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Milan says private AI requires crypto payments for scale

Wednesday, May 27, 2026 · from 4 podcasts
Ungovernable MisfitsThe Jake Woodhouse Podcas…Peter Attia DriveAI Daily Brief
  • NanoGPT's users have paid with Monero for ten months straight, choosing privacy over card-based surveillance.
  • Proprietary models like Claude Opus still dominate for quality, maintaining a 3-6 month lead over open-source rivals.
  • The AI revenue boom is confirmed, with Google Cloud up 63% and Amazon targeting $200B in annual AI infrastructure spending.

Private AI can't scale on the credit card rails used by ChatGPT. Milan, co-founder of NanoGPT, argues billing identities turn every medical query or personal prompt into a data-point that feeds the model provider's central database. For a platform built to avoid that surveillance, the payment method became decisive.

Monero emerged as the dominant currency. NanoGPT supports twenty crypto assets, but for ten consecutive months, users have primarily paid in XMR. Milan sees this as the foundation for a circular crypto economy where software agents manage their own wallets to buy compute as needed, removing the human from a surveillance-tainted transaction loop.

The quality gap keeps users paying for the best. On NanoGPT, Anthropic's Claude Opus 4.7 is used five times more than any other model. Milan notes closed-source leaders maintain a three-to-six month performance lead over open-weight alternatives like GLM or DeepSeek, making them the default for high-stakes coding or medical advice.

"Credit cards are the ultimate honeypot for AI labs."

- Milan, Ungovernable Misfits

The demand fueling this privacy arms race is massive and proven. Nathaniel Whittemore notes Google Cloud revenue surged 63% year-over-year, with AI as the primary driver. Amazon plans to spend $200 billion annually on AI infrastructure, a sign the monetization phase is already here. The market has moved past asking 'if' to racing to build enough data centers.

The frontier is now the harness, not the model. Performance data shows the same model can produce wildly different results based on its runtime environment. GPT-5.5's functionality score jumped from 61% to 87% when moved from its native harness to Cursor's, suggesting the competitive advantage is shifting to the execution layer.

For mainstream businesses, the AI tool is already the COO. Jake Woodhouse built a full marketing funnel in a week using Claude as a multi-role executive, solving technical roadblocks from DNS updates to ad campaigns. He argues adoption is more immediate than Bitcoin because the ROI - identifying operational 'leaks' - is visible within weeks.

"The narrative has shifted from 'if' companies can monetize AI to how fast they can build the data centers to handle the load."

- Nathaniel Whittemore, The AI Daily Brief

The stack is splitting: privacy-seeking users route through crypto and local buffers, while enterprises pour billions into scalable cloud harnesses. The connection is liquidity; private AI needs a payment rail that isn't a tracking device, and for a growing cohort, that rail is crypto.

#AI Infrastructure#Models#Privacy#Stablecoins
Nathaniel WhittemoreAmazonAnthropicDeepSeekBitcoinChatGPTClaudeGoogle CloudMoneroCursorGoogleGPTGPT-5

Source Intelligence

- Deep dive into what was said in the episodes

Ungovernable Misfits
Ungovernable Misfits

AI Sub Slave VS NanoGPT with Milan | FREEDOM TECH FRIDAY 41 • May 26

  • Milan explains NanoGPT offers subscription and pay-per-prompt access to hundreds of text, image, video, and audio AI models through a single interface, with strong privacy defaults and crypto payments.
  • Milan says OpenAI's GPT 5.5 and Anthropic's Claude Opus 4.7 are the leading closed-source AI models for general chat and coding. Claude Opus 4.7 is used five times more than any other model on NanoGPT.
  • Milan states Google's Gemini 3.5 Flash is a top closed-source model because it is very fast and cheaper, while Opus 4.7 is expensive and slower.
  • Milan argues open-source text models like GLM 5.1, DeepSeek V4 Pro, and Kimi K 2.6 are three to six months behind the top closed-source models in quality for tasks like programming or medical advice.
  • Milan notes open-source competition drives down AI model costs and increases efficiency, while closed-source models have fixed prices due to monopolies from providers like OpenAI or Azure.
  • Milan observes running top AI models locally on consumer hardware like a MacBook or phone is currently unrealistic due to their size, but smaller image models are more feasible for local use.
  • Milan says proprietary image models like Midjourney and GPT Image 2 offer higher quality than open-source options, but they impose stricter content censorship than local fine-tuned models.
  • Milan describes users employing NanoGPT for creative applications like detailed role-playing in constructed worlds and automated polymarket betting operations where AI agents research and place wagers.
  • Milan founded NanoGPT as a Telegram bot to let people pay small amounts in crypto to try ChatGPT, aiming to make AI accessible without credit cards or personal data after his own privacy experiences at a central bank.
  • Milan says NanoGPT prioritizes privacy by default, allowing use without accounts and storing data locally, but added optional encrypted storage and Google sign-in for users who want syncing.
  • Milan states NanoGPT's development is driven 90% by user feedback, leading to additions like video and audio models, APIs, trusted execution environments, and a browser-installed local model for memory.
  • Milan demonstrates NanoGPT's local model feature, which downloads a 500 million parameter model directly in the browser for tasks like conversation memory, aiming for accessibility on basic devices.
  • Milan explains NanoGPT's global memory uses a local model to learn user background details across chats, while context memory expands a model's window by feeding it only the most important parts of long conversations.
  • Milan notes users can optimize costs by using expensive models like Claude Opus as orchestrators and cheaper models for simple tasks, or by setting spending limits and choosing between premium, standard, or basic auto-model routing.
  • Milan says NanoGPT's OpenAI-compatible API allows integration with any coding harness or agent tool like Claude CLI, and its agents page provides endpoints for web search, image generation, and other functions discoverable by AI models.
  • Milan advises starting AI agent setups in a sandboxed environment like a separate computer or VPS and using AI models themselves to configure the workflows, rather than giving them blind access to emails or local files.
Also from this episode: (2)

AI & Tech (2)

  • Milan explains NanoGPT supports around twenty cryptocurrencies, with Monero being the most used for ten months, followed by Bitcoin and Nano, to meet users where they are and foster a circular crypto ecosystem.
  • Milan outlines NanoGPT pricing: a $12 monthly subscription for open-source models with a 30-60 million token weekly allowance, or pay-per-prompt starting at $1, where costs vary widely based on model and task complexity.
#Agents#Open Source#Stablecoins#Coding
The Jake Woodhouse Podcast
The Jake Woodhouse Podcast

Behind the Scenes: Using AI to Build a Real Business in Real Time (JWP125) • May 25

  • Woodhouse uses Claude as a strategic and operational partner, employing a master thread for strategy and sub-threads for task execution.
Also from this episode: (12)

AI & Tech (11)

  • Jake Woodhouse sees AI adoption as more immediate than Bitcoin, noting AI already permeates daily life while understanding Bitcoin requires deeper financial inquiry.
  • Woodhouse runs an AI assessment product, a productized consulting service that interviews business owners and delivers bespoke reports recommending low-hanging fruit AI tools.
  • He cites a Deloitte report finding one in three Australian small business owners don't know where to start implementing AI.
  • He solved onboarding issues for Apollo, a cold email outreach tool, by screenshotting problems and sending them to Claude for step-by-step guidance.
  • Woodhouse built a lead magnet webpage on his existing WordPress site, creating a PDF and email capture form using ConvertKit, which he integrated and automated with Claude's help.
  • Claude assisted him in updating DNS records on Squarespace to ensure email deliverability, a task he would have previously outsourced.
  • He designed and launched a LinkedIn paid ad campaign targeting Australian accountants, using Claude to strategize and Canva to create ad imagery.
  • Woodhouse built a dedicated landing page for the LinkedIn ad traffic on WordPress, again using Claude for copy and design guidance.
  • He asserts AI tools enable execution two to four times faster than traditional methods like Google searches, podcasts, or business books.
  • Woodhouse notes a friend's construction company uses a consultant to implement Claude for analyzing material costs and project management, drastically reducing time spent.
  • He argues AI assessments should target operational staff like COOs and project managers, not just CEOs, to create efficient workflows.

Startups (1)

  • Woodhouse claims he built a complete marketing funnel from scratch in one week despite having no technical background and multiple other commitments.
#Startups#Labor#Enterprise
The Peter Attia Drive
The Peter Attia Drive

#393 ‒ AMA #85: A guide to medications and supplements: determining what to take, what to skip, and how to know if they're working for you • May 25

Also from this episode: (6)

Longevity (5)

  • Peter Attia argues exercise is the single most effective lifespan and healthspan intervention, citing superior impact on all-cause mortality compared to smoking cessation, hypertension, lipid, and diabetes management.
  • Attia uses a 'Centenarian Decathlon' exercise with patients, forcing them to rank ten physical goals for their last decade and mapping the functional requirements needed to achieve them.
  • Attia's longevity strategy focuses on extending life without chronic disease, distinguishing it from the 'Medicine 2.0' model of managing life with chronic illness.
  • Attia states a zero coronary artery calcium score carries an approximate 15% risk of being a false negative, noting he has seen many cases of soft plaque on CTA scans after a zero CAC result.
  • Attia believes APOB is an unambiguous causal driver of atherosclerosis and must be treated even in metabolically healthy individuals, using an APOB of 150 as an example to treat down to a goal of 60 in a clean-artery patient.

Health (1)

  • Attia compares treating high APOB in a patient with pristine arteries to convincing a new smoker to quit before lung damage appears, arguing causality not certainty guides the intervention.
#Longevity#Health#Exercise#Nutrition
The AI Daily Brief: Artificial Intelligence News and Analysis
The AI Daily Brief: Artificial Intelligence News and Analysis

Nathaniel Whittemore

Why Agents Still Need Humans • May 24

  • Nathaniel Whittemore frames the agent landscape in three phases: the weights phase focused on model parameters, the context phase centered on prompts and RAG, and the current harness engineering phase, which builds persistent environments around static models.
  • Sam Altman told Ben Thompson the harness runtime is inseparable from model performance for effective agents, conceding he often cannot distinguish whether a great outcome stems from the model or its surrounding tools and state.
  • Google Cloud revenue grew 63% year-over-year, with a $460 billion backlog in new orders, up from $240 billion in Q4. CEO Sundar Pichai said AI is now the cloud unit's largest growth driver, though compute constraints limited revenue.
  • Google reported a 40% quarter-over-quarter surge in paid enterprise Gemini customers. The company's infrastructure now processes 16 billion tokens per minute, a 60% increase from the previous quarter.
  • AWS revenue grew 28% year-over-year, its fastest pace in nearly four years, making it a $152 billion annual recurring revenue business. Amazon added more server capacity than any other company in 2025.
  • Amazon's Q1 capital spending hit $43.2 billion, a 60% jump from last year, driving free cash flow down to $1.2 billion from nearly $26 billion. CEO Andy Jassy said the company's custom silicon business would be a top-three data center chipmaker if standalone.
  • Microsoft reported 39% Azure growth and 20 million paid Copilot seats, up from 15 million in January. CFO Amy Hood projected Azure's 40% growth rate to continue into Q2 and lifted annual CapEx guidance by $25 billion to $190 billion.
  • Meta reported quarterly revenue of $56.3 billion, up 33% year-over-year, but raised its 2025 CapEx forecast from $135 billion to $145 billion. The stock fell 5% as the market reacted negatively to the increased spending.
  • Whittemore argues harness as a service tools like the Cursor SDK represent a new infrastructure category, providing a pre-built agent runtime that handles tool dispatch, sandboxing, and error handling so builders only need to supply a model, tools, and a task.
  • An Endor Labs report found GPT-5.5's functionality score on a coding benchmark jumped from 61.5% to 87.2% when switched into Cursor's harness, demonstrating how the runtime environment dramatically changes model performance.
  • Early Cursor SDK use cases include a Gmail-integrated coding agent and a bug-catching agent that can view a live app in a browser, aiming to close the feedback loop between agent-written code and real-world performance.
#AI Infrastructure#Big Tech#Enterprise#Agents#Chips

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