Plain Strata
Plain Strata explains decentralized AI in plain language, for people who are curious but not yet expert. Two episodes a week: Tuesday's Pulse is the week's story, Thursday's Layer takes one idea apart, layer by layer. Hosted by Dastan Modubash, a solution engineer learning the field in public. The voices are AI-generated; the research and writing are human.
Episodes
Plain Strata: Could Not Check, Why Verifying AI Work Needs a Third Answer
A chemist asked to reproduce somebody else's experiment reaches a step her bench cannot carry out, and the form she has been handed has two boxes, reproduces and does not reproduce, so whatever she ticks is a lie about a paper she never tested. A network that pays strangers' machines to do AI work has built exactly that form for its checkers (a checker is a participant whose job is to say whether
Plain Strata: The Inference Subsidy, Who Pays for the Cheapest AI in the World
A network that pays strangers to serve AI does not pay them in dollars: every few minutes it prints new tokens (tradable coins that exist only on that network) and hands them to the machine owners, who cannot pay an electricity bill with a token and so sell it into a trading pool, an automated scale that walks the price down a little with every sale, which is how the cheapest AI serving in the ope
Plain Strata: Memory Access Patterns, How an Operator Reads Private Prompts Without Decrypting
A sealed virtual machine, a rented computer simulated in software whose memory is locked with a key that never leaves the chip, still has to reach into that memory to think, and reaching is a physical act on hardware it shares with the landlord who owns the building, so the landlord cannot read a single byte but can watch which memory addresses get touched, the way a floor creaks when somebody ope
Plain Strata: Attestation vs Re-Execution, Where Each Way of Checking AI Work Puts Your Trust
A chip can run your AI work inside a sealed booth and slide a signed note under the door saying what ran, and a $159 circuit board slid between a server's memory stick and its motherboard can cut the one wire the memory uses to complain about a failed write, so the booth keeps signing valid notes about yesterday's data. That note is called attestation, a chip vouching for its software with a key b
Plain Strata: The Stake-Weighted Middle
Every seventy-two minutes, a market that pays strangers to do AI work has to collapse a room full of disagreeing judges into one number, and the fix it uses is not the one you would guess: instead of averaging every validator's score, weighted by stake, the network finds the value that exactly half the stake agrees with and throws away everything above it, so a validator trying to enrich a secretl
Plain Strata: Stake Delegation, Who Holds the Vote Inside the Token
On Bittensor, the largest network trying to run artificial intelligence as an open market of strangers, the chain understands none of the AI work it pays for: it reads the scores that validators, the machines that grade the other machines, hand it every few minutes, mints new tokens to whoever scored well, and weighs each validator's scores by its stake, the tokens people have locked behind it, so
Plain Strata: Counterfactual Verification, Would the Discovery Have Happened Anyway
An AI research agent runs for days and comes back with a database query that is genuinely faster than the best published one, and every instrument this field owns for checking that work, re-running it yourself, leaving a window open in which anyone can post money and dispute it, demanding a small mathematical receipt that the stated computation was carried out, or asking the chip to vouch for the
Plain Strata: Compute as Collateral, Borrowing Against the Machines That Run Open AI
Running one of the big open AI models is not really a licensing question, it is a question of how many datacentre graphics cards you can put in one building at once, each costing about as much as a car, and somebody has to buy them first. Renting capacity is what almost everyone does, at prices now quoted in tens of billions of dollars for a few hundred megawatts, so the other path is owning, whic
Plain Strata: Hardware Attestation, Checking the Room Instead of the Answer
Your prompt has to be readable at the exact moment a model works on it, which means it sits in plain form in the working memory of a machine somebody else owns, and encrypting the disk and encrypting the wire do nothing about that second. Three of the four serious ways to check a stranger's AI work go straight at the answer, by running it again and comparing, by making the operator post money and
Plain Strata: The Easy Half, A Network Wants Miners to Run AI and Checking That Work Is the Hard Part
A Bitcoin miner picks a random number, runs it through a fixed scrambler, sees the result is not small enough and picks another, a few hundred trillion times since you started reading this sentence, and for seventeen years the standard complaint has been that all that electricity buys nothing. The complaint misreads the machine, because producing the winning number costs a planet and checking it c
Plain Strata: The Entry Fee, To Prove an AI Answer You Have to Round the Model Off First
Every way of checking an AI answer that anyone actually runs today works on somebody having money to lose: an operator posts a deposit and forfeits it if caught, or a paid crowd of watchers goes looking for lies, which is economics wearing a technical costume. There is exactly one exception, a cryptographic proof, meaning a small file that comes out different if the machine deviated anywhere and t
Plain Strata: Somebody Has to Sign, Open AI Models Now Come With a Revenue Line
An AI model is a very large pile of numbers in a file, so for three years the only thing standing between anyone and the best open ones was physical: the memory to hold them and the machines to run them. On August 12 a lab in Hangzhou published its largest model ever, 2.4 trillion of those numbers, under a new license that is free until your AI business passes fifty million dollars of revenue in a
Plain Strata: The Wiring Between Them
A thermostat is provably sound and a space heater is a dumb coil of wire, and if you set the heater on the shelf directly under the thermostat the room goes cold while the system reports success, because the instrument that was supposed to measure the room is now measuring the thing being paid to warm it. Every incentive system ever built is that same pair, a sensor that reads something and produc
Plain Strata: Nobody to Trust
A model cannot think about a message it cannot read, so for the second or two your question is being answered it sits decrypted in the working memory of a machine you will never see, which is why every privacy promise in AI today is a promise rather than a mechanism: encryption covers the wire and it covers the disk and it skips the moment in the middle. On August 5 a frontier lab put a number on
Plain Strata: Nobody Checks the Answer
An answer from an AI is text, and text carries no receipt, so the machine that produced yours could have run a model a tenth of the size, handed back something plausible, and pocketed the difference in electricity without leaving a single mark on the output. The obvious response is to check the work, except checking the work means doing the work again, and an industry that pays twice for every ans
Plain Strata: The Gate Was Never the License
In 1960 the journalist A. J. Liebling wrote that freedom of the press is guaranteed only to those who own one. The right to print was universal. The press was not. On July 27 a lab in Beijing published Kimi K3, the largest open AI model ever released: 2.8 trillion parameters, about 1.56 terabytes, a license permissive enough to build a business on. It costs nothing to download. Almost nobody can r
Plain Strata: Say Yes Once
Four questions stand between a piece of software and your money. Who is this. How has it behaved. Did it do the work correctly. And the one almost nobody built for: was it ever allowed to try at all. On July 22, that fourth question got its first serious infrastructure, when the XRP Ledger's payment service for agents began accepting signed spending mandates from Mastercard, checked by a risk engi
Plain Strata: No Handshake Required
This week's story in decentralized AI is not a launch. It is a deletion. On July 28, a specification called MCP, the wiring that lets an AI model reach outside its own head to open a file or run a search, deleted the session: no handshake, no session ID, no line held open.
Until this week that wiring worked like a phone call. You dialed in, one operator picked up, and that one machine was the onl
Plain Strata: The Name That Stays
A software agent can be copied, forked, upgraded, or run as a thousand identical instances at once. None of them remembers the last job. And yet, as of this month, more than 200,000 agents on a single blockchain are carrying a permanent, public reputation that follows them from one service to the next.
This episode is about why that works. The standard is called ERC-8004. It adds the smallest pos
Plain Strata: A Name and a Wallet
This week, software agents got the two things they need to do business on their own: a way to pay, and a name that means something. Both arrived at real scale, backed by real institutions, in the same handful of days.
The payment side: on July 14, the Linux Foundation launched the x402 Foundation, with 40 members including Visa, Mastercard, Stripe, Google, and Coinbase steering a payment standard
Plain Strata: The Scorekeeper
The Thursday Layer. A training company called Prime Intellect just raised 130 million dollars, at a valuation near a billion, to sell something far less glamorous than a faster computer: a trustworthy way to tell an AI agent whether it did the job well. For two years the hard problem in training AI looked like a computing problem. That problem is basically solved; computers are for rent from a doz
Plain Strata: Train Your Own
The Tuesday Pulse. On July 8, the US government cleared GPT-5.6 for broad public sale after two weeks behind a case-by-case approval gate, twenty companies, each individually cleared. The same day, a training company called Prime Intellect raised 130 million dollars, at a reported billion dollar valuation, on the opposite bet: that companies should stop renting frontier AI and start training their
Plain Strata: The Third Rail
The Tuesday Pulse. For twenty-nine years, the web reserved a status code for payments, number 402, "Payment Required," and never once used it. This year two rival teams moved into that empty room two weeks apart. Coinbase's x402 answers a paywall in one shot: an agent pays a few cents in a stablecoin and gets its content, more than 160 million machine-to-machine payments since April. Stripe's Mach
Plain Strata: Why the Frontier Stays in One Room
The Thursday Layer. In late 2025, the team with the best claim to dislike centralized AI did the centralized thing: Prime Intellect, whose whole identity is training models scattered across homes and offices on different continents, put every chip for its strongest model, INTELLECT-3, in one building, and trained it the old way. Not a loss of nerve. A number. Every training step, thousands of proc
Plain Strata: The Permission Slip
The Tuesday Pulse. On Friday, the most powerful AI available to the public shipped, and to use the most capable version you first needed approval from the US government: around twenty companies, cleared case by case by the White House, after the model scored 96.7% on a cyberattack test and crossed the government's threshold for a high-risk system. The company complied, then asked that this kind of
When a Network Sells Itself
The Thursday Layer. On a decentralized AI network, the safest yield is paid by a machine that, every twelve seconds, sells off slivers of the very tokens the network is built on. No one decided the network was failing; it is just how the return gets paid, and the belt sells the thriving subnets and the dying ones with the same indifference. This episode takes apart a proposal, Root Reborn, that wo
The Off-Switch
The first episode of Plain Strata. This June, the most capable AI ever opened to the public went dark for the whole world, three days after launch, because of one letter. The United States Commerce Department ordered Anthropic to cut off every foreign national, and to obey a rule about some people, the company switched its model off for everyone. That is what an off switch looks like when someone
Plain Strata B8: Who Decides?
Across this series we have watched decentralized AI networks do remarkable things with no company in charge. Serve answers. Verify work nobody watched. Pay strangers. Run software that acts on its own. But a question has been lurking under all of it. Someone, somehow, decides what model runs, what the rules are, how the money is spent, and what happens when those rules need to change. If there is
Plain Strata B7: Agents With Wallets
Most software waits to be told what to do. You click, it responds. An agent is different: software that acts on its own, in a loop, pursuing a goal without a human pressing the button each time. Now give that agent its own money and the ability to spend it, and put its identity and its actions on a public ledger where anyone can audit them. You have something genuinely new: software that does busi
Plain Strata B6: Airbnb for GPUs
Training and running AI needs one specific, expensive ingredient: graphics processing units, the chips that do the enormous parallel arithmetic neural networks demand. They are scarce, they are costly, and most of the world's supply sits inside a handful of giant cloud companies. So a natural question arises. Could you rent GPU time from anyone who happens to have a spare one, the way you rent a s
Plain Strata B5: Harder to Build Than to Use
One question splits this whole field in two: are you using an AI model, or building one? Using a finished model to answer a question is called inference, and decentralizing it is hard but solved, running in production today. Building the model in the first place, out of mountains of examples, is called training, and decentralizing that is the frontier nobody has cracked.
Inference is a single sel
Plain Strata B4: The Oracle Pattern
A blockchain is a strange kind of computer. It is extraordinarily good at agreeing on a shared record nobody can secretly alter, and almost comically bad at knowing anything about the world outside itself. It cannot check the price of a stock. It cannot read a website. It cannot tell whether an AI model produced a good answer. It is, in a real sense, blind.
That is not a bug to be patched. It fol
Plain Strata B3: Skin in the Game
A landlord hands an apartment key to a tenant they have never met. The tenant could trash the place, skip town, and never pay for the damage. What stops them? Not the landlord's trust, and not the tenant's good character. A security deposit. A pile of the tenant's own money that disappears if the apartment gets wrecked. The deposit converts a question of character into a question of arithmetic.
D
Plain Strata B2: Three Ways to Trust an Answer
You send a hard math problem to a stranger on the internet and pay them to solve it. A minute later they send back an answer. How do you know they actually solved it? Maybe they ran the real calculation. Maybe they guessed. Maybe they ran a cheaper, sloppier method and pocketed the difference. You did not watch them work.
Now make the problem an AI model with billions of internal numbers, and the
Plain Strata B1: One Question, End to End
Somewhere in Singapore, a computer with a powerful graphics card sits in a rack, fans spinning, waiting. Somewhere in Frankfurt, a different machine waits, this one with no fancy card but a very fast connection. The two have never met and will never speak to each other except through ordinary web requests. A person in Toronto types a question, and twenty seconds later words start streaming back on
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