Latest / TFTC: A Bitcoin Podcast / #721: The Human Skills That Matter Now That AI Can Code with Calle

Transcript

#721: The Human Skills That Matter Now That AI Can Code with Calle · TFTC: A Bitcoin Podcast

0:00
Calais, it's been a year and a month almost exactly to the date since we published our last podcast where we met in person in the jungle.
0:10
And a lot has happened since then.
0:11
How have you been, sir?
0:13
Oh, yeah.
0:14
I've been doing great.
0:16
And wow, that's been over a year.
0:19
That's crazy.
0:21
I wish we were in the jungle again, though.
0:24
I've been looking out at 20 inches of snow.
0:27
the jungle is much preferred to this but for anybody who's listening who didn't catch that
0:33
first episode doesn't know who cali is i'd be surprised if you don't cali is one of the
0:38
most prolific and active individual builders in the bitcoin and freedom tech ecosystem
0:43
working on bitcoin the cash you e-cash protocol bitchat claw eye ai and other open source dev
0:54
projects. You've got a PhD in physics.
0:58
And I mean, I've been following the sparse
1:01
podcasts you've been doing throughout the year. I think you were on Citadel Dispatch
1:05
the summer of last year, and you were talking about this proliferation
1:09
of AI tools and how Vibe Coding helps you build the Android app
1:13
for BitChat. That has blown up. We'll talk about BitChat, but I think
1:16
focusing in on what's happening now
1:20
with claw eye ai and basically you launching agents to help you do your work you tweeted
1:28
yesterday about a devops engineer that you launched that would typically cost two hundred
1:33
thousand dollars but you have it running autonomously 24 7 what uh what's going on
1:39
yeah i i i don't know what's going on that the i i strongly believe that no one does
1:46
where we're heading and it really feels like everything that we're doing right now is something
1:53
that hasn't been done before so we are like 100 in discovery or in a discovery mode or in a pioneer
2:03
mode where you know any new idea on the table is basically is is is probably the first time that
2:11
someone tries it out. As you made some examples, I've been focusing a lot on AI agents recently,
2:20
particularly focusing on OpenClaw, and I like it a lot and try to make it as useful as possible
2:26
and try to figure out ways how to integrate it into the projects that I'm working on to be more
2:32
effective, more cost-effective, and faster, ship more and higher quality code. But we'll be talking
2:40
about that i'm sure in this part in more detail yeah i think i mean just dive into like how
2:50
prolific this is for you somebody who actually understands like i was saying just before we hit
2:57
record i'm having some sleepless nights pushing my open claw agent uh to the edges and i barely
3:05
know what I'm doing from the systems admin back in engineering programming perspective at all and I
3:12
can't imagine what it's like for you um and in terms of like productivity wise and what you're
3:21
able to do what's what um how profound has it been for you well everything has completely changed and
3:28
I would have never thought that I would be able to say that in my uh like programmer career so
3:33
So like many people, I've been programming for decades at this point.
3:37
So I consider myself a professional developer with lots of experience.
3:43
And probably everyone has noticed by now that the work of being a programmer has flipped by like 180 degrees.
3:55
It has changed in a way that no one would have predicted even only two years ago maybe.
4:00
So in the last one or two years, maybe we'll start a little earlier.
4:06
So the way I see this in my mind is we have multiple stages of innovation in AI with regard to LLMs and agents.
4:16
So level one was using an LLM in a browser, chat GPT.
4:21
That was the most pivotal moment in AI history, so to speak, when you think about how actual normal people interface and interact with AI.
4:32
That was the biggest moment.
4:34
And I think also up to date, comparing to the penetration speed of other technologies, it has been the fastest growing and fastest adopted technology in history was ChatGPT.
4:47
So it has conquered the entire world.
4:50
That's level one.
4:51
you open a browser, you ask a question, you get a response.
4:54
And we've been doing that for a year or two.
4:58
And also programmers started noticing quite fast
5:02
that you can copy code from your code base
5:05
and put it into a chat GPT, ask a few questions,
5:08
get some code back and put it back into your code base.
5:10
So there were many manual steps still involved
5:14
when doing development work using AI.
5:17
And so after level one, we reached level two around maybe one and a half years ago, which is the introduction of agents.
5:29
And agents finally gave the LLMs that were previously confined in the browser, gave them kind of legs and arms to act on your computer.
5:41
So that is, for example, Cloud Code is probably the most popular one.
5:46
And then there's codecs and so on from OpenAI.
5:51
What I use the most is OpenCode, which is a LLM agnostic framework, fully open source, really high quality projects.
5:59
So that is most of the code that I write today goes through these tools.
6:06
So and now I'm talking to other software engineers all the time about this.
6:12
And it's very fascinating to see what people think about this and how they perceive their job changing over time.
6:22
And you have a small portion, what feels like 10 to 20% of developers resisting the change and they don't like AI and they think it's fallible and it's not as good as they are.
6:35
And then you have this way larger percentage of developers who use it and try to increase their productivity.
6:45
And what I see is, you know, those who value the manual aspect of coding, and I compare them to artisms.
6:54
So people who take pride in having done the work themselves and also enjoy the process of doing so and see some mastery in it or try to perfect their mastery and skills in it have a harder time giving up the job to an AI.
7:13
Whereas, and then there is kind of like the opposite of that is prolific coders who've been in the business for decades at this point, who noticed that they can increase their output by, and I'm not exaggerating when I'm saying like 5 to 10x, which is, you know, if you are confronted with an efficiency boost of 5 to 10x, then it's really, really hard to say no.
7:40
And the only good reason that remains to say no is extreme safety.
7:47
So you're dealing with Bitcoin, for example, and you're not going to have a machine just write all the code for you that deals with money.
7:55
Or you're in an industrial sector where it's the critical infrastructure or something like that where you need the human in the loop.
8:06
and or those who really want to perfect their art.
8:12
So there's still some extremely good,
8:15
a very tiny number of human workers,
8:18
coders who can't be matched by the AI
8:21
and they are getting paid large sums of money these days
8:26
to be like the one big expert in COBOL
8:30
or something like that working in the companies.
8:32
But for the rest, you know, the adoption of agents has led to an incredible output boost and productivity boost.
8:45
And so that's what I've been focusing on for the last year and a half or two, which is like, how can I make use of these tools to improve all of these projects that I'm working on a lot, you know, a lot faster and also help all my peers to also get on that train.
9:02
and basically making sure that anyone in our cashier ecosystem uses AI tools
9:09
and realizes that if you're a software developer today and you're not using AI,
9:15
I'm willing to put money on the table that you will lose your job in five years.
9:19
Like you won't have a job in five years.
9:21
I am 99% sure that this is what's going to happen to most people
9:26
if they don't adopt this technology.
9:30
And the economic realities will force you to do so.
9:32
So that is level two. It has changed the industry completely, which, again, is something that I never have thought that I would experience this.
9:44
And level three. Now, this is the level that we are currently in.
9:48
This is the next evolution of AI agents are these proactive, always on running agents, personal AI agents that have a memory and the context about you that run either on your own home computer all the time or on a server somewhere in the cloud all the time.
10:09
you're the only one who has access to that one computer and the agent has its own computer can
10:16
do anything on that computer and with that power and with a loop that closes kind of like tells the
10:22
agent to work around the clock and with all these ingredients combined we've seen what the future
10:31
of personalized AI agents will look like a couple weeks ago when you know open call blew up and when
10:38
When I first discovered OpenCall, I had, like we're talking about this before the recording,
10:44
as you said, almost like two or three sleepless nights, just trying to process what this means.
10:49
Because when you try technology for the first time and then you get this intuition that,
10:56
oh my God, like this is so powerful.
10:59
Everyone will have this in one year.
11:02
This will be everywhere in one year because it's too powerful.
11:05
It's like this ChatGPT moment again, I think, where the first moment you tried ChatGPT, you were like, sure, this is so significant that there is no way this won't penetrate everywhere.
11:20
This is how I felt again with the latest iteration of level three autonomous AI agents.
11:27
And yeah, that's been on my mind a lot lately.
11:30
yeah and what would you say to people because i've um been using open claw for like i was i'm an og
11:39
i was using it when it was clawed bot and i had to set it up uh in the cloud via cli i didn't have
11:45
is it clawy or claw i.ai i call it clawy clawy i didn't have clawy i didn't have like one click
11:52
deploy so i set it up like a like a caveman in a vps and i've been using and i've similarly had
11:59
this like holy crap this is so powerful everybody's going to be using this eventually but there there
12:04
are naysayers out there like it it's like cloud code like i've been using cloud code and cloud
12:08
co-work and it's the exact same from what i understand um what are the differences and what is
12:14
the difference between just using cloud code or cloud co-work um uh sort of in in a silo versus
12:22
is creating an open claw and giving it access to cloud code.
12:28
And the way I understand is open claw is like a harness
12:31
that really adds a bunch of power to cloud code
12:35
and other models for that matter.
12:38
Yeah, so we definitely have to differentiate
12:40
between kind of like what's the LLM
12:42
and that can be cloud, sonnet or opus or GPT
12:47
or whatever it is, like the brain.
12:49
and then the body, which is the Claude Code CLI, for example, or OpenClaw.
12:57
So kind of where do you put that brain into?
12:59
And the biggest difference between the level two coding tools
13:03
and the level three personal agents is the loop.
13:08
Personal agents are alive all the time.
13:10
They don't care whether you leave your keyboard or not.
13:12
It's not meant to interact.
13:14
They're not meant to be interacted with using that one single keyboard that you have on your computer.
13:21
And when you close your computer, it's gone again.
13:24
But it's rather meant for something that is active all the time, can do something in the background,
13:31
and has memory about everything you've done so far.
13:35
And that is what OpenCore also does.
13:37
It has a persistent memory.
13:39
Sometimes it struggles with that memory, but it at least tries to remember everything that you've been doing.
13:44
You can talk to it like a normal person via chat.
13:47
So you usually interact with it with Signal, WhatsApp, Telegram, whatever you want.
13:53
And you can tell it to every day at 2 p.m., make a report about all the activity that's been going on in this GitHub repository, for example.
14:04
This is one of the many examples that we're using in our dev organization,
14:08
which is we have one of these queries that basically just tracks our progress on GitHub
14:14
and gives us daily reports about, hey, these are the new pull requests that were open.
14:20
These are the new issues that were open, sorted by Severity.
14:23
And these people are working on that.
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And there is no activity in this project.
14:27
So maybe you should look at it or something like that.
14:30
Having something like that that gives you automated responses every day, for example.
14:35
It could be every hour.
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It could be every week.
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Whatever you want.
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It could be news aggregation, research on the latest topics that you're interested in,
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or just something very banal and related to your personal life.
14:47
So there are clear differences in the capabilities between level two and level three.
14:53
I think, you know, it's very normal that there will be skeptics about, you know, what is this useful for?
15:00
I've seen many technologies come and also go where you always have the same thing.
15:05
and since we're so new
15:08
and so early with this technology
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basically the limit is your
15:13
imagination right now is if you
15:14
cannot think of a way how this can be useful
15:16
for you then think a little
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harder that's what I would suggest
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because I'm pretty sure everyone
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who deals with computers
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and that's everyone as something
15:26
that they don't like doing
15:28
themselves or they would
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like someone else to do it
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like in the background for them
15:34
and yeah so so you can probably come up with stuff yourself i'll just give you one uh one anecdote
15:40
of mine is you know i've been on a conference and using like uber or bolt or something like that for
15:47
for taxi rides so at the end of the conference i need to put all the invoices together for my
15:51
accountant so they can you know be properly accounted for and i hate that stuff like it's
15:56
it gives me anxiety just to think about that little task that i have to do after every single
16:01
conference is download all the pdfs from uber they're like have these weird file names and then
16:06
i need to go into every pdf take out the date and rename it and send it to my accountant like these
16:12
are like a couple of stupid steps that i need to do after every conference and this time i just
16:18
like downloaded 15 invoices as a pdfs and i dropped it over to my chloe over signal and i told it like
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hey you know just you know look into the pdfs extract the dates rename the file send them back
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to me. And I just could go on with my life. And three minutes later, I have received 15 PDFs back,
16:36
perfectly formatted in a way that I can just drop and forward to my accountant and I'm done with the
16:40
task. This is something very personal to me. No one would build a product just for that because
16:46
it's too specific, but we don't need to anymore. We have now machines that can do basically everything.
16:52
And that's just mind blowing. And another thing that I think is something that we're just getting
16:59
adjusted to is how we talk to computers. Something is fundamentally changing in how we interact with
17:05
computers. Because, you know, for example, just the experience of installing software until now,
17:11
it was either, you know, go to a browser, download a file, and then click on it, go through that,
17:17
set up, blah, blah, blah, and then you have a software. Or if you're a Linux person, you just,
17:22
you know, you do it over the terminal, you install it, and then it's there, and maybe you need to
17:27
configure it and then you can use it.
17:29
And lately, the way I've been installing most of the software
17:34
over for an AI agent is basically just taking the link to the GitHub or to the website of the thing that I want it to use I send it to Ling and say install this And I just turn around and do my thing
17:47
It comes back after two minutes and says, it's done.
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It's working.
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I've tested it.
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What do you want me to do with it?
17:53
And, you know, it's just, it's mind-blowing.
17:58
These basic interactions that hadn't changed for over, you know, for decades
18:05
Since the invention of the personal computer, everything has now changed.
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Every single person can now use basically everything through a language-based interface.
18:16
And I think that's amazing.
18:20
It opens so many new doors and helps so many new people to use software and be more productive humans.
18:29
yeah it's i mean it's become clear to me over the last six weeks the form factor with how we
18:35
interact with computers is changing right before eyes like voice to text voice to voice even
18:40
um is how i mean a month and a half ago i would use voice to text for some things
18:47
but really not much and now whenever i'm on my computer i'm hitting option spacebar and just
18:53
talking for five minutes and then sending sending that prompt or that conversation to to my agent
19:00
and then just doing these tasks and it's like we're projectionists now we can just think of
19:05
something we want in your example of the uber receipts for your accountant like i need that
19:10
you can just project it into reality which is insane
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and
19:17
you know it goes even
19:19
there's even
19:20
it goes even deeper I'll tell you
19:23
just a little story about
19:24
how I started
19:27
working on BitChat because
19:28
when I saw Jack
19:31
release BitChat
19:32
for iOS initially
19:34
I was like oh no this is
19:37
iOS I'm an Android guy
19:39
I would like this to exist for
19:41
Android why did he only build it
19:43
for iOS, right? And we're in times where you can just do it. But the thing is, I'm not an expert
19:49
on Android. I've never made a real Android app before. And I've been searching for experts in
19:57
several fields for so long. For example, we're working a lot with NFC these days for Cashew.
20:05
and try to find an Android expert
20:09
that also has experience with NFC.
20:14
You're looking for someone very specific
20:16
and even if you have the money to pay them,
20:20
it's super hard to find them.
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And even if you say like, okay, I'm going to learn it.
20:24
So you go out and search for documentation
20:27
and what you see is code from eight years ago
20:32
that hasn't been updated
20:34
or like super old documentation or PDFs that look like technical sheets
20:39
that you really don't like to read or you can't understand
20:44
or something like that.
20:45
It's like even for someone who has a good amount of skill in a certain field,
20:53
there are blockers that would have cost you either a lot of money
20:58
or time to find someone who can help you.
21:01
and now I can just talk to the machine and tell it like,
21:05
can you please explain to me how NFC on Android works?
21:08
It will figure everything out.
21:10
It's the best expert that you can think of
21:13
in several very specific domains
21:15
in the thing that you are good at already.
21:18
So it not only helps the uninitiated to raise the levels
21:25
and become more productive humans that can focus on their lives,
21:29
but also the ones that are really deep into their own profession helps them to, you know, broaden their scope and figure out things that they weren't able to figure out before.
21:42
It's truly mind-blowing.
21:44
And I had a discussion with Justin Moon a couple weeks ago about what this means for Freedom Tech.
21:51
And since you brought up BitChat, I think BitChat's the perfect example of something that's been accelerated via these AI tools and is a freedom tech project that found, I think it's safe to say, like mass adoption during the elections in Uganda, when they turned the Internet off in Iran, when they had the hurricane in Jamaica, people have been turning to BitChat, which you've been working on.
22:15
But I think talking about a broader topic, like how important are these AI tools for the proliferation of freedom tech generally?
22:26
And what does it mean for how we build these freedom tech apps moving forward?
22:32
Does it give you more hope that we can actually win this battle?
22:35
Yeah, 100%.
22:37
And interestingly, it's a human factor.
22:40
The answer is the human factor at the end of the day, because with AI, what effectively happens is that you increase the number of people who can reach a certain goal.
22:53
And previously, it was confined to a very small number of people.
22:56
You need like the Android, NFC, Bluetooth expert who has worked on some project five years ago.
23:04
And that's why he is the perfect person to build BitChat today, for example.
23:09
Right.
23:10
So the chance of this happening is just way lower.
23:14
But today, we're 100% at a point where you can build a solid and useful application with a single person who's motivated enough to actually pull it off.
23:29
So Jack has proven that.
23:31
He's basically said, I wanted to research how Mesh Networks works.
23:35
And he's built this incredible app.
23:36
or another example is OpenClaw itself.
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It was built by a single person.
23:43
It's unheard of.
23:44
It's impossible.
23:45
There's no way in the world one year ago
23:49
that this would have been possible.
23:51
And today, like only a year
23:53
or maybe two years into this technology,
23:55
we've already seen profound effect,
23:58
profound impact of highly motivated individuals
24:02
who are now able to execute.
24:04
I still think, you know,
24:06
it requires some upfront work from you as a human
24:11
because it's not like everything has now the same difficulty for everyone.
24:19
It definitely equalizes everything,
24:22
but still being an expert in a certain field,
24:24
knowing what the pain points are,
24:27
having all that context that you only gain through experience,
24:30
That is what makes you stand out in the sea of equal capabilities.
24:40
And I think that's the move forward, is figuring out who's motivated and less who's skilled.
24:50
It's more about you as a person, what are your goals and your ideals.
24:53
And if you're a person who's like a doer who doesn't sit there and wait until someone else does it, but you're motivated enough to do it, previously the biggest obstacle was skill. And today it's not anymore. And that's just, that's amazing. We can't even start to comprehend what it can change.
25:12
I believe that software is one of the most important driving factors in today's world.
25:17
How we, as humanity progress, we see this in mass adopted software and social media.
25:24
And so like all these things have a massive impact on the world today.
25:28
So, you know, one plus one equals two.
25:31
Give them the tools and they will build.
25:37
Well, it goes both ways too, right?
25:39
It's a double-edged sword because it can be used for good and bad.
25:44
And so how do you view that particular nature of this beast that we're working with?
25:50
Because it seems like we're in an arms race to avoid the digital panopticon
25:55
and ensure that we can leverage free and open source software tools
26:00
that preserve privacy, sovereignty, and the ability to operate outside the wall gardens.
26:06
I mean, I'm almost getting goosebumps thinking back to our previous conversation in the general now because we're kind of closing the loop and we talked about similar topics a year and a half ago.
26:20
But things were so different back then that it felt like, you know, and here's what I want to say actually about your question is the good usually comes from the many, whereas the bad comes from the few.
26:33
But the bad from the few usually has all the resources that they need to build a centralized social media platform that conquers the entire world.
26:43
So although everyone has improved their skills, I think it's vastly disproportional in how much it has helped the many.
26:53
We are way more people who want to see good in the world than those who want to see bad in the world.
27:01
And we as the mass of people have increased our ability disproportionately more than the large mega corporations who can also now use Vibe coding.
27:12
All right. Okay. You can use Vibe coding now too.
27:15
But they were able to do anything that they want anyway because of a large amount of resources.
27:21
But this technological shift has benefited especially those with smaller resources or smaller teams and individuals.
27:32
And so my hope, I'm very hopeful because I know that there are more good people than bad people in the world.
27:40
And those good people now have way more tools to express themselves, to actually change the world, and to show us their vision of the world and inspire others.
27:54
So I'm way more optimistic in that regard than one and a half years ago because we have now the way more powerful weapons that we can use to fight against surveillance or repression and the digital panopticum, as you call it.
28:17
Yeah, I completely agree.
28:19
And to your point about just figuring out what your skill is, what you're good at.
28:23
For example, like when I view my contribution to to this space is just the ability to observe and curate.
28:32
And so that's what I've been using my agent to do is just that the media company is observe and curate.
28:38
So I have it running all these prong jobs to surface information that I think people aren't getting enough exposure to.
28:46
And then I can then curate that and put it in a podcast or a newsletter or share it on social media.
28:55
And it's been incredibly impactful.
28:57
Like the amount of sort of output that we've been able to push out over the last couple of months has increased, I think, at least five, maybe 10x just because we have these tools available.
29:11
And so now when I'm thinking of TFTC, it's like, OK, I want a CBS, NBC, CNN, Fox News, but for Freedom Tech and sort of economic economic storylines that people aren't getting in the mainstream.
29:27
And I think it's it's I think it's successful.
29:32
We're like two weeks into this five day a week newsletter that we've been putting out with the help of our agent.
29:38
and I've gotten a ton of responses like, hey, I love the mix of content.
29:42
I haven't heard these stories.
29:43
And so that's been a signal to me like, okay, these tools are working for my particular niche in the media world.
29:50
And I think on that note, it took me like a few weeks to really like download a CloudBot,
29:57
started working with it, and it took me like a week or two of understanding how its memory works
30:02
and basically what it could do, pushing it to its limits, exploring the territory which it operates in,
30:08
where after a week and a half, two weeks,
30:11
I was like, okay, here's how I can use this.
30:14
But it took experimentation.
30:17
The point I bring this up is to ask you,
30:19
in terms of practical first steps
30:22
for anybody listening to this
30:24
who isn't experimenting with these technologies,
30:26
how do you think they should approach using this stuff?
30:31
I want to start with especially the security aspect first.
30:35
So you should be aware that using agents on your computer or with your personal accounts can go terribly wrong.
30:46
So that is something, you know, that's the first thing you could think about.
30:50
We're not at a place yet where, you know, some highly polished experience exists made by a large company or something that is fully safe to use.
31:02
And to be honest, I also don't think that that will happen anytime, you know, very soon, at least not very soon, because his agents are just too kind of powerful to put them in a box yet.
31:15
So first, what you do is you set it up.
31:20
You can set it up on your own machine.
31:21
Sorry, on a separate machine.
31:23
Let's say a Mac mini is the trend.
31:25
Or you can also use a service that runs it for you.
31:28
and one of them is Chloe, C-L-A-W-I.ai.
31:35
And the process is basically super simple to set up an agent.
31:40
You make a subscription, you pay for it monthly,
31:42
and there is like AI credits included,
31:45
and off you go, and then it starts.
31:48
And the next step is to connect it to one of your messengers
31:52
that you want to use in order to interact with it.
31:54
So then you're set up, and you have your own personal agent
31:57
that you can ask questions about.
32:00
And what I do is think about things
32:05
that I wish I had someone,
32:07
like my own personal human agent,
32:10
basically do things for me.
32:12
So one of them could be accounting bookkeeping,
32:14
for example, that's one thing.
32:16
But in Kesha, we run a large organization.
32:20
As I said, we need to basically have something
32:22
that can observe progress.
32:25
That is also something that many people use.
32:27
is having a bot that just observes things and writes reports on it.
32:32
And in your case, it can be news, for example.
32:35
And in my case, it's pull requests and issues on GitHub, for example.
32:39
And lately, what we've been experimenting, especially with Chloe,
32:44
in order to make our operation more efficient,
32:47
is to pick off kind of jobs that we would have hired someone for,
32:53
where we can carve out some specific aspect
32:56
where we think this is safe and nothing can go wrong there
33:00
if you automate this part, for example, observing something
33:03
and then build like a dedicated bot just with those skills.
33:09
And in the case of Chloe, we run our infrastructure
33:13
on a system called Kubernetes.
33:15
It's a fairly common advanced provisioning system
33:19
where the cloud basically is Kubernetes.
33:22
and you have experts for that.
33:27
Obviously, there's people who know Kubernetes in and out
33:30
and you can pay them to do a certain job for you.
33:34
But you also know we have these agents
33:37
that know Kubernetes really, really well as well.
33:39
So if you plug in a relatively good LLM into it,
33:44
say you use Sonnet 4.6 or even Opus or something,
33:50
You kind of get to a better than junior person in that specific job that just works for you 24-7.
33:59
And that's what we've been doing.
34:01
So we have this DevOps agent that lives in a Signal chat with us.
34:08
And I can ask the bot in real human language, hey, how's everything looking?
34:14
Are there any problems with our cluster?
34:16
and then it'll say, yeah, there are like two people whose agents have crashed
34:22
and they haven't come back for like five hours.
34:24
Maybe you should look at them and just gives me further hints to any problems
34:29
that might have come while I was doing something else.
34:31
So this is for our operation.
34:34
It's extremely useful already today.
34:37
And I'm just thinking about, let's say you run a factory, right?
34:40
So you have a factory with all sorts of sensors and monitoring and reporting
34:46
and all of that needs to be observed.
34:48
Like a human needs to sit there
34:49
and look at that data basically to make use of it.
34:52
And what we've been doing so far before AI
34:54
is like dashboards.
34:55
That's the way we typically try to condense information
34:59
so it's useful for us as humans.
35:02
But today, I mean, you can still do the dashboard.
35:04
It's no problem.
35:05
But you can also just plug an agent into that system
35:08
that can read the raw data.
35:10
And it will probably come up with like even better ways
35:12
to look at the data and report anything
35:15
that is out of the ordinary for you.
35:17
So just this one little thing and again we just talking about one thing that it can do that it was not particularly designed to do but it does exceptionally well Just this one thing is by itself already huge
35:32
Imagine what it means for the industry, well, the industry producing physical goods in real factories,
35:39
what it means to have agents plugged in into their system that can observe everything 24-7 all the time.
35:45
and that costs basically no money.
35:48
I mean, you pay for the LLM,
35:49
but the difference between a human doing that job
35:53
and the bot doing that job is basically no money.
35:56
So if I can think of like two or three ways
35:59
how this can be extremely useful for me,
36:01
I know there must be millions of ways
36:04
for millions and billions of people
36:06
how they can make it useful for them as well.
36:09
And the nice thing about these agents
36:11
is we don't need to know before what they're going to do
36:15
because they're general purpose machines.
36:17
They can probably do way more than we think that they will.
36:21
And they will continue improving in the coming months and years
36:25
and will be just like mind blown for the next couple of years.
36:28
I'm pretty sure about that.
36:30
Yeah, that's the crazy thing to realize is how this thing is pretty good right now,
36:35
but it's probably the worst it's going to be.
36:38
100%.
36:38
It's going to get faster and better at doing what it's doing.
36:41
and just from a software engineering perspective,
36:45
if you go back to level two,
36:46
the agent then writes code for you in your computer.
36:49
Right now the flow is you enter a prompt
36:51
and then you wait a couple of minutes
36:53
and then you observe what the agent has produced.
36:56
That loop will become like 100 milliseconds at some point.
37:00
You will just enter it and press enter
37:02
and it will be there instantly for you to observe.
37:05
And if you don't like it,
37:06
you can just redo everything instantly as well.
37:08
So just the flow of talking to the thing and getting something back, all that is going to compress a lot in the next coming years.
37:17
And even just the speed aspect, just the performance aspect itself will open, unlock new ways of working with it again.
37:25
Yeah, I guess I'm diving into particulars of building products with it, whether it's the Cachew Protocol, BitChat, Klawi.ai using the AI to build that service, now Numopay.
37:44
So it seems like you've been shipping at an increased clip, just observing publicly.
37:50
And I'm assuming that you're using all these tools to do that.
37:54
I think it's a safe assumption.
37:56
I guess let's just talk about some of the things,
37:59
particularly at the intersection of Bitcoin and eCash with the Cashew Protocol,
38:04
what you've been able to ship that's been on your mind for many years, I'm sure.
38:09
Yeah, so I just hinted towards NFC.
38:13
NFC is something that I've been researching for years at this point.
38:16
And I'm very jealous about the fiat world in that sense,
38:23
that tap to pay is just an incredible user experience and everyone loves it people use it
38:29
all the time everywhere globally i remember a conversation i had with miles miles suitor from
38:34
from cash app where we were talking about uh bitcoin adoption around the world and how we can
38:39
improve ux for bitcoin payments and he told me the story that doesn't leave my mind anymore which is
38:45
is somewhere in peru in some like distant uh isolated mountain somewhere and he finds his little
38:52
shack that sells him a Coke.
38:55
And in this mountain somewhere in the nowhere, the person hands him over a POS device and
39:02
she takes his iPhone and she taps it and it makes beep and it takes like three seconds
39:07
and the payment is done.
39:08
And he said, that thing made him more bearish than anything else with regard to Bitcoin.
39:16
And that just resonated completely with me because that is what makes me bearish about
39:21
Bitcoin as well is the user experience. Because if fiat feels so good, like why do you even need
39:28
Bitcoin? That's what many people think, how many people think. So obviously we need to get better
39:33
in Bitcoin and offer at least the same experience, the quality of experience or better. And I think
39:40
we can do better because we're an open source system and we can, you know, where improvements
39:46
of one thing help also the other thing.
39:49
We don't need to compete.
39:50
We can also collaborate.
39:52
And that's what we're doing with open protocols.
39:54
And that's the whole idea about Bitcoin, basically,
39:57
is just we all work on the same thing.
39:59
So NFC, I think, is a vital part.
40:03
Tap to pay just works.
40:04
Everyone loves it.
40:05
And in order to build that,
40:08
I needed to get all this expert knowledge,
40:11
which I wasn't able to obtain over the years.
40:13
And I said, like, I was actively looking for people who can help me, but found no one and so forth.
40:19
Until at some point, I think this started all more than a year ago again with a little project I called NSC Chat.
40:28
And that is kind of a, if I think back, it's kind of like a precursor of BitChat.
40:34
Because it's like BitChat, but with way less radius distance.
40:38
It's just a simple chat app that you run on your phone and you write a message.
40:42
and you have to tap the other phone in order for the message to go wrong,
40:46
one phone to the other.
40:47
So it's like a very stupid, simple chat app
40:50
where you need to touch the phones in order to send the message.
40:52
And I built that as a step towards kind of NFC payments
40:57
because with Cashew,
40:59
and that's the Charmin eCash protocol that I'm working on,
41:02
money can be sent as a bearer asset, bearer token.
41:05
So that means like if you can package it in some kind of a data package
41:09
and you can send it over and there could be,
41:11
you know, email or telegram or SMS or whatever it is, any communication channel, you can make a payment.
41:19
So I wanted to see Bitcoin payments happening with tap to pay using Cashew by sending the e-cash token from one phone to another.
41:28
And that was the first proof of concept I was able to only achieve because of AI.
41:32
So I thought like, that's neat. Awesome. That's great.
41:34
So this is exactly like these are the building blocks that I was looking for for so long.
41:38
We have Cashew as a protocol that we can build on that runs on Bitcoin and with this incredible property that if you can send data, you can also send money.
41:52
So that's what Cashew enables us.
41:55
And at the same time, I just should clarify, if we deal with money, for example, the core libraries of Cashew, they're all handwritten.
42:03
because we're not at a point yet where I can safely just say
42:08
that the agent does a better job than I do in figuring out what could go wrong
42:13
or how you could lose money and so on.
42:15
So that's very important to us is the critical parts are
42:18
handwritten, normal programmed libraries,
42:22
and that's what usually a casual library is.
42:25
But once you have that, once it's running, once it works,
42:28
then you can build all the scaffolding around it, pipe coding.
42:31
Like there's nothing that can go wrong basically because the library itself works.
42:35
You know that you won't lose e-cash.
42:38
So now let's build an app around it.
42:41
So we started with this NFC chat, sending around e-cash tokens and then showing like, okay, this is possible.
42:46
And then this ultimately ended, like culminated in something, in a project we call Numo.
42:52
We've been working on this for a couple of months at this point in stealth mode.
42:58
We haven't announced it to anyone until like yesterday.
43:00
and Numo is our approach to introduce tab to pay to Bitcoin using eCash.
43:08
Because with eCash, it has this very simple flow of data flowing from one phone, the payer, to the receiver, the POS device.
43:17
So Numo runs on a normal Android POS.
43:21
I have one here, I control it, for example.
43:23
This is a standard POS that runs Android.
43:26
But it can also be any Android device, any Android phone.
43:30
So it needs to be an Android phone because iOS doesn't allow you to use the NFC chip in that way.
43:38
So the POS device itself, of the merchant, runs Numo.
43:42
And then any other phone, and now this can be iOS or Android, doesn't matter, can basically just tap to pay to it.
43:48
And if it runs a cash audit, then the cash audit will see that there's an NFC chip and then take the token and send it over to the POS.
43:57
And why is this cool?
43:58
because, first of all, it's using eCash generally.
44:04
Cash-to-us privacy inherits this incredible privacy by default.
44:09
So while the UX is amazing, you also have the best privacy possible,
44:15
which is a great combination.
44:17
Usually you have a trade-off there.
44:19
And the next best thing is that it works offline.
44:24
So as a payer, so the device paying at the POS, could be your iPhone, your Android, doesn't need internet to make that actual payment because all you're doing is you take e-cash from your wallet and you set it over NFC without touching the internet.
44:39
So that also gives you incredible privacy, obviously, because you're not even online.
44:43
But it also means that it just works everywhere.
44:46
And that's, again, one point that fiat payments already have been doing for years.
44:51
If you do tap to pay with your credit card or if you do tap to pay with your phone, it also works while you're offline because your phone doesn't talk to the Internet.
44:59
It kind of hands something like a token from the phone to the POS device in fiat land.
45:05
And so we're doing now the same in Bitcoin land, but with incredible privacy and open protocol.
45:11
And so the way it works today is you can install Numo on your Android device or on your POS device.
45:17
It can be any generic POS device.
45:21
and you can set up a cashew mint.
45:23
So cashew is a custodial system.
45:25
You need to trust the mint operator
45:27
with the Bitcoin that you receive.
45:29
So you set up one or more mints
45:32
and then any payer from any mint,
45:35
it can be like even if we don't share that mint,
45:37
you can still pay with the eCash to the device
45:40
and then the device will take that eCash
45:42
and withdraw with Lightning to their mint.
45:45
So anything, all the mints are still interoperable
45:48
because we have Lightning that glues everything together.
45:50
and you can receive payments from basically any Mint out there.
45:55
And we've built a cool feature into Numu,
45:58
obviously realizing, recognizing that it's custodial.
46:01
There is a rug risk associated with the Mint that you're using.
46:05
So you should only be using Mints that you trust already.
46:09
But in Numu, there is a very simple way to say that
46:12
if we ever reach 50,000 Satoshis, for example,
46:16
you can enter a Lightning address there
46:17
and it will just automatically withdraw to that Lightning address
46:20
whenever you reach the threshold.
46:22
So that way, you can build this POS in a way that the maximum amount
46:27
that you put in custodial risk can be very limited.
46:32
And so you can also withdraw every single payment if you like,
46:36
but for very small payments, it might not make sense.
46:41
So we've just released this yesterday.
46:43
You can find it on numopay.org.
46:47
download it, check it out, and we'll be working on a BTC Pay integration soon.
46:54
We've already started working with that, so it also worked with existing BTC Pay server infrastructure.
47:00
But if you don't want that, you can just download the Numero app itself.
47:05
It doesn't need any backend. There is nothing that you need to install or set up.
47:09
Just install the app, choose a mint, and you're done. So check it out.
47:13
yeah i mean i completely agree i remember miles telling me that same story too
47:17
i think the offline nature of the the ability to send cashew which should be e-cash via the
47:25
protocol offline is massive because you think miles in that mountain in peru like his cell
47:31
phone probably didn't have service but the secure enclave had his credentials for his card and then
47:36
he was just able to send it to the pos and make the payment probably offline i'm assuming um and
47:42
now we have feature parity via via eCash now.
47:47
And I guess what do you want to see in terms of like what or what do you what do we need
47:55
to see for this to become more prominent as a wallet sort of integration of the NFC standards?
48:01
Is it proliferation of just simply more eCash wallets?
48:06
What wallets work with it now?
48:07
Like Macadamia, I'm pretty sure I could use Macadamia on iOS.
48:10
And just to clarify, for the iOS stuff, you can pay with iOS, but running the POS to receive via NFC is something that you can't do.
48:20
That's right. Exactly. To receive, you need an Android phone, but paying, you can do it with any phone.
48:25
So, yeah, as I said, Macadamia, but they're already, we've worked in the background and we've added this NFC capability to around like six or seven different casual wallets at this point.
48:36
Most of the popular cash wallets already support this from day one.
48:42
And Numo also supports bare Lightning.
48:46
So you don't need to have a cash wallet in order to use Numo.
48:49
Obviously, that would limit the number of people who can pay with that terminal.
48:54
So it supports Lightning just out of the box as well.
48:58
And you can use any Lightning wallets to scan the QR code.
49:02
And some Lightning wallets, particularly Phoenix, can also use Tab to pay for Lightning.
49:10
So it will kind of fetch the Lightning invoice via NFC and then pay that over the Internet.
49:14
So it is compatible with all the wallet infrastructure out there.
49:18
But generally, the thing that limits growth in Bitcoin today is the utility, not the utility, but I want to say the penetration of Bitcoin.
49:31
itself. So I'm very well aware of the fact that our technology can only grow as fast as Bitcoin
49:40
can grow. And when I say grow Bitcoin, I mean people using Bitcoin, not the price going up.
49:46
So our ultimate goal with Numo is to further Bitcoin as money. That's our main North Star
49:54
goal for everything that we do, is to support the adoption of Bitcoin for everyday payments
50:00
around the world.
50:02
So the infrastructure for that is being built out,
50:06
and there are great projects out there.
50:08
For example, we've noted ETC Pay Server.
50:12
So anyone could already use some form of on-chain payment,
50:17
a Lightning payment with several existing solutions out there.
50:21
But I think what's most needed today is kind of a penetration
50:30
in real economic transactions.
50:34
And we need more merchants to use Bitcoin.
50:37
And I think that Cash App is doing an amazing job there.
50:41
I should say Square, to be more precise.
50:45
Square is doing an amazing job there.
50:47
There's BTC Map that you can use to find merchants.
50:51
There's obviously BTC Pay Server,
50:53
which is the most popular kind of web checkout system
50:57
that the Bitcoin ecosystem has produced.
51:01
And so all these projects help towards the same goal.
51:05
And we now support that effort as well using Numo and our NFC-capable payment systems that we built.
51:15
If you want to support this in your Bitcoin wallet, what you can do is, first of all, look at all the NFC specs that exist in Bitcoin.
51:24
You can read Lacking Invoices by NFC.
51:26
If your app doesn't support that yet, think about integrating that.
51:29
If you want truly the tap-to-pay offline instant experience that Cashew can give, then you can also just plug in a Cashew library into your Lightning wallet and pay with eCash for that single step.
51:45
It doesn't even need to be a full-fledged Cashew wallet.
51:48
You can just like that single one step that you want from Bitcoin to eCash.
51:54
You can also do that in order to support tap-to-pay.
51:57
So there are a couple of wallets working on that.
52:00
And generally speaking, I think as a community, as a bigger project than Bitcoin,
52:07
we need to help get Bitcoin more onto the radar of merchants
52:12
and hope and drive the adoption of real brick-and-mortar stores.
52:19
So that's what we want to contribute to.
52:23
I completely agree.
52:24
Thank you for your focus on this.
52:26
It's funny, too, because when we last recorded, I think I asked what your archetypal cashew user was.
52:33
And you said a woman in the jungle selling selling mangoes.
52:37
And I think I think we knew MoPay and projects like a BTC pay server.
52:43
I think that's going to proliferate.
52:46
Obviously, what Square is doing here in the United States for their merchants, I mean, merchant adoption, because of Square's rollout at the end of last year went literally parabolic.
52:55
I think there was something like 2 merchants on BTCMAP There probably more than them in the United States that haven put their store on BTC map But I think the way Square rolled it out and Cash App in collaboration
53:15
with them rolled it out, they automatically added all these merchants and went from like
53:18
2,500 to over 6,000 over the course of a month, which is great to see.
53:22
shifting gears back to this intersection of AI
53:27
in Bitcoin and particularly Casio
53:30
it's a big topic of discussion right now
53:33
particularly in our world and in the fintech world as well
53:37
is agents using payments on the network
53:41
excuse me, using payments with each other
53:45
to complete tasks on behalf of the humans
53:48
sending them out to do things
53:49
And I think it's a wide open landscape right now.
53:52
I think you have Visa, MasterCard working on their own protocols.
53:55
You have Stripe, then obviously you have stable coins, Bitcoin over Lightning.
53:59
I saw that the guys at ARK Labs launched the ability to receive stable coins and automatically
54:06
turn them into VTXOs via their ARK protocol implementation.
54:11
And then obviously we have eCash and CashU specifically with the NUT402 protocol.
54:17
and i think you've made the case that due to this sort of error nature of ecash and the fact that
54:24
you can send the file that it's actually um the most efficient way for agents to make payments is
54:30
that correct characterization yeah so that was just like from from our experience what instantly
54:36
worked it was extremely simple it was almost shockingly simple to teach an agent how to use
54:41
cashew because we basically told him you know here's your cli and the cli it will produce cashew
54:48
tokens and you take the token and do something with it depending on what you're doing and
54:53
instantly got that and because you don't have this get an address here check your balance there
54:59
send sign and send you have these packets of data that the agent can simply send in an htp request
55:06
for example so what today you know getting back to the original um question or the idea of 402
55:15
payments or 810 payments i think it's a very hot topic today we're still yet to see how much of
55:22
that sticks because we're in this like discovery mode of agents what should they do how much money
55:27
would you give them how dependable are they with the money that you give them and so on there are
55:34
stories out there of an agent like sending a random stranger 350k or something because he
55:40
begged him online and the agent made like a single mistake and the person who owns that agent lost a
55:46
substantial amount of money due to that uh because they were kind of you know trying at all i guess
55:53
so um how much of that really manifests we will see but it is clear that the the big ones and i
55:59
You mentioned the big fiat one, the big fiat monsters like MasterCard and Visa and also Stripe are looking into it.
56:07
What frustrated me a lot looking at this is that the 402 idea, the idea that we will have services online that ask for money.
56:18
So you want your machine to be able to pay another machine is a very Bitcoin driven topic, has been a Bitcoin driven topic in the last years.
56:27
for the last 10 years or so,
56:31
the only people who talked about this were Bitcoiners
56:33
because we always thought of ourselves
56:37
and still think of ourselves as the native currency of the Internet.
56:40
So obviously the connection there is pretty direct.
56:44
And there's been development from Lightning Labs on L402.
56:50
We've been contributing to 402 with X402 and cash payments.
56:55
The Albi guys have been working on this as well.
56:57
So it was kind of only this niche topic until the agent came a couple months ago.
57:04
And then you saw Coinbase working on it, Stripe working on it, the credit card providers working on it, because they all seem to agree that payments of machines to machines will be a thing.
57:17
And the rails that they market or want to see being used are usually stablecoins.
57:25
And stablecoins have the benefit of feeling more natural to people, I think.
57:35
I think the cognitive leap to use a stablecoin is way smaller than the cognitive leap to use Bitcoin.
57:44
Because the stablecoin is denominated in the same currency that you already use.
57:48
So it feels like you're still just doing the same thing, but now in a kind of a digital way or something.
57:53
So the stablecoin people have been pushing really hard to make sure that the agents of the future will use USDC or USDT or whatever it is.
58:05
Obviously, I don't want to see that future happening because I think it destroys the fiat system and stablecoins are inherently trust-based.
58:16
And there's all sorts of problems with that.
58:21
You need KYC to get in and out and all these problems with civil coins that Bitcoin doesn't have.
58:27
Bitcoin just is born on the Internet and lives on the Internet and doesn't leave the Internet.
58:31
It stays inside the Internet.
58:33
And so that's why Bitcoin is still the native currency of the Internet.
58:38
And civil projects in the Bitcoin space have been trying to, you know, also rival this new trend
58:44
and make sure at least that we're up there with the others
58:49
and can show that we show up and that we are ready to compete with them.
58:59
And one example is the art protocol that I think is a fantastic idea to use.
59:05
I checked it out already and it works really well.
59:08
And another way of doing it for even smaller transactions
59:12
and high frequency transactions.
59:15
Cache is just amazing for it
59:16
because it's basically instant,
59:18
basically free and with insane privacy.
59:22
All of these factors, I think,
59:23
are super important,
59:25
especially in an agentic world.
59:27
So eCache is just something
59:30
that works really, really well with agents.
59:35
Yeah, and particularly in a world
59:36
where the subject of ID verification
59:39
on the internet is becoming more prominent.
59:42
I think the ability to opt out and have these internet-native options
59:48
that don't require KYC at the edges like stablecoins are imperative
59:53
because it seems like the digital ID conversation
59:55
is definitely beginning to pick up again.
59:59
Every stablecoin is permissioned.
1:00:00
All of them can be turned off if they don't like your digital ID.
1:00:05
Yeah.
1:00:07
I want to be respectful of your time because I know I pinged you
1:00:09
in the afternoon yesterday to do this.
1:00:12
And you were gracious enough to do this last minute, but to end it, love getting philosophical with you.
1:00:19
Last year when we spoke, I really dove into how you view yourself as an artist in the digital world.
1:00:25
And I think what you've done since then has proven that to be true.
1:00:29
But thinking about the proliferation of these AI tools and humans beginning to interact with these at an accelerating pace.
1:00:38
What are your hopes for the future?
1:00:39
Obviously, the meme of the permanent underclasses here, the meme of the singularity and Skynet having been launched already and will only recognize it in retrospect is beginning to permeate.
1:00:50
What is your view for how these tools affect our humanity?
1:00:56
Oh, that's a that's a big one.
1:00:57
Because so first I'll start with my craft.
1:01:02
And I hinted towards this already in the beginning of our conversation today.
1:01:06
But it's been amazing to watch how things can change in a way and in a pace that no one would have predicted.
1:01:14
the penetration, the proliferation of AI in society
1:01:22
was always predicted to have the most negative influences
1:01:26
on the old kind of manual job markets
1:01:31
and the plumber and the robots will come
1:01:34
and everyone will lose their jobs and so on,
1:01:37
which I think is still a risk.
1:01:41
But I wouldn't have predicted myself
1:01:43
that programmers would be the ones who are affected first or even the most,
1:01:49
and I think probably will be the most.
1:01:52
So we are at a time, you know, zooming out,
1:01:56
that software engineers had this incredible run in the last decade or two
1:02:02
and made astronomical sums of money and still software engineering,
1:02:07
you know, the salaries associated with it,
1:02:10
kind of like still detached from rest of society.
1:02:14
So we have been seeing a decoupling of what you just maybe called
1:02:21
the permanent underclass and the Silicon Valley upper class.
1:02:27
But what I see is what's happening right now is changing that drastically.
1:02:34
And I think that's maybe for the better
1:02:36
because software engineering has never changed this fast before
1:02:41
and has become just way more accessible to many, many more people.
1:02:46
It's not this exclusive skill anymore that you have to acquire yourself
1:02:52
by decades and decades of working on your own
1:02:54
and acquiring all these special skills that you can then use to find a job, for example.
1:03:00
So every software engineer out there who still didn't get it, I just want to say it again, you will lose your job in five years, you're done if you're not using AI.
1:03:12
Like, I'm sure of this.
1:03:15
And I cannot say this about, like, another job category just yet.
1:03:21
So I think it's just a, let's say, let's see, it's ironic that today's, in today's world, the plumber and the carpenter and, you know, manual labor folks are, I think, more valuable than ever before.
1:03:41
and have more security about their jobs than ever before
1:03:46
relative to the rest of society.
1:03:50
But that is something to think about.
1:03:52
It's almost beautiful to see it happen this way.
1:03:57
And at the same time, getting a bit more philosophical on this is
1:04:01
when we last talked, I spoke of software engineering
1:04:04
as something like an art form where if you have the energy to produce,
1:04:11
and you have the skill that you can really affect the world with your ideas,
1:04:16
which is ultimately how I think what drives art itself is finding ways to materialize your thoughts.
1:04:26
That can be a book or a painting, but it can also be software.
1:04:31
And although we're in this renaissance of software development,
1:04:38
we're seeing that the brush really doesn't matter as much as we thought it would anymore.
1:04:45
So the manual part of it is just completely changing.
1:04:50
But that means that the rest of software development is becoming more important.
1:04:56
So now that everyone can write software, or those who can write software before can write even more software,
1:05:05
software just becomes kind of like a disposable artifact of your activity so what matters now is
1:05:15
why why do you do what you do and that makes things a bit more complicated as a human to
1:05:23
figure out why you do something or what you should be doing what's a good thing to do you know what
1:05:27
makes sense to do those require a completely different set of skills to figure out good
1:05:34
answers to these questions than just like the learning Postgres and C-sharp and whatever.
1:05:41
Right.
1:05:41
So now it's about ideas and execution.
1:05:48
Some people say taste and aesthetics.
1:05:53
But I also think about communication and marketing and trying to explain to people
1:06:01
why you do certain things and why they should be interested in it.
1:06:06
So all of these way more human things and way more soft-skilled things
1:06:12
are suddenly at the center of software development.
1:06:17
And so I think that's the reason why everything is going to change
1:06:22
and it's changing right now.
1:06:24
So we might see a new wave of software.
1:06:28
where we might see a new wave of cyber culture emerge
1:06:32
because of these changes that we're experiencing, right, Neil?
1:06:37
Yeah, we may find that all the fears of our humanity being stripped from us
1:06:42
are actually completely wrong,
1:06:45
and the technology forces us to explore our own humanity
1:06:48
and bring it out via our creative endeavors
1:06:50
in the world of projectionist software.
1:06:53
There is this idea that it's popular in this universal basic income circles about what do you do once you have everything you need?
1:07:05
What do you do if you don't have to work anymore?
1:07:09
And it forces us as humans to really answer that question.
1:07:15
I think that question is important, whether UBI has arrived or not, whether everything is fully automated or not.
1:07:23
You should be asking yourself this question like 10 years ago.
1:07:28
And today, you're forced to ask that question.
1:07:32
If you're a software engineer, you're literally forced today.
1:07:35
If you're not a software engineer, you'll be forced in like five years to answer that question, maybe in 10.
1:07:41
And the good thing is that we're getting more prosperous as a society.
1:07:46
Hopefully, at least we can all.
1:07:47
I mean, if this doesn't turn into a dystopia.
1:07:50
But the good news is that we only have more time on our hands, more life quality on our
1:07:55
hands to think about the more important questions like who do we want to be?
1:08:00
What is the goal of all our actions?
1:08:01
How do we want to live in a society?
1:08:04
What should this world look like?
1:08:05
So there's room for new ideas and it's the most exciting times to be alive.
1:08:12
It really is.
1:08:15
It really is.
1:08:16
Happy that you have that perspective.
1:08:18
Somebody I respect in the world of software development.
1:08:21
It's great to see that you're optimistic about this.
1:08:25
Thank you for all you've done.
1:08:28
I mean, from BitChat to Cache Protocol, now Numopay, Clawi.ai,
1:08:33
making this agentic world more accessible for other people
1:08:37
who I think should be experimenting with this.
1:08:39
It's insane to see what you've shipped since we last recorded.
1:08:44
So keep it up, brother.
1:08:46
Thank you. And I want to forward all of those great words that you just shared with me also to the team, which did most of that work.
1:08:55
And we are a great developer team with incredible people who are working on cashew day and night.
1:09:02
And we all just want to see Bitcoin succeed.
1:09:06
And I also want to use this dance to talk to the people who are listening out there thinking, you know, what should I do?
1:09:15
how can I help, how can I help improve this world we live in, is I, you know, this is a,
1:09:25
Bitcoin is a free and open source system that lives off the contributions of people like you.
1:09:34
And if people don't choose to work on Bitcoin, Bitcoin stops working, it will die. So I hope that,
1:09:42
you know there's at least one person out there with things like i've been a software engineer
1:09:46
all my life and i'm fed up with this job and i want to do something else to consider you consider
1:09:53
becoming a bitcoin developer and help with you know help us with driving these freedom technologies
1:10:00
forward because no one else is doing it there is no one except this circle of people that we've
1:10:07
talked about trying to counteract the massive growth of surveillance technology and centralized
1:10:17
control. And so if you feel that you need or you can change something in your life and you want to
1:10:25
contribute your energy towards something good, please join us and become a Bitcoin developer,
1:10:31
become a cash developer, look at BidChat, look at all the other projects that are out there and
1:10:36
contribute.
1:10:38
If not you, then who?
1:10:40
Ali, it's been a pleasure, sir.
1:10:42
Likewise. Thank you, Marty.
1:10:45
Peace and love, freaks.