May 2026
Lukas Czinger, chief executive of Divergent Technologies, argues on This Week in Startups that U.S. defense manufacturing can move faster and at lower cost if factories are treated as software-defined infrastructure rather than product-specific plants. The article also follows Brandon Goode and Mark Horowitz’s case for Outro Health: that antidepressant prescribing has scaled without an equally developed system for helping patients stop safely. Across the defense, healthcare and AI segments, the source frames the central problem as incentives — what existing systems pay companies to build, maintain or automate, and what they leave underbuilt.
John Coogan and Jordi Hays use the reported IPO plans of SpaceX, OpenAI and Anthropic to argue that the U.S. tech market is not entering a modest reopening but a concentrated “giga boom” led by companies large enough to reshape indices, capital flows and investor expectations. The Diet TBPN segment extends that scale argument across Starship’s role in SpaceX’s filing, AI infrastructure bottlenecks, frontier-model oversight and the disappearance of world’s fairs as a public stage for technological ambition.
Gavin Baker joined the All-In panel to argue that AI’s economics are becoming tangible: Anthropic’s reported profitability, surging LLM revenue, Nvidia’s results, and SpaceX’s compute contracts all point to infrastructure demand that is no longer speculative. The group framed SpaceX’s potential $2 trillion valuation as a bet on Starlink, launch, and AI compute rather than current earnings, while Baker defended Nvidia against share-loss and GPU-useful-life bear cases. The counterweight was political and macro risk: public backlash to AI, labor displacement, regulation, higher inflation, rising yields, and U.S.-China tension.
Bloomberg reports that SpaceX’s upgraded Starship launched from Texas, reached space within minutes, and deployed 20 dummy Starlink satellites in a closely watched test flight. The source frames the launch as a demonstration of improvements over earlier Starship prototypes, with the clearest technical marker coming at T+30 seconds, when all 33 Raptor 3 engines on Booster V3 were reported operating.
OpenAI is presenting workspace agents in ChatGPT as shared, scheduled operators for repeatable team workflows, generally available to Business, Enterprise, and Edu customers. Using a Product Feedback Intel demo, the source argues that such agents require layered controls because they can read across tools, post outputs, remember feedback, and create downstream work. Builders set an individual agent’s tool access, actions, and constraints, while enterprise admins govern role access, app permissions, available actions, and human confirmation requirements across the workspace.
Sami Inkinen, the founder of Virta Health and former Trulia chief executive, argues that type 2 diabetes and related metabolic disease are not failures of willpower but conditions driven by a food environment and care model that manage decline rather than reverse it. In a conversation with Tim Ferriss, Inkinen makes the case for treating individualized nutrition as a supervised medical therapy, supported by remote monitoring, coaching, physicians, and data, while using drugs such as GLP-1s when appropriate rather than making them the whole answer.
TBPN’s John Coogan and Jordi Hays argue that SpaceX, OpenAI and Anthropic are no longer just IPO candidates, but infrastructure-scale companies whose listings could move index flows while arriving after much of the frontier-technology upside has accrued in private markets. Across the discussion, they frame AI models, memory chips and agentic software as strategic infrastructure forming before public markets, regulation, costs and supply chains have settled around it. Apeel founder James Rogers gives the adoption-side warning: he says a regulated food-preservation product with real retail traction was driven out of U.S. stores by a suspicion campaign that exploited trust gaps in the food system.
OpenAI presents ChatGPT for PowerPoint as an embedded drafting and editing layer for business presentations, now available in beta to all customers. The source argues that the tool is meant to turn scattered company material — notes, account context, market research, prior deck fragments and analysis files — into a structured executive deck inside PowerPoint, with the user reviewing the storyline before generation and refining slide content afterward. Its claim is less that ChatGPT can make slides from a prompt than that it can keep the source material, outline, draft and edits in one workflow.
Yash Patil, chief executive of Applied Compute and a guest speaker in Stanford’s MS&E435 seminar, argues that the enterprise opportunity in AI is shifting from access to general frontier models toward the ability to define and optimize company-specific tasks. General models provide a baseline, he says, but durable advantage comes from internal evals, verifiers, feedback loops, proprietary context and product constraints that teach systems what “correct” means inside a business.
Lukas Czinger, co-founder of Divergent Technologies, argues that the bottleneck in defense hardware is not design but the tooling and fixed production lines that make iteration slow once a product leaves prototype. In a livestream interview, he said Divergent’s software-defined factory can move autonomous aircraft and other complex systems from digital design into production without rebuilding the supply chain around each change, citing a 71-day clean-sheet build of a flyable small uncrewed aircraft as proof of the model.
Bloomberg Technology framed the day’s tech news around a common test: whether ambitious hardware and AI claims can be backed by execution. Ed Ludlow and guests treated SpaceX’s scrubbed Starship V3 launch as more than a minor delay, because the vehicle is central to SpaceX’s payload, reuse and IPO story, while Lenovo CFO Winston Cheng argued that the company’s AI growth rests on both devices and infrastructure despite component constraints. The program also contrasted Zoom’s usage-based AI pitch with Bloomberg reporting that some Salesforce agentic AI demonstrations remain ahead of real customer deployment.
Sarah Chieng of Cerebras argues that fast coding models such as Codex Spark, which she says can generate code at roughly 1,200 tokens per second, require more disciplined developer workflows rather than looser ones. In her account, a 20x speedup over models such as Sonnet and Opus makes old habits — large prompts, unattended agents, delayed validation, and sprawling context — produce technical debt faster than developers can inspect it. Her playbook is to use speed for bounded execution, continuous testing and linting, variant generation, stricter permissions, and external memory that keeps short sessions from losing the plan.
Laura Crabtree, Epsilon3’s chief executive and a former SpaceX engineer, told Bloomberg Technology that SpaceX’s delayed 12th Starship test flight should be read less as an unusual failure than as evidence of the system’s complexity. A launch-tower pin that failed to retract was enough to halt the countdown, but Crabtree argued that Starship’s importance lies in whether SpaceX can turn the vehicle into bookable capacity for larger payloads, lunar transport and, eventually, human missions beyond Earth.
Lenovo CFO Winston Cheng told Bloomberg’s Ed Ludlow that the company’s AI growth should be understood as a portfolio story, spanning PCs, tablets and smartphones as well as infrastructure for AI training and inference. After Lenovo’s shares jumped on earnings, Cheng argued that AI demand is a multi-decade opportunity for the company, with AI revenue already about 38% of quarterly sales. He also said component shortages and memory inflation are manageable in infrastructure, where demand supports pass-through pricing, but more difficult in lower-end devices.
Zoom CFO Michelle Chang told Bloomberg that the company’s raised full-year earnings and revenue forecast reflected more than a quarterly beat, framing it as evidence that Zoom is repositioning beyond video meetings. Chang argued that AI features such as AI Companion and My Notes are helping turn Zoom into a broader “system of action” around workplace conversations, while the company continues to emphasize profitability, cash generation, and the reliability that built its original meeting business.
David Plouffe, Barack Obama’s former campaign manager and a partner at Orchestra, argues that AI is becoming a political problem because Americans experience it less as a tool than as another elite-driven transformation being imposed on them. In his view, economic anxiety, distrust of technology leaders, the legacy of social media, fears about children and jobs, and local fights over data centers could turn AI into a dominant issue by the 2028 presidential race. Better messaging will not solve that backlash, Plouffe says; voters will need concrete evidence that they have agency, economic pathways and local benefits as the technology spreads.
Sally Ann O’Malley of Red Hat argues that an OpenClaw agent setup should be shared as a container image rather than as a bundle of markdown, YAML, copied keys and informal instructions. Her demo uses Podman locally and Kubernetes for distribution, with the same image, separate secret backends, volume-backed state and a curated agent bundle so a personal setup can become a reproducible team baseline.
In a Hoover Institution California update, Bill Whalen and Lee Ohanian argue that the state’s newly balanced budget reflects another capital-gains windfall rather than a sounder fiscal model. They say California remains dependent on a narrow group of high-income, mobile taxpayers, with AI and possible IPOs offering more revenue upside while reinforcing the same volatility. The discussion extends that critique into state and Los Angeles politics, where they see unsettled Democratic fields and Spencer Pratt’s mayoral bid as symptoms of frustration with incumbent governance.
Ross Gerber, co-founder and CEO of Gerber Kawasaki Wealth and Investment Management, told Bloomberg that Nvidia’s first-quarter earnings should be read less as a single-company event than as a gauge of a multi-year AI infrastructure build-out. He argued that demand for AI capacity and enterprise productivity gains remain underestimated, while the main risk is whether power, data centers, capital and political approval can keep pace with the investment required.
Political scientist Ian Bremmer tells TED’s Helen Walters that clearer news judgment comes less from finding neutral sources than from building controls against bias, spin and overreaction. He argues for varying national and institutional inputs, using long-term relationships to test public information, ranking events by likelihood, imminence and impact, and separating personal preference from analysis. For ordinary news consumers, his advice is to know where identity distorts judgment, favor longer treatments of complex issues, and use AI or social feeds only in ways that force balance rather than affirmation.
Matt McCusker describes the “fap nap” as a practical touring-comedian habit: masturbation after a high-adrenaline show to fall asleep alone in a hotel room. Andrew Huberman treats the routine as biologically plausible, arguing that orgasm can push the body from catecholamine-driven arousal into a lower-arousal refractory state. The discussion separates that short-term downshift from Huberman’s broader warning that pornography can train users, especially younger men, toward ever-higher stimulation without the constraints of a relationship.
EY global consulting chief Errol Gardner argues that enterprise agentic AI remains far earlier than the market narrative suggests, rating adoption at less than 1 on a 0-to-10 scale. In a conversation with Craig Smith, Gardner says the main obstacle is not model capability but the difficulty of changing large organizations: aligning leaders, managers, workers, data controls and governance around redesigned workflows. He expects agentic AI to matter, but says scaled adoption will be slowed by human resistance, regulation, workforce displacement concerns and unresolved questions about who captures the value.
Google’s Florina Muntenescu and Oli Gaymond argue that Android’s on-device AI strategy depends on treating Gemini Nano as a shared system service, not something each app ships and manages itself. In their account, AICore centralizes the three-to-four-gigabyte model, scheduling, battery management and privacy boundaries, while developers call higher-level ML Kit GenAI APIs. The constraint is reach: those APIs need recent flagship-class devices, so Google is positioning hybrid cloud fallback and LiteRT-LM as alternatives when local Gemini Nano is unavailable or too limiting.
Billionaire value investor Mohnish Pabrai tells Shaan Puri that top-tier investing is less a stock-picking contest than a discipline of inactivity: study businesses deeply, reject almost everything, avoid leverage, and act only when a mispricing is obvious. Drawing on Buffett, Munger, Turkish equities, and Constellation Software, Pabrai argues that most investors lose because they trade too much, sell winners too soon, or chase what sits outside their competence. For those without the temperament to wait years for a “fat pitch,” he says indexing is likely the better game.