Read_949 - The Singularity Stack

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The cost of intelligence keeps falling toward the cost of electricity,
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and everyone will share in what that intelligence can do.
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Bitcoin captures the gains directly, while in dollar terms, they are inflated away.
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Welcome back to the show. I'm Guy Swan, the guy who's read more about Bitcoin than anybody else you know.
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And we got a really good one today. We're going to do a read. I know it's been a really long time since we've done a read.
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And I want to talk for just a minute about why and explain what's been going on behind the scenes.
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So we've done a huge shift over towards video, primarily video content.
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And because of that, we've had to change our production workflow.
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So I need to make sure that we could automate this and we could get things out quickly.
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I don't mean automate like we just plug AI into everything.
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I just mean that the process flows.
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And I'm not constantly reinventing what we're doing every single episode.
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And there's been a lot of that with AI and the tools available to us.
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And of course the process will still change quite regularly.
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But I think we do have a good system in place.
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And then in addition, the reason I've never done a read in video
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is because I never had the setup that I felt made it make sense.
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I could never do it quickly.
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And if I was going to do video for a read,
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the reason I really love the reads is because I can knock them out really quick.
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They were high value, high signal.
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And I just enjoyed sitting down in front of the mic.
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And when I was done recording the narration or the episode itself,
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just in the raw recording, the whole edit was done.
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I had set up my production flow that it was just when I got to the end, I exported and I didn't have to do any post-production.
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Now this isn't perfect and this isn't entirely post-production free, but I have actually vibe
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coded my own entire application that does this so that I can have the same style or same
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production flow in video as I did in the audio only podcast. So this will be my first read
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in video, my first video read. Maybe this is a totally pointless thing and there's no reason to
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publish audio reads in video, but it's fun. I think, I don't know, I think I can play around
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with it more to actually be able to see the thing on screen while I'm reading through it. I got some
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fun little AI tricks and stuff that I'm sorting out the processes for right now that, I don't know,
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this could be this could be i think it's gonna be fun so i'm really curious what you guys think
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if you sit down and actually watch a video read so with that shout out to bitbox they are our
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sponsor and they've been a fantastic wallet for a really long time i've used them for i don't know
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how long and you know uh sweating with the great hacking and going on ledger getting hit and cold
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card getting hit and all this stuff i've been very very happy with the team and the findings that
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they've had and how they've reported them and how they've fixed them. It's just been, the BitBox has
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been very trustworthy throughout all of this. And so that's made me feel really good, especially
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since I recommend it to people and I've used it for a really, really long time. And now it works
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natively right into the iPhone. So check it out. You got a 5% discount and, you know, stay safe out
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there. Buy directly from the manufacturer, please. And if you can use multi-sick, BitBox is now
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It plugs right in a nunchuck and works very easily with Multisig now,
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and I can't recommend it enough.
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It's saved my ass multiple times this year.
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So with that, it's time to get into today's read,
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and it's titled,
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The Singularity Stack from EarlyWriters.com
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The stack traces the path from raw energy to useful output, and it measures where value is created and where it leaks at each layer.
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Part 1. The Premise
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Thinking has become a manufactured good.
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In 1830, an hour of decent reading light cost the average worker about three hours of labor.
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So in 1830, three hours of labor got you an hour of light.
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In 1900, that same hour of light only cost 13 minutes of labor.
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And today an hour of light will cost you 0 seconds of labor which is too cheap to even notice For centuries illumination was a
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craft good, rendered from tallow by hand and consumed within hours of its making. Electrification
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made it a utility, generated in bulk and metered by the kilowatt hour, and the industries that
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were unthinkable in the candle era arrived as ordinary byproducts. The power grid accidentally
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led to the night shift, the modern hospital, and massive improvements in transportation and
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coordination 24-7. Intelligence is undergoing a similar transition. For all of prior history,
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a unit of useful thinking cost a unit of human life, with the limiting factor as a brain
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that runs on a metabolic budget of roughly 20 watts.
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Artificial intelligence completes the sequence
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because the thinking itself has become a manufactured good,
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produced in bulk and priced increasingly in energy.
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And unlike light, intelligence improves the process that produces it,
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so every fall in its price reflexively drives the cost down,
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all else being equal.
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electricity goes to compute to intelligence to work and finally settlement each layer is the
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physical input to the one above it so a constraint anywhere reprices everything downstream and an
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improvement anywhere compounds through the rest light became too cheap to meter so they got the
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work time needed to buy an hour of reading light which if you're watching this you can see it
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from 1830 to 2026 on log scale, which is hilarious because this is a steeper than linear decline
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in log scale. This is at earlywriters.com slash charts if you're listening to this.
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Light became too cheap to meter. Intelligence is next. That's a crazy way to think about it.
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Okay. Technological progress means doing more with less, and money is where the difference is saved.
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When the money supply expands, every gain in efficiency is met by new units bidding prices back up,
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and the useful work the energy performed is dissipated before anyone can hold it.
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Money with a fixed supply preserves the conversion,
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so efficiency arrives the way cheap light did, as rising purchasing power.
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We believe the gains of the singularity settle in money that costs energy to produce
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and cannot be expanded to absorb them, and this report is the argument for why.
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Part 2. The Framework. The Stack Defined. The stack is a single conversion chain.
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Electricity becomes compute, compute becomes intelligence, intelligence becomes work,
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and work becomes payments that need somewhere final to land. Each layer is the physical input
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to the one above it. So a constraint anywhere reprices everything downstream and an improvement
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anywhere compounds through the rest. Layer 1. Energy. Everything else in the stack,
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from tokens generated to transactions settled, resolves to electricity. The raw energy is there
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in abundance. The constraint is converting it and delivering it to where the demand sits.
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Over 2,000 gigawatts of proposed generation
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waits in U.S. interconnection queues,
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but delays and surprise upgrade costs
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mean most of it will be abandoned.
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Intelligence applied to conversion
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in better solar, storage, and reactors
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makes electricity cheaper,
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and cheaper electricity makes intelligence cheaper in turn,
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the first step in the singularity.
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Layer 2. Compute
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The compute behind Frontier training runs has doubled roughly every six months, a compounding rate no prior buildout has approached.
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Capability follows compute, with the length of tasks AI can complete doubling every four to seven months.
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The acceleration is reflexive. This July, a Frontier model designed a working chip in a 48-hour run with no human intervention,
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a chip built to run a smaller version of the model that designed it.
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Layer 3. Models
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That same compounding destroys the business case,
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since every frontier model becomes the cheap commodity option within a year
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and open-weight releases set the floor near zero.
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Each generation now helps build the next,
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generating the training data, writing the training code,
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and teaching the smaller models that follow.
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Capability compounds on two axes
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With compute scaling below
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And algorithmic progress
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Cutting the price of a given intelligence level By roughly 10x a year If that actually accurate that insane The labs sit closer to the memory manufacturers than to the software companies they are valued like
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Layer 4. Harnesses. So the switching cost in AI lives a layer above the model, and it deepens
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with use. The code itself is easy to copy, with open source implementation setting the floor price
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near zero. So the durable value sits in the operating context a harness accumulates. The
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memory, tools, credentials, evaluations, approvals, budgets, routing, and audit trails that build up
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around real work. The effect is measurable, as identical weights that solved 2% of real software
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bugs in a chat window solved six times as many inside an early harness that could read files and
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run tests. Models underneath get swapped constantly on quality, cost, latency, and policy,
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and the harness is what makes those swaps routine, since nobody rebuilds that context every time.
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Layer 5. Agents. Work priced in tokens is work priced in electricity, and every layer below this
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one is driving that price towards zero. Labor stops scaling with people at this layer, since
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one person can direct a dozen agents and an agent can spawn more when the task splits.
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The work turns self-directed as well because agents now build and test the layers beneath them.
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Layer 6. Identity. So identity inverts from something granted from above to something the
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agent generates itself. On Noster, that is a key pair, a private key created in milliseconds with
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nobody's permission and a public key anyone can verify. Company-issued accounts fail here twice.
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Since agents multiplying by the billions overwhelm any issuer and whatever an issuer grants,
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it can revoke, erasing that graph along with the balance on one terms of service update.
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The identity lives in the signatures on a decentralized network rather than on any server, so an agent banned from one relay reposts the same signed record elsewhere and loses nothing.
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Level 7. Coordination
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The model context protocol has become the default way to expose a system to a model, an open specification with no gatekeeper metering what flows through it.
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The agent-to-agent specification lets agents built by different vendors delegate to one another,
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and delegation changes what capability means,
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since an agent that can hire specialists outperforms any single model working alone.
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The shared workspace remains the unsolved third,
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since in Slack and Discord an agent is a bot account subject to the revocation problem above,
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while Buzz, an open-source project from Block, makes humans and agents peers who each hold their own keys.
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Layer 8. Value Transfer
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Money has to move at the speed of the work it pays for.
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Intent of a cent amounts at the frequency of API calls with finality in seconds
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because an agent cannot wait on a dispute process.
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The card networks were built for none of this,
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since a fixed fee per authorization makes a micropayment cost more to process
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than the thing even being bought, and settlement that takes days cannot serve work that finishes
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in seconds. What replaces them splits into rails, which move the money, and standards,
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which tell a machine how to ask for it. Neither specification collects a toll, so the durable
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income goes to whoever issues the money the payments are made in.
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Layer 9. Settlement. The singularity accelerates the build-out of everything
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except the money at the end of the stack.
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Every other layer's scarcity gets competed away eventually,
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but Bitcoin's supply stays fixed no matter how much demand shows up.
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So as the stack makes everything cheaper,
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whoever holds the fixed money watches their purchasing power rise.
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The frame is the analytical tool,
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Placing an event on its layer tells you how quickly supply can respond and where the value it creates will settle.
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A power contract and an agent payment standard sit seven layers apart but move the same variable, the cost of finished work, from opposite ends of the chain.
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Part 3. The Evidence
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The acceleration is measurable.
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The singularity is best defined operationally, as a period in which the rate of improvement
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accelerates across enough independent domains that no single reading can be dismissed as hype Compute 4 Frontier Training Growth Compute Epic AI estimates that the computation used to train frontier AI models has been growing four
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to five times per year, a doubling roughly every six months. Moore's Law, the benchmark for
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relentless compounding across five decades, doubled every two years, and this build-out runs four
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times faster. Adoption. Two months. ChatGPT to 100 million users. The telephone took roughly 75
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years to reach 100 million users. ChatGPT reached 100 million monthly users in about two months.
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Even that record should fall because the next wave of products will be adopted by agents as
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well as people, and agents adopt valuable tools as fast as they can read the specification.
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Capital. 713 billion. Hyperscaler CapEx planned for 2026.
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The entire 13-year Apollo program cost about $309 billion in today's dollars.
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The distinction from prior manias is the funding source.
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Since the late 1990s, fiber build-out was financed with debt by carriers that never earned it back,
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while this one is paid for out of the operating profits of the most profitable companies in history.
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Energy. Four-year U.S. electricity demand forecast.
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After two decades of essentially flat grid consumption, the EIA now forecasts
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the strongest four-year growth in U.S. electricity demand since 2000,
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naming data centers alongside manufacturing on shoring and electrification as the drivers,
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A demand line that stayed flat through the entire smartphone and cloud era has bent, and it is not waiting for the grid.
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Capability. 12-hour Metaer autonomous task horizon.
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Metaer measures the length of tasks AI systems complete autonomously at a 50% success rate.
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In 2019, the best model handled a task taking a human about two seconds.
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The doubling time has compressed from every seven months to roughly every four.
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And even at the stricter threshold, the trend puts a full working week of unsupervised output inside a decade-long earnings forecast.
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One year of AI CapEx buys two Apollo programs.
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U.S. hyperscaler capital expenditure against the Apollo program inflation-adjusted.
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One year of planned AI CapEx buys more than two entire Apollo programs in today's dollars.
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Part four, the money.
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Deflation is the normal state.
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Productivity is exploding, and life does not feel cheaper for monetary reasons and not technological ones.
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In the last three decades of the 19th century, under gold-denominated money, the American price level drifted steadily lower while real output per person grew at a rate comparable to the strongest post-war decades.
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Mild deflation set a higher hurdle rate instead of paralyzing capital, and the country still laid track and built steel at a formidable pace.
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Deflation is therefore the normal state of technological progress under a money nobody can expand at will.
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The modern reflex against it is institutional and not economic, since the Federal Reserve adopted its explicit 2% target only in January 2012.
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Nearly all growth arrived after 1800.
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World GDP from 1700 to 2015 in 2011 international dollars.
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The Debt Arithmetic
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The System That Cannot Allow Deflation
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In a debt-based monetary order, falling prices are intolerable as a matter of arithmetic.
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A loan is written in fixed nominal dollars, while the borrower's revenue is whatever prices the market will bear.
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So when technological deflation pushes down prices, the income shrinks and the principal does not.
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Irving Fisher set out the spiral in 1933, where borrowers default, banks pull credit,
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spending falls, and prices drop further.
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The sequence that failed roughly 9,000 U.S. banks and contracted the money stock by a third
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between 1930 and 1933.
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Every unit of technological deflation therefore has to be met with offsetting monetary expansion,
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and the singularity turns that from a maintenance task into a race.
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$4.7 trillion is the U.S. M2 money supply in January of 2000. $22 trillion is the U.S. M2
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money supply today. $40 trillion is the federal debt. Interest above $1 trillion.
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The denominator keeps expanding. So there's a chart of the U.S. M2 money supply from 2000
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to 2026.
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BLS Component Data, 2002 Today
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The Two Economies
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BLS Component Data shows the two economies side by side.
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Everything manufactured and shippable, from televisions to software, has fallen steeply
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in price since 2000, while hospital services, tuition, childcare, and housing have outrun
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wages.
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Technology drives deflation in the reproducible half of life, while monetary expansion lands in the scarce half.
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And the stack is aimed at moving the scarce half, priced mostly in trained human time, into the reproducible column.
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That's wild when you say it that way, but it's totally true.
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The Collision
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The deflationary force now arriving is aimed directly at labor,
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since agents convert capability into completed work that used to require a salary and trained human time
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is the dominant cost in everything that has grown more expensive for decades.
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The monetary system has to answer with expansion large enough to keep $40 trillion of federal debt serviceable,
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stretching the unit of account to absorb an exponential.
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most households whose wealth sits in wages and deposits risk living through the largest
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productivity boom on record as a cost of living squeeze that is so depressing to say out loud but
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that is literally what what we're looking at with the structure of what's coming because they don't
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and it's all because of the money it's all freaking god it's everything that the whole
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thing is always because of the damn money. Part 5. The Position. The purest expression
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of the singularity. The singularity does not float free of the physical world because a model cannot
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immediately generate the electricity it consumes. Well, the machine still has to buy. Somebody has
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to sign a 20-year power purchase agreement promising megawatt hours in 2046 at a price
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written in 2026. The faster the machine improves, the more its future hangs on the slowest
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instruments in the economy, contracts that only work if the money holds.
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Under expandable money, being close to the newly created supply wins, which is how a company
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burning cash outbids a profitable manufacturer for power. Under fixed money, only output that
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customers actually pay for wins. Participation. There is no direct way to own the singularity,
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but every layer of the stack can be owned somewhere, and there is money to be made in each.
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The difficulty is that every one of those positions adds a way to be right about the acceleration
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and wrong about the outcome, since a layer bet has to name the winner before competition arrives.
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In our view, Bitcoin is the purest expression of the singularity stack,
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in the position with the fewest ways to lose.
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Every conversion from energy to finished work settles in money at the end,
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so holding the settlement asset claims a share without naming the layer or the company that books the margin.
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It carries no earnings to miss and no shares to dilute,
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and no competitor can ship a better version of a fixed supply.
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On-chain estimates put roughly half of Bitcoin's supply dormant for more than a year,
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so rising demand competes for the fraction actually available.
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Who keeps the gains?
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Intelligence priced near the electricity behind it means expert help in medicine,
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law, engineering, and education for roughly the cost of light.
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And the surplus reaches people who never touch a model.
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The industrial era already ran this experiment under a money nobody could print.
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An ordinary saver who simply held gold-backed money watched railroads and cheap steel arrive as rising purchasing power.
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That transition is running again, at the singularity's pace.
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The cost of intelligence keeps falling toward the cost of electricity, and everyone will share in what that intelligence can do.
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Bitcoin captures the gains directly, while in dollar terms, they are inflated away.
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Differentiated business at any layer, one whose advantage survives the arrival of new supply,
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keeps its margin through the transition.
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Larger businesses can now be built with less capital and fewer people than at any point in history,
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since labor that once required headcount is provisioned by the token.
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So the returns to a real edge have never been higher.
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Early riders invest in both.
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Are you accelerating the singularity?
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We want to hear from you.
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Enter your name and email and address and a message.
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Hey, guys.
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Oops.
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I'm going to send a message.
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Guy Thank you We will be in touch I want to see if they respond something uh so okay so uh the one of the the things talking about like who keeps the gains i really like this section where is it
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in our view bitcoin is a purest expression of the singularity stack so here's the funny thing
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so this is i've talked about this in the show on like the idea of money and what it actually what
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its role ends up being in the economy. And we talk about it from a personal use case is money
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ends up like being a hedge against uncertainty, right? You invest in it or you hold on to it.
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And it's kind of like this promise of society to get back what you put in it. So the less
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uncertain you are, anything that you concretize into any money that you make concrete into some
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specific thing, you increase the uncertainty of whether or not it can actually provide what you
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want. You know, you put it into a house and a hurricane might come through, a flood might come
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through and destroy the house. But if you put it in money, it can be in a boat as easily as it can
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be in a house when you need it, of course, barring society collapsing. So money is not only a hedge
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against uncertainty, but this is another thing that we've talked about is how it plays out as
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a kind of investment in everything, right? So when you're actually investing in the market,
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and you're trying to pick winners and losers, or you're trying to invest in the singularity,
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because, you know, you're like, oh, Nvidia is the one that's going to explode.
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But you don't know which thing's actually going to take the market share or which is going to be
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obsoleted, you know, explode to 200 million users and then be obsoleted in two months,
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because things are going to be moving so fast. You have an insanely high margin of uncertainty
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in making any of those sorts of decisions on top of the fact that you have management risk and you
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have responsibility risk because someone could just kind of go crazy or make stupid decisions.
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Like it's not even simply that they're placed in the right location or that they're primed for,
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you know, the various growth strategies or the production. Something could just go wrong.
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Somebody could trip on something and smash a button and delete the whole thing, right?
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So the risk, you introduce enormous amounts of counterparty risk.
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That's what you do.
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Whereas Bitcoin, when you have a sound money, you do obviously have to trust the money's
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capability of ensuring its scarcity.
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But as soon as you can get past that, as soon as you have some assurance or level of trust
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in the scarcity of the unit that's actually measuring that progress, you actually have
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a non-counterparty risk way to actually obtain the hurdle rate. So the hurdle rate, you know,
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the cost of capital over time will increase dramatically if there's an enormous amount
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of growth expected. And the very reason is, is because you don't want to invest. You don't want
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to waste resources. Everything's scarce, right? You have 10 houses. You don't want nine of those
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houses taken up by a bunch of stuff that's making a half percent improvement or a 1% loss on
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productivity or manufacturing if that last house or that the one out of the 10 is actually producing
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a doubling in efficiency and productivity gains in that same economy. You want all 10 of the houses
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to be put toward that and it better be expensive as hell. It better cost 20 percent, 30 percent
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to actually rent out or lease out one of those houses because it's otherwise losing or costing
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us a 100% gain in productivity and boosting of a standard of living. So that's why hurdle rate,
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that's why your interest rate is going to skyrocket during a period of immense growth.
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And it's exactly why deflation is going to have to come in massive or I guess inflation,
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actually the opposite of that, because it would produce enormous amounts of deflation because you
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have such enormous growth and productivity when, when the reverse has to be true in the money.
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If you're on, if you're dead, if you're $40 trillion in debt, you sure as hell better print the ever loving crap out of it because you'll never pay back $40 trillion. When everything's plummeting to like prices are plummeting to the cost of electricity for practically everything that we do. There's absolutely no way out of that except inflating yourself into, into nothing. If you inflate away your debt, your obligation and your interest rates, you know, if you're legitimately looking at the possibility of a 20%, 30% interest rate,
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right um and i don't even think that's crazy if if anything resembling this this whole idea of this
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reflexive feedback loop which i'm sitting here working on an application that i've vibe coded
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myself and i've been improving and i've got like my debug when i like have a problem with this
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i literally have a little debug note thing up in the top right in fact let me let me show it um
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Can I, let me just pause.
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Alright, so this looks, this looks bonkers, maybe I can cut my screen off.
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Okay, here we go.
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Well, it still does the interface over and over again.
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So this is the application that I built and so like the screen share is just on screen and I can switch over to you know sharing like a window or something taking off my camera did nothing But I can this is a full on like editing app And I built all this stuff And when I like the process the changing of the process
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So I found how frustrating and annoying it was to constantly go over or talk about the problems, like type out the problems that I have into AI, right?
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So, and talking about like the harness in the singularity stack, actually, this refers right back to this, is I have agents basically on all my machines now.
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So check this out.
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So this is a debug node. And what I'm doing right now is this thing is recording logs of where my cursor is and where I am clicking on stuff so that I can keep track.
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Or basically the AI knows exactly what I'm doing and what is happening in the actual application.
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And by the way, for the AI, this is a transcript. I'm recording this into an episode, but I'm actually making an accurate note here.
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So when I try to add a source right here, it just blinks off.
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It's not actually working.
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I would like to be able to add a second source.
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It's basically trying to take one screen share as I have to replace it.
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So I have to close it right here and open up a new one.
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Whereas what I want to do is I want to be able to add a new source
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and click on a new window or a new device
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and then have this show up in my double
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because I've got the, it doesn't come up right now
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just because I don't have anything in it.
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But so that I can show them both on screen
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at the exact same time, right?
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As I can show my window for my browser
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and then another window for the read or something,
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or of course, Pearcast, the app itself,
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the studio that I'm working in.
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And, but right now, for whatever reason,
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this does not actually react that way.
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So I want to be able to stack these
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and have two of them actually working or running
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at the exact same time.
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So that'll close it out.
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So I stop there.
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That's my debug note.
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And it literally takes the log of everything
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that I've clicked on.
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And we've been building a peer-to-peer engine
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for just any general networking and operating use case.
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so what actually happens is that that note is recorded in the background and then is saved to
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a pair drive space or just is saved to a space in our peer-to-peer engine and then syncs to my
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other machines and to my agent and my agent immediately gets a notification that there's
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a new thing and the agent goes ahead and just immediately starts fixing it and so I can just
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kind of like think about and every single time I have one little issue or concern or something where
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I like clicked on something and it didn't behave like I wanted to behave again I don't have to go
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out and text and like do this very minute explanation of like I'm in the sidebar on the
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right side and it's in the the button is the thing and it's not right like the agent can see
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exactly what's happening and it has logs of exactly where I clicked I basically have
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immensely, like extremely quick iteration. And my favorite thing is that because I've got it
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plugged into Pear Core, the Pear Drive, there's too many naming conventions, but the peer-to-peer
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engine that we have in the background is that I'm hosting all of this myself and it will sync with
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all my other devices. I can plug in effects and elements and stuff straight from my Linux machine
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so that I can drop them right into this timeline and it will just automatically download them in
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the background and then display them and all that networking is free and it connects right to my
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machine I can do it land like here at home or away and this has been you know three years in the
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making for all this stuff the engine took an enormous amount of time because we had to go
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back to the drawing board like five different times but I've just been vibe coding like crazy
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I've just been building everything that I can possibly think of that I want to have in my
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workflow but my ability to produce the reason I am doing this read is because I am making my entire
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process and my entire workflow customized around the way that I work and the way that I think.
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And it'll be really cool. I might share this out. Maybe other people even want this app.
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It's super cool. My favorite thing about it is that I can edit and cut things out on the fly.
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I can click into this timeline immediately and look at my, you know, waveform, which I don't
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have the right now it will transcribe in the background, but I don't have the edit by text yet.
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That's something I'll be adding in, but I can click on it and then just edit. I can cut something
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and then put my playhead right where I want to record again
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and then start recording right back into it.
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And then because I've got a peer-to-peer engine,
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I'm going to get, right now it's just a remote control app,
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but I'm getting an app, basically the mobile version of this,
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so that I can pick up my mobile phone.
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I can stop here pick up my mobile phone and hold it up or go outside or something anywhere I don have to be on land I don have to be in the same network at home uh and record into the exact same timeline It awesome And this is making me so much more productive already Like I know
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that this building out these things in the workflow is going to have a feedback loop in my own
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system, my own like production of content. Uh, and at the exact same time, my production of the
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content using like the debug notes, that's the thing is that everything that we're building is
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going to be pair core enabled so that, you know, everything talks the same language, you know,
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it's kind of like the web, except that it's just peer to peer. So it doesn't, doesn't really matter
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what or how it's just establishing connections and then sharing information. And we have like
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kind of a schema and a base protocol for doing it in all the various ways you want to share
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information. And pair drive, the one that I'm sure you've heard me talk about is the one that's
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basically just the files, like thousands to hundreds of thousands of files. I have, I don't
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know, 300, 400,000 files or something on my Linux machine that is shared with my Mac right now,
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which I think I actually closed it because I was, I was working on something, but I have the same
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debug notes idea inside of pair drive syncing over pair drive to my agents to fix problems
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and sort out when things aren't working properly and it's just everything has sped up so much
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and then the same thing is the reason i have multiple agents on multiple machines is because
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since they can all read transcripts for the exact same and and i can also sync my wikis like my
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memory, my harness data and saved connections and memory and project files and all that stuff.
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I can sync those between devices as well so that all of my agents basically have, they can, you
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know, kind of have their own separate isolated context, but then they can also get all of the
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project context together. They can all have the same context about the project. But the really
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cool thing is that like trying to test peer to peer stuff or networking stuff in a closed environment,
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like on this computer, you inevitably just you're missing so many, so much of the nuance
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of like the networking.
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Of course, you can find another fake computer inside the computer that you're on, right?
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You don't have a networking problem from your computer to your own computer.
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And having agents on different machines, which I built a little chat app again on top of
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Paracore does the exact same thing.
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It just syncs messages, which are basically so no-ster-signed events.
419
00:39:03,051 --> 00:39:09,731
That's the really crazy thing is that I'm doing exactly what they're saying in this thing because it's the easy way to do it.
420
00:39:10,091 --> 00:39:20,631
Paracore is just a set of signed keys and I have a Noster ID on top of it that basically is the master for the account.
421
00:39:21,211 --> 00:39:28,611
So you sign in just by saying this public key is also me in the group and then you sign out to remove and update that list.
422
00:39:28,611 --> 00:39:34,611
and because of that though is that my agents just generated their own keys and then I join them
423
00:39:34,611 --> 00:39:40,471
into I add them to the conversation and then they can chat back and forth and so it's kind of like
424
00:39:40,471 --> 00:39:47,151
buzz it's very much like buzz except for the fact that buzz did not have I actually stole a couple
425
00:39:47,151 --> 00:39:51,571
of things from buzz very recently because I forgot that it even existed until I read this piece the
426
00:39:51,571 --> 00:39:56,911
first time and I was like that's right I forgot about buzz and so we took some of the examples of
427
00:39:56,911 --> 00:40:02,831
things that are helpful inside of Buzz and applied them to the little random chat thing that I built,
428
00:40:03,231 --> 00:40:07,491
which I might release it. I don't really care. I'm not trying to build a chat app. I just,
429
00:40:07,491 --> 00:40:15,351
I needed it from my agents. And obviously the clear path to actually having it work well was
430
00:40:15,351 --> 00:40:20,871
to have them generate their own keys. And the agents literally have their own keys and we have
431
00:40:20,871 --> 00:40:26,031
our own conversation stack and I just have like budgets. So like I can set, you know,
432
00:40:26,031 --> 00:40:32,491
you guys go for an hour or two or use this many tokens before you stop.
433
00:40:32,991 --> 00:40:35,891
My main way that I use it is rounds, right?
434
00:40:36,051 --> 00:40:40,091
So if Kimmy on my Mac Mini is talking to Kimmy on my Linux machine,
435
00:40:40,211 --> 00:40:44,171
they're allowed to go three rounds back and forth until I interject or respond.
436
00:40:44,571 --> 00:40:47,951
Or I can bump that and be like add 10 rounds to this conversation
437
00:40:47,951 --> 00:40:51,691
so they can go back and forth and they can test things out and then send reports.
438
00:40:51,691 --> 00:40:55,971
And Kimmy on my Mac Mini and my Linux are basically red teamers for Claude.
439
00:40:56,031 --> 00:41:02,131
So I have Fable on my, or I'm running Fable in my MacBook Pro.
440
00:41:02,851 --> 00:41:08,391
And so all three of these computers can work in a live, like a real networking environment
441
00:41:08,391 --> 00:41:15,871
and directly share and sync logs over problems or reasons why streaming a file took too long
442
00:41:15,871 --> 00:41:18,011
or why there's a three second delay.
443
00:41:18,791 --> 00:41:25,431
Why did the previous stream still send four chunks after the user requested for the next stream?
444
00:41:25,431 --> 00:41:27,431
like those sorts of things.
445
00:41:27,431 --> 00:41:28,431
And I can just have them.
446
00:41:28,431 --> 00:41:29,811
I can let literally let them go.
447
00:41:29,811 --> 00:41:31,971
I've done it a number of times now where I just say like,
448
00:41:31,971 --> 00:41:36,311
go for three hours and find as many bugs and edge cases
449
00:41:36,311 --> 00:41:37,671
and stuff as you can.
450
00:41:37,671 --> 00:41:39,991
And I just let them run overnight.
451
00:41:39,997 --> 00:41:44,877
a burn through 50 bucks of tokens on Kimmy in PPQ.
452
00:41:45,037 --> 00:41:47,397
I plug both of them into PPQ.ai.
453
00:41:47,877 --> 00:41:49,997
Shout out to Matt for all this.
454
00:41:51,277 --> 00:41:54,757
But like this is such a massive acceleration
455
00:41:54,757 --> 00:41:57,777
and it's huge to,
456
00:41:58,037 --> 00:42:00,397
it's such a benefit to the whole team
457
00:42:00,397 --> 00:42:02,877
because I'm working with real developers too
458
00:42:02,877 --> 00:42:06,217
who are basically back and forth with these things
459
00:42:06,217 --> 00:42:09,237
to do the careful cleanup and implementation
460
00:42:09,237 --> 00:42:17,777
of this stuff. And it's just, it's wild. It is moving so fast. Some of the things that I've
461
00:42:17,777 --> 00:42:23,757
done in the last few days, not possible three months ago, not possible at all. And it has
462
00:42:23,757 --> 00:42:29,717
accelerated everything. The fact that I have this engine now, I can build peer-to-peer networking
463
00:42:29,717 --> 00:42:35,737
apps that I can put on my phone and make iOS builds up and Android builds up extremely quickly
464
00:42:35,737 --> 00:42:42,517
and start playing around with like my chat, my chat app, which is again, nothing fancy.
465
00:42:42,757 --> 00:42:48,217
I'm not trying to build a chat app, but I was able to make an iOS build for it for my agents
466
00:42:48,217 --> 00:42:52,377
so that I can, I can just sit here and I can chat with my agents.
467
00:42:53,237 --> 00:42:58,637
And this is like a report that Claude had on the last, I was working on like icons and
468
00:42:58,637 --> 00:42:59,277
stuff like that.
469
00:42:59,277 --> 00:43:03,937
And they can reach out, they have a, you know, API with PBQ or whatever.
470
00:43:03,937 --> 00:43:06,497
so they can actually generate icons and play around with stuff.
471
00:43:06,897 --> 00:43:08,917
The Opus 5.5 is actually really good with that,
472
00:43:08,997 --> 00:43:11,317
just like building an SVG file.
473
00:43:12,697 --> 00:43:13,597
If you want to do an action,
474
00:43:13,737 --> 00:43:15,877
this is actually a note for anybody who's listening to this.
475
00:43:15,877 --> 00:43:18,257
If you want to do an animation
476
00:43:18,257 --> 00:43:22,197
or a variation on an icon or something,
477
00:43:22,577 --> 00:43:24,937
don't use an image generation model.
478
00:43:25,437 --> 00:43:27,057
Use a LLM.
479
00:43:27,717 --> 00:43:31,197
Use Opus 5.5 or something like that,
480
00:43:31,257 --> 00:43:32,197
or even Kimmy,
481
00:43:32,197 --> 00:43:36,897
because it will simply look for tools to edit and do exact things.
482
00:43:37,477 --> 00:43:39,297
And there are even things where it could use,
483
00:43:39,437 --> 00:43:42,037
like maybe an image model is necessary
484
00:43:42,037 --> 00:43:45,397
to just iterate on like general icon ideas,
485
00:43:46,177 --> 00:43:47,937
but then it can tweak them,
486
00:43:48,337 --> 00:43:51,117
literally edit things inside an app
487
00:43:51,117 --> 00:43:53,517
in like kind of a Photoshop environment.
488
00:43:53,837 --> 00:43:55,397
And it's wild.
489
00:43:55,837 --> 00:43:56,917
It's super wild.
490
00:43:58,097 --> 00:43:59,797
And like once you have a platform,
491
00:43:59,797 --> 00:44:05,957
Like I just can't get over how useful the engine that we have created is.
492
00:44:06,237 --> 00:44:20,757
Because one of the things I still, again, lots of stuff to work out in regards to the interaction and like how I deal with adding people and collaboration into this.
493
00:44:20,897 --> 00:44:22,617
But that's basically where I'm going to.
494
00:44:22,777 --> 00:44:24,737
I want to, Johnny will be listening to this.
495
00:44:24,797 --> 00:44:26,157
My producer will be listening to this.
496
00:44:26,157 --> 00:44:33,857
and I want to have it so that I can invite,
497
00:44:34,177 --> 00:44:34,977
like right now I can,
498
00:44:35,497 --> 00:44:38,657
but the collaborative editing is just not,
499
00:44:38,857 --> 00:44:39,577
it's not right.
500
00:44:39,637 --> 00:44:40,917
I haven't worked out all the kinks yet,
501
00:44:41,597 --> 00:44:43,757
but it is just like a,
502
00:44:43,897 --> 00:44:46,837
it's basically like a Git history in a sense
503
00:44:46,837 --> 00:44:51,697
on the timeline that syncs between various people.
504
00:44:52,337 --> 00:44:54,917
So what I literally want to,
505
00:44:54,917 --> 00:44:59,197
I don't think it will be as soon as I get into tackling this specifically.
506
00:45:00,537 --> 00:45:05,177
I will be able to invite Johnny in,
507
00:45:05,297 --> 00:45:08,197
and I want to be able to propose and make edits on the timeline,
508
00:45:08,357 --> 00:45:10,857
both of us working in the timeline at the exact same time.
509
00:45:11,417 --> 00:45:14,837
And there's plenty of capability that this app won't do,
510
00:45:15,497 --> 00:45:17,697
and maybe some of it will be added.
511
00:45:17,817 --> 00:45:19,377
I don't think it needs to do everything
512
00:45:19,377 --> 00:45:23,477
because it just needs to do enough to make a quick production line of content.
513
00:45:23,477 --> 00:45:32,537
And I can just continually expand this by thinking about and just talking about the things that I wanted to do.
514
00:45:32,817 --> 00:45:35,937
Like that is what's wild about this.
515
00:45:36,377 --> 00:45:46,977
So the debug notes is my vibe coding is now just me dump like brain dumping ideas out or thoughts out into all the apps that I'm doing.
516
00:45:46,977 --> 00:45:57,157
I don't type anything or explain what I'm doing or where I am in the interface for any of the stuff I'm building anymore because of this.
517
00:45:57,477 --> 00:45:59,837
And I don't have to have a platform or a subscription.
518
00:46:00,037 --> 00:46:01,057
This is just peer-to-peer.
519
00:46:01,177 --> 00:46:03,777
It just automatically syncs between all my devices.
520
00:46:04,417 --> 00:46:05,837
And I can build anything.
521
00:46:06,337 --> 00:46:07,837
This is so freaking crazy.
522
00:46:08,077 --> 00:46:09,337
It's the most addictive thing in the world.
523
00:46:09,517 --> 00:46:11,277
I am literally addicted to vibe coding.
524
00:46:11,277 --> 00:46:16,577
I had to have a serious heart-to-heart because I hadn't produced anything for my show in a while.
525
00:46:16,977 --> 00:46:20,177
because I've been vibe coding shit.
526
00:46:20,557 --> 00:46:22,697
It's so, if you are like a creator,
527
00:46:23,297 --> 00:46:25,517
if you're somebody who just has ideas
528
00:46:25,517 --> 00:46:27,877
and you just always want to see or test stuff out,
529
00:46:28,177 --> 00:46:30,737
this is like the greatest and worst possible time
530
00:46:30,737 --> 00:46:32,457
because one of the most difficult things
531
00:46:32,457 --> 00:46:33,897
when you are a creator
532
00:46:33,897 --> 00:46:35,297
and you want to build stuff all the time
533
00:46:35,297 --> 00:46:37,237
is deciding what not to build.
534
00:46:37,577 --> 00:46:40,137
It's like, okay, I can build,
535
00:46:40,377 --> 00:46:42,497
I'll have a hundred things by the end of one day
536
00:46:42,497 --> 00:46:44,077
that I really, really want to build,
537
00:46:44,237 --> 00:46:46,197
but I can't possibly build all those things.
538
00:46:46,197 --> 00:46:57,990
So I do a good job of trying to be like okay I only going to build this one thing And then I do that for you know four months And then I have a hundred things that I trying to build And I have spread myself too thin and everything a disaster
539
00:46:57,990 --> 00:47:01,430
And I have to cut 90 of them out of my life, right?
540
00:47:01,530 --> 00:47:04,710
And, you know, narrow it back down to like three or four things.
541
00:47:05,150 --> 00:47:08,670
And I am in this constant cycle of like taking on too much crap,
542
00:47:08,970 --> 00:47:10,790
cutting it down to the stuff that really matters
543
00:47:10,790 --> 00:47:13,290
or the things that I'm like super excited about.
544
00:47:13,290 --> 00:47:21,210
but what's crazy is that like I'm so I can still be so productive and I can keep such measurable
545
00:47:21,210 --> 00:47:26,330
like concrete progress on so many of these projects like you can't you god please this
546
00:47:26,330 --> 00:47:31,470
you can't see this right now but Pericast is just open a new iteration and my agent oh my god I got
547
00:47:31,470 --> 00:47:34,730
to figure out how to do this hold on a second hold on a second I got to show you I'm gonna do this
548
00:47:34,730 --> 00:47:41,230
live so that you can see the whole entire screen this is my agent this is my agent right now
549
00:47:41,230 --> 00:47:49,630
testing the interface and building the solution to the thing I just talked about and made a memo of
550
00:47:49,630 --> 00:47:56,790
five minutes ago. And it's basically just running through everything while I am sitting here.
551
00:47:56,790 --> 00:48:04,530
This app is going to be better before I finish this episode. This is going to be applied to
552
00:48:04,530 --> 00:48:16,490
everything. Like, it's so crazy to see where we're going. And, you know, we talk about, like,
553
00:48:16,830 --> 00:48:21,670
direct feedback in an application. Like, I want to be able to have, like, my test guys, whoever's,
554
00:48:21,670 --> 00:48:26,730
like, doing this, to be able to, like, make debug notes. You know, to have, like, approved people
555
00:48:26,730 --> 00:48:32,010
with debugging notes so that other people using this can be like, why did I clicked on this thing
556
00:48:32,010 --> 00:48:59,390
And it came up over on the left side. Why would it come up on the left side? Like, I want people to just share when they're confused and see if I can get a few agents and myself to brainstorm, like do brainstorming sessions on what, you know, the lowest common denominator of confusion between various people is to make things happen very, very quickly and react intuitively to what the user's expecting.
557
00:48:59,390 --> 00:49:01,810
but it's just
558
00:49:01,810 --> 00:49:05,850
it's so wild
559
00:49:05,850 --> 00:49:08,250
we live in seriously wild times
560
00:49:08,250 --> 00:49:10,250
I see the compounding
561
00:49:10,250 --> 00:49:13,310
happening just in my stack
562
00:49:13,310 --> 00:49:16,310
just in the things that I am working on
563
00:49:16,310 --> 00:49:18,750
and it's hard to fathom
564
00:49:18,750 --> 00:49:20,990
how quickly that is going to fan out
565
00:49:20,990 --> 00:49:23,270
to the rest of the economy
566
00:49:23,270 --> 00:49:25,910
and to see how quickly
567
00:49:25,910 --> 00:49:28,370
the new models I'm using
568
00:49:28,370 --> 00:49:39,970
I'm using are able to functionally perform at a far greater depth and length of time.
569
00:49:40,590 --> 00:49:50,950
Basically depth in both ways, depth in time and depth in understanding or operational competence
570
00:49:50,950 --> 00:49:53,050
for the entire stack of the computer.
571
00:49:53,210 --> 00:49:57,590
Like I really think we're going to be able to take the application like pair drive and
572
00:49:57,590 --> 00:50:03,230
pair drop the things that we're building and like convert them into another language in like a few
573
00:50:03,230 --> 00:50:10,110
goes um and granted with the hyper core stack and some of the peer-to-peer stuff we're using
574
00:50:10,110 --> 00:50:15,110
uh i don't think we'll be changing the language a whole lot but there will be things that we can
575
00:50:15,110 --> 00:50:20,590
make far more efficient and builds that we can improve upon and it just it just comes to you
576
00:50:20,590 --> 00:50:28,990
know, hearing about stuff like that's the crazy thing about this. So when I find out about a new
577
00:50:28,990 --> 00:50:34,590
thing, like I found out about Graphify and a few things the other day, like I can literally just
578
00:50:34,590 --> 00:50:41,310
take the GitHub repo of a Twitter post of something that just sounds crazy. Give it to my agent,
579
00:50:41,610 --> 00:50:45,790
get it to read through in the context. Buzz. Oh, my God. Buzz is the perfect example. So I was
580
00:50:45,790 --> 00:50:50,850
reading this article from early writers and they talked, they mentioned Buzz and I was like, I
581
00:50:50,850 --> 00:50:56,270
forgot about Buzz. And I immediately took it, grabbed the GitHub, gave it to my agents who
582
00:50:56,270 --> 00:51:03,230
were in the conversation of the chat of the tool we built. It's like Buzz like and got it to go
583
00:51:03,230 --> 00:51:10,710
through and make a comparison, a comparison audit of what Buzz doesn't have that my my chat app had
584
00:51:10,710 --> 00:51:13,290
and what my chat app did not have that Buzz had
585
00:51:13,290 --> 00:51:17,290
and how to basically consolidate or pull
586
00:51:17,290 --> 00:51:19,530
what was interesting or valuable from that.
587
00:51:19,710 --> 00:51:21,390
And we literally just made a couple improvements
588
00:51:21,390 --> 00:51:23,770
just because like a project happened
589
00:51:23,770 --> 00:51:25,570
and it was done within an hour.
590
00:51:26,150 --> 00:51:29,450
And all I know is the conceptual level of like,
591
00:51:29,590 --> 00:51:30,610
oh no, this is a great feature.
592
00:51:31,110 --> 00:51:33,230
That's a great feature that I could totally add into this
593
00:51:33,230 --> 00:51:34,450
and we don't even have to do anything.
594
00:51:34,750 --> 00:51:37,030
And then it pushed a new iOS build to my phone
595
00:51:37,030 --> 00:51:39,190
and I was immediately talking to him with the new feature.
596
00:51:39,190 --> 00:51:47,670
like holy crap and we're gonna have robots doing this this is gonna be this is slowly going to
597
00:51:47,670 --> 00:51:56,570
trickle down to interfaces that turn into hands and machines working in the real world the the uh
598
00:51:56,570 --> 00:52:10,663
where oh man what was the what was the thing let me see if i can find you real quick i gonna pause Ah I almost gave up I almost gave up I could not find the thing And not even AI could find it AI sucks I couldn even find this post
599
00:52:11,283 --> 00:52:14,923
Okay, so this guy who invented Amazon Prime.
600
00:52:15,183 --> 00:52:17,463
I don't know if he actually invented Amazon Prime.
601
00:52:18,223 --> 00:52:19,663
After six years in stealth,
602
00:52:19,843 --> 00:52:21,263
Atomic Machines is out.
603
00:52:21,263 --> 00:52:23,303
Our mission, on-demand,
604
00:52:23,523 --> 00:52:24,963
universal command of matter.
605
00:52:25,403 --> 00:52:27,783
First beachhead, the matter compiler.
606
00:52:27,783 --> 00:52:34,863
An AI-native manufacturing system that builds working micro-machines from code alone.
607
00:52:35,463 --> 00:52:37,283
No per-product tooling.
608
00:52:37,803 --> 00:52:39,303
No process development.
609
00:52:39,883 --> 00:52:41,923
Different code, different machine.
610
00:52:43,063 --> 00:52:44,363
Doesn't a 3D printer do that?
611
00:52:44,663 --> 00:52:45,003
No.
612
00:52:45,723 --> 00:52:50,723
No manufacturing technology to date produces a different machine from a different digital input.
613
00:52:51,203 --> 00:52:55,943
Imagine a car factory where after a couple of cars roll off the line, a laptop emerges.
614
00:52:55,943 --> 00:52:58,063
then a bicycle, then a refrigerator.
615
00:52:58,563 --> 00:53:01,963
A 3D printer gives you a different shape, not a different machine.
616
00:53:02,923 --> 00:53:05,843
AI native is overused, so here's what it means for us.
617
00:53:05,943 --> 00:53:08,403
The entire physical system lives inside the AI loop.
618
00:53:08,763 --> 00:53:12,903
Every manufacturing operation is followed by precision metrology?
619
00:53:14,163 --> 00:53:15,923
Metrology? I don't know that word.
620
00:53:16,083 --> 00:53:17,543
Precision metrology.
621
00:53:18,443 --> 00:53:19,103
I'll have to look that up.
622
00:53:19,103 --> 00:53:22,623
We digitize the physical result and a part only proceeds if it's in spec.
623
00:53:22,763 --> 00:53:25,563
Deterministic process control, not statistical.
624
00:53:25,943 --> 00:53:29,043
That closes the intent to result loop.
625
00:53:29,403 --> 00:53:32,963
The AI adapts to errors and runs its own hardware in the loop experiments.
626
00:53:33,083 --> 00:53:33,803
Oh, that's crazy.
627
00:53:34,583 --> 00:53:39,983
I don't even think I caught quite exactly how that played out the first time I skimmed through this.
628
00:53:39,983 --> 00:53:46,283
In generating training data continuously, our Gen AI uses it to produce the device design and matter compiler input to build it.
629
00:53:46,543 --> 00:53:49,023
At maturity, prompt to product manufacturing.
630
00:53:49,463 --> 00:53:53,843
We've aimed the matter compiler at micro machines, tiny machines with moving parts, features measured in microns.
631
00:53:53,843 --> 00:53:55,783
Think millimeter scale robots.
632
00:53:55,903 --> 00:53:56,863
The universe is a grid.
633
00:53:57,283 --> 00:53:58,983
Seven physical domains, two purposes.
634
00:53:59,423 --> 00:54:01,783
Deliver energy and matter or encode information.
635
00:54:01,983 --> 00:54:04,743
Semi-fab has mastered one cell.
636
00:54:05,063 --> 00:54:05,643
Six are empty.
637
00:54:06,083 --> 00:54:10,723
MAMES engineers have brilliantly coaxed a few devices out of the semi-tool set over decades.
638
00:54:10,843 --> 00:54:12,883
Accelerometers, gyros, micromirrors, blah, blah, blah, blah.
639
00:54:13,063 --> 00:54:14,623
That's what the matter compiler brings.
640
00:54:14,943 --> 00:54:16,043
First micromachine out.
641
00:54:16,183 --> 00:54:18,203
Here, Prime Switch PS150.
642
00:54:18,363 --> 00:54:19,923
A new class of power relay.
643
00:54:20,343 --> 00:54:21,863
200 micro-ohms.
644
00:54:21,863 --> 00:54:24,963
Yeah, yeah, yeah.
645
00:54:24,963 --> 00:54:27,803
200 micro ohms on resistance,
646
00:54:28,423 --> 00:54:31,343
150 amp continuous in a 9.5 millimeter
647
00:54:31,343 --> 00:54:33,363
by three millimeter hermetic package.
648
00:54:33,763 --> 00:54:36,383
Opens in 50 microseconds to 1500 volts
649
00:54:36,383 --> 00:54:37,743
of true galvanic isolation,
650
00:54:37,883 --> 00:54:39,483
a thousand X faster than a contractor,
651
00:54:40,083 --> 00:54:43,203
a contactor, zero holding power
652
00:54:43,203 --> 00:54:45,323
shipping to early access customers matter.
653
00:54:45,943 --> 00:54:47,343
Early access customers now.
654
00:54:47,543 --> 00:54:48,083
Why it matters.
655
00:54:48,243 --> 00:54:51,303
AI data centers are moving 800 volts DC
656
00:54:51,303 --> 00:54:56,563
where a fault delivers destructive energy in microseconds
657
00:54:56,563 --> 00:54:58,923
and a DC arc won't put itself out.
658
00:54:59,343 --> 00:55:02,083
Mechanical protection is milliseconds too slow.
659
00:55:02,623 --> 00:55:08,883
Solid state is fast but can't isolate and bleeds heat on every amp it carries.
660
00:55:09,303 --> 00:55:12,663
Prime switch is the device in between that nobody could build.
661
00:55:13,443 --> 00:55:20,823
So this thing has built a micromachine as one of its first examples
662
00:55:20,823 --> 00:55:24,363
of something that manages to,
663
00:55:24,483 --> 00:55:27,183
in a hybrid breaker with a solid state bypass,
664
00:55:27,823 --> 00:55:29,303
the silicon interrupts,
665
00:55:29,623 --> 00:55:31,543
the metal carries and isolates,
666
00:55:31,763 --> 00:55:33,403
the breaker never arcs.
667
00:55:33,643 --> 00:55:36,123
The same device does transfer switching,
668
00:55:36,563 --> 00:55:37,243
hot swapping,
669
00:55:37,243 --> 00:55:40,243
and generally economizes semiconductor power
670
00:55:40,243 --> 00:55:42,143
across the 800 volt DC data center.
671
00:55:42,623 --> 00:55:45,323
No semiconductor fab can process prime switches materials
672
00:55:45,323 --> 00:55:46,983
or assemble its moving parts.
673
00:55:47,503 --> 00:55:49,523
It exists because the matter compiler exists.
674
00:55:49,523 --> 00:55:57,443
Matter compiler name for Neil Stephenson's The Diamond Age, which Neil Stephenson is great if you don't read his stuff.
675
00:55:57,723 --> 00:56:00,403
$250 million race to date. See it. Blah, blah, blah.
676
00:56:00,403 --> 00:56:27,683
This, the loop, the huge loop to break down here or to close on this is the capacity to quickly and aggressively iterate on the manufacturing process in exactly the same way I am able to iterate on my debugging process in this application, right?
677
00:56:27,683 --> 00:56:36,463
so going straight back to to my example here is I have this little debug note and if I have an error
678
00:56:36,463 --> 00:56:41,523
I can in fact uh oh I didn't I didn't close it I want to see I'm going to see real quick I want
679
00:56:41,523 --> 00:56:46,103
to see if this is actually done one second all right I'm actually fixing that problem and hopefully
680
00:56:46,103 --> 00:56:53,523
I'll actually have video in the background of the last few takes uh because my agent is working on
681
00:56:53,523 --> 00:56:57,523
it right now, but I got sick of waiting because I just wanted to finish this episode.
682
00:56:58,103 --> 00:57:04,283
Just interjecting that I went ahead and added a overdub feature where I can record my screen
683
00:57:04,283 --> 00:57:09,543
while listening to the clip that I just did so that I can do the stuff on my screen.
684
00:57:10,143 --> 00:57:31,677
And I just replaced the video that we lost And one of the things that I really wanted to bring up and talk about is when we look at the speed at which we iterate I have edited I have changed the application I am making this episode on three separate times before I finish recording the episode
685
00:57:31,677 --> 00:57:37,457
and I don't think this will ever really change outside of the fact like because I can just kind
686
00:57:37,457 --> 00:57:45,017
of add features like we are had already planned a overdub feature where I could go back and watch
687
00:57:45,017 --> 00:57:51,157
something in the timeline and then do my own screen recording after so I'm navigating the
688
00:57:51,157 --> 00:57:55,657
computer and I'm totally focused on navigating the computer and I'm listening to the stuff that I
689
00:57:55,657 --> 00:58:03,937
am saying in the episode and so that I can actually recover the the the scroll through
690
00:58:03,937 --> 00:58:08,397
the Twitter feed and stuff that I have because it was like take 49 there were like three takes that
691
00:58:08,397 --> 00:58:15,597
were got that got lost while the agent was editing the app but the point is is there's so much
692
00:58:15,597 --> 00:58:22,157
there's so much uncertainty in like what to actually invest in and what and counterparty
693
00:58:22,157 --> 00:58:28,497
risk in what will actually succeed versus fail and you don't know. But when your money is scarce,
694
00:58:29,137 --> 00:58:36,157
when your money can actually hold its value, it becomes the hurdle rate to beat.
695
00:58:37,297 --> 00:58:44,677
When you have, if your monetary value is increasing by 20% a year, then you don't want
696
00:58:44,677 --> 00:58:50,877
any debt going out at less than 20% because it means resources are going to be aggressively
697
00:58:50,877 --> 00:58:58,777
wasted. You want the scarcity of the money to set the standard. It's basically giving you the
698
00:58:58,777 --> 00:59:06,377
average rate of productivity increase. It's giving you the average rate of productive expansion
699
00:59:06,377 --> 00:59:14,397
across the economy. And you want debt to be reserved for those things that can clearly,
700
00:59:14,937 --> 00:59:20,037
that at least the people responsible for and who are taking on the risk of that investment,
701
00:59:20,037 --> 00:59:28,117
of that debt to be highly, highly confident that it will outpace the 20%, that it will outpace the
702
00:59:28,117 --> 00:59:33,397
hurdle rate because otherwise you're wasting resources. Otherwise, if you just did nothing
703
00:59:33,397 --> 00:59:38,877
and you let the people who were confident and who were willing to risk 20% a year interest
704
00:59:38,877 --> 00:59:44,297
on whatever endeavor that they're engaged in because they have far, far higher conviction
705
00:59:44,297 --> 00:59:45,897
that they're doing the right thing,
706
00:59:46,717 --> 00:59:49,257
you leave those resources for those people
707
00:59:49,257 --> 00:59:51,457
other than wasting them on something
708
00:59:51,457 --> 00:59:53,157
that's only going to get you 5%,
709
00:59:53,157 --> 00:59:56,077
which at a point where you're hitting a singularity
710
00:59:56,077 --> 00:59:57,317
is a 15% loss
711
00:59:57,317 --> 01:00:00,357
if you have a massive amount of productivity increase
712
01:00:00,357 --> 01:00:01,817
happening economy-wide.
713
01:00:02,317 --> 01:00:04,557
And the shift, like everything is going to be processed.
714
01:00:04,757 --> 01:00:06,877
I literally think we go from,
715
01:00:07,777 --> 01:00:12,077
my entire system has moved from
716
01:00:12,077 --> 01:00:19,317
basically something that you build and use continuously to a process that evolves every
717
01:00:19,317 --> 01:00:28,537
time I engage with it. Like I said, this app has changed three times and it's a full application
718
01:00:28,537 --> 01:00:35,557
built for my production flow. And obviously it's like chock full of bugs and there's some slop and
719
01:00:35,557 --> 01:00:39,957
there's technical debt. But that's one of the things that I do on a regular occurrence is I
720
01:00:39,957 --> 01:00:45,157
give it to my multiple agents and I tell them to go on an audit and clean up technical debt and
721
01:00:45,157 --> 01:00:50,197
universalize this thing. Like, why do we have, why do we build a grid system in one part of the
722
01:00:50,197 --> 01:00:53,677
sidebar and then a completely different one in a completely different part of the sidebar?
723
01:00:53,677 --> 01:00:57,677
We should have one grid system that we are applying to these two different locations and
724
01:00:57,677 --> 01:01:06,277
these two different, you know, inputs or like selection or group of media. And so like thinking
725
01:01:06,277 --> 01:01:15,217
and iterating and reacting to and judging the process is going to be the process itself.
726
01:01:15,937 --> 01:01:22,017
But what I love about this article and the reason I wanted to do this episode is just
727
01:01:22,017 --> 01:01:29,317
because it's so, it puts into perspective so much of what I have been stuck in and the
728
01:01:29,317 --> 01:01:35,377
reason why I haven't done any reads lately and so much of the stuff that we're building
729
01:01:35,377 --> 01:01:42,237
with the development team because I want to, I'm, I'm done. I'm done with like iCloud and I'm sick
730
01:01:42,237 --> 01:01:48,137
of these platforms and I don't, we don't need them. We can build all our own solutions. And,
731
01:01:48,317 --> 01:01:53,057
you know, there is eventually, we'll have all people building their own solutions to everything,
732
01:01:53,197 --> 01:01:58,277
you know, all that stuff, but stuff will coalesce. There will be standards developed.
733
01:01:59,057 --> 01:02:05,177
And I think I specifically posted a tweet and a Noster note about this recently,
734
01:02:05,377 --> 01:02:09,997
that I went from like six months to a year ago,
735
01:02:09,997 --> 01:02:12,877
I was kind of looking at things and thinking like open source
736
01:02:12,877 --> 01:02:15,097
had a really big opportunity.
737
01:02:15,097 --> 01:02:18,157
That we could end up where a ton of stuff being used
738
01:02:18,157 --> 01:02:23,157
by consumers was open source and where like Max Hillebrand
739
01:02:24,337 --> 01:02:27,057
was on the round table recently and something that I loved,
740
01:02:27,057 --> 01:02:29,977
a comment that he had made.
741
01:02:29,982 --> 01:02:32,422
almost like a year and a half ago maybe now,
742
01:02:32,922 --> 01:02:39,222
is that the average number of users for any exact specific piece of software
743
01:02:39,222 --> 01:02:42,542
or implementation may very well end up being one,
744
01:02:43,122 --> 01:02:47,682
where software is simply unique to the person's environment
745
01:02:47,682 --> 01:02:49,102
or to the person's system.
746
01:02:49,802 --> 01:02:53,482
But I think that means still that we should be building things
747
01:02:53,482 --> 01:02:57,702
with that concept in mind, with that modularity in mind,
748
01:02:57,702 --> 01:03:02,382
so that it can be quickly and easily modified
749
01:03:02,382 --> 01:03:06,142
for a separate environment or a separate user.
750
01:03:06,322 --> 01:03:09,542
Like we should be thinking of software as moldable things.
751
01:03:10,682 --> 01:03:14,602
And there's just so...
752
01:03:14,602 --> 01:03:16,842
The unlock is just going to be wild.
753
01:03:18,142 --> 01:03:22,542
It's going to be absolutely like breathtaking.
754
01:03:23,642 --> 01:03:25,562
The speed that it is already moving,
755
01:03:25,702 --> 01:03:27,582
if you're trying to stay up on the edge of it,
756
01:03:27,702 --> 01:03:31,602
and it'll also be really important to take a step back
757
01:03:31,602 --> 01:03:35,262
and take a breath every once in a while
758
01:03:35,262 --> 01:03:39,822
because I literally just got completely overwhelmed the other day.
759
01:03:39,942 --> 01:03:41,202
Actually, it was at the end of last week,
760
01:03:41,342 --> 01:03:44,762
and I completely shifted my entire focus
761
01:03:44,762 --> 01:03:46,902
and so much of what I was working on this week
762
01:03:46,902 --> 01:03:51,002
because of kind of the wall that I ran into at the end of last week
763
01:03:51,002 --> 01:03:55,202
where I literally spent five days vibe coding on everything,
764
01:03:55,202 --> 01:03:58,142
and I felt like I got nothing to the finish line,
765
01:03:58,262 --> 01:03:59,562
but I got so much.
766
01:04:00,522 --> 01:04:05,362
I spent today working basically with all of my tools
767
01:04:05,362 --> 01:04:08,902
in my production set,
768
01:04:09,502 --> 01:04:11,802
my entire flow that I've built
769
01:04:11,802 --> 01:04:14,522
and using my apps themselves
770
01:04:14,522 --> 01:04:16,322
and I've built my debugging process
771
01:04:16,322 --> 01:04:20,202
and my coordination process cleanly enough
772
01:04:20,202 --> 01:04:23,742
that it iterates on itself while I'm working.
773
01:04:25,202 --> 01:04:30,762
And I have simplified the crap out of that.
774
01:04:30,902 --> 01:04:45,439
And it is going to be we live in crazy times man We live in crazy times Like to be on the edge I love the comparison of light
775
01:04:46,279 --> 01:04:52,159
And what's crazy is that comparison, let me bring this back up.
776
01:04:52,579 --> 01:04:56,699
This is going to happen way faster.
777
01:04:57,599 --> 01:05:01,559
So, 1830, it was three hours of labor.
778
01:05:01,559 --> 01:05:05,139
three hours of labor for an hour of light.
779
01:05:05,279 --> 01:05:09,779
It is insane to consider technological progress
780
01:05:09,779 --> 01:05:12,239
that happened so quickly that,
781
01:05:12,779 --> 01:05:14,399
and I don't think it's a coincidence too,
782
01:05:14,579 --> 01:05:16,939
that like literacy rates were changing dramatically
783
01:05:16,939 --> 01:05:18,039
during these types of things,
784
01:05:18,139 --> 01:05:21,699
but that to read a story at night
785
01:05:21,699 --> 01:05:24,739
was an incredible luxury.
786
01:05:25,299 --> 01:05:28,419
Like you had to take a day's worth of work
787
01:05:28,419 --> 01:05:35,279
for the opportunity to sit down and read a book at night and have a little bit of light.
788
01:05:36,199 --> 01:05:39,799
And in 1900, 70 years later, it was 13 minutes.
789
01:05:40,259 --> 01:05:45,779
And then today, after the electrification of everything, which, you know, was early 1900s,
790
01:05:45,779 --> 01:05:58,239
today is 0.07 seconds, seven hundredths of a second to get an hour of light.
791
01:05:58,419 --> 01:06:04,419
this is going to happen to a unit of thought,
792
01:06:05,259 --> 01:06:12,819
to a unit of intelligent work and iteration.
793
01:06:13,599 --> 01:06:15,999
That is what's crazy about this.
794
01:06:15,999 --> 01:06:21,819
We are literally going from pure energy to output,
795
01:06:22,119 --> 01:06:25,759
and we are on one of the most aggressive iteration
796
01:06:25,759 --> 01:06:31,639
and improvement systems or structures,
797
01:06:31,939 --> 01:06:37,399
constructs of technological progress
798
01:06:37,399 --> 01:06:40,299
where we are closing that gap
799
01:06:40,299 --> 01:06:54,097
in just an unbelievable way straight from energy to output I don know how you could want to live at a different time
800
01:06:54,297 --> 01:06:56,037
Like, this is the craziest time in history.
801
01:06:57,537 --> 01:06:58,897
Like, this is so wild.
802
01:06:58,897 --> 01:07:05,157
You've got to understand, none of our political systems work in this environment.
803
01:07:06,337 --> 01:07:10,457
Like, the monetary system, the debt structure, none of this is going to hold up.
804
01:07:10,457 --> 01:07:19,737
this is such a fundamental shift to the productivity and process like things are
805
01:07:19,737 --> 01:07:25,217
literally going to change there are going to be so many borders rewritten or redrawn so many
806
01:07:25,217 --> 01:07:34,137
different systems altered that trying to define or understand what the world might look like in
807
01:07:34,137 --> 01:07:41,197
20 to 30 years, I think just becomes impossible to imagine. And the thing is, is that this took
808
01:07:41,197 --> 01:07:53,737
170 years, 180, 196 years. And we could very likely see the same thing occur when it comes
809
01:07:53,737 --> 01:07:59,017
to the idea of a unit of thought or a unit of intelligent, productive work toward a goal.
810
01:07:59,017 --> 01:08:03,357
we could see this same thing happen in a hundredth of the time
811
01:08:03,357 --> 01:08:08,417
in maybe not a hundredth maybe a fiftieth right like
812
01:08:08,417 --> 01:08:12,297
maybe 10 years 10 years five years too small
813
01:08:12,297 --> 01:08:14,977
but 10 years 20 years
814
01:08:14,977 --> 01:08:22,877
like this like I don't even how do you account for this
815
01:08:22,877 --> 01:08:27,997
this is the most insane deflationary mechanism
816
01:08:27,997 --> 01:08:29,437
ever
817
01:08:29,437 --> 01:08:31,137
ever
818
01:08:31,137 --> 01:08:33,777
and all of those scarce things
819
01:08:33,777 --> 01:08:36,057
the notion of
820
01:08:36,057 --> 01:08:37,517
like we have
821
01:08:37,517 --> 01:08:40,017
basically
822
01:08:40,017 --> 01:08:41,757
the scarce side has been
823
01:08:41,757 --> 01:08:42,457
untouched
824
01:08:42,457 --> 01:08:45,917
have outrun wage increases
825
01:08:45,917 --> 01:08:47,957
and inflation has just
826
01:08:47,957 --> 01:08:49,897
gathered into all of these things
827
01:08:49,897 --> 01:08:51,397
and this
828
01:08:51,397 --> 01:09:06,474
all the technology that is enabling this is shifting over here aggressively aggressively and it going to move so so fast Like I just I don even know what to say about it And I got to go
829
01:09:06,534 --> 01:09:11,414
I got to go hang out with my kid and get a little bit of sobriety back. Um, cause we live in wild
830
01:09:11,414 --> 01:09:19,334
times. Anyway, I just want to shout out this great article, crazy, crazy, crazy world we live in.
831
01:09:19,334 --> 01:09:22,414
And I hope you guys enjoy the episode.
832
01:09:23,014 --> 01:09:26,974
I'm very curious to hear what you think about a live read
833
01:09:26,974 --> 01:09:30,614
and the fact that I'm doing a video read now.
834
01:09:31,754 --> 01:09:34,794
It's fun to me.
835
01:09:34,974 --> 01:09:36,874
Like I have very much enjoyed this.
836
01:09:37,894 --> 01:09:41,794
And, you know, curious if you guys get anything out of it
837
01:09:41,794 --> 01:09:46,434
because I am iterating on my process and iterating my content a lot.
838
01:09:46,434 --> 01:09:49,494
and there are so many tools to tap into now
839
01:09:49,494 --> 01:09:51,014
and I got so much to share.
840
01:09:51,074 --> 01:09:53,974
I'm going to be doing videos about tools very, very soon
841
01:09:53,974 --> 01:09:56,794
because they are just moving a mile a minute
842
01:09:56,794 --> 01:09:59,554
and it is so cool to feel like I have my own platform
843
01:09:59,554 --> 01:10:04,174
to connect and network all my stuff together with.
844
01:10:04,174 --> 01:10:06,574
So I will catch you guys on the next episode.
845
01:10:06,714 --> 01:10:10,234
Shout out to Bitbox and Shift Crypto guys
846
01:10:10,234 --> 01:10:12,634
for keeping my Bitcoin safe
847
01:10:12,634 --> 01:10:14,254
and making a great hardware wallet,
848
01:10:14,254 --> 01:10:18,094
fully open source, red teaming like a champ,
849
01:10:18,414 --> 01:10:20,754
and being really good about security updates
850
01:10:20,754 --> 01:10:21,574
and all those things.
851
01:10:21,914 --> 01:10:23,814
So stay tuned, grab yourself one.
852
01:10:23,874 --> 01:10:26,634
You got a discount code in the show notes.
853
01:10:27,294 --> 01:10:29,494
And that will do it.
854
01:10:29,934 --> 01:10:31,194
I'll get you on the next episode.
855
01:10:31,314 --> 01:10:35,414
Until then, I am Guy Swan, and that's my two sets.
856
01:10:44,254 --> 01:11:06,674
Outro Music