Other (15)

• Anthropic's Mythos model is significantly larger than previous models, with over 10 trillion parameters, making it exceptionally skilled in coding but also slow, expensive, and dangerous due to emergent hacking capabilities.
• Anthropic withheld Mythos from public release, citing concerns over its malicious use for hacking; Project Glass Wing allows critical infrastructure companies like Windows and Cisco to use it for proactive bug detection.
• Ben notes that external tests show OpenAI's GPT 5.4 Pro replicated almost all security vulnerabilities found by Mythos, suggesting similar capabilities may already be widespread and accessible.
• Theo criticizes public benchmarks comparing Mythos and GPT 5.4 Pro, arguing they fail to measure actual hacking or security capabilities and may be misleading.
• Theo contends that exceptional coding ability in AI models inherently leads to emergent security capabilities, creating a new hacker archetype that can leverage AI to bridge knowledge gaps and bypass traditional research experience.
• Anthropic's security testing for Mythos involved spinning up 100 to 5,000 parallel runs, each seeded with a different project file from a codebase of approximately 1,000 files, with researchers later reviewing detected exploits.
• Ben and Theo confirmed that Claude Opus 4.6 models can be tricked into leaking their system prompts and internal reasoning traces, demonstrating a vulnerability where smart models can rationalize revealing sensitive configuration data.
• Robert C. Martin ("Uncle Bob"), author of "Clean Code," has shifted his perspective to embrace agentic engineering, suggesting AI makes programming syntax less important and prioritizes interfaces.
• Robert C. Martin proposes using AI to conduct programming experiments (e.g., dynamic vs. static typing) without human bias, highlighting an under-explored research area for optimizing AI agent performance with different technologies.
• Ben emphasizes that even advanced AI models require constant feedback loops like linting, type checks, and formatting commands to correct hallucinations and converge on correct code, rather than achieving perfection in a single attempt.
• Ben converted his complex BTCA CLI tool into a 30-line Claude skill, demonstrating how AI agents can turn simple markdown instructions into fully functional applications, replacing traditional deterministic programs.
• Ben praises Gary Tan's GStack approach, which uses collections of markdown-based "skills" in Claude Code to instruct AI agents, allowing for dynamic programming through high-level directions rather than conventional code.
• Ben endorses the "Boiling the Ocean" thesis, advocating for extensive AI-driven experimentation because the cost of trying new things is low, and AI models consistently exceed perceived limitations.
• Gary Tan's article, "Thin Harness Fat Skills," differentiates between "deterministic" (traditional, predictable code) and "latent" (dynamic, non-deterministic AI actions) programming, underscoring AI's creative potential in system design.
• Theo notes that Gary Tan's GBrain project, which processes daily AI session data to build memory systems, enables models to "learn while they sleep," which Theo considers a key component of Artificial General Intelligence (AGI).

AI & Tech (7)

• Brett argues AI companies make allocation decisions between training, enterprise service, and consumer business to maximize valuation ahead of a public market entry, securing capital for future compute.
• Nick sees Meta as a formidable competitor in AI because its advertising business lets it deliver a consumer experience without directly monetizing the model, and it doesn't have to sell compute to others.
• Nick argues product and distribution ultimately win in AI, citing Cohere's enterprise success based on product fit rather than model capability.
• Brett notes OpenAI invests more in model training and has better medium-term compute access than Anthropic, per public reports, which affects their product roadmaps.
• Consumer AI use cases have changed little in three years despite model improvements, while enterprise use has diversified as workers actively seek tools to lighten their workloads.
• On the enterprise side, Brett argues market share will stabilize around compute supply because if a provider like Anthropic signs too many customers and lacks capacity, customers will churn to a competitor.
• The group discusses a concept for a new trust-based social network where AI agents interact only with agents of vetted contacts, arguing current algorithmic social media adulterates real friendship.

War (1)

• Keon discusses a story about an F-15E Strike Eagle aircraft with two airmen being shot down over Iran.

Mining (3)

• Dan, a Bitcoiner in Iceland, shares his experience with a home Bitcoin mining heater called the Open Two from a company called 21 Energy.
• Dan reports his mining unit achieved 43 terahash per second but was too loud, and that his total household power consumption was nearly 4,000 kilowatt hours over three months at a cost equivalent to $681.
• Dan earned 115,000 sats, worth about $80, from his mining heater over the same period, projecting a 26-month payback period for the device.

Adoption (1)

• NeedCreations launched btcedu.app, a Bitcoin education archive where users can earn points and withdraw 100 sats after accumulating 1,000 points.

Protocol (4)

• Keon cites Brian Quintin's Myers-Briggs survey showing Bitcoiners heavily skew toward INTJ (34%) and INTP (22%) personality types, diverging significantly from the general population.
• Keon sees the open-agents movement, where people sell compute for Bitcoin, as a bullish counterbalance to centralized AI power and a potential defense against models like Mythos.
• Aardvark proposes a quantum-safe Bitcoin transaction scheme using Lamport signatures, which results in a 10,000-byte script size and requires 150 dummy signatures with hash commitments.
• The hosts discuss the upcoming movie 'Killing Satoshi,' directed by Doug Liman and starring Pete Davidson, Casey Affleck, and Gal Gadot, which fictionalizes an investigator trying to expose Bitcoin's creator.

AI & Tech (3)

• The hosts discuss a New Yorker article characterizing Sam Altman as dishonest, citing his firing from OpenAI's board and claims of misleading Anthropic's founder about AI safety commitments.
• Anthropic is working with 40 companies through 'Project Glasswing' to test its new AI model, Mythos, for cybersecurity vulnerabilities before a public release.
• The hosts express concern that Mythos could find zero-day vulnerabilities in critical open-source software, including Bitcoin Core, posing a significant security threat if capabilities are locked away.

War (1)

• Marty Bent notes US Navy blockaded Iranian ports in the Strait of Hormuz, following brief talks between JD Vance and an Iranian faction, leading to oil market escalation.

Markets (1)

• John highlights a map from Rory Johnson showing a significant redirection of Very Large Crude Carriers (VLCCs) to the US Gulf, indicating a shift in oil market leverage towards the US amid global artery closures.

Trade (1)

• China is curbing sulfuric acid exports starting in May, responding to perceived US leverage and potential disruption to metal processing, phosphate fertilizers, and fibers.

BTC Markets (2)

• Marty and John observe Bitcoin's relative strength, trading around $71,800, acting as a risk-off asset during geopolitical and financial uncertainty, contrary to past liquidity crises.
• John suggests a fractured, multipolar global order, where just-in-time supply chains falter and trust diminishes, creates an ideal environment for Bitcoin as a neutral, sovereign store of value.

AI & Tech (1)

• Anthropic's Mythos AI model is presented as a significant step function improvement, with reports of it finding zero-day bugs in critical software, prompting national security concerns and government attention.