stan Lee vehicle completed
Speaker 2: the challenge successfully, they had it they'd been running for
Speaker 2: a couple of years at that point.
Speaker 1: That was the best show I ever watched on the
Speaker 1: Discovery Channel.
Speaker 2: Yeah, it was great, And here we are twenty years later,
Speaker 2: still trying to figure it out. All right. On the
Speaker 2: space side, January is a crazy month. It starts with
Speaker 2: a group of astronomers identifying a Cooper object they called
Speaker 2: Aras at the time, when they identified it, they thought
Speaker 2: it was larger than Pluto and kicked off the cascade
Speaker 2: that results in Pluto being demoted as a planet. Right,
Speaker 2: So the issue being here, now that they found Arison,
Speaker 2: they're pretty sure there's other objects of that size. They'll
Speaker 2: laterally find them, things like said and so forth. Initially
Speaker 2: they say, okay, well there's ten plants in Solar system.
Speaker 2: Then there might be eleven or twelve or thirteen, but
Speaker 2: they're different from the main nine or the main eight.
Speaker 1: But they do or at the Sun.
Speaker 2: Right all or at the Sun. So they had to
Speaker 2: The reality is there was no definition for a planet
Speaker 2: at the time.
Speaker 1: Right right. I remember Neil de grass Tyson was one
Speaker 1: of the guys who put the nail on the coffin
Speaker 1: of Pluto as a planet.
Speaker 3: That's actually how Neil Degrass Tyson became famous.
Speaker 1: Yeah.
Speaker 2: Yeah, it was support of this argument. The problem is
Speaker 2: that the definition is weak orbiting the Sun, fine is
Speaker 2: round or has hydrostatic equilibrium aka enough gravity pull itself
Speaker 2: into shape. Fine, here's the one they added to make
Speaker 2: it planet has quote cleared its orbit.
Speaker 1: What does that mean?
Speaker 3: So that's exactly so it sucked up everything which is
Speaker 3: in its orbital path itself.
Speaker 2: Yeah, to be clear, no planet has actually done that.
Speaker 2: Every planet has both Trojan and Apollo asteroids following in
Speaker 2: its orbit. But one would argue that is clear that
Speaker 2: they are on the same orbital path, just in gravitational equilibrium,
Speaker 2: so they never get to the planet. You know, Pluto
Speaker 2: isn't on the plane of the elliptic, it doesn't actually
Speaker 2: orbit flat with the other eight planets. It also crosses
Speaker 2: Neptune's orbit like it's a different object. Now. At the
Speaker 2: same time, they also had Serres, which is the probably
Speaker 2: the remains of a planet that existed between Mars and
Speaker 2: Jupiter and was torn apart, and it's a planetary core,
Speaker 2: so they considered they called that a dwarf planet as well.
Speaker 2: Was originally called an asteroid, even though it's huge, and
Speaker 2: now they had ris as well, also not on the
Speaker 2: planet ecliptic also, you know, doing some crossing and asymmetry,
Speaker 2: and so the dwarf planet category sort of picks all
Speaker 2: those Cooper objects up.
Speaker 1: I remember being blown away by the images of Pluto.
Speaker 1: That was a voyager.
Speaker 2: Oh when new Horizons gets there, new Horizons.
Speaker 1: Yeah.
Speaker 3: Yeah. My favorite thing about that whole sort of dwarf
Speaker 3: planet drama is that Eris is named after the Greek
Speaker 3: goddess of mischief and discord and chaos, which is very appropriate.
Speaker 3: Completely through the whole astronomical establishment into disorder for years, you.
Speaker 2: Got people wound up and still wound up. There's a
Speaker 2: movement again to make Pluto a planet.
Speaker 1: Yes, so Hailarius. That's right, it's not over yet. I
Speaker 1: recently heard that.
Speaker 2: Yeah, all right, well let's move on. That's a fun one.
Speaker 2: Also in January, the Huygens probe off of Cassini lands
Speaker 2: on Titan and gives us our first images of the
Speaker 2: surface of Titan because it has a very thick hydro
Speaker 2: chemical atmosphere methane and methane primarily, and we can see
Speaker 2: as it's descending and sends back these photos erosion patterns,
Speaker 2: just not erosion caused by water. Water is frozen solid there,
Speaker 2: it's like rock there. This is done by hydrochemicals, by
Speaker 2: things like ethane raining out of the sky and eroding
Speaker 2: the terrain. So amazing pictures. Great accomplishment there, and also
Speaker 2: in January. We're still in January the Deep and Impact experiments.
Speaker 2: This launched off a Delta two to impact on the
Speaker 2: Temple one comet as it went by, so they get
Speaker 2: there by July. It was a very quick intercept, but
Speaker 2: mission will go a little bit wrong. They will have
Speaker 2: the impactor, but the sensors will be overwhelmed by the debris.
Speaker 2: It'll kick up far more than expected.
Speaker 1: I remember that.
Speaker 2: But the Stardust mission that's already up there, that's been
Speaker 2: doing collections off of other comets, will be able to
Speaker 2: do a pass on Temple one's debris cloud as well
Speaker 2: and get material that way, so they'll recover from.
Speaker 1: You want to land on the head of the comet,
Speaker 1: not the tail.
Speaker 2: Well this they only sent an impactor in it. The
Speaker 2: idea was to kick up debris to try and measure
Speaker 2: the contents and actually collect some of that de breach.
Speaker 2: It didn't work out. Finally for space There was only
Speaker 2: one flight of a shuttle after the Columbia disaster in
Speaker 2: two thousand and three. There were no flights in two
Speaker 2: thousand and four. There's one in two thousand and five.
Speaker 2: It was supposed to be the return of flight. It
Speaker 2: was the Discovery Shuttle bringing supplies to the space station
Speaker 2: that brought up the Rafello, the MPLM European capsule that
Speaker 2: they would take out of the cargo bay of the
Speaker 2: shuttle and dock to the station to leave it there
Speaker 2: that they could refill it with garbage and or experiments
Speaker 2: and bring it back. There will be enough problems with Discovery,
Speaker 2: including damages to its tiles, that they will not fly
Speaker 2: again that entire year. They'll have to do further corrections.
Speaker 2: This is when they add the additional arm to be
Speaker 2: able to inspect the hull, and that'll be later. This
Speaker 2: one they did of they because they went to the
Speaker 2: space station. They did the inspection by pulling Discovery off
Speaker 2: of the space station and flipping the shuttle over so
Speaker 2: they could photograph it and saw some problems. So the
Speaker 2: issues of the tile system are becoming more and more apparent,
Speaker 2: and it will ultimately result in the end of the
Speaker 2: Shuttle program. On the computing side, in the Microsoft lands,
Speaker 2: we get XP National sixty four bit, the first sixty
Speaker 2: four bit version of Windows.
Speaker 1: I ran it, yeah, I remember that show. Yeah, we
Speaker 1: did on sixty four bit, and that also prompted the
Speaker 1: sixty four bit question yeah, which we end our conference
Speaker 1: shows with.
Speaker 2: It also goes alongside dot net two and Studio two
Speaker 2: thousand and five, which includes sixty four bit support, except
Speaker 2: that they had law offered the option as compile any,
Speaker 2: which really meant running thirty two bit and crash in
Speaker 2: sixty four bit.
Speaker 1: Yep, I remember.
Speaker 2: Any wrong? We did that show. Don't do it any
Speaker 2: If you're not sure you're going to run in sixty
Speaker 2: four bit, set it to thirty two bid. Oh you
Speaker 2: will be sad. And really the only thing you were
Speaker 2: getting was do you get more than two gigs of
Speaker 2: address space?
Speaker 1: Right?
Speaker 2: And I think I said this on the show at
Speaker 2: the time. If you need more than two gigs of
Speaker 2: address space, what do you do? Do you doing, especially
Speaker 2: for a web page? I want to run. I want
Speaker 2: to run is sixty four bit moode. It's like more
Speaker 2: than two gigs for a web page?
Speaker 1: What do you doing?
Speaker 3: Like a tudy stories.
Speaker 2: Coming out of the dot com bust last year. In
Speaker 2: two thousand and four, we had YouTube going public because
Speaker 2: the SEC required they had too many shareholders, so they
Speaker 2: start making some our Google goes public and this is
Speaker 2: when YouTube is founded and the first YouTube video called
Speaker 2: Me at the Zoo is published. This is before you know,
Speaker 2: Google hasn't bought them yet, right, but they will. But
Speaker 2: my Google does launch Google Maps in two thousand and five. Yeah,
Speaker 2: and a little bit on the hardware side, Microsoft launches
Speaker 2: the Xbox three sixty, the weirdo version of Xbox that
Speaker 2: all the game developers hated. The first r duinos are sold,
Speaker 2: and this really begins this wave even before Raspberry Pie
Speaker 2: and things of the little micro controller you can program
Speaker 2: and do cool computer things. Yeah, and Lenovo buys IBM
Speaker 2: think padline and becomes you know, today, I think the
Speaker 2: coolest laptop maker on the planet, not that I want one,
Speaker 2: but they do cool stuff.
Speaker 1: The think pads where coveted. Yeah.
Speaker 3: The coolest maker on the planet that is an Apple.
Speaker 3: Let's put it that way.
Speaker 2: The Apple doesn't make a lot of machines. They make
Speaker 2: the highest quality machines, like by far. But when I
Speaker 2: say cool, I mean like you never know what logos
Speaker 2: Leno was gonna do. Is like this one has two screens,
Speaker 2: this one has three screens, this one full. Yes, yes,
Speaker 2: it becomes right like they're nuts. Yes, all right, standing down.
Speaker 2: They make it. They make a dedicated knock for teams
Speaker 2: because everybody hates themselves, Like I don't know it all right,
Speaker 2: that's all I got, thanks.
Speaker 1: For Okay, before we talk to MS. Let's do better.
Speaker 1: No framework, roll.
Speaker 2: It awesome man, you got.
Speaker 1: So there's this project on GitHub called Sophia Script for Windows.
Speaker 2: Oh what is that?
Speaker 1: And basically it's a PowerShell module for fine tuning Windows
Speaker 1: on GitHub. It's got one hundred and fifty unique functions
Speaker 1: to configure Windows using Microsoft's officially documented ways without without
Speaker 1: harming your system. Okay, And there is now or there
Speaker 1: was recently a Windows version of this. So this is
Speaker 1: Sofia app in the Sofia community. So they say, it's
Speaker 1: the next chapter of the Sofia script project. And this
Speaker 1: is a free, open source app for fine tuning Windows
Speaker 1: ten and Windows eleven. Offers a modern UI UX with
Speaker 1: more than one hundred and thirty unique tweaks and shows
Speaker 1: how Windows can be configured without making any harm to Windows.
Speaker 1: So I haven't used it, but there's you can install
Speaker 1: it with Chocolate Scoop and beta versions you can just
Speaker 1: you know, expand them and run them and yeah, it's
Speaker 1: this is good stuf.
Speaker 2: Yeah, sure, you know. Over my other life on Windows Weekly,
Speaker 2: Paul the Rod has been working steadily on how do
Speaker 2: you make Windows eleven not suck? Yeah, right, like just
Speaker 2: turning removing stuff and getting the base configuration down, you know.
Speaker 2: And if you don't want to deal with one drive,
Speaker 2: here's how to actually make it go away without nagging you.
Speaker 2: If you don't want a Microsoft account, here's how you
Speaker 2: actually can figure it. But this looks like a tool
Speaker 2: just make your life a lot easier for that sort
Speaker 2: of thing.
Speaker 1: Yep. There's one feature that I'm going to check to
Speaker 1: see if it has, and that is this persistent the
Speaker 1: first persistent feature quote unquote that anytime you're in file
Speaker 1: Explorer and you've got wave files and MP three files
Speaker 1: and stuff, it insists on using the music format for
Speaker 1: the fields that it shows rather than regular documents. And
Speaker 1: I don't care about artists and album and contributing artists
Speaker 1: and you know, all this stuff. I want to see
Speaker 1: the file sized, because I'm you know, I deal with files.
Speaker 2: Yeah, I don't care about how big the file is.
Speaker 1: And it's and you turn it off and you turn
Speaker 1: it and it comes back, and it's just really really aggravating.
Speaker 1: I just want that feature out of Windows. So I'm
Speaker 1: gonna look for that. Stop fighting me, right, That's that's
Speaker 1: what I'm talking about. Who's talking to us?
Speaker 2: Richard grabbing camming off the show nineteen sixteen. You know,
Speaker 2: back in the World War One days done with one
Speaker 2: Rendel called how simple is as simple as possible? Because
Speaker 2: we get good show names, generated a ton of comments.
Speaker 2: Of course, this is when we were talking primarily about
Speaker 2: things like is our micro services essential? Like what are
Speaker 2: better ways to build software? How do you keep this
Speaker 2: just as complicated as it needs to be? In no
Speaker 2: more than that? And just got a ton of comments
Speaker 2: off of this show. Yeah, and I'm gonna grab this
Speaker 2: one from Robin Osborne who says, thanks so much. When
Speaker 2: I'm really doubting myself during the decade long tsunami of
Speaker 2: JavaScript all the things, and I'm thinking, surely this isn't
Speaker 2: the best approach. Am I wrong? Do I just not
Speaker 2: understand something that everybody else gets. It's a load off
Speaker 2: my chest to hear people I respect in the industry
Speaker 2: talking about lovely things like HTMX and referencing Alex Russell's
Speaker 2: great articles. I love Polly, I love twelve factor back
Speaker 2: in the day. I love making things as simple as possible,
Speaker 2: simple to build, simple to maintain, and still for the
Speaker 2: end user. Gagny and kiss for the win. Shit, I'm
Speaker 2: not going to argue with that. How about kiss? You mean,
Speaker 2: keep it simple?
Speaker 3: Stupid?
Speaker 2: Yeah, I don't know where you want to go, but
Speaker 2: you know what ramin where on board. You obviously heard
Speaker 2: it on that show and probably hear more of that
Speaker 2: today too. So thank you so much for your comment.
Speaker 2: A copy of music Coby. It's on its way to you.
Speaker 2: And if you'd like a copy of music Cobe, I
Speaker 2: write a comment on the website at dot at Rocks
Speaker 2: dot com or on the facebooks we publish every show
Speaker 2: there and even comment there when I read it on
Speaker 2: the show, we'll send you copy of music Cobayah.
Speaker 1: Music to Koba, of course, is a project I started
Speaker 1: a long time ago to create twenty five minute music
Speaker 1: tracks that can slip into the background and help you
Speaker 1: focus and it's been wildly popular. Now we have twenty
Speaker 1: two tracks. Twenty three is coming, I promise, and music
Speaker 1: too by dot net if you want to get it
Speaker 1: in MP three, wave and FLACK versions. Okay, let's bring
Speaker 1: back ms Rendel. Ms has been writing code since childhood,
Speaker 1: getting paid for it since her teens, and inflicting opinions
Speaker 1: on conference audiences for the last fifteen years. The former
Speaker 1: CTO with deep roots in dot net, c sharp APIs
Speaker 1: performance engineering and system architecture. She's now working in financial
Speaker 1: technology by day, then spending her spare time building ambitious, weird,
Speaker 1: and occasionally beautiful things at the intersection of ar AI
Speaker 1: and human connection. Welcome back with MS.
Speaker 3: Hey, Hey, thank you for having me.
Speaker 1: Thanks for participating in the intro. Yeah, fun, Yeah, I'm
Speaker 1: sure since the ast time we talked, you've got a
Speaker 1: lot of things on your mind.
Speaker 3: It's been a wild couple of years. Yeah, yeah, I
Speaker 3: just I've continued trying to keep things as simple as possible.
Speaker 3: There's a bit of a movement has kind of popped
Speaker 3: up in the last couple of years. Actually, Chris Woodruff,
Speaker 3: who I know, you guys know, has been doing a
Speaker 3: lot of writing sort of around the simplicity first approach.
Speaker 3: She's a big advocate of that. There's the use what
Speaker 3: works initiative, which is sort of the whole buy don't
Speaker 3: build kind of trying to suggest to people that just
Speaker 3: because an open source project is asking for commercial support money,
Speaker 3: that's not a good reason to go off and build
Speaker 3: your own messaging stack or warth authentication stack or whatever it.
Speaker 2: We wrote this code not because it was easy, but
Speaker 2: because we thought it was easy.
Speaker 3: Yes, we wrote this code because we thought it would
Speaker 3: save us five thousand dollars.
Speaker 1: And I think it's a trap of modern AI development,
Speaker 1: which we're all finding ourselves doing some somewhat, is that
Speaker 1: you think, you know, oh, I'll just I need this,
Speaker 1: I'll just have my AI write it. Where the first
Speaker 1: question should be does it exist? You know?
Speaker 2: Yes?
Speaker 3: And that's literally in my prompt that I use for
Speaker 3: exploring new ideas, there's a sort of thing very near
Speaker 3: the top saying if something exists, let's just use it,
Speaker 3: tell me about it.
Speaker 1: It kind of reminds me of the days when you know,
Speaker 1: everybody wanted to build an iPhone app, an Android app,
Speaker 1: and they come to you with ideas. You know, hey,
Speaker 1: I got this great idea for an app, I'll tell
Speaker 1: you what you build it it will split the yes,
Speaker 1: okay question number First of all, no, in question for you?
Speaker 1: Does it exist? Did you love to see if it exists?
Speaker 1: In the apisode? Oh no, I didn't do that.
Speaker 2: All right, Well, yeah, where do you exists? Bet? It does?
Speaker 3: So anyway, I'm building something that definitely exists.
Speaker 2: Nice, but I wanted to talk.
Speaker 3: To you guys about it anyway because I am Actually
Speaker 3: it's been a while since I built something kind of big,
Speaker 3: and in dot net there's been a bunch of sort
Speaker 3: of interesting projects, but they weren't really they were either
Speaker 3: kind of closed source and I wasn't allowed to talk
Speaker 3: about them, or they were outside the dot net ecosystem.
Speaker 3: But yeah, I've actually I've been working on a thing
Speaker 3: and it's in dot net, and I thought you guys
Speaker 3: would be interested.
Speaker 2: All right, tell us about it.
Speaker 1: Well, you don't need to tell us about it. We
Speaker 1: can just talk about something else if you like.
Speaker 3: No, So, I'm building my own coding agent harness. Oh thing,
Speaker 3: So like clawed code or codex or open code or
Speaker 3: pie or any of the millions of different ones that
Speaker 3: are out there.
Speaker 1: I got to tell you before you go any further.
Speaker 1: I tried that and it I was tearing my hair
Speaker 1: out so much that I just gave up.
Speaker 3: It's going quite well.
Speaker 1: It's not easy.
Speaker 3: It's not easy, and there's a lot of things that
Speaker 3: sort of pop up along the way where you kind
Speaker 3: of go, oh, I didn't think of that. Oh that's interesting.
Speaker 3: Oh yeah, I suppose that is, but yeah, no. Doing
Speaker 3: it in dot net and c sharp is provide some
Speaker 3: interesting opportunities that I was kind of like, well, if
Speaker 3: I was using dot Net, then I could use new
Speaker 3: get to distribute extensions. I would have kind of very
Speaker 3: firm interface boundaries, and I could have an abstractions and
Speaker 3: an extensions package with different kinds of extension, and people
Speaker 3: could extend around those. And there's a phenomenal first party
Speaker 3: ecosystem around building AI tools and agents with dot net,
Speaker 3: because you've got like Microsoft dot Extensions, dot Ai, You've
Speaker 3: got Semantic Kernel, you've got the Multi Agent framework. These
Speaker 3: are all things that are being built and supported by
Speaker 3: somebody else, which takes a lot of the sort of
Speaker 3: more complicated bits of effort.
Speaker 2: You know.
Speaker 3: Just talking about providers, you've got sort of three anthropic
Speaker 3: open AI and Gemini and then you've got like local
Speaker 3: providers like Olama, Lama, cpp LM Studio, OMLX and all
Speaker 3: the other things that are out there that are like
Speaker 3: open Ai compatible, like deep seek and Kimmi and GLM
Speaker 3: and all these different things, and there are either pre
Speaker 3: existing rappers for them. You know, there's a Anthropic ship,
Speaker 3: an implementation of I Chat client which is in the
Speaker 3: Microsoft Extensions project. There's an Alarma sharp out there which
Speaker 3: interacts with Alarm. So yeah, there's all these sorts of things,
Speaker 3: and so it makes a lot of the building of
Speaker 3: this thing more like lego and sticking sort of pre
Speaker 3: built bricks together, which really really helps.
Speaker 2: So, yeah, do we need another one?
Speaker 3: Yes, yes we do. I do. I definitely do.
Speaker 1: You find all these other ones are lacking.
Speaker 3: So my sort of daily driver and the thing I've
Speaker 3: been using at work for the last year is Claude
Speaker 3: Coat and claud Coke is amazing. But it works with
Speaker 3: Claude and you can do sort of interesting hacky setting
Speaker 3: anthropic environment variables and get it to work with other engines,
Speaker 3: especially when they have an anthropic compatible API. But we
Speaker 3: are approaching the rug pull. Yeah, the point where in
Speaker 3: the same way that Uber went right, We've destroyed the competition.
Speaker 3: Now we can rack the prices up. The vcs are
Speaker 3: kind of like going, it's probably time that we start
Speaker 3: charging what it actually costs and make it profitable. And
Speaker 3: there are multiple outcomes that could happen from that.
Speaker 1: Yeah.
Speaker 2: I mean, I'm going to wrestle with this being a
Speaker 2: rug pull so much as a reality check.
Speaker 3: Yes, yeah, okay, yeah, No, definitely.
Speaker 2: It's is like, hey, this stuff costs more money than
Speaker 2: you were charging, so how much is it really.
Speaker 1: Well, it depends on what side you're looking at. If
Speaker 1: you're looking at the LM providers, it's a reality check.
Speaker 1: If you're looking at users, it's a rugbull. Yeah, no
Speaker 1: doubt about it.
Speaker 3: I mean that's certainly for a lot of the less
Speaker 3: technical users who don't understand the constraints and limits and
Speaker 3: energy use and everything.
Speaker 1: I just want to tell you what I'm doing. I'm
Speaker 1: using GitHub copilot Cli against a local machine that's running Olama,
Speaker 1: and I found a couple of models that work really
Speaker 1: really well. Which ones so that so Quinn yep, Quinn
Speaker 1: three point six latest is the best? Yes, and even
Speaker 1: two point five thirty three thirty two billion yea Quin coder. Yeah,
Speaker 1: works works the best, that's the second best. And then
Speaker 1: we did this on code with Ai dot com. The
Speaker 1: last two episodes were local language model roundups, and I
Speaker 1: did and I tested a bunch of them with against
Speaker 1: my Olama machine, and those two are the only ones
Speaker 1: that I would use going.
Speaker 3: For I've been using Gemma four. I tested at the
Speaker 3: thirty one billion parameter and it's good. Quinn is better
Speaker 3: for coding, yeah, but Gemma four I'm using for a
Speaker 3: project that I'm not ready to tell you about it
Speaker 3: but because I don't want to. It's it's in stealth
Speaker 3: and at some point somebody's going to give me sacks
Speaker 3: of money to actually productize it. Still, this is kind
Speaker 3: of at the core of that. But yes, I think
Speaker 3: I don't know whether sort of the big funded cloud
Speaker 3: LM providers and Thropic and open AI, it's it's kind
Speaker 3: of questionable whether they even survive because they're a real
Speaker 3: questions especially, I mean, you Knowthos. Was Mythos held back
Speaker 3: because it was exposing sort of vulnerabilities in ten thousand
Speaker 3: two power fundamental internet projects? Or was it held back
Speaker 3: because the compute capacity did not exist to run it?
Speaker 1: Yeah? Yeah, it's pretty big, you know, and.
Speaker 3: Thropic of basically least Colossus one and two off SpaceX
Speaker 3: now to try and run this stuff. But you know,
Speaker 3: I keep seeing analysis that these we're expecting to build
Speaker 3: hundreds of gigawatts of capacity per year, but we're actually
Speaker 3: building tens of gigawatts if we're lucky.
Speaker 2: So well he did. Yeah, it turns out you can't
Speaker 2: just build power plants over night. It's not that quick. Yeah,
Speaker 2: you know, as the guy who does a bunch of
Speaker 2: talks about power, it's like, hey, pretty much the fastest
Speaker 2: you can build one power plants about five years. Yeah,
Speaker 2: and this thing hasn't been going on for five years.
Speaker 2: So how many power plants do you think we've so
Speaker 2: far forward?
Speaker 3: One of my favorite things about the power plants was,
Speaker 3: I think it was Hank Green on YouTube did a video.
Speaker 3: There's lots of old shutdown coal power stations which have
Speaker 3: got all the everything that they need to be turned
Speaker 3: into small nuclear power stations. You could just stick a
Speaker 3: reactor core in there. The reason they can't do it,
Speaker 3: certainly in the United States, is that they're already radioactive
Speaker 3: to a level that exceeds EPA regulations. For how radioactive
Speaker 3: and nuclear power station can be just from burning coal. Wow,
Speaker 3: which is it's lovely. Yeah, Trump plants to refire these
Speaker 3: coal plants. Yeah, I mean that's also crazy. Yeah, but yes,
Speaker 3: I kind of see a potential future where you've got
Speaker 3: to exist in between the cloud llms and the on
Speaker 3: device things by providing like custom training. So a customer
Speaker 3: comes to you and goes, I want coding agents that
Speaker 3: I can run locally that all I care about is
Speaker 3: dot Net and typescript and you know, React. And you
Speaker 3: either get like a completely ground up trained thing, or
Speaker 3: you get a fine tuned trained thing training and fine
Speaker 3: tuning models.
Speaker 1: I think so too.
Speaker 3: A it's compute expensive, and B it's it's not easy,
Speaker 3: it's not sort of straightforward. It's a it's a skin.
Speaker 1: Well you know. The other the other option is to
Speaker 1: take something that does know, you know, c sharp, typescript,
Speaker 1: all of those, but also knows a lot of other
Speaker 1: stuff and just pare it down to what you need
Speaker 1: it for. The distillations kind of like stubbing out when
Speaker 1: you're compiling, you know, stub out the stuff that you
Speaker 1: don't want to link in.
Speaker 3: Yeah, and so yeah, I want something that I can
Speaker 3: make work with Claude or Gemini, or I can make
Speaker 3: it work with OMLX running a local thing, or I
Speaker 3: can make it work with Olama running on a DGX
Speaker 3: Spark sitting in my house. And yeah, so, and I
Speaker 3: wanted something that I had more control over. I looked
Speaker 3: at the source code for the Pie Coding Agent, which
Speaker 3: is the closest thing, and it's written in typescript, which,
Speaker 3: apart from anything else, means you have to have Node installed.
Speaker 3: And I have a long history of railing against the
Speaker 3: need to install mode and so yeah, and I thought
Speaker 3: I would I would sort of build my own Pie
Speaker 3: inspired thing in C sharp. And it's so nice to
Speaker 3: be back in c sharp and to have the agent
Speaker 3: generating code that I fully understand and can refactor with
Speaker 3: kind of sharper and those sorts of things. And so yeah,
Speaker 3: it's uh, it's it's out well, it's not quite out
Speaker 3: there yet. I haven't done a proper launch, but it's
Speaker 3: public on GitHub at demonic ai with an A and
Speaker 3: then the demon d m o N dash core.
Speaker 1: And will add that to the list.
Speaker 3: Yeah, I'll send you the I think I sent you
Speaker 3: the link in the pre show thing. And yeah, the
Speaker 3: core of it runs as a separate process, and it's
Speaker 3: it's a Jason RPC server, so you I'm currently building
Speaker 3: a terminal client for it, like a net console app,
Speaker 3: but there's going to be an Avalonia app, and it
Speaker 3: is also going to be there will be another thing,
Speaker 3: which is a public gRPC server that exposes it over
Speaker 3: gRPC so you can talk to it from your phone.
Speaker 3: And yeah, but the things I'm kind of excited about.
Speaker 3: So dot net means I can compile it as a
Speaker 3: standalone thing, so people don't have to necessarily have the
Speaker 3: dot Net SDK installed, although if you have the dot
Speaker 3: Net SDK installed, you'll also just be able to do
Speaker 3: dot netool installed demon and it will be distributed that
Speaker 3: way as well. And I've borrowed so the process isolation
Speaker 3: thing is is cool. It's using Microsoft Extensions AI, which
Speaker 3: means there's a bunch of stuff out there that I
Speaker 3: can already import and wrap quite lightly. I've borrowed the
Speaker 3: session system from Pie, so you have a tree of
Speaker 3: sessions and when you spawn a subagent, it kind of
Speaker 3: creates a fork from the current session, and so you
Speaker 3: end up with a tree. I don't know if you've
Speaker 3: looked at pie at all. But it has this concept
Speaker 3: of sessions as trees with sub sessions and sub sub
Speaker 3: sessions and all that sort of thing. It's really quite clever.
Speaker 3: And they're all just files in the directory.
Speaker 1: Course, so you're basically persisting the history in all the
Speaker 1: context around that is in MD files, yeah, yeh.
Speaker 3: MD files and JSONL files. And then and this is
Speaker 3: the bit that I'm sort of I think is my
Speaker 3: my value proposition is the extension model. So you can
Speaker 3: create an extension. You have a new Get package that
Speaker 3: you can get, and you build your extension based on that,
Speaker 3: and then you publish it to new get with a
Speaker 3: tag of DMA nash extension and with the source code available.
Speaker 3: And then Nougat is already one of the more secure
Speaker 3: package platforms out there, whereas you know, NPM has been
Speaker 3: having some disasters lately, and PI has its share of
Speaker 3: issues and everything else. New get is pretty secure. And
Speaker 3: if you publish it as source available and you get
Speaker 3: the new package that goes alongside the new package, then
Speaker 3: you install it using the agent. So you go, hey,
Speaker 3: I'm going to install an extension, and it goes off
Speaker 3: and it gets it and it gets the source code
Speaker 3: and it scans the source code for vulnerabilities before it
Speaker 3: allows you to load the package. So if someone tries
Speaker 3: to distribute a package that's got a Bitcoin minor or
Speaker 3: something that's going to extract all your bank details and
Speaker 3: credit cards, it's got a built in secure scam before
Speaker 3: it does anything.
Speaker 1: How far along are you with this project?
Speaker 3: It's working, I can use it to build itself. And yeah,
Speaker 3: I'm expecting it's as we're recording this. It's NDC Copenhagen
Speaker 3: next week, and I'm expecting to be making a lot
Speaker 3: of noise about it at NDC Copenhagen and trying to
Speaker 3: persuade people to give it a look. But yes, and
Speaker 3: then the sort of the much much bigger thing, the
Speaker 3: startup that's being built on top of it, once the
Speaker 3: core of this is done, should progress fairly quickly as well.
Speaker 3: And that's not only kind of personal AI and playing
Speaker 3: in the kind of open claw and Hermes space. It's
Speaker 3: also adorable, okay, And I'm going to bring adorability and
Speaker 3: beauty to.
Speaker 1: The manifest itself.
Speaker 3: Actually at the moment, as a bird, oh.
Speaker 1: Bird bird, is it an avatar you interact with or
Speaker 1: is it just I will.
Speaker 3: Go I will come back and tell you more about
Speaker 3: it at another stage. But it is, it is. It's
Speaker 3: leveraging a lot of the things that I've been working
Speaker 3: with over the last couple of years and bringing them together.
Speaker 1: I can smell the smoke and see the wheels turning
Speaker 1: in the brain of yours.
Speaker 3: Oh but no, I've been I've got kind of like
Speaker 3: a proof of concept app installed on my phone that
Speaker 3: is really incredibly simple that is already blowing people away.
Speaker 3: They're kind of go, oh, that's really that's amazing. And
Speaker 3: then yeah, well, hooking it up to aiye is just
Speaker 3: going to do very interesting things.
Speaker 1: I think this is a good time to take a break,
Speaker 1: so we'll be right back after these very important messages.
Speaker 1: Don't go away, and we're back. It's darting at rocks.
Speaker 1: I'm Carl Frank, and that's my friend Richard Campbell, and
Speaker 1: that's our friend M's Randall. Hello, talking about some new stuff,
Speaker 1: a new way to interact with your local language model
Speaker 1: or your large language model.
Speaker 2: Yep, yep, I am circling back on this whole. Aren't
Speaker 2: we going to get to a place where you have
Speaker 2: an LM associated with an application that can modify the application.
Speaker 3: Yes, I mean that's that's one of the things with
Speaker 3: this is especially the LLLM can briefly extend itself by
Speaker 3: writing a CSX script, which you can you know, distributing
Speaker 3: the Rosslyn things. We can compile that, load it into
Speaker 3: an assembly context. That becomes a temporary extension, and then
Speaker 3: there's actually a built in promote command, right that then
Speaker 3: converts that into an actual sort of dot Net project
Speaker 3: with a cs pro file and ne get packaging and
Speaker 3: everything else.
Speaker 1: In the work Vanilla was doing was extension. He was
Speaker 1: using squad dash to to modify a squad dash.
Speaker 3: Yes, and there are there's there are platforms out there
Speaker 3: where it is literally this, you know, create a new
Speaker 3: application and it just starts and it's an empty screen
Speaker 3: on your iPhone or your desktop browser or whatever, and
Speaker 3: you literally start telling, hey, application, this is what I
Speaker 3: want you to be, this is what I want you
Speaker 3: to do. And yeah, it kind of builds itself from
Speaker 3: the inside out, and if you want a new feature
Speaker 3: at any point, you can just go, hey, come back
Speaker 3: and I need you to add a new feature, right,
Speaker 3: And I think that is there's that level of things
Speaker 3: where it's kind of like build an application so that
Speaker 3: I can track my to do list or whatever. And
Speaker 3: then there's the point at which, and this is kind
Speaker 3: of one of the things that's very heavily on my
Speaker 3: mind is we have ways of interacting with agents that
Speaker 3: the idea of having an actual application with a specific
Speaker 3: user interface will just be silly. Why would you do that?
Speaker 2: Well, yeah, text boxes and buttons and things seem silly.
Speaker 2: The screen will be used to present information.
Speaker 3: Yeah, sort of. ALI is generating infographics and charts and
Speaker 3: pictorial representations so we can all forget to learn how
Speaker 3: to read and all these sorts of things.
Speaker 2: Look, the line goes up to the right, this is good.
Speaker 2: You should get a raise. Or the line is going down,
Speaker 2: you are going to be down.
Speaker 3: So yes, the Onion did a good story a couple
Speaker 3: of weeks ago about high schoolers lacking objectssistance skills, which
Speaker 3: is something that toddlers developed about eighteen months. So yes,
Speaker 3: But yeah, know that the bigger idea I think is,
Speaker 3: and and this is the kind of core of having
Speaker 3: this as a standalone thing with an STDO RPC interface
Speaker 3: is does it need an avaloniar application, does it need
Speaker 3: a command line application, or can it sort of just
Speaker 3: run as a server somewhere and I can talk to
Speaker 3: it using my phone and my AirPods and that sort
Speaker 3: of thing just persistently, and it can run locally. I
Speaker 3: can run it in my house, I can access it
Speaker 3: over tail scale or a cloud flare tunnel or something,
Speaker 3: and it can keep all my data locally. To me, yeah,
Speaker 3: that's important on my own sort of you know, And
Speaker 3: that's I mean to me, that is a huge thing.
Speaker 3: That is, it's very much. I don't want to send
Speaker 3: every email email I get, and every Apple message I
Speaker 3: get and and all these different things through a hosted
Speaker 3: cloud model. It would be much better if I could
Speaker 3: run them locally.
Speaker 1: And so I'm with you, and I think that the
Speaker 1: future is, you know, big machines running locally that are
Speaker 1: running some you know OLAM or some kind of local
Speaker 1: model host and because that's the big thing, right for
Speaker 1: the expense can be absorbed by big companies. I mean,
Speaker 1: but you know, guys like us don't want to be
Speaker 1: paying a couple of thousand dollars a month for large
Speaker 1: language model access. But but you know, privacy is a
Speaker 1: big problem.
Speaker 3: Privacy is a really big thing. And you know, I
Speaker 3: can see a business model where actually, what we're selling
Speaker 3: is like an appliance in the same way that people
Speaker 3: would buy an Alexa or whatever they called those things,
Speaker 3: an echo, or they would buy a Google Home device.
Speaker 3: And you could sell, like I mean right now, a
Speaker 3: DGX Spark clone, the thing with one hundred and twenty
Speaker 3: eight gigs of unified memory and a petaflop of COUDA
Speaker 3: and tensor cause and you can pick one of those
Speaker 3: up for three thousand, three and a half thousand of
Speaker 3: your local dollarish currencies. And that's the first generation of
Speaker 3: that thing. And so in five years time, that spec
Speaker 3: is going to be available. As you know, it's not
Speaker 3: going to be quite Raspberry Pie, but it'll it'll have
Speaker 3: come down under sort of close to the Mac Mini
Speaker 3: level of pricing. Mac minnis, you know, with sixty four
Speaker 3: gigs or one hundred and twenty eight gigs would be
Speaker 3: plenty big enough.
Speaker 1: My machine is a MD Rising nine nine ninety x
Speaker 1: twelve core ninety six gigs RAM, the Nvidia g tour
Speaker 1: g fors rtx fifty ninety with thirty two gigs of
Speaker 1: v RAM. And yeah, like I said, quenn three six
Speaker 1: runs in there just fine.
Speaker 3: Yep, And yeah, I do. I think that's that's where
Speaker 3: we're going to end up. One of the things, particularly
Speaker 3: with with Demon, one of the sort of features that
Speaker 3: it has because I couldn't figure out how to get
Speaker 3: other things to do this is every extension can specify
Speaker 3: a different model, and so it's like you could have read, write,
Speaker 3: Bash edit all these different things. The extension that talks
Speaker 3: to your Gmail account and those run on your locally
Speaker 3: hosted model. But web search, which is a pain to
Speaker 3: do locally because you need an API endpoint that you
Speaker 3: can hit and you have to pay for all of those.
Speaker 1: There are MCP servers for that. Yeah, so you could
Speaker 1: just plug those in as you want to do.
Speaker 3: But or you could, you know, just say, use the
Speaker 3: Gemini model whenever you want to do a web search
Speaker 3: and you can just drop out quickly go to Gemini,
Speaker 3: or maybe use sort of a slightly bigger, more complicated
Speaker 3: model on Olarma cloud because you're doing a web search, so.
Speaker 2: It's a different process. You can use it different mechanism.
Speaker 3: Yes, I suppose technically what you searched for or is
Speaker 3: useful information, but somebody's recording that anyway. If you search
Speaker 3: at Google, it's not like they're not keeping track of
Speaker 3: that sure, and so you know, so it's like, yeah,
Speaker 3: the ability to be pragmatic about privacy and security and
Speaker 3: where things are hosted and all this sort of stuff
Speaker 3: and to be able yeah, like I say, to use
Speaker 3: a completely different model for certain extension types and be
Speaker 3: able to configure that is a useful thing.
Speaker 1: We have a new customer at appinax. In reading the contract,
Speaker 1: there's a clause in there that no date, none of
Speaker 1: their data will ever be entered into an AI large
Speaker 1: language model for privacy reasons and you know, none of
Speaker 1: their code and all that stuff. So then we get
Speaker 1: working and we've got to get up repo with all
Speaker 1: the code that has access to other data, and you know,
Speaker 1: kind of had to clarify with the customer. You know,
Speaker 1: what is the reason, what is the thing that you're
Speaker 1: most concerned about that you have this clause in here,
Speaker 1: and it was privacy. You know, it's basically they've heard
Speaker 1: the stories of people just taking requirements dumping them into
Speaker 1: chat GPT. Chat GPT now knows all about them, and
Speaker 1: you know, they lose control of their intellectual property and
Speaker 1: all this stuff. So it's taking some convincing, but we're
Speaker 1: convincing them that with getthub copilot, there's a way to
Speaker 1: opt out of them using your data to train their models.
Speaker 1: And they have your data anyway in GitHub, so it's
Speaker 1: not like it's going outside of that. The only thing
Speaker 1: that I need to be sure of is that if
Speaker 1: we're using Claude sonnet for example, does Claude know does
Speaker 1: Anthropic now know about your data?
Speaker 2: I mean, this is what happens when you mix a match,
Speaker 2: right is now you have to think of each of
Speaker 2: the layers.
Speaker 1: Yeah, so that's the stuff we're working through right now.
Speaker 3: So yeah, it's it's the thing I'd love about all
Speaker 3: of this stuff. And you know, the work I've been
Speaker 3: doing with various kinds of AI and everything over the
Speaker 3: last two years, it hasn't settled yet.
Speaker 2: It's like we're far from it. We're nowhere, But I say,
Speaker 2: what do we know?
Speaker 1: Here comes the rug.
Speaker 3: I've done a lot of kind of historical talk looking
Speaker 3: at the history of programming languages and that sort of thing,
Speaker 3: and Fort Tram and Cobold and Algol and whatever, and yeah,
Speaker 3: there was a time when people were inventing the paradigms
Speaker 3: and that sort of thing. But then at some point
Speaker 3: we had C and then we had C plus plus
Speaker 3: and it's kind of like everything since then has just
Speaker 3: been variations on a theme to one extent or another.
Speaker 3: There was the dot com thing and the internet thing,
Speaker 3: and that was it was cool. But yeah, this is
Speaker 3: still at that kind of pioneering gold rush stage where
Speaker 3: there's a lot of stupidity going on, but there's also
Speaker 3: a lot of like really creative work still to be done,
Speaker 3: and it's fun to be a part of that.
Speaker 2: Well. Part of this is while there's too much money around,
Speaker 2: you don't make good choices, like we do need to
Speaker 2: be more efficient and more disapinted. And so as you
Speaker 2: see the money starting to come out of the system
Speaker 2: and they you know, your chances are becoming a billionaire
Speaker 2: now and are disappearing. So those folks leave and good
Speaker 2: riddance to them. Yes, we get to the engineering side
Speaker 2: of can we make this actually practical and useful? You know?
Speaker 2: Comparing this to the dark com boom, it's like it's
Speaker 2: two thousands, the end is coming, but the heck's not
Speaker 2: going to go away, just the dumb. The Dumb's going
Speaker 2: to go.
Speaker 3: Yes, Yeah, And one thing I'm hoping with this is
Speaker 3: that you know, back in the day with not a
Speaker 3: mollusk I did. I got a lot of engagement with
Speaker 3: that project. People wrote kind of a Mongo dB adapter,
Speaker 3: and I think there was actually simple data for Twitter.
Speaker 3: Somebody wrote a thing where you could write simple data
Speaker 3: queries against the Twitter fire and I think, you know,
Speaker 3: I know there was still a ton of net shark
Speaker 3: programmers out there, and I know they're using sort of
Speaker 3: generative AI, but this is something where I'm kind of
Speaker 3: like going, hey, look, here's the actual harness is written
Speaker 3: in dot net, and it's kind of moved it a
Speaker 3: little bit further along from just the Microsoft extensions, which
Speaker 3: give you fine grained building blocks, and it's kind of
Speaker 3: here's an actual agent and you can hack on it,
Speaker 3: and you can share your hacks and you can contribute
Speaker 3: back and so forth. And I'm hoping it's going to
Speaker 3: open up this kind of the joy of experimentation to
Speaker 3: a bunch more people who, for whatever reason, you know.
Speaker 2: I'm talking to teams now who are no longer arguing
Speaker 2: over futures, are just building all the versions they can
Speaker 2: think of and then comparing them.
Speaker 1: Ah.
Speaker 2: Yes, as the code generation goes so quickly, Yeah, I
Speaker 2: could just think about code differently now.
Speaker 3: Yeah, and yeah, it's like which of these is I've
Speaker 3: actually so I had Demon dot Console, which was just
Speaker 3: a standard console application, and then briefly there was Demon
Speaker 3: dot TUI, which was using the terminal dot guy newgat package,
Speaker 3: but that was very broken for a variety of reasons,
Speaker 3: and so then it reverted back, and now it's Demon
Speaker 3: dot terminal, which is using Spector Console. But yeah, and
Speaker 3: it's like going down the TWI dead end would have
Speaker 3: wasted a week of development time a couple of years ago,
Speaker 3: whereas this time it was just one evening. We got
Speaker 3: halfway through the evening and I was kind of like,
Speaker 3: this isn't working, and we're going to revert back the
Speaker 3: last few changes and pick up from the console application again.
Speaker 3: And yeah, it's it doesn't cost anywhere near the same,
Speaker 3: so you can actually spike you can. Actually I've always
Speaker 3: had this thing about you should build it once and
Speaker 3: then throw that away and then build it again properly
Speaker 3: with all the lessons you learned from that first build.
Speaker 3: And that's actually a reasonable proposition. Now it's kind of
Speaker 3: do a really dirty, exploratory vibe coded build, but get
Speaker 3: the agent to keep a record of all the things
Speaker 3: and the decision record architecture decisions and so forth, and
Speaker 3: then you can literally use that to generate an insanely
Speaker 3: detailed spec and effectively do a clean room implementation of
Speaker 3: your prototype. The prototype is.
Speaker 2: A sort of off the back of the experiment.
Speaker 3: Yeah, and then you know, you get people going all
Speaker 3: vibe coded stuff. The code's an absolute mess. But this
Speaker 3: is a solution to that. Use the vibe coding to
Speaker 3: prototype and then with all the constraints and clean code
Speaker 3: and don't repeat yourself and yagny and kiss and whatever
Speaker 3: else to a ground up reimplementation.
Speaker 1: I find myself doing a lot of reading when I'm
Speaker 1: working with an AI agent. In other words, I sort
Speaker 1: of give it an overview. Is if it's a greenfield project,
Speaker 1: I'll give it an overview, and then I'll ask it
Speaker 1: to come up with a plan, you know, in multiple steps,
Speaker 1: and then write a customer facing document that even I
Speaker 1: can understand, well that even my customer can understand and
Speaker 1: I can understand. And then I go through the plan
Speaker 1: and figure out is this step necessary, why you know?
Speaker 1: And what about this step? And it'll come up with
Speaker 1: things that I hadn't thought of. But you know, sometimes
Speaker 1: it might be a little over ambitious and but but
Speaker 1: I like to work that way first on the architecture,
Speaker 1: on the plan, before I even do anything coding wise,
Speaker 1: and that is the most important part of the project,
Speaker 1: if you ask me. But it's a lot of you know,
Speaker 1: talking and a lot of reading.
Speaker 3: Absolutely. Yeah.
Speaker 1: Yeah, So we have the link to it on GitHub.
Speaker 1: I think you already provided that the show notes.
Speaker 3: Yeah, so yeah, and yeah, by the time it's this
Speaker 3: episode goes out, I will have been making noise about
Speaker 3: it and hopefully that'll be.
Speaker 2: The force goes out during the conference.
Speaker 3: Nice, Oh that'll look brilliantly then, yeah, almost like we
Speaker 3: had a plan. So yeah, I've actually I've turned up
Speaker 3: with my list of things to cover and so forth.
Speaker 3: So yes, but I think anything covered, No, it's I
Speaker 3: think we've covered everything. It does local models, it's the
Speaker 3: permission models and all this sort of stuff. It is.
Speaker 3: It is properly open source. It's Mozilla Public License two
Speaker 3: point zero. And yeah, I hope people will at least
Speaker 3: take a look at it. If nobody, I'm definitely going
Speaker 3: to tell if nobody engages, I do actually need it
Speaker 3: for my bigger more elaborate plans, but it would be
Speaker 3: nice if people did like it and use it and
Speaker 3: play with it and stuff.
Speaker 2: So, because the way all good things start, you build
Speaker 2: a thing you need and you wonder if other people
Speaker 2: need it.
Speaker 1: Yeah, Frankly, well, I'm going to check it out, and
Speaker 1: I'm really looking forward to your more adorable project that
Speaker 1: we will learn more about sometime in the future, and
Speaker 1: you will come back and tell us about that.
Speaker 3: Right, you will be the first people I tell fantastic.
Speaker 1: Yeah, Endell, thank you very much. It's always a pleasure
Speaker 1: to talk to you, and h this was no different,
Speaker 1: mind blowing as always doing the awesome.
Speaker 3: Thank you.
Speaker 4: I will We'll talk to you next time on dot rocks.
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