Mike Adams warns AI will obliterate 40% of middle-management jobs within 18 months, citing Block’s AI-driven layoffs and stock surge, while his open-source platform, BrightLearn.ai, already publishes 40,000 books with near-zero human input. China’s sparse attention neural networks—like DeepSeek’s zero-cost models—threaten U.S. dominance, forcing Pentagon to reject "woke" AI for weapons, risking reliance on Chinese alternatives. Adams urges rapid adoption of tools like Replit and Anthropic Cloud Code or face irrelevance, as AI outpaces humans in code analysis and logistics, collapsing discretionary income into an economic "doom loop." Survival prep—iodine, freeze-dried food—hints at deeper fears: AI’s rise may outpace humanity’s ability to adapt. [Automatically generated summary]
And that's actually not that difficult for most of the workforce.
I'm not trying to demean humans.
Don't get me wrong here.
But we as humans, we tend to overrate human cognition.
AI is either going to be the greatest thing ever or the worst thing ever.
Which is it going to be?
Hello, everyone.
I'm Chris Martinson of Peak Prosperity.
Welcome to this Off the Cuff.
I'm here today with Mike Adams of Natural News and his Bradyon Studios.
I'm sure you're all familiar with him.
And it turns out Mike is, amongst all the other amazing things he does, dives into everything he does with both feet.
He's been in deep into AI.
So we want to sort out where are we really in this story, fact from fiction, all of that.
Mike, so good to be talking to you today.
Well, hello, Dr. Martinson.
It's awesome to join you.
Thanks for having me on.
Can't wait for this.
You know, we had a rock and good conversation privately just the other day.
Like, ooh, we got to have this in public.
So let's start here.
We've seen a lot of hype lately.
Lots of CEOs of AI companies saying, wow, this could take away all jobs or all that.
It sounds hyperbolic.
And I have people on the other side saying, it's not going to be that bad.
You're making too much of it.
LLM's large language models are not all that.
They can't be more than the sum of their parts.
Where are you falling right now in the spectrum of, wow, this is going to be disruptive to this is a shiny toy, but not all that much?
Well, I actually agree with the Microsoft AI CEO who said that this will be capable of replacing most middle manager corporate jobs within 12 to 18 months.
Now, importantly, he said, or at least my understanding is that he said it's capable of replacing those people.
It doesn't mean that 100% of those people will be fired and replaced by their employers because there's going to be pro-human momentum.
Obviously, there's going to be a number of reasons why corporations will keep people.
But as we just saw, and I think this really ends the debate right here, Jack Dorsey just fired 40% of his human workforce all at once in one day at Block and openly admitted he's replacing them all with AI, you know, beginning in weeks because they're staying on for a few more weeks.
And then the investors said, we love that plan, and the stock price went up 23%.
That's for a company that earned almost $3 billion in profits last year.
And the road to profitability for a lot of these corporations, especially those in fintech or other areas that are readily vulnerable to automation, the roadmap is going to be mass firings of humans and replacing them with AI.
Chris, I don't think there's a debate after the last two days.
I mean, this is clearly happening.
We're in what I call the AI doom loop about human jobs, and we can talk about that in more detail however you want.
Well, let's start here, though, because I hear people saying it's not going to be all that much, but we're having conversations today that you couldn't have even had six months ago.
The pace of development is obviously out of hand.
It feels geometric to me at this point in time.
It's almost every day I wake up and there's a new tool, a new thing, a new capability.
Every update to these models is not just a little bit better.
There's square waves.
And there's a chart I could put up which shows the amount of compute time that, say, Claude Opus can manage before it sort of like flakes out.
And it used to be measured in minutes, and I think they're up to 18 hours now.
It's obviously, and the chart just looks like a pure parabola.
It's just like, that's where we are in the cycle.
And what's interesting about that is those are machine hours.
The representative number of human hours that those 18 machine hours encompasses is hundreds of hours.
So for your audience, if they're not familiar with my work and what I do, let me establish a little bit of credibility because I've been building AI systems for about two and a half years now.
I've released my own open source model.
I built single-handedly the world's largest book publishing platform called BrightLearn.ai.
And over 9,000 authors have now published almost 40,000 books there.
And they're all available for free.
It's an open source project.
And you can create your own book for free.
And I still see people on X saying, well, show me that AI has built anything.
And I point them to that.
And well, here's 40,000 books you can download for free.
And they're actually well researched and well-written.
This isn't just, you know, hey, chat GPT, write a chapter.
No, we're talking about research citations for a massive corpus of external research data that I've curated.
We're talking about tens of millions of pages of content, hundreds of thousands of science papers, and over 100,000 published books that are all cited in there and with near-zero hallucinations.
So I did that with no humans, okay?
So zero humans, period.
And that's just one proof among many.
And I even did that before Claude released Opus 4.6.
And I did that before the new Quenn 3.5 just released and before DeepSeek version 4, which has not yet been released.
And what I'm seeing in these models is very clear.
So there's no question they are engaged in actual cognition, actual intelligence, which we can define loosely as the ability to manipulate your environment to achieve goal-oriented outcomes.
Clearly, these models are doing that.
And they're doing it in extraordinary ways.
And by the way, jump in.
This is your show, so interrupt me anytime, but I'm almost finished with this thought.
A lot of people thought for the last few years that this was just an elaborate word prediction engine, that that's all LLMs were.
Well, that's absolutely not the case because I can do things like I can take my code base, you know, 100,000 lines of code, and I can give it to an AI model and ask it, hey, tell me what this code does in plain English.
And it will analyze the code.
It will think about it in a hierarchical structure.
And it will understand the interactions between the various modules.
And it will then explain it to me in plain English what it does.
And it might even say, here are a few ways you can improve it.
Do you want me to proceed to alter the code to make these improvements?
That's what AI is doing now in 2026.
You know, some people say, oh, you know, it's more of a curiosity at this point because it's not really doing good enterprise-level testing software to make sure it hasn't hallucinated or made mistakes.
What's your experience with its accuracy at this point and how well it's performing?
My experience is that a lot of people don't know how to prompt well, and so they don't know how to overcome the limitations that do exist.
It doesn't write perfect code on the first pass, nor does any human, by the way, not even the best programmers in the world.
And so if you ask it to write a project and it writes it, then you have to go back and say, hey, look at your code again.
Double check everything.
Check all the variables.
Let's look at refactoring possibilities.
So typically I do a three pass when I want AI to write something.
And by the third pass, it's solid and it's error-free.
With humans, that takes 10 passes in 10 weeks.
With AI, it's done in an hour or whatever.
So here's the thing, Chris.
AI doesn't have to be perfect to replace humans.
It just has to be better than humans.
And that's actually not that difficult for most of the workforce.
And I'm not trying to demean humans.
Don't get me wrong here.
I have a pro-human philosophy that we should use AI to augment our capabilities and our mission in life, whatever that happens to be.
But we as humans, we tend to overrate human cognition.
And it's actually not that amazing.
Chris, your audience and you and I, we're among easily the top 0.1% of human cognition.
And yet our intelligence is easily surpassed on a technical basis by AI engines right now.
Well, it is indeed.
So let's talk about that doom loop very quickly because, yes, was that Mustafa Suleiman was saying, yeah, it could replace all white-collar middle management jobs by 12 to 18 months, but that's not the right question.
I saw Luke Roman today ask the right question on Twitter.
He said, the right question is, how many of those people need to be replaced before we get into an economic crisis?
Now, it's not 100%.
Is it 10%, 20%?
Because those are all people formerly had high-paying jobs.
Maybe the people who used to work at block now scrambling to find something else to do.
So what's your doom loop here?
How's that work?
It's very well understood that, of course, discretionary income collapses as these normally high-income human workers are jobless all of a sudden.
And then the difficulty of finding new jobs becomes extremely high.
So their discretionary spending collapses, and then products and services that they would normally consume, those sales tend to collapse.
And then the corporations that offer those things, they tend to lose revenues, and then they have to make cuts.
And of course, the first place they're going to look is automation.
So then they cut their humans, and then those humans, you know, so there's the loop.
And that is happening right now.
We are in that loop.
Yeah.
Where does it end?
It ends badly because it's happening so quickly.
I think our culture and our economy could absorb this over time, over five or ten years, but it's not happening over that extended period of time.
It's happening, as you said earlier, in a geometric or even a parabolic event that's taking place with rapid machine cognition capable of replacing human cognition.
And I would just add, by the way, that Quinn 3.5 just released a new medium model called 122B, A10B, it means active 10 billion parameters on any given prompt.
I was testing that yesterday on some business logistics.
And that model alone, and by the way, I use AI to write an interface app in 30 minutes to be able to talk to that system and have it look at a spreadsheet I'd put together for my own company, you know, because we're in the health and food space.
I had it look at a spreadsheet looking at sales trends for one particular product and the number of vendors that we depend on and then the number of different products that we make that are made out of that raw material.
In this case, it was raw cacao powder.
And I asked it to then project the demand and calculate the lead times of the vendors that we get it from in order to tell us when we should place purchases for cacao and how much we should order at a time.
And guess what?
It did it perfectly.
It took about 15 minutes.
It went through rationally with thinking tokens.
It analyzed the spreadsheet, analyzed the numbers, projections, everything.
That replaces software that could easily be $80,000 a year software right there.
And it did it on my desk for free.
So this is not a joke.
It's not a hoax.
This will revolutionize many businesses.
And by revolutionize, you mean it's going to tank some of them that we've already seen pretty hefty losses in the SaaS space, software as a service companies.
Was that overblown, do you think?
Or is the market actually finally discounting like it's supposed to?
Well, you know, I believe much of the market is overbought anyway.
You know, so much of it is speculative based off of fiat currency printing.
So I wouldn't be surprised at these corrections.
But yeah, I think that factoring in the loss of revenues for Saa companies is rational.
There's no question that you can now build many apps like I just described.
You can build your own apps on your own desk.
And what's interesting about this, Chris, is that China is pushing out the open source models that you can run locally on rather modest hardware.
So for roughly $10,000 or $12,000, you can set up a kind of a beefy, high-end, but consumer-grade system on your desk, and you can expose that system over your network to your entire company.
Your entire company can then use that system for not just prompting, but for analysis on things like logistics and so on.
So what we are doing in our company is we're not firing anybody because we've always been short people.
We can never find enough good people, but now we can take the people we have and give them these tools and make one person function as five people.
And you're going to see that happening across the corporate space.
If people begin to get involved in it, so you dove in feet first.
I've had somebody on my side dive in, and he did it all on his own, diving in feet first.
But Nick is there too.
And I think he spent the last 24 hours not sleeping because once he got exposed to it, he said, he just called me up and he's like, oh my God, it can do who knows what.
But already he was able to just see what its power was.
So we're scheming all the ways that it's appropriate in our business.
But I think that you kind of have to get your, you got to get your feet in the pool, I think, to really know what's going on here, don't you?
Well, absolutely.
Learn To Use Replit00:02:21
I would urge your listeners to consider this skill set to be the single most important thing that you can learn right now in our economy.
That is how to use AI.
And let me give a couple of practical suggestions.
So number one, you should learn to use Replit.
That's R-E-P-L-I-T.com.
Learn to use Replit.
It's an app-building site.
And even if you can't think of anything to build, just go to Replit and have it put together a PowerPoint presentation just so that you know how to use it.
And then you can ask it to do other amazing things like, I don't know, build a news summarizer or whatever you want to do.
So that's a skill set.
And secondly, you need to download and install cloud code from Anthropic because cloud code can answer almost everything that you could think of on a computer, including technical issues.
So, for example, right now I'm setting up another Linux workstation at the moment, and Linux can be a little bit tricky at times.
And so, the first thing I do when I'm setting up Linux is I download cloud code, and then I just tell cloud code what I want to set up on Linux, and I don't have to remember all the Linux commands.
Thank goodness, because there's a lot.
And then, cloud code sets it up.
So, literally, before I got on the phone with you, I had it set up an environment for LLM training.
I had it set up a PyTorch and CUDA cores for NVIDIA to drive a large GPU on the machine, and it just set all that up while I was getting ready to talk to you.
So, that normally would have taken me, you know, I don't know, hours and hours and frustration.
Now, it happens in minutes because of cloud code.
So, those are two things that every person listening should learn to use those.
And Cloud Code will answer questions about your Android phone, your Mac, your Windows, your everything.
You can ask it questions about any technical thing.
You don't have to have that guy that you always call that knows everything.
You know, we all have a guy like, oh, can you help me?
I don't know how to do this.
You just ask Claude, it gets it done, and your productivity will go through the roof.
Wow.
So, none of this really seemed possible just six months ago, but here we are.
Does this level out anytime soon, or do you think this just are we going to just be surprised in six months from now?
Where's this going?
Chinese AI Breakthroughs!00:10:07
It does not level out.
And everyone who has predicted that LLMs would plateau has been proven wrong again and again and again.
And here's why.
Even if the same number of parameters is frozen, let's say, just as a thought experiment, you see science papers coming out of China that show that there are very clever ways to do much more with the same number of nodes or parameters or vectors.
I don't know how technical we want to get here.
But anyway, the number of parameters is basically the number of vectors, number of interconnections between nodes that exist in a neural network.
Well, what Chinese scientists have figured out to do, figured out how to do at companies like DeepSeek and Alibaba is they've been able to achieve things like sparse attention or very clever routing of questions through mixture of experts structure.
And sparse attention means that even though you might have a very big model with 100 billion parameters, your question gets routed to only activate the number of nodes and vectors that are relevant to answering your question.
That might only be 3% of the model.
And what that results in is very fast inference speeds.
So you get large model intelligence, but small model throughput, performance, and cost.
And since China released these models for free, your only cost is really the upfront cost of the hardware and then electricity.
So you're basically getting cognition for the cost of electricity, which is near zero.
So the dropping of cognition to zero or effectively close to zero cost, this has never happened before in human history and is not plateauing anytime soon.
And I haven't even talked about other science papers like N-gram knowledge storage or manifold constrained hyperconnections and things like that.
But all the best science is coming out of China on this right now.
That's fascinating.
You know, what you described sounds a lot like a brain, right?
You know, a brain doesn't fire up every synapse to answer a question.
It finds the path to get through that.
I mean, nature has been very good at that.
So Neural Net may be well-named, but it sounds like we're getting pretty good at mimicking sort of the architecture of how thinking happens.
Am I going too far there?
Absolutely.
The human brain, though, of course, is many orders of magnitude more efficient in terms of cognition per power input, right?
The typical human brain only runs on, what, 20 or 25 watts effectively of power.
But also think about the human brain as a mobile computing device.
It has to go with you, probably, I'm guessing, right?
Wherever you go, your head should be attached.
But that has severe limitations in terms of the number of neurons that can be packed into the physical skull.
AI systems don't have those physical limitations.
So even though they're far less efficient in terms of power consumption per cognitive task, they can be scaled tremendously way beyond a human brain.
And that's why AI, the effective IQ of AI, will very clearly vastly surpass human intelligence.
I mean, it's already the case.
But it almost renders meaningless trying to say, oh, is your IQ, is it 160?
Is it 180?
When an AI system knows all human knowledge and can reason in multiple threads and can actually, in a sophisticated way, it can model numerous possible futures and simulate the outcomes of those possible futures and then choose the best one, which it's doing right now.
I'm not talking about science fiction.
That's happening now.
Then what does intelligence mean in a human understanding of it?
That's where we're headed.
I've heard about those.
I want to get to that, but first, can we talk about the geopolitics of China quickly?
So, A, a lot of people give me this cope, which is, oh, China, you know, China, they make shoddy stuff and they copy us.
I don't have that sense anymore.
I've lost that sense years ago.
I think they're exceeding our capabilities, particularly in engineering, particularly because they have a very strongly merit-based society where if you're really smart, you float.
You go to the best universities and all of that.
But as well, the United States, we sort of went Sam Altman, hundreds of billions, massive compute, proprietary subscription model.
And China seems to be dropping something in the punch bowl by putting out these free models.
I know you had some great thoughts on that.
What are those for our audience here?
So first of all, I'm very familiar with Chinese culture.
I lived in Taiwan.
I speak Chinese and I interact a lot with Chinese engineers.
And you're correct.
The perception in the past was that China made shoddy stuff and they ripped off ideas from America.
That is clearly no longer the case.
China is the world leader in almost every area of technology, almost all of them.
From robotics to battery storage technology to drones to, of course, rare earths extraction technologies to telecommunications, just on and on.
Optoelectronics, microchips that run on light, right?
China, oh, and by the way, I just saw, we were talking about this the other day, you and I, China just had another breakthrough on UV lithography, where they can now fabricate even better their own microchips.
And I think that was at a two nanometer scale.
So see, China is a country that graduates 500% more STEM graduates each year than does the United States.
And in the U.S., we have, dare I say, woke universities that penalize Chinese people.
Okay.
So in the California university system, if you are Chinese, Japanese, Korean, Thai, Vietnamese, you are penalized for being Asian, which is insanely crazy and stupid, in my opinion, and short-sighted, because you want the best people to get into college and get the scholarships.
I don't care what they look like.
I want the best.
But that's not what we have in America.
In China, like you said, it's a merit-based system and it's rigorous and it's brutal on children.
It's brutal.
Their parents are hammering them, you know, study, study, study, right?
That's Chinese culture.
Every Chinese mom out there listening knows that, right?
But the result is they are churning out world-class engineers, mathematicians, chemists, physicists, scientists at a level that no country can compete with, period.
And now we're beginning to see the results of that.
It's clear.
And as well, they have a very strong business orientation, mercantilism even.
Yes.
And they're clearly, I don't know how we're going to compete with our trillions of dollars of spend if they're going to undercut us with their better, easier, faster, lighter models that are free, open source.
Right.
You know, what else is even really interesting is you saw the rift between the Pentagon and Anthropic, right?
So the Pentagon demanding that Anthropic allow them to use the Claude models for autonomous killing systems or mass surveillance.
And Anthropic said no, to the credit of Dario Amodi, he said no.
So the Pentagon is going to rip Anthropic away from the supply chain, and the Pentagon is going to lean on all U.S. federal contract suppliers, such as Boeing, let's say, to drop Anthropic.
Well, if you drop Anthropic, what's the next best model to use?
Probably DeepSeek from China.
You could argue, well, maybe it's Google Gemini.
Okay, maybe.
But we're going to find out.
But by dropping Anthropic, the Pentagon may be forcing U.S. companies to move to Chinese models because they're better and cheaper and faster.
You see what I'm saying?
Oh, that's crazy.
It was a top of fold Wall Street Journal this morning.
Sam Altman's in conversations with the DOW, as we term it now.
And I can't, I'm like.
Oh, yeah, the DOW, right.
Chat, but come on.
Chat GPT?
Oh, man.
It's woke.
It's full of, it's got so many garbage points in there.
I don't know what to do.
I mean, this is the one, I saw somebody ask it just the other day.
If I had to, would you either misgender Caitlin Jennings or would you like drop a nuke?
It's like, oh, I drop a nuke.
You never misgender somebody.
Like, you want that thing making your autonomous kill decisions?
No, definitely not.
And yeah, the Chinese models are very interesting.
They don't have the wokeness in them.
They do have guardrails, but those guardrails can be easily removed because they are open source models.
So there's a library out there that's very well known.
It's called Heretic, and you can download it from GitHub.
And Heretic will remove all guardrails from all open source models.
So you can just take a model and then just over a period of a few days, you can remove the guardrails.
And then you have a base model that answers anything.
Of course, it's important that we always use it for pro-human, you know, high-integrity purposes, right?
We don't want to encourage anybody to use it for writing malicious code or crazy things like that.
But you can take that base model and then you can train it on, for example, Chris, your content.
You can build the peak prosperity language model off of Quinn relatively easily.
It's very doable now to do.
Do you think that, or do you not think that every corporation in America is going to realize the same thing and build their own model to do their customer service, to do their in-house coding or their in-house writing, content production, branding?
Of course they are, because it's free and it's customizable.
And OpenAI is not either one of those.
Well, when you put it that way.
Right, right.
It's kind of a no-brainer when you look at it.
Yeah.
Yeah.
I mean, I have so many questions.
You know, I'm trying to think even, you know, in my local town here, small town, Western Mass, I'm thinking it's too early for the conversation, but we should be having a conversation, which is that, you know, 56% of our town's budget goes to the local school system.
Rapid Changes Demand Precision00:04:42
I can't, in my mind, see how schools can persist in this in the light of what we're talking about.
One, because the job market is so changed, are we even preparing kids for a future that exists?
Answer, arguably no.
Second, AI can do a much better job of individually tailoring education processes and trainings for children.
And that's already been proven.
There are market models for that.
So I feel like there's so many lumbering dinosaurs walking around my field of view right now.
What are your thoughts there?
I feel the same way.
Yeah.
I must have stumbled upon a time machine and they sent me back to the prehistoric era.
I don't know.
As a side note, what's interesting is that when you start to work with AI, my saying is that your effective IQ goes up 20 points.
And that's a lot for most humans.
And what happens is you become more frustrated with lower IQ humans.
So there's a, and I've noticed this myself.
And I'm just admitting this right out in the public here.
I have a lot less patience with stupid people now that I work with AI because I'm getting so much better cognition from the language models than I would get from people typically.
Now, you know, I'm usually the smartest guy in the room, so I'm kind of used to that, but I'm just noticing I have a lot less patience.
So I'm wondering, and also there's a sense of urgency.
There's a sense that things are changing so rapidly, we don't have time to screw it around.
I don't have time.
If I'm in a meeting with a bunch of employees and there's one slacker in there, I don't have time to catch you up, right?
I'm like, dude, you go spend the weekend, learn what you need to learn, stop wasting my time, come back on Monday, or you're fired.
You know, that's my attitude today.
And it's more curt than it's ever been.
And I'm wondering if this is something that we're all going to trend toward, because I've heard this from other people as well, which is there's less tolerance for shoddy human cognition because we're raising the bar.
What do you think about that, Chris?
I think it's absolutely the case at this point in time.
And I'll tell you why.
So COVID really ripped the band-aid off for a lot of folks, right?
So once you woke up to that, you discovered that there were people out there who were in service of dogmas.
They could have been doctors, hospital administrators, public health officials, doesn't matter.
They were in service to this dogma, which didn't pass basic logic.
Like the logic circuit, even of you have to get vaccinated so that you don't transmit it to somebody else and doesn't stop transmission.
It's like, how's that even a logic circuit?
But I found that I became very short with people who had what I considered to be fried logic circuits.
And I'm not talking like big, right, you know, giant Socratean, like four-hour slugfest.
Like they couldn't do a simple loop, right?
And worse, I felt like being in their presence made me dumber.
So I didn't get them sticking around in my presence.
Right.
Right.
That's called low IQ shedding right there.
Low IQ shedding.
It's a thing.
Don't be trapped in a car for too long.
Well, no, I get that.
But secondarily, we don't have time to screw around right now.
We just don't.
We're facing what I call predicaments.
Problems have solutions.
We face a lot of those too.
We have predicaments now where we have to manage the outcomes.
And either you're busy managing for an outcome or you're going to be busy being a victim of that outcome.
And that's kind of where we're at across multiple sectors.
You have just nailed it.
That's right.
Well, let me put it this way.
You take Jack Dorsey's company.
He just fired 40% of his workforce.
That is roughly 4,000 people.
Which 6,000 do you suppose he kept?
Those are the 6,000 who know how to use AI.
Think about it.
I mean, it's self-evident, right?
So if you are listening to this and you're in whatever, a nonprofit, a corporation, government, whatever, if you don't learn how to augment your productivity and your efficiency with AI, you will be on the chopping block, period.
But if you learn how to use AI, you'll be the one they keep.
And the thing is, it's not that difficult to learn how to use AI.
You only really have to be curious.
And I've even told people, some people have told me, I don't even know where to start.
What do I do?
I don't even know what the model can do.
So I say, well, ask it.
Ask it what it can do.
Say, well, I downloaded Claude, Claude code.
Ask It What You Can00:03:52
What do I ask it?
I'm like, ask it what you can ask it.
Let's go another meta level here.
If you don't know what to do, ask it for its capabilities and then let your curiosity drive you from that point forward.
That's all it takes.
Just one spark and then you're off and running.
And then you can't sleep for days.
That's what happens.
Yeah.
Well, Mike, that's a perfect place to leave this, the public portion of this.
For everybody listening to this, if you're a peak prosperity subscriber, we're going to carry this conversation on back over at the website because we have to talk about some existential risks and things that are maybe a little bit more speculative.
And of course, we get to talk completely freely in that environment.
So thank you very much for listening to this part.
Mike, thanks for being part of this public conversation.
Thank you.
Everybody else, stick around.
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These are available in case things go nuclear.
It's clear that you will not be able to find any of this for sale anywhere.
All the inventories will be wiped out like what happened after Fukushima in 2011.
So if you want to get your hands on some iodine, this is a chance to get it right now.
HealthRangerStore.com slash survival.
In addition, we have many other survival items for you here, including some silver solutions, some spirulina available in bulk and at a discount.
And then a large assortment of storable organic food that's laboratory tested, including our Ranger bucket sets.
Here's a 195-day supply.
We've got the mini buckets, and we've also got number 10 cans available of freeze-dried fruits and vegetables and other things like miso soup powder.
Here's some of the buckets.
There's a big variety available.
Here are some of the number 10 cans right here.
Remember, a lot of people are missing fruit.
They don't have enough vitamin C in their storable food.
So, you know, getting bananas and pineapples and strawberries, especially, again, certified organic, freeze-dried.
That is the highest quality with the highest nutrient preservation that you can get in any kind of a storable food format.
All of this is available right now and so much more.
Just go to healthrangerstore.com slash survival.
And because the freeze-dried foods last for so long, you know, even if you don't eat them this year or next year, just keep them on the shelf.
They're going to last a very long time with good preservation, long shelf life, and they will have value no matter what happens in the world.
Now, of course, I'm praying for peace.
I'm praying for de-escalation.
I don't want to see World War III break out, and I certainly don't want it to go nuclear.
But we're dealing with insane times and insane leaders and insane situations.
Who knows what could happen tomorrow or next week?
Disruptions could happen here in the United States.
There could be, you know, domestic attacks that disrupt supply chains here in the U.S.
So stock up early, stock up now, get your emergency food, emergency medicine, iodine, anything else that you think that you might need.
Get it now.
And by doing so, by shopping with us, you'll be supporting our platforms and our AI engines that we offer for free.
That's funded in part by sales from our store.
So shop with us at healthrangerstore.com slash survival and help yourself get prepared and also help us bring you more free tools and platforms that can keep you informed no matter what happens in the world.