S1: All right. Welcome to episode 494. Sorry, it's been a while.
S1: Had some, uh, config issues been working on with the
S1: home gear. I think I got them sorted out, and
S1: we are ready to, uh, keep going. So my stress
S1: and excitement levels continue to rise. Feeling basically unbelievably excited
S1: about the future and, like, what we could potentially do
S1: and like all the different ways that I'm using AI
S1: and I'm trying to get other people to use AI.
S1: I'm doing probably, I don't know, five sessions a week
S1: with various friends, showing them how I'm building my stack,
S1: how I'm building out my dachi, and how they can
S1: build their own for their own purposes. A lot of
S1: the stuff that I talked about in the augmented course
S1: really is basically starting to happen, um, instantiated inside of
S1: cloud code. So it's like this extreme optimism and thought
S1: about possibilities and like, everything I could possibly do and
S1: help other people, do, you know, escaping from the drudgery of, like,
S1: corporate work? A lot of corporate work, not all corporate work,
S1: of course. And just like thinking about a better future
S1: and trying to actively build that future, especially when I
S1: start talking about some of the stuff from previous episodes,
S1: podcast episodes of the newsletter. And when I want to
S1: call out is, uh, Damon, which is this new service
S1: that I've stood up. So it's damon.com. And what I'm
S1: essentially doing is bringing back this idea that I've always wanted,
S1: I think, even before the book stuff that I think
S1: this is like early 2000, there was this one service
S1: in the past called Friendfeed, and I had it kind
S1: of like integrated in my website at the time. And
S1: what it did was it, it was able to follow
S1: what you were doing on Reddit, on Facebook, whatever the
S1: current services were at the time. I know Reddit was
S1: definitely one of them. Uh, book feeds, RSS feeds, basically
S1: you could subscribe to or you could publish like click
S1: the options for all these different accounts and connect them.
S1: And then when someone comes to your Friendfeed page, they
S1: would see like the books that you're looking at, like
S1: the stuff. Oh, it was upvotes as well. So we
S1: could see what you upvoted on like Hacker News and
S1: what you upvoted on Digg and what you upvoted on Reddit.
S1: So it was like this live dashboard thing that was
S1: going on with that person. It was just unbelievably awesome.
S1: It was called Friendfeed, and I have always been trying
S1: to get back to that thing. And so Damon is
S1: essentially just like a more pure form of that because
S1: rather than it being a third party service, the idea
S1: is that each of us hosts our own just using
S1: a common protocol, and we all just know how to
S1: call it, you know, it's a common protocol. Therefore there's clients,
S1: there's servers, and like it's very simple. But the idea
S1: is that world. And it wouldn't just be humans that
S1: have this right. It's it's also the businesses and the
S1: buildings and everything. Um, so everything gets an API, but
S1: it's like this format. But if I'm in a coffee
S1: shop and, you know, I share people with things around me,
S1: they have their favorite. Their top book is also their
S1: top fantasy book is also The Name of the wind,
S1: which is my top fantasy book. So it would show
S1: me that right. My digital assistant would be able to say, hey,
S1: you know, check out this person next to you. You
S1: should say hi. They also love name of the wind. Boom.
S1: Human connection. So everything comes back to the human connection
S1: facilitated by the tech. So that was one of the
S1: things I talked about a lot in a previous part
S1: of the newsletter. I've been blogging like, absolutely crazy. Just
S1: absolutely crazy. Like I've been blogging higher quality stuff. Um,
S1: more thorough stuff. More well researched stuff. I've put out
S1: probably ten of these in like the last month. It
S1: is unbelievable the amount of output I've been able to
S1: do because of Chi. All because of my AI stack.
S1: Because what I'm now doing, my workflow now is to
S1: use Whisper Flow to record into vim or record into
S1: Apple notes or record into whatever. And then I just
S1: copy and paste that into Kai and I say create
S1: blog and it knows to not change my language. It
S1: doesn't write anything for me. It just puts my language
S1: in there. Um, I actually do have a rewrite command,
S1: and if I use that, it's allowed to fix grammar
S1: and typos and like sentence structure, but it's still not
S1: allowed to change the content. And what happens is it
S1: still reads exactly like me because all it did is
S1: really clean up. Like, should that have been a semicolon
S1: or a or a dash or a period or whatever?
S1: And then I could say, okay, enrich. Okay. You know,
S1: in like the movies it says like enhance. Well, now
S1: I can say enrich. And what that does is it
S1: goes and gets links, right? Because when I'm narrating, this
S1: is insane. When I am narrating, I can literally in
S1: Whisper flow. I say things like, yeah, and um, go
S1: get a quote from Viktor Frankl about this and put
S1: it here. Right. So I'm just narrating. I'm like, okay,
S1: we need some data to back this one up. Um,
S1: I'm talking about, you know, tech layoffs. So find the
S1: latest data on this from a reputable source and link
S1: to that here. Also create a visualization using our standard
S1: D3 visualization. And boom. So I press enter to that thing.
S1: And this thing fires off. And like 10s later I
S1: have a linked like graph with real data and the
S1: data sources listed and the data sources listed inside the graph.
S1: It's all annotated, all the notes are there, and all
S1: I did was talk. All I did was talk. It
S1: is unbelievable. And, you know, for the longer ones, I
S1: end up going back in multiple phases. But I'm working
S1: on that workflow. Ideally, I'd like to have as much
S1: of it as done as possible. What has not worked
S1: for me is kind of like iterating back and forth.
S1: It's no fun to do that. I prefer to either
S1: just capture like violently and like this giant thing and
S1: then just work from there, or try to have the
S1: thought fully parsed out. Done. Inside of the note over to,
S1: you know, Claude. And he just takes it and runs
S1: with it and just knows I've got all these different
S1: custom commands for adding links for cleanup. I have a
S1: separate command for publishing, which does like editor type stuff.
S1: So it makes sure none of the links are broken.
S1: It it, uh. It'd make sure I don't have any
S1: unsubstantiated claims that it thinks I should add data to
S1: and stuff like that. It checks to make sure quotes
S1: actually came from that person. Right. So I'm checking basically
S1: for like, hallucinations and mistakes that I've made. I've got
S1: a piece of errata for the newsletter that just went out.
S1: So the open source package that does the bug bounty stuff,
S1: searching for vulnerabilities that was not released by XPO. And
S1: I guess this is a good example of how I'm
S1: not using AI for for a whole lot of stuff
S1: on the newsletter. Um, I actually wrote that and it
S1: was incorrect. Um, I had just read both articles and
S1: somehow in my mind I must have like crossed. I
S1: don't know, cross pollinated or something. But anyway, yeah, that'll
S1: be in the errata in the next newsletter. But since
S1: I'm doing a podcast and it's after it, I can
S1: correct it now. Uh, okay. What was I talking about? Yeah,
S1: basically just this workflow is completely insane and I'm just
S1: ultra excited about it now. All that to say, I'm
S1: still extremely worried. Like I talked about in that other post,
S1: that other post was talking about the. How worried I
S1: am about the, uh, the future and especially for a
S1: whole lot of workers globally, basically knowledge workers. I'm really worried.
S1: And I'm not just worried about them. I'm worried about
S1: systemic effects of them losing so many jobs and there
S1: being some sort of like threshold where if it crosses that,
S1: then enough people lose their jobs, it creates enough panic,
S1: it creates enough reduction of income into local businesses, so
S1: enough businesses close. So it kind of turns into like
S1: a like a mini pandemic effect, where it's like every
S1: I mean, that one was like different because it's so
S1: obvious why it's happening. But in this case, it would
S1: be like, oh, we're having some sort of economic meltdown.
S1: And then so the business is closed because no one's
S1: coming to the businesses, because they're panicking, because they don't
S1: have any money. And it's just like this massive cascade effect.
S1: So I'm really, really worried about that. And I'm really
S1: worried about I don't think a lot of these people
S1: are going to be able to reskill. I think this
S1: whole reskilling narrative is like something we tell ourselves to
S1: make ourselves feel good. And I'm not sure it's like
S1: how realistic it is. And it's it's like, really, I
S1: don't know. It's really depressing to me, the whole thing.
S1: So thinking about that side of it and how little
S1: I can possibly do is, is just not good for
S1: me to dwell on. So I literally dwell on it.
S1: I sit inside of the the suck, you know? And
S1: I sit inside there and I'm like, what can I do?
S1: What can I do? Um, how bad is it going
S1: to be? I have to, you know, share how bad
S1: it's going to be or whatever. So then I write
S1: a post like that which goes into all the detail,
S1: and I get it all out, and I basically put
S1: it there, and then I like, basically say, okay, that's it.
S1: We're not thinking about this anymore right now that we're
S1: setting that aside because the solution is always the same.
S1: The solution is to expand the mind to, you know,
S1: brush that off to to have the stoic mindset and
S1: be like, okay, yep, that super sucks. Okay. Well. Anyway. Right.
S1: I've been talking about this human 3.0 thing. I did
S1: that previous post called The End of Work. I didn't
S1: think this would be happening this fast when I wrote that, but.
S1: In end of work, I've already talked about it in
S1: David Graeber's book Bullshit Jobs. Right. I've always seen this
S1: current structure of like 9 to 5, and everyone, or
S1: a vast majority of people can't stand to go to work.
S1: It's cutting out 9 to 5 is the most important
S1: hours of the day. And all they have time to
S1: do is to get ready for the next day of work,
S1: which they don't want to go to, to have a
S1: bunch of stupid meetings. Like it? It's a bad situation
S1: that we're in, right? It's also bad that it's going to,
S1: you know, catastrophically come to an end. I would say,
S1: or at least, you know, very badly come to an end,
S1: I would say. Disruptively. Right. It's going to be extremely
S1: disruptive to millions upon millions of people, maybe billions. I
S1: don't know, it depends how you count, but it's going
S1: to be massively disruptive to the global economy. What is
S1: what is happening but going back to the positive, I
S1: think that needs to happen. It needs to happen that
S1: we get rid of this corporate structure. I mean, corp okay,
S1: this all comes from the military, the hierarchy. You work
S1: for Mr. Johnson. Mr. Johnson works for Mrs. Williams. Right.
S1: And Mrs. Williams is trying to get her presentation together, uh,
S1: to give to Mrs. Clark, because she's the one who
S1: put all this together, and we're all just happy to
S1: work for her. It's a very submissive, very hierarchical. Very
S1: unhealthy structure to have. Most people in any company be
S1: in this, like. Oh, yeah, I only contribute this little piece. Oh,
S1: they don't ask me for ideas. I just help them
S1: implement them. I'm just happy to be a part of it.
S1: Like that's cool for 1950s or whatever. I mean, we
S1: have to move through stages as humans. Well, it's time
S1: to get out of this stage. We should all be founders.
S1: We should all be CEOs, not not CEOs in the
S1: old style. I'm using the CEO term for what it
S1: is in the future, which won't be called a CEO.
S1: We are all individual contributors to society and we should
S1: be sharing with each other. We have companies. Yes, we have,
S1: you know, products. Yes, we have offerings. Yes. And of course,
S1: somebody gives us something in return for us giving them
S1: that service. Right. So there's still a currency here, but
S1: that currency won't be won't be based on this negative
S1: infrastructure that we currently have, where it's all based on
S1: your labor and it's all based on your, uh, you know,
S1: your participation in this negative hierarchical structure that creates all
S1: these bullshit jobs like David Graeber talks about in the book.
S1: And the way I think about this is this is
S1: just a natural progression. And this idea, I think I
S1: got most from Harari and I can't remember which book
S1: it was. I think it might have been the second
S1: one after sapiens. They use so that basically what he
S1: talked about is that, um, governments and systems of organization
S1: and systems of government are basically their time bound based
S1: on what is needed for the society at that time.
S1: So it's like, it's not that we shouldn't have had, uh,
S1: capitalism or we shouldn't have communism or whatever. It's like
S1: those structures are like best cases. They are the things
S1: that fit where humanity is at the time. And it's
S1: a good way of looking at like, okay, why didn't
S1: Iraq suddenly become a democracy as soon as we got
S1: rid of Saddam? Well, that's not where the population is
S1: ready for. Right. And maybe there's an argument that, like,
S1: we are no longer, uh, up to the task of
S1: maintaining a democracy because our population has declined so much. Cognitively, philosophically,
S1: education wise, or I would say knowledge wise. And so
S1: we're losing our ticket or we're losing our ability to
S1: be worthy of democracy. That's one argument. That's one argument.
S1: So I like this framing. I like the structure. And
S1: so essentially what we would be saying here is that
S1: the capitalist structure is super useful at a certain phase
S1: of our maturity and development. And that ideally we would
S1: move out of it and move into something more like
S1: not like a Stalin communism, not like a mao communism.
S1: It wouldn't even really be communism because it wouldn't be
S1: like state control of things. It would be more like
S1: shared human control of things and shared human voting. It
S1: would be actual democracy instead of democracy. Republic. Of democracy
S1: or a republic. Because we would have the tech, presumably,
S1: to do so. And you could use other things for
S1: the whole federal versus state or whatever. We could basically
S1: figure out these problems. Right. And the more advanced we
S1: are as a population, the easier that would be to do,
S1: because you just make a good argument and people are like, oh, yeah,
S1: it's a pretty good argument. Yeah, let's do it that way. Right.
S1: Which we clearly don't have today. But so the point
S1: of all of this is to say that the only
S1: way I can function is to take all of my
S1: concern and worry and sort of pain around. Holy crap,
S1: this is going to get bad and use that exact
S1: same force and that exact same energy and just be like, no,
S1: you know what? I am not thinking that way. I
S1: don't know that we have a chance to get out
S1: of this clean. We might exterminate ourselves. We might go
S1: into massive civil war. We might have, like, a huge
S1: amount of problems. There's a million what ifs. There is
S1: nothing I can do about it. There's nothing you could
S1: do about it. This is a thing that is happening
S1: to the planet right now, and it's just kind of
S1: playing out. And it's really weird with this whole free
S1: will thing. It's like, I know that we don't have
S1: the free will to fix this, but guess what? There's
S1: a guaranteed way it doesn't get fixed is to think
S1: that you don't have the free will to fix it.
S1: Which means I behave as if. And this is another
S1: essay I'm working on, but you behave as if you
S1: had the freedom, and ironically, that ends up bringing forth
S1: a more positive thing. Now you could say, well, that
S1: was what was going to happen anyway. Well, cool. Whatever.
S1: I don't have time to think about that right now.
S1: I need to think about positivity and trying to make
S1: it happen because we are humans. Actually, the name of
S1: this essay, and I know I'm sort of going on
S1: a tangent here, but hopefully it's okay. The name of
S1: this essay is Reality is Layer Dependent, which means at
S1: my layer right now, when I am trying to fix
S1: the world at my layer right now as a human,
S1: free will does exist. Because if I go outside and
S1: someone has stolen my trash cans and I see them
S1: across the street in front of their house and they're
S1: full of garbage. I'm going to walk across the street
S1: and ask them to not do that again. Please. I'm
S1: not going to say I'm not going to walk across
S1: the street and say, hey, I just want to let
S1: you know, I know you don't have free will. And, um,
S1: you there was nothing you could have possibly done to
S1: not steal my garbage cans and fill them up full
S1: of garbage. That is not a conversation I'm going to have.
S1: I'm going to have a conversation about them changing their behavior,
S1: which means at this layer of of reality, which is
S1: human interaction and the perception of free will. These are
S1: the kinds these are the types of conversations that we have. Right.
S1: And layers below this, it's kind of lame and stupid. Uh,
S1: the biological layer, the chemical layer, the physical layer. You
S1: talk to atoms about the fact that somebody stole garbage cans.
S1: They don't understand that. You know what I mean? So.
S1: All this coming back to. I'm trying to focus. I
S1: recommend other people do this as well. Take all that
S1: hurt energy, all that negativity, all that everything, and just
S1: move it over into this positivity category because everything could
S1: go horribly wrong. Or this could be the origin story
S1: for a few scrappy people got together and they planned
S1: on building a better internet. That was human based and
S1: they just, you know, steadfastly refused to give into the suck.
S1: And they started building the better thing. And, oh, the
S1: idea started catching on. And when things got bad enough,
S1: people leaned over into the positive side that that's actually
S1: what we ended up building. and it turns out we survived.
S1: It was way better. We got rid of the corporate
S1: work we're now teaching in schools that everyone is a creator.
S1: Everyone is a builder. Everyone is a entrepreneur. Everyone has
S1: value to give to the world, right? Not the special few.
S1: Your job is not to get out of school and
S1: find a really cool company, because that's a really smart
S1: person and you're going to give your little meager skills,
S1: you know, to, to help them succeed. Screw that. This
S1: is new world. This is we all have that capability, right?
S1: So if we have a tiny chance of this happening,
S1: that chance is larger if if we all try and
S1: push towards it. So that's that's why I'm very. Sort
S1: of sad and very excited all at the same time. Okay.
S1: That was the first line of the newsletter. After 22
S1: minutes in. That was literally the first line of the newsletter. Okay,
S1: we're scrolling down. Incredibly awesome conversation with my buddy Jason
S1: Haddox over the weekend about automated recon pen testing type
S1: stuff that we're building together. So mine is called Helios.
S1: I've had it for like, whatever, 15 years, I don't know,
S1: 12 years, something like that. And before it was just
S1: like nasty Python and bash and stuff like that. Basic
S1: automation stuff. Linuxi type automation stuff. Using a whole bunch
S1: of custom tools, a whole bunch of project discovery tools
S1: and like it does the job. But now I'm basically
S1: doing a full AI upgrade on it, and Jason's been
S1: working on his stack as well. And so, uh, we
S1: talked a bunch about, uh, what I'm doing currently with
S1: my stack with Kai, and he pings me like, I
S1: don't know, like 15 minutes later, he's like, dude, um,
S1: my thing just found a bug. Um, a P1 bug.
S1: And it turns out that, um, he had this password
S1: field for a thing that he was testing, and, uh,
S1: it was just the password field, and it was for
S1: some sort of admin site, and he was thinking, like,
S1: do I? Okay, what do I want to try to
S1: brute force this thing? It doesn't look extremely vulnerable. And
S1: his I found something that he and I would not
S1: have thought of. Uh, right. I mean, it's somewhere in
S1: my methodology, but it's not part of my main methodology. Um,
S1: which is to start messing with parameters. That's fine, but
S1: it in one shot, it's first thing that it tried
S1: was to add a parameter to post, which was id
S1: equals one and instantly bypassed. So an actual live real
S1: world P1. And he said he had to mess with
S1: it a little bit to get up to that point.
S1: But in terms of like doing an actual exploit, a P1,
S1: doing something that he wasn't going to do, I wouldn't
S1: have thought of, uh, at least in that immediately. I'm
S1: sure somewhere deep in our methodology, we have to not
S1: only modify parameters, but also to add parameters. I mean,
S1: that's a pretty common thing, actually, but it didn't come
S1: to mind, right? That's the point. It was like, that
S1: was pretty cool. It was pretty cool. So I think
S1: the takeaway that we have there is just like, this
S1: stuff is not theoretical. This stuff is like getting very,
S1: very tangible. And my point about this has always been
S1: that we just have an orchestration problem, like the individual
S1: steps don't require all that much intelligence. It's not super
S1: hard to do this stuff. The problem is keeping the
S1: plot when you're doing it and you're doing like, you know,
S1: 175 different mini tasks, and you're gathering all this context
S1: and there's too much context, you know, falling out of
S1: different places. So like a big part of what I'm
S1: doing with Kai is breaking context into separate subfolders with
S1: their separate cloud MD files and their separate large pieces
S1: of context, so that the subagents are consuming context and
S1: they're not polluting the main agent with that context. Right.
S1: Because you absolutely need this when you're, you know, parsing
S1: like complete Doms and stuff like that. Um, there's just
S1: so much content in there. Then you have, uh, haystack
S1: performance issues, right? You're trying to find like endpoints inside
S1: of a giant, you know, Dom full of JavaScript. It's
S1: like it's pretty nasty. And it takes up a lot
S1: of tokens, and it's traditionally not great for for AI.
S1: And the other thing to mention about this is like, no,
S1: when you should be using AI and no when you
S1: shouldn't be. Right. Um, I'm going to talk about this
S1: somewhere else. But one thing that's really cool is, is
S1: to think about the fact that, um, you should use
S1: as little AI as possible. I talk about this a
S1: little bit later in the newsletter, but uses little AI
S1: as possible. Ideally, the whole workflow would be legacy traditional
S1: deterministic tech, just regular code, right. So like addition, subtraction,
S1: multiplication like no reason to enter AI into this. Right.
S1: And then there are certain types of problems that do
S1: require that that do require intelligence. So if it requires
S1: intelligence it's the type of thing like hey is this
S1: a cat, for example. That's not an if this, if this,
S1: then that statement that you can give to regular code,
S1: which is why we needed machine learning, which is why
S1: we use AI. Right. So just knowing when to use
S1: which is super important. Um. All right. Scroll down. Peace.
S1: About limitations to creativity. And I realized there's actually a
S1: third limitation. So I'm writing another blog post that kind
S1: of unifies them all. But the third one, the third
S1: type of limitation to creativity, is not even thinking about
S1: some options for creating a new solution or solving a
S1: problem because it was previously impossible. It's like being stuck
S1: in like old world, old mind, old tech or whatever.
S1: And I got an example from this weekend, so I
S1: was I'm not very happy with like my, my um.
S1: Web analytics tech. So my web analytics stack is currently fathom,
S1: but I would much rather be using a chartbeat. But
S1: even Chartbeat doesn't do everything. It doesn't have a menu
S1: bar thing. Um, it also doesn't have historical metrics, right?
S1: I can't use it like Google Analytics. So I for
S1: like over a decade, I use Google Analytics and Chartbeat
S1: Chartbeat to look at Google Analytics to go and get
S1: reports from. And that's kind of lame, but I never
S1: questioned it. I never thought it was a problem. I
S1: was just like the way the world is, no big deal.
S1: Like that's just reality. Well, I was messing with, uh, fathom,
S1: which is my current replacement for both of those, because
S1: Chartbeat is too expensive now, and Google Analytics is garbage now.
S1: So I use fathom, and it's like it doesn't have
S1: the Google Analytics, like, I guess like enterprise feel. Um,
S1: it doesn't look nearly as good as Google Analytics or Chartbeat. Um,
S1: and it kind of has like a, uh, I found
S1: a way to give a menu bar icon, but I realized,
S1: hold on, I actually know how Chartbeat works. It works
S1: by having a piece of JavaScript on the page that
S1: sends a beacon every few seconds. And that's how it
S1: actually sends the difference between. It can tell the difference between, um, well,
S1: its primary functionality is that it can tell you who's
S1: reading the website. Right? Like right now there's 165 people
S1: reading my website. And that's that's my current count. I'm
S1: looking at my menu bar that's 165 people with a
S1: tab open that are reading it. Right. So that that's
S1: what I care about. I care about who's currently looking
S1: at what pages. Right. Google analytics doesn't have this. Chartbeat
S1: has this. It's the only one I've found that really
S1: had this feature. And they also had a guy that
S1: was like super pretty and it was just like a
S1: really cool way to visualize it. And I'm like, this
S1: is the best thing ever. So I paid for it
S1: forever and ever and ever. And now I just suddenly
S1: realized on Sunday while I was working on the newsletter, hey,
S1: I wonder if I could just make chartbeat. So I'm like, hey,
S1: I want a piece of JavaScript called analytics. I'm going
S1: to serve it inside my page. Here's where you're going
S1: to put it. Here's the functionality it's going to have. Um,
S1: here's how often it's going to beacon. Set up an
S1: endpoint on Cloudflare to receive the beacon. You're going to
S1: parse referrers like this, blah, blah, blah, basically. And I
S1: gave it a whole bunch of spec sort of stuff,
S1: you know, um, basically a full spec of what I
S1: want to build, uh, in the Google Analytics JavaScript, also
S1: in the receiving endpoint, also in the front end showing it.
S1: And I give it a bunch of examples and stuff
S1: like that. And in about 18 minutes of me just
S1: talking to it and giving it to it in that format,
S1: it then produced the full spec and wrote the entire thing.
S1: So within 18 minutes I literally had a chart beat replacement.
S1: And I then spent many hours after that trying to,
S1: you know, tweaking and adding fields and, you know, tweaking
S1: the color scheme slightly and display and stuff like that.
S1: So it's not like I was done after 18 minutes,
S1: but I had live visitors showing up and showing up
S1: on my graph, and the site looked pretty much like
S1: Chartbeat within 18 minutes. That is ridiculous. And the whole
S1: point of talking about this is, yeah, it's cool. So
S1: I want to talk about it. I think it's cool.
S1: I love, uh, live telemetry from the world is just
S1: a thing that, like, I'm obsessed with. You have a map.
S1: You realize that there's some human who's reading some thought, uh, and,
S1: you know, maybe maybe you've seen this person before. Maybe
S1: you've walked by them in a coffee shop or something.
S1: It's just like human connection, I think is really cool.
S1: But the thing I want to focus on here is that.
S1: Literally the second before I had this thought, I was
S1: caged by this concept of like, well, that's too bad.
S1: Short beats expensive because there's no way I could make
S1: a heartbeat. I wasn't actually even thinking there's no way
S1: I could make a heartbeat. That was an automatic default
S1: barrier inside my brain. I didn't even have to think
S1: that the barrier was there. The barrier is invisible. Now,
S1: keep in mind, I've been able to do this, this
S1: advanced level of like building for like the last couple
S1: of years, I've been building tons of stuff. Why did
S1: I never think to build a better analytics system? I've
S1: paid for Fathom Analytics. I've paid them hundreds upon hundreds
S1: of dollars for a thing that's worse than what I
S1: made in 18 minutes. Let that sink in, okay? 18
S1: minutes to be way better than my Google Analytics solution
S1: and my Chartbeat solution and my fathom solution. The limitation,
S1: the reason I hadn't done it, is because it hadn't
S1: popped into my mind that I was able to do it.
S1: And what really breaks my brain is I'm still currently
S1: limited by an infinite number of those walls and those barriers.
S1: So in this blog this is type three creativity limitation.
S1: And we seek. My argument is we seek or should
S1: seek type three freedom. In fact, all three type one
S1: freedom is freedom from internal um, not not being able
S1: to reach our internal child like creativity. So the freedom
S1: is to be able to and the restraint is not
S1: being able to. And then the second one is audience capture.
S1: So it's like you're worried about what your parents and
S1: your friends and your your surroundings. It's not really audience.
S1: It's more like peer or societal, uh, capture and like limitation.
S1: So you literally stop having good thoughts because you can
S1: only think along certain lines of what you're expected to
S1: produce and what is acceptable to produce. So that's layer two.
S1: And level three is thinking in the past being limited
S1: by the past. So it's like I grew up thinking
S1: only certain things were possible. And I can't even know
S1: all the ways that those limitations are still on me.
S1: I mean, I was born in the 70s, right? So phone,
S1: cell phones, right? I mean, all these things that we
S1: have now, how many of them? How many of them
S1: are like limiting me in me thinking that those things
S1: are possible. I feel like I'm way ahead of the
S1: game against most people in the world, honestly, including extremely
S1: young kids who grew up with tech. I feel like
S1: I'm more unbounded than most, but I still feel very
S1: bound by this. I feel extremely sort of caged by this.
S1: So I'm writing this post to kind of remind myself.
S1: Do you have all three types of these freedoms? Oh,
S1: and by the way, the reason I got on to
S1: this at all is from reading, uh, Rilke and Rilke's
S1: Letters to a Young Poet, um, which is a book
S1: that I've been recommending. And that's where I first started
S1: thinking about this. But then I started thinking about it
S1: from this book, Mathematica, which I just finished. And oh
S1: my God, it is extraordinary. So anyway, um, a bunch
S1: of that stuff is in the previous two posts about creativity,
S1: but I'm about to do this third one that kind
S1: of unites all of them. Oh, and by the way,
S1: I'm going to tell Kai to once I'm done with
S1: the third post to go and update the other two
S1: to point to the third one. And I can also
S1: say in the third one, hey, I wrote these previous
S1: two posts and it's going to Kai is going to
S1: automatically go find those two posts and link to them.
S1: So this is an example of a thing that you know,
S1: in the whatever 26 years that I've been blogging, I've
S1: had to do that manually. And it's just really, really
S1: great to think that I could just say one thing
S1: into Whisper Flow, and all of that gets dynamically updated
S1: by Kai. Okay. So, uh, all right, so that's the, uh,
S1: whole chart beat creativity thing. Um, oh. Had a really cool,
S1: interesting conversation with Matthew Brown from Trail of Bits. So
S1: we were talking about this AI system design thing that
S1: I was talking about earlier, and he gave me a
S1: couple really cool, um, ways to think about this and like,
S1: design principles that I'm going to use for my meta
S1: system designer. Um, and one of the things he said
S1: that was really cool is problem design, problem understanding and
S1: problem problem categorization is what it is really. So he's
S1: talking about problems that could be solved or problems that
S1: are like identifying a cat in a picture. That is
S1: a certain type of problem that code doesn't work for.
S1: You need machine learning, right? Or you need intelligence. Which
S1: machine learning is like a proxy for that. And then
S1: AI is a proxy for it as well or a
S1: type of it. So but there's other problems where you
S1: should not be using AI at all. Now, the reason
S1: I was talking to him is because he's, uh, he
S1: led the team on Trail of Bits team that won
S1: second place in the AI competition, which is a fully
S1: automated discovery and and patching system. Agent system. It involves
S1: multiple agents broken into multiple components. And so my main
S1: question for him was like, are you relying on the
S1: model the most or are you relying on the system
S1: the most. And he ended up saying system as well.
S1: I've thought it was system, so I was so happy
S1: to hear I wasn't wrong about that, at least in
S1: his opinion. And um, yeah, he just had some really
S1: cool ideas about like how you design the agent system, um,
S1: to constrain it and make sure you give it, like,
S1: only specific types of context. But, um, that episode should
S1: come out soon. Um, that's going to be on YouTube
S1: and also in the, in the audio and the regular podcast.
S1: And so, uh, really cool conversation. That guy is sharp.
S1: I mean, this guy's been doing AI forever. Like, he's
S1: probably going to get hired by Google for $74 trillion
S1: would not surprise me. Um, a few weeks back I
S1: posted about feeling really guilty about eating meat, and then
S1: I saw a Dwarkesh episode where he had this, uh,
S1: meat guy on or animals, you know, kindness guy on,
S1: and he's like, yeah, we've got this thing called Farm
S1: kind and it's a charity. And like, you know, even
S1: $10 can save a lot of animals from suffering. Um,
S1: and just just to, like, clarify why I care about this,
S1: it really upsets me how similar we are to some animals,
S1: especially like pigs, even chickens. I would say, like, obviously,
S1: I don't know what's in the mind of a chicken,
S1: but a pig looks and feels very normal to me.
S1: It looks and feels like a a more advanced animal.
S1: If you hear a pig squeal, especially if it's like
S1: in pain or something like that sounds like pain to
S1: my brain. It sounds like pain. And, um, there are
S1: people in, uh, I think it's groups in Africa. Or
S1: maybe it's Australia. Um, they call humans long pig. Uh,
S1: because the flesh is similar and in flesh means muscle.
S1: I mean, they're also pink, and a lot of humans
S1: are pink, right? I mean, there's so many similarities here,
S1: and I'm just like, oh, evidently we taste the same.
S1: That was that was the point of of being called
S1: Long Pig because, uh, these groups eat humans. They also
S1: eat pigs, uh, I assume like wild boar or whatever.
S1: And they're like, yeah, they kind of taste the same.
S1: And I'm like, okay, uh, good to know. Uh, how
S1: do I get out of here? Um, but I just like. Oh,
S1: and then you see the pictures of, like, this farm
S1: kind thing and just rows and rows and rows like
S1: matrix where you see all those, you know, human eggs
S1: or whatever, but it's rows and rows and rows of pigs.
S1: And this is the craziest part to me. They are
S1: laying on their sides like kind of like rotting from
S1: like infections or whatever, like, like bed bed sores or whatever.
S1: So they got bugs all over them rotting. These are pigs.
S1: They want to run around like young kids, right? They
S1: want to run around and have fun and, like, squeal
S1: or do whatever pigs do. They live their entire life
S1: on their side, and they can't stand up. They can't move.
S1: They can't run around. And they just. Okay, so I
S1: imagine a meter, this is the way I kind of
S1: see the thing. There's a meter for planet Earth. There's
S1: a suffering meter. And there is a like, fulfillment and
S1: happiness meter. Right. And we can go deeper with that
S1: of like, is it true meaning or whatever? Let's just
S1: say fulfillment is the far right. It's like just complete
S1: and utter, like deep contentment with life and happiness and such. Right.
S1: And on the far left is like a an AI
S1: designed like torture device, which embeds directly into your brain
S1: and produces the maximum amount of suffering. Okay, so that's
S1: the far left. And then you got the far right
S1: is kind of the opposite. Now, having millions of animals
S1: that cannot move and are stuck in a cage and
S1: are just like experiencing extraordinary hardship. This is not hundreds
S1: of animals. This is not thousands. It is hundreds of millions.
S1: I think it's actually billions think it's billions of animals
S1: who that we farm to eat or eat their meat
S1: and they are producing suffering into the world. It's not
S1: quite AI brain implanted torture, but it's too close for
S1: my happiness. It is pretty close. Just just imagine a
S1: conscious creature. Okay? We're not talking about a gnat or
S1: an insect or a caterpillar who knows what their brains
S1: look like, but I'm sure I'm not sure they're experiencing suffering. Okay.
S1: A pig is. Maybe a chicken is as well. So
S1: pigs and chickens? Cows? I care about this. I care
S1: about what that meter says on planet Earth right now. Obviously,
S1: I care more about humans, right? Because we got billions
S1: of humans who also need help, or at least hundreds
S1: of millions or millions who are in a suffering category
S1: as well. And obviously that's the highest priority. But the
S1: irony is this we could lower the meter more effectively
S1: with these types of things. And this gets back to
S1: the point I was making here. This this charity is
S1: able to move that meter. I wish they had a
S1: I wish they had a visualization for this. Should I
S1: should make one because I'm not limited by type three restraint.
S1: There should be a way to visualize. And they are
S1: able to do this with metrics. They actually have a
S1: way to say $10 will reduce. Will seems to through
S1: the lobbying effects and through the various programs that they implement.
S1: And they've got dozens of of programs. It's not just
S1: one that they put in. So there's like a cage one,
S1: there's like a cleanup one, there's like a medicine one,
S1: there's like a requiring that they are able to go outside, um,
S1: the size of the cages, um, cage free. Um, the
S1: types of medication, um, the, the number of inspections that
S1: they have to do, like, I'm, I can't remember all
S1: of them, but there's multiple programs that focus on particular
S1: parts of the problem. And this farm kind thing basically
S1: can allocate money into different ones of those. And so
S1: they're saying they're getting extreme results from a small amount
S1: of money. So anyway, I reached out to them and um,
S1: so they set up a thing for unsupervised learning. So
S1: it's farm kind. I forget the URL. It's farm kind, something. Um,
S1: but but it'll be in the show notes. It's in
S1: the newsletter, obviously, which is the show notes. So yeah.
S1: Go check this thing out. Click on the link. Give $1,
S1: give $1 billion whichever one you have. And we could
S1: actually like put a dent in this suffering meter on
S1: planet Earth because like my suffering okay, I'm a human,
S1: but I'm just one, one thing like is my suffering.
S1: How much higher does that rate? Because mine is existential
S1: versus a pigs. Who is? I mean, it probably feels
S1: just as bad, like just because it's not existential suffering.
S1: I think it feels just as bad. Right? And if
S1: there's a billion of them, they damn well damn well
S1: outrank me. So I love having a leverage via a
S1: donation system like Farm Kind to be able to actually
S1: do this. So, um, I recommend I ask you to
S1: go and actually put some money into this thing. And
S1: I love the fact that they set up a campaign
S1: for us because, you know, a lot of people get
S1: their newsletter, a lot of people get the podcast, uh,
S1: plus YouTube or whatever. Um, we should, you know, be
S1: able to help a lot of animals is, um, what
S1: I'm thinking. And I would say, don't even think if
S1: you don't care about animals, don't even think about animals.
S1: You could help a lot of earth based Consciousness, experience
S1: less suffering and reduce that that suffering. Meter down a
S1: couple new blogs two primary limitations on creativity. Talked about
S1: that one are 20,000 eyes thought experiment about how AI
S1: transcends transforms us from workers building other streams into creators
S1: with 20,000 eyes and hands building our own. Cybersecurity Expo
S1: raised 117 million for hackers, then open sourced the whole thing.
S1: This is the errata. This is the wrong thing. This
S1: Strix repo is really cool. This is it's my top
S1: story to. This is super annoying. Um, clear evidence that
S1: I didn't use AI. Um, because this was my mistake. Um, anyway, yeah.
S1: Strix GitHub repo is a cool thing. It's basically an
S1: automated vuln checking system. Um, and it wasn't Expo that
S1: did it. Expo was someone doing kind of something similar,
S1: and they just decided to stop doing their experiment on
S1: hacker one. So that part of the story is correct. Um,
S1: and Expo is doing cool stuff, but they did not
S1: release this GitHub repo. That's that's the part that's wrong.
S1: Here's workday lost data through social engineering targeting Salesforce. So
S1: a whole bunch of people are getting Salesforce compromised, which
S1: is really, um, social engineering attacks targeting Salesforce data about
S1: that company. And that's kind of the why you keep
S1: seeing stories that are kind of the same around these lines.
S1: And workday appears to be the most recent victim of this.
S1: Russia hacked a Norwegian Dam and released 1.9 million gallons
S1: of water zoom patches, a critical privilege escalation vulnerability affecting
S1: windows users new public exploit chains for two SAP flaws
S1: with RC agents. Um, getting zero false positives in security
S1: testing with deterministic validation. So that deterministic validation thing is
S1: really interesting. This is, um, this conversation, this, uh, blackhat presentation.
S1: There's a link to Expo here. Maybe this is how
S1: I got confused because I was reading like 20 of
S1: these things at the same time on Sunday, and I
S1: just like, got cross-pollinated whatever. Uh, my mistake. Um. Basically,
S1: the idea here is similar to what I was talking
S1: about before and what Matthew Brown was talking about, which
S1: is deterministic. That's code. Right. Um, and then you have
S1: AI and like don't make don't confuse the two. You
S1: can mix the two, but don't confuse the two. And
S1: they're basically saying like, here's a general thing. You don't
S1: want to ask it, hey, is this vulnerable? Because they
S1: want to please you. They'll be like, yeah, it looks
S1: vulnerable to me. So many false positives. So it's better
S1: to use like a deterministic system to check if something
S1: is vulnerable, if you can't. And then use the AI
S1: for different parts of the system that require intelligence, critical
S1: vulnerabilities and flow wise, AI platform 9.8 on the Richter
S1: scale is going to happen. It's going to keep happening
S1: because more and more systems are being built. So the
S1: attack surface by its very nature is growing, therefore going
S1: to be more vulnerable. Um, and then you have the
S1: fact that AI is building so much of that code.
S1: I'm not actually sure. Now I think about it. I'm
S1: not actually sure if we add a 100 no. 2
S1: million new websites to the internet that are suddenly built
S1: by humans or suddenly built by AI. Which one is worse?
S1: I guess it comes down to the question of what
S1: made it be sudden. Why is there so all of
S1: a sudden, so many 2 million more people making websites?
S1: And who are those people? That's the question. Um, but
S1: right now, I mean, humans aren't good at making secure code.
S1: Really good humans are really good secure coding. Writing humans are,
S1: but most aren't. Which is why Stack Overflow is full
S1: of garbage. Which is why I trained on it. And
S1: it's also making garbage. But AI is making lots of
S1: slop on the internet, and it's shipping code very fast.
S1: So it's bad. Um, now, over time, I think that's
S1: going to get better and better. But in the meantime,
S1: the slop will have already been made. And then you'll
S1: need something like the AI automation bots to go clean
S1: it all up. Chinese hackers breached Taiwan web servers using
S1: customized open source tools. This is a Cisco Talos. Fine.
S1: Lars shows us how missing MFA turn valid logins into
S1: full compromise. Russia hackers breached US federal courts through vulnerabilities discovered.
S1: But they were not fixed in 2020. So getting compromised
S1: by something that you should have or you were told
S1: about but didn't fix. Cisa releases new guidance telling companies
S1: to inventory their OT systems. What do you know? Asset management.
S1: This is going to be one of the biggest, coolest
S1: things ever. Oh, by the way, I want to um,
S1: I just thought of another idea which I didn't put
S1: in the newsletter. Here's a cool idea and related to
S1: my USC concept of unified entity context for enterprises. And
S1: I got this idea, um, well, it's in the USC
S1: idea as well, but I got this very specific idea
S1: from a prince who's part of, um, Project Discovery. And
S1: the idea is you send your agents out and their
S1: job is to be like, they just sit inside of software.
S1: They just sit in different places. They sit inside of wikis,
S1: they sit inside of like organizations. They sit inside of software.
S1: They sit inside of GitHub repos. And I forget how
S1: he was talking about it. Um, but he basically said
S1: distribute agents and have them do things and report back.
S1: And so mine, my mind started jumping towards the USC idea. Um,
S1: but I also jumped to the idea of security champions.
S1: You know how like a lot of security teams, they'll
S1: send their people out, like into the field, which is like, oh,
S1: you live with engineering now? Oh, you live with product now.
S1: You live with sales now or whatever. And their job
S1: is to like sort of like understand report back but
S1: also subtly influence them. Well, what if you didn't have
S1: three of those people for the entire company, but instead
S1: you had 3 million of them? Just imagine that every
S1: piece of software, every piece of tech like your AWS accounts, your, um,
S1: all your infrastructure, everything has agents inside of them watching
S1: and reporting back. And some, of course, would be able
S1: to make changes that'll come later. Um, and if you're
S1: freaking out, that's because you work in security. Um, because
S1: I'm freaking out. Just saying the words. So you have
S1: millions of these agents out there They're gathering, reporting back,
S1: blah blah blah. Who's controlling these agents? What identity do
S1: they have? How are we logging their information? Like auditors
S1: are going to freak out about this, but I think
S1: this is absolutely the way that USC happens. Or one
S1: of the ways that USC happens. There's different ways to
S1: do this. You could have centralized agents that go, just
S1: go and hit the stuff live and pull the stuff back.
S1: But I think it's better to just deploy agents into
S1: the systems themselves and have them point back to the center. Right?
S1: Because I feel like we well, it's probably going to
S1: be both. It's kind of like asset management, which is
S1: how I got in the point. If you have the
S1: agents inside of all of these systems and they're reporting back,
S1: guess what they're doing? They are updating and breaking out
S1: sub contexts, which then get summarized by other agents to
S1: report up into a higher context, which which is the UFC,
S1: and that UFC ultimately becomes this conglomeration of all these
S1: mini contexts that got updated from all the air systems
S1: and the project management system and the budget system and
S1: all of those, like somebody buys, you know, a toothpaste
S1: while they're traveling overseas on a work trip, being they
S1: paid for the toothpaste. Okay, that hit some system somewhere.
S1: Well guess what? In this world, which, by the way,
S1: this is going to take a very long time to
S1: roll out. So we're talking between two and, you know,
S1: 15 years, right. I'm sure someone's already doing it a
S1: little bit, but it's going to take a very long
S1: time to move through all of enterprise it in that world.
S1: Whenever whoever gets it, that agent lives inside of the
S1: finance system and the accounting system, and it sees the
S1: toothpaste hit, and it reports up a tiny little entry
S1: into a subcontext, which goes into another subcontext, which goes
S1: all the way up. And ultimately, that probably wouldn't be
S1: part of a big strategic picture, but at least it
S1: would increment values, right? Um, and maybe it didn't need
S1: to report that because that's part of traditional tech, which
S1: gets valued later, but maybe they weren't supposed to be
S1: traveling and that that, uh, purchase of toothpaste means they're
S1: not where they're supposed to be. And now we have
S1: a traveling problem and the VPN connection is turned off.
S1: Whatever it is, the point is, all these different agents
S1: in the different systems can be updating the central picture
S1: of not just USC. But guess what you get for
S1: free when you have USC, if it's reporting on the
S1: proper stuff. Asset management we've never been able to do
S1: asset management. Never. It's it's hard Like I consult for
S1: Jupiter one because I love their vision of doing this
S1: with a graph. It is really, really hard. It is
S1: really hard. Um, I did this for Robin Hood. I
S1: did asset management for Robin Hood using, um, a product
S1: like this. Right. And I'm telling you, this is like,
S1: it's completely like shifting, like game shifting stuff to have
S1: actual real time understanding of the systems. Right? That's what
S1: it comes down to. Asset management is an old word.
S1: Let's let's not use that anymore. Um, you know, uh,
S1: real time information gathering or whatever, like, there's old words
S1: to use, and they're kind of dead in our minds.
S1: Here's just another way to think about it. Millions of
S1: agents deployed across your entire organization inside of all the
S1: different tech stacks. Stocks. That is very hard for a
S1: centralized entity to go and audit. And by the time
S1: you do go and audit it, it's too it's too late.
S1: That information is rolled off like there's a million examples
S1: of this. And if you're in it or security or whatever,
S1: you already know this, right. So planning, finance, tracking what
S1: you know people are doing and if they're happy or
S1: unhappy and how we can how can we make them happier.
S1: How can we keep people from quitting? Um, customer churn.
S1: That's a great one. Customer management. I mean, think about that.
S1: Look at all the different things that we know the
S1: customer is doing, and which one of those could be
S1: signals that they're getting ready to churn? And what can
S1: we do as a, as a result, like a reactionary action? Um,
S1: so they haven't come to the portal recently. Okay, cool.
S1: They start. Um, I don't know. They start blogging about
S1: how the competitor looks better and their team at their current, uh, offering. Doesn't, uh,
S1: ever reach out to them? Well, that's a great one.
S1: Are there any agents right now watching customers public blog posts,
S1: trying to figure out if they're unhappy with the product,
S1: or they're getting excited about another product and then sending
S1: them a preemptive email that says, hey, haven't seen you
S1: log in recently. Hey, here's a $5 discount code or whatever. No,
S1: I don't think so. And if there are, there's very few.
S1: This will become commonplace. The point here, and I'm just
S1: saying the point over and over. So, um, I'm saying
S1: in different ways, hopefully it's sinking in. It might have
S1: sunk in like, uh, 38 minutes ago. If so, I apologize.
S1: Real time updating at the edges inward, as opposed to
S1: being the central person who is responsible for all these things,
S1: and all the systems are opaque. You have to reach
S1: out to that owner. You have to get a user
S1: and a login like it doesn't work. It hasn't worked.
S1: That's why asset management has been so difficult. Um, and
S1: that takes us all the way back to the point
S1: I was making with Sisa releasing new guidance, telling companies
S1: to inventory their OT systems. It's hard to inventory your
S1: OT system, right? It's also hard to install agents on
S1: OT systems because they don't want to install anything and
S1: haven't wanted to for decades. So this will be a
S1: slow process. Um. National security UK police are getting ten
S1: facial recognition vans to catch serious criminals. And they're saying
S1: like sex offenders, people wanted for serious crimes. So they're
S1: looking for, like, outstanding warrants. But you know what? It's
S1: still the van with cameras. And, uh, it all depends
S1: on the government you have on how those tools will
S1: be used. Will it be the best thing ever for humanity? Yeah, maybe.
S1: Depends who's using the tool. America's gray zone blind spot
S1: is becoming serious national security problem. So, uh, someone at
S1: the cipher Brief is basically saying that, like, Russia, China,
S1: Iran are ramping up, sabotage, cyber attacks, other hybrid warfare attacks.
S1: And basically the US is not good at these things. Now,
S1: what I would hope is we actually are understanding these.
S1: We're preparing to do them, uh, not not in a
S1: terrorist way, but like we're we understand and we're learning
S1: how to defend against them. And we could potentially use
S1: some of these tactics ourselves. Um, but that we just
S1: don't talk about it. I think that's more likely to
S1: be the case, and I hope it's the case. US
S1: military transforms Indiana training grounds into drone warfare innovation hub.
S1: Happy to see this. We are behind on drones, especially
S1: as it relates to China. Russia blocks signal and WhatsApp
S1: to control communication. US Navy wants 150 unmanned ships by 2027. Yes, please.
S1: Our ships. I remember in the early 90s, I was
S1: in the army. I was studying assassin's mace weapons, and
S1: there was some general talking about how our fleets are
S1: going to be extremely vulnerable to assassin's mace weapons by
S1: specifically China, where they could deploy something. And our giant
S1: like projection of power through aircraft carriers and carrier fleets
S1: could just be taken out in a matter of minutes
S1: or hours. using one of these types of weapons, or
S1: multiple of these types of weapons, that costs very little
S1: to make. And it turns out the number one assassin's
S1: mace weapon. That has started to happen. I don't remember
S1: if he was talking about it back then, because I
S1: just wasn't smart back then, and I just can't remember
S1: that far back. But, um, it is drones. Absolutely. It's drones.
S1: And I will mention kill Decision by Daniel Suarez. Go
S1: read that Israel says Iran recruited dozens of Israeli citizens,
S1: highlighting concern with like, yeah, it's pretty easy for foreign
S1: Intel services to like recruit citizens. I mean, if you
S1: have enough, if you have thousands or millions of citizens,
S1: it's just a matter of like finding, you know, it's
S1: a filter system to find the right ones. And it's
S1: unfortunately pretty easy. China detained second senior diplomat in expanding probe.
S1: So they're arresting a bunch of diplomats. Not exactly clear
S1: what they're doing wrong. I'm guessing it might be like
S1: not being pro-China enough. Maybe they're becoming too Western. No idea,
S1: but I'm curious about that. I Anthropic's also Anthropic's CEO,
S1: says I will write 90% of code in 3 to
S1: 6 months. He said stuff like this before, and to
S1: be clear, he's not saying there won't be people writing
S1: code like only 10% of people now will be writing code.
S1: He's saying that just there will be so much more
S1: AI code that it'll be 90% of the total. OpenAI
S1: is building chromium based web browser with AI agents that
S1: can browse for you. My buddy Jason is like, yeah,
S1: the next big thing is, uh, AI for AI is
S1: basically browsers. And I think he's turning out to be correct. Like,
S1: I keep waiting for the next step, which is the Da,
S1: which is what I'm building. And I think that's kind
S1: of the final step there is to have your Da
S1: do all this for you. And a browser would just
S1: be a tool, but it sounds like he's correct in
S1: that this is going to be the home for a
S1: while because we all use our browsers. We don't have
S1: DA's yet. Da platforms aren't there yet with like Apple
S1: and Google or OpenAI with like a separate device. So
S1: that ecosystem like hasn't started happening yet. Um, but browsers have.
S1: So I think he's turning out to be very correct
S1: about this. And now OpenAI is getting in the game.
S1: Sam Altman says we're in an AI bubble. I agree
S1: with this. I just think it's not the kind of
S1: bubble that people think it is, because it's not like
S1: AI is going away or it's going to crash. So
S1: when I think bubble, I think NFTs or, um, Pets.com.
S1: Because largely those things don't exist anymore. And it was
S1: it turned out to be kind of a scam. Now,
S1: I'm not an expert on, uh, the.com bubble because I
S1: kind of wasn't sentient at the time, but, um. My
S1: understanding was a lot of hype around, like, if you
S1: just have like a.com, blah, blah, blah, like you're just
S1: going to make tons of money. And the NFT thing
S1: is like, yeah, you're going to have this, you're going
S1: to buy it for $18.14, and you're going to be
S1: a millionaire if you hold on to it for a
S1: year and a half. Those are bubbles to me. Okay.
S1: The AI thing, to me, it's the most important tech
S1: ever invented, bar none. No questions asked. Bigger than internet.
S1: Bigger than mobile. Bigger than steam engine. It's the simply
S1: the biggest tech ever. Okay. That is not a bubble
S1: at all. What's a bubble about? I is thousands of
S1: people putting hundreds of billions of dollars. I think we
S1: can call it trillions of dollars now. Like invested and,
S1: you know, earmarked or whatever. Like, let's just call it
S1: hundreds of billions of dollars into new startups, new websites,
S1: new whatever. And everyone's jumping in there like, oh, yeah,
S1: you know, I do a slightly different prompt and, um,
S1: I've got this cool website and I'm going to raise
S1: a whole bunch of money and I'm going to hire
S1: some people, and I have a startup and it's like, no,
S1: not really. Not when OpenAI and anthropic make a slight
S1: change to their their code base, which just eliminates your
S1: company and 40,000 other companies just like it. It's a
S1: bubble because people are unsure of what it is and
S1: they're getting in in unsafe ways and haphazard ways and
S1: kind of stupid ways in a lot of cases. A
S1: lot of people aren't, obviously. But there is going to
S1: be a major correction because there is so much money invested.
S1: The investors don't understand AI. They're starting to a little
S1: bit now, but they've been investing hundreds of billions of
S1: dollars for like the last year or two years. I
S1: don't know how far back all that money was sent
S1: in on FOMO. It was sent in on hype. Okay,
S1: so this is this is the distinction. This is why
S1: people need to think about this super clearly. Both things
S1: are true at the same time. AI hype that's going
S1: to die down because people got in in very stupid ways.
S1: People are going to call that a bubble. Look what
S1: happened to AI. It turns out to be garbage. Very
S1: huge mistake. Like massive mistake. That is not a bubble.
S1: That is stupidity about a thing that is not understood
S1: and basically incautious and ignorant action taken as a result.
S1: And absolutely that's going to crush. Honestly, I think it's
S1: going to crush the majority of companies, the vast majority
S1: of these small little companies. Um, how about Google? How
S1: about meta? Are they going to have an AI hype
S1: and crash cycle? Uh, no, they are not. Because what
S1: people are doing inside of those companies is they're looking
S1: at all their existing processes. Another good example. Bank of America.
S1: Are they going to have an AI hype cycle? No
S1: they're not. They already know how everything works inside their company,
S1: and they are carefully figuring out how to apply AI
S1: to those existing processes. They're going to save tons of money.
S1: They're going to do things way better. And looking back
S1: ten years, they're going to be like, yeah, we wish
S1: we had this earlier. Like we would have saved tons
S1: of money. Unfortunately, they'll probably get rid of people as
S1: a result as well, which is a whole separate talk show. But.
S1: For people who are doing AI correctly and will do
S1: AI correctly in the future, it is laughable. Laughable to
S1: think of AI as a bubble or as hype. Okay,
S1: for all the NFT like crypto, like people who just
S1: thought I was a way to make money. It's absolutely
S1: a bubble. 100%. And they are going to get crushed.
S1: So just keep both of those ideas in your mind
S1: at the same time. Whenever you hear AI bubble AI hype.
S1: All right OpenAI updates GPT five to be warmer and friendlier.
S1: A lot of people really hated it. They hated the personality.
S1: I mean, there were I think there were suicides over
S1: using GPT four. Oh, he had to return GPT four
S1: back because everyone loved it so much after they complained
S1: about it constantly. Uh, should be noted. Slop squatting is
S1: when attackers register fake packages that llms hallucinate. I should
S1: have put this in the cybersecurity section. Yeah, this is
S1: really funny. So you make up a whole bunch of
S1: AI slop names, and then later on when I slop generates, uh, packages,
S1: names that are real people start using them. They will
S1: own the real estate. So they basically just like man
S1: in the middle, your, uh, your stupid AI named library
S1: shadow AI is like having rogue interns secretly running parts
S1: of your business. Yeah, especially given what I just talked about,
S1: about millions of agents deployed. You imagine an auditor coming
S1: into a place and they're just like, yeah, I just
S1: need to see, you know, who has access to change things.
S1: And it's like, yeah, we've got, you know, so and
S1: so AI platform it um, it's running on average 2
S1: million active agents, but they're, they're swapping in and out
S1: all the time with like a variance of like 2
S1: to 400,000 agents active at any one time. And it's like, okay, cool.
S1: Can you print me out a spreadsheet? I just want
S1: to review those line by line. Like that's going to
S1: be a nightmare. An absolute nightmare. Of course they'll be
S1: using AI to do that, but whatever. It is weird
S1: to think about millions of things deployed that have agency. Um,
S1: and they could see things and they could report things.
S1: I mean, think about central AI system compromise in this world.
S1: I mean, are you kidding me? I mean, a single
S1: kill command. Because ideally, you're supposed to be able to
S1: talk to all these agents, right? You obviously need to
S1: be able to give them commands. You need to be
S1: able to update their instructions. What if you could just
S1: tell them, wipe everything? What if you could tell them
S1: inject this tiny little like cuckoo's egg, steal half of
S1: a cent or whatever and send it to this Bitcoin account? Like,
S1: I mean, this is just wild world we're about to
S1: move into. Now, ideally you'd really, really defend this thing,
S1: but oh my goodness. You know mistakes will be made.
S1: DeFi startup replaces 45,000 in content staff with 23 agent
S1: AI systems for $23 per month. No. $20 per month
S1: 23 agent AI systems. This is a type of thing
S1: I'm hearing about this all over the place. They're like, yeah,
S1: I was spending, you know, 400 grand on this thing.
S1: Now I'm spending $284 and getting better results. Oh, best
S1: example of this is like, big giant reports. Big giant.
S1: So two names that I'm super like, I just think
S1: they're about to get destroyed. Gartner and McKinsey. And like
S1: everyone who's like Gartner and McKinsey. So the more expensive
S1: it is for, the nicer the looking report it is there,
S1: the more the most screwed. Like there is expertise inside McKinsey.
S1: There is expertise inside Gartner. But they're going to have
S1: to become like influencers. They're not influencers, but like content creators,
S1: like basically what I'm doing, they're going to have to
S1: go independent essentially, and have their own broadcast of their
S1: talent and their skill and their expertise, because it's going
S1: to be hard to differentiate because most, I would say
S1: most high quality reports like that. First of all, they
S1: show up with the coolest people like me who've been
S1: in the industry for 30 years, and I go do
S1: the sales call and dazzle them, and then I leave.
S1: And then, you know, 14, you know, smiling 22 year
S1: olds show up who just basically learned what a command
S1: line is and basically learned what security is. And those
S1: are going to be the consultants writing your report. And
S1: really they're using the expertise from all the previous reports.
S1: And like how does that match. Oh, and by the way,
S1: it's going to be $180,000 for this report, which takes
S1: nine weeks to make. Okay. And it's a giant opaque thing.
S1: It takes time to parse it and everything or whatever,
S1: as opposed to all the same context that those smiling
S1: 22 year olds had to get from you by all
S1: the interviews, you could just give that to your eye.
S1: Your eye is actually way smarter than the collective knowledge
S1: of all of McKinsey. And so you make that same
S1: report in four minutes for $1.17, or let's just say
S1: it's actually way more expensive. We're actually going to spend
S1: way more time. We're going to use the most expensive
S1: AI ever invented, you know, you know, uh, Claude Coad fucking, uh, seven, right?
S1: So it's actually $14. It's the most expensive prompt ever
S1: run in the history of mankind. It's a $14 report,
S1: and it took, uh, nine minutes to make compared to
S1: whatever the cost was of the other one. That took
S1: nine weeks. These companies are in dire, dire trouble. Technology.
S1: Robin hood CEO says remote work was a mistake. Orders
S1: executives back five days a week. Yeah, honestly, I think
S1: on site work is better. I really do. I love
S1: working remotely. I think certain people are as good or
S1: better working remotely, but the vibe of a team is
S1: a hundred times better on premise. I've seen it multiple times,
S1: and I've seen CEOs learn this the hard way multiple times.
S1: And I know lots of people who've done both and
S1: tried both. And this is my current wisdom level, is
S1: that in general, on site work is better. So cool. Uh,
S1: what I do like about the announcement was for executives,
S1: it's mandatory five days on site. For managers, it's four
S1: days on site, and for regular workers, it's three days
S1: on site. And his his quote here is, um. Your
S1: boss should be feeling more pain than you. I love that.
S1: I hate the fact that it's pain. Uh, which is
S1: why I think we need to move to human 3.0.
S1: Because this is ridiculous. We should all be working remote
S1: and doing, like, live meetups to work on our mutual projects.
S1: And if we have companies together or whatever. But this
S1: whole thing of you must come in. Uh, I just
S1: I think it's very old world. Uh, unfortunately, it seems
S1: to be more effective in the current model. China mandates
S1: domestic firms source 50% of chips from Chinese producers should
S1: have put that in Natsec. Text only websites are faster, cleaner,
S1: more accessible than modern web bloat. I love text only websites.
S1: I have very few images on mine. Researchers create micro
S1: microfliers that levitate using only sunlight. I need many of these, um,
S1: although I want to give them lots of capabilities. Which
S1: means they'll be too heavy, which means they won't float. Um,
S1: but this is a project I want to work on
S1: humans more. Most Americans think AI will permanently eliminate jobs.
S1: This is from Reuters Ipsos. Multiple studies show transfers to
S1: poor Americans basically don't help. This is like UBI studies.
S1: Looks like UBI studies are not looking good. The hope,
S1: including my hope, was that you give them this money
S1: and they're just going to focus on growing themselves and
S1: like learning and blah, blah, blah. The more I think
S1: about this, the more I kind of always knew this
S1: would not happen. Most people simply don't want to learn.
S1: Most people do not want to improve themselves. Most people
S1: are not like, curious and ambitious and like they're looking
S1: for their next Netflix show. The vast majority of people
S1: I would say, I don't know the numbers, but I
S1: think this is a thing that can be helped. I
S1: think this could be an education thing. I think some
S1: of this could be trauma, it could be bad education,
S1: it could be bad training, it could be bad culture.
S1: It could be lots of different things that make this happen.
S1: But for example, um, most libraries like, don't have people
S1: like knocking down the doors. It's free. Those are free books.
S1: Nobody's reading them. Okay. Okay. Free books. Nobody's reading them. Okay.
S1: The internet is full of free books. Nobody. Nobody's reading them.
S1: If you ask the average person, like what books are
S1: you reading? They're like, are you stupid? Like, I graduated
S1: high school a long time ago. I barely read those books.
S1: Why would you make me read a book? Now, some
S1: people read a lot of romance books, a lot of, like,
S1: comics or whatever I'm talking about, like. And I would
S1: say that's already just brilliant and amazing, just that by itself.
S1: But I'm talking about actually, like mostly non-fiction or really,
S1: really good fiction, difficult books, books that grow us. That's
S1: what I'm talking about. Very few people like, I'm in
S1: the San Francisco Bay area, okay. And most people here
S1: aren't reading. Most people I know in San Francisco Bay area,
S1: I don't want to make like, broad statistical things. Um,
S1: because I think, you know, first of all, that's impossible. But, Um,
S1: and I think a lot of the stats are wrong.
S1: I think when you report, how many books do you
S1: read a year? I bet you most of those stats
S1: are complete garbage. Who wants to say I haven't read
S1: a book since high school? Not very many people. My
S1: point is, I know lots of very smart people who
S1: make decent money, and I know all their friends as well.
S1: And I mean, I know hundreds or thousands of people.
S1: So this is my anecdotal data set. Most people don't
S1: read books, right. So. I don't know why I went
S1: so heavy into the book thing, but my point is,
S1: in general, most people don't care about self-improvement. They're not
S1: obsessed with it. Um, so when UBI money comes in,
S1: they're not thinking, wow, I can learn a new career. Wow.
S1: I could, I could buy even more books with this
S1: so long way of saying. I think this is why
S1: we're seeing the results from these UBI studies. Like, they'll
S1: just eat out more. They'll just, you know, improve their
S1: lives in other ways. They'll, you know, buy more subscriptions,
S1: buy clothes. And what's wrong with that? There's nothing wrong
S1: with that. I'm just saying, like, we should stop, like
S1: deluding ourselves that everyone is trying to be in this
S1: category that they think they are. All right. Europe faces
S1: an emergency as American markets completely dominate global investing. China's
S1: economy slowed in July despite exports staying strong. I'm about
S1: to do a major substrate project here to gather economic data.
S1: A whole bunch of data, actually. But economic data. I
S1: want to know where we're getting these numbers from because
S1: we know China's numbers are bad. Like, what are we
S1: judging this based on? And I want to kind of
S1: establish some ground truth there or at least triangulate onto it.
S1: Nobody's buying homes or switching jobs as American mobility stalls.
S1: Americans are drinking less alcohol than they have in 90 years.
S1: This is from a Gallup poll. Williams syndrome makes people
S1: hyper social and trusting of everyone. It's basically the opposite of.
S1: Being autistic. I almost said autistic. It's way different. UK
S1: drought group tells citizens to delete emails to save water.
S1: That's why the UK cannot have nice things. They're telling me.
S1: It's not the UK, it's some drought group. Okay, it's
S1: a country didn't do this, but whatever. It rhymes with
S1: a lot of things that the UK is trying to
S1: do to stop progress. The story behind Timothy Leary's turn on,
S1: tune in, drop out. You got to go check this
S1: thing out. Tune in. No. Turn on, tune in, drop out.
S1: Definitely something to check out. Ideas. Happy about this section?
S1: I feel like I is going to have a profound
S1: impact on globalism, especially for knowledge work. So the first
S1: jobs to go away are like the Fiverr jobs, the
S1: Upwork jobs, um, a lot of creative work, a lot
S1: of build me a basic website. And that's the first
S1: stuff to go with I and I'm really worried about
S1: millions of people because, like, we're always so us focused.
S1: Obviously I live in the US. I'm very US focused,
S1: but it's like, what about the rest of the world?
S1: What about all these really smart, ambitious knowledge workers who
S1: learned how to make websites and they're getting crazy income
S1: and helping their families and helping their local economies from
S1: all over the world. You know, Vietnam, Poland, like all
S1: over the place. And now suddenly that faucet gets turned
S1: off because smaller groups of people can use more AI
S1: and take more of that work. One of the primary
S1: directives of building AI systems should be to use as
S1: little AI as possible. Cool. Talked about that one. Thought
S1: I forgot it. It's in there. It's number two. If
S1: most people aren't confused about what I'm writing and sharing,
S1: that means I'm not properly exercising my type one freedom
S1: or my type two freedom. Actually, now that I think
S1: about it. But yeah, this is a whole thing and
S1: this is already a 17 hour podcast. So I'm going
S1: to I'm going to pass on this one for now.
S1: But basically if you are speaking from your true authentic self.
S1: You should be surprising yourself and you should be surprising
S1: everyone around you. If you only say things that people
S1: are like, yeah, that's that's perfectly correct. And they're not like, hmm,
S1: that guy's a little bit weird. Like, yeah, what? Why
S1: is he talking about that? That's kind of weird. Like,
S1: it doesn't match any of his other content. Um, so
S1: this is why I like Tyler Cowan. This is why
S1: I like Dwarkesh is they just explore things. Okay? And, like,
S1: I don't think Dwarkesh is sitting around wondering, like, oh, gee,
S1: I can't put out this video because no one will
S1: like it because I'm supposed to talk about AI. He
S1: literally just goes on rants about China and he just
S1: did the animal one. He's literally just chasing his his, uh,
S1: his interest. Right? And that's I feel like that's what
S1: I do as well. It's massively hurt me. It's massively
S1: hurt my socials because I'll talk about whatever and they'll
S1: be like, don't talk about politics. Don't beat up on Trump.
S1: He's a great guy. And it blunts my stuff there.
S1: But I think it's just a better way to live,
S1: to not be restricted in this way. Number four, a
S1: lot of what comes out in your words and your
S1: writing comes not from your thoughts or what you wanted
S1: to say, but from your current emotional state. So the
S1: way I think about this is there's a thing you
S1: think you're saying, like, for example, in this whole podcast,
S1: there's a think thing that I think I'm saying, right?
S1: I think I'm sounding smart. I think I'm sharing information
S1: with people. I think I'm like being helpful. I think
S1: I'm being excited. But people might be hearing something else.
S1: They might be hearing, oh, this guy's actually trying to
S1: promote his products. Like, let's say I was actually trying
S1: to promote a product, which I'm not right now, but
S1: maybe I will be in the next podcast. Who knows? Um,
S1: let's say I was actually trying to promote a product,
S1: but I was trying to talk in a way in
S1: which it seemed like I wasn't. I was like, oh, yeah, well,
S1: you know, everyone all use threshold, for example. I'll be like, yeah,
S1: everyone has a problem. You know, I just think it's
S1: really weird. People, you know, can't find whatever, they can't
S1: find the right stories and like, they're not rated high enough. And,
S1: you know, there's there's, uh, small creators around the world
S1: and they can't get their stuff found or whatever. And
S1: the receiver is like, I feel a pitch coming. And
S1: in my mind, I don't think I'm sending that, but
S1: they can receive it. So I'm obsessed with this idea of, like,
S1: receivers can hear things beyond the senses. They have an,
S1: you know, an extra sensory way to sense truth in
S1: what's being sent. So it's almost like what I'm sending
S1: is beyond words and meaning, and what they're receiving is
S1: beyond words and meaning. So the words I'm saying and
S1: the words they're hearing are at that surface level, but
S1: what they're actually understanding, what I'm actually sending is different
S1: than what I think. And the only thing that I
S1: can interpret it is, is a receiver. And they're going
S1: to receive it emotionally, and I'm going to send it
S1: emotionally at another layer than my words. So I'm like
S1: obsessed with this. I'm like, that's how I could read
S1: a whole bunch of tweets, including from my own, and
S1: just be like, um, well, I'll just use someone else,
S1: for example. They're like, oh, blah blah, I'm such a
S1: hero and blah blah blah. And I did this and
S1: I didn't even want any appreciation from it at all. And,
S1: you know, I just put a lot of effort in
S1: and blah, blah, blah. And the thing that they're trying
S1: to send with their words is. Um, well, they're trying
S1: to create the impression that they're just a selfless person,
S1: and they just do it for the community or whatever.
S1: But what a tuned receiver hears is I'm a giant narcissist,
S1: and I want everyone to love me and think I'm
S1: the best person ever. And I am obsessed with the
S1: difference between those signals and how the second one is
S1: often invisible in the text that they said, but also
S1: to the to the sender, to the person who said it.
S1: They're like, what are you talking about? I'm just like,
S1: just sharing some of the things I've done. Like I
S1: donated blood nine times yesterday. Like I'm just sharing that information.
S1: I'm not trying to say that I'm a hero. Now,
S1: if you want to call me a hero, you, you're
S1: free to do so. Um, anyway, that's kind of the
S1: point there. All right. Discovery I apps are becoming like
S1: music personal, contextual and infinite. Really cool little idea. So
S1: it's not like there's not like the music. Everyone has
S1: their own world of music. Isn't that cool? That's a
S1: cool idea. Claudia is a desktop companion for cloud code.
S1: Haven't messed with this command line person, as everyone knows. Uh, which,
S1: by the way, I was trying to convey there that
S1: I'm awesome. Even though I just said I'm a command
S1: line person, I was actually trying to convey that I'm awesome.
S1: And you should be awesome too. And use the command
S1: line context seven brings always fresh documentation to AI coding
S1: assistance via MCP. This is cool. Okay, so this is
S1: an MCP you put in your AI system and what
S1: it does is it will go get the current documentation.
S1: So if you're like hey, build me a new website
S1: or build me a website. It will go and get
S1: just without even asking. Go and get the latest Shadchan documentation, um,
S1: before it starts doing the design phase using your specs.
S1: So it won't just start building using its current model knowledge.
S1: It keeps it updated based on what you mentioned. So
S1: if you mention MVP, it'll go read the latest MVP stuff.
S1: If you mention cloud code it'll go read all the
S1: cloud code docs. Really really cool. Amsterdam's Ritman Library puts
S1: 2178 rare occult books online for free agent auto updates
S1: to jobs or auto applies to jobs for for free. Um,
S1: I haven't used one of these, but, um, I'd like
S1: to make one and give it to my friends. That's
S1: what I would like to do. Holy crap. That's a
S1: project I need to do. Why have I not done that? Okay.
S1: Hold on. Writing this down. Oh, then I'm going to
S1: put a stripe page on it and sell it. Um,
S1: but not for my friends. Okay. Make, um, automated. Sorry.
S1: Doing this live. Make automated job agent or. Oh. See that? See?
S1: Watch this. What what what did I actually say? What
S1: I said was I was making an agent for friends.
S1: What am I actually conveying? Um. Oh, this guy makes
S1: stuff for his friends and gives it to him for
S1: free because he's a nice guy. I am absolutely sure
S1: I was subconsciously sending that. Um, I'm also consciously sending
S1: that all the time, so I don't mind that it's
S1: unconsciously being sent, but there are cases where I'm unconsciously
S1: sending something that I don't want to be consciously sending. Uh,
S1: let's see here. Oh, whisper. Oh, whisper makes local text
S1: to speech as simple as. Oh, llama. This is a
S1: pretty cool little project. Uh, generated EDM is getting really good,
S1: so I went and made some EDM. I'm telling you,
S1: you can make fun of EDM for this, but, like,
S1: it's starting to sound pretty good. Same with rap songs. Um. Oh,
S1: metal songs too. Oh my goodness. I've heard some metal
S1: songs actually. Chad. My buddy Chad made one for my
S1: character that I just made in this one game. It's
S1: one D&D game we play on Fridays, and, uh. It's,
S1: I mean, it was themed to my character and the
S1: character concepts. I think he used Suno to make it,
S1: and it was a song. What I sent back to
S1: him in the text was I would go see these
S1: people live. I would seriously go and see these people live.
S1: Of course, there is no these people because he made
S1: the song in like, you know, 14 seconds using Suno. Um,
S1: insane insane world. I tools spawn equal and opposite I tools.
S1: This is Joan Westerberg. She is just killing it. Absolutely
S1: killing it with the essays, like every single one, is good.
S1: Shadow AI agents are creating the same security chaos as
S1: early Wi-Fi adoption. That's another cool analogy I really like.
S1: We've replaced anxiety with apathy as our defense mechanism. This
S1: is another one from Westerberg. 70 kids jumped bikes over
S1: each other constantly. That was me. Um, and there's pictures
S1: in there and they look very familiar. Actually, a lot
S1: of the kids look exactly like me. Uh, I Automation
S1: specialist post job search on Reddit. That was a cool
S1: one to check out. Recommendation of the week. Think about
S1: the distance between your thinking, speaking and writing versus your feeling.
S1: Speaking and writing. Have someone read. Basically, have someone read
S1: some of your stuff where you think you're going to
S1: get an unexpected reaction and see what they hear or
S1: see when they read it. So what were you saying
S1: without you knowing you were saying it? And you'll have
S1: to do this with like a very smart friend who's
S1: also very honest. And then if you find a big gap,
S1: try to work on making sure that your verbal words
S1: are the same as your emotional words in the receiver.
S1: ISM of the week. The first principle is that you
S1: must not fool yourself and you are the easiest person
S1: to fool. First principle is that you must not fool
S1: yourself and you are the easiest person to fool. Richard Feynman.