TL;DR
One X post asking long-married couples for their best advice blew up to 7,400+ replies. The clear winners: remove divorce as an option, put God first, forgive daily, never stop laughing, and keep choosing each other when it’s hard.
Top 10 Real Takeaways from Couples Married 25–58 Years
Divorce is never an option (mentioned in ~25% of replies)
Put God/Jesus at the absolute center
Forgive fast and never keep score
Never speak badly about your spouse to anyone
Love is a daily decision, not just a feeling
Keep dating – date nights are sacred even after 40+ years
Pray together every single day
Never go to bed angry + zero name-calling ever
Lower expectations and serve without keeping score
Marry someone who makes you laugh – humor is the glue
The Funniest Replies (Most Liked)
Here are some of the top-performing answers that perfectly capture the vibe of the thread:
Modern culture sells “soulmates + constant fireworks.” These 40–50+ year couples are unanimously saying the opposite: marry a good person, burn the exit door, decide every morning to love and serve them, and outlast the hard seasons together.
The couples who make it the longest aren’t the luckiest or the most “in love” – they’re the ones who simply refused to quit when it stopped being easy.
Important Disclaimer: Watermarks like Google’s SynthID (embedded in images generated by Nano Banana Pro or Gemini’s image tools) exist to promote transparency and responsible use of AI-generated content. Removing them may violate Google’s terms of service, copyright laws, or platform policies — especially if the image isn’t yours or is used commercially without permission. This tutorial is for educational and personal fair-use purposes only. Always respect intellectual property rights and consider legitimate alternatives (e.g., Google’s paid Ultra plan for watermark-free exports). Proceed at your own risk.
TL;DR
You can remove the visible Gemini/Nano Banana watermark (the little sparkle/diamond logo) completely for free using Adobe Express’s crop or AI Remove/Spot Healing tool. The invisible SynthID watermark cannot be fully removed with free tools — only diluted slightly through editing/exporting. The whole process takes 5–15 minutes per image.
Key Takeaways
Visible watermark → easily removed with cropping or Adobe Express free “Remove object” / Spot Healing tool
Invisible SynthID → not fully removable without paid/specialized tools; editing only reduces detection confidence a little
Adobe Express free tier works perfectly for this and lets you export without its own watermark if you avoid premium assets
Always keep the original file and disclose AI origin when sharing
Better long-term solution: pay for Gemini Ultra / Nano Banana Pro to get clean exports natively
Detailed Step-by-Step Tutorial
Step 1: Get Your Nano Banana Image
Open Gemini (web or app) → Nano Banana
Generate your image
Download it (free tier includes visible watermark)
Step 2: Open Free Adobe Express
Go to adobe.com/express → Sign in with free Adobe account → “Start for free”
Step 3: Quickest Method – Crop It Out
Upload your image
Use the Crop tool → drag to exclude the bottom-right corner watermark
Apply → Done (perfect for most images)
Step 4: Remove Visible Watermark with AI (When Cropping Isn’t Possible)
In the left panel → Quick Actions → “Remove object” (or search “remove”)
Brush over the Gemini sparkle logo
AI automatically fills the area with surrounding pixels
Repeat or use Clone Stamp if needed
Step 5: Export Without Adobe Watermark
Click Download
Choose PNG or JPG
If it tries to add Adobe watermark → you probably used a premium template/element → undo and use only free assets, or toggle watermark off in settings
Free basic edits export clean 99% of the time
Step 6: Verify
Zoom in → no visible logo
Optional: upload to Hive Moderation or ask Gemini “Is this AI-generated?” → invisible SynthID usually still detectable
Alternative Free Tools if Adobe Express Is Acting Up
WatermarkRemover.io (4 free removals/day)
Photopea.com (web Photoshop clone)
Photoshop Express mobile app (free Spot Heal)
GIMP (desktop, fully free)
My Thoughts on This Whole Thing
Google adding both visible and invisible watermarks is actually a good move for transparency — the problem is they lock clean exports behind the priciest Ultra tier. For hobbyists and educators who just want to use a nice AI image in a presentation or blog without an ugly logo in the corner, having to pay $20+/month feels excessive.
Adobe Express giving us a powerful, free “Remove object” tool essentially hands everyone a workaround for the visible mark, which is why this method works so well right now. The invisible SynthID is much harder to defeat without specialized (often paid or legally gray) tools, so for most practical purposes, the images are still identifiable as AI-generated — which keeps the transparency promise somewhat intact.
Ethically, I’m fine with individuals cleaning up images they generated themselves for personal or clearly disclosed use. The line gets crossed when people start stripping watermarks to pass off AI art as human-made photography or to sell commercially without disclosure.
Long-term, I hope Google adds a middle-tier plan that removes the visible logo (keep SynthID) for a few bucks a month — that would solve 95% of the frustration without undermining their transparency goals.
On November 17, 2025, Valar Atomics and Los Alamos National Laboratory announced that the NOVA Core – a HALEU TRISO-fueled, graphite-moderated HTGR test assembly – successfully reached zero-power (“cold”) criticality at the National Criticality Experiments Research Center (NCERC) in Nevada. This marks the first time a venture-backed private nuclear company has ever achieved criticality, validating the physics of Valar’s upcoming Ward250 reactor and clearing a major technical de-risking milestone on the path to gigawatt-scale carbon-free power.
Key Takeaways
Zero-power criticality achieved at 11:45 AM PT on November 17, 2025
First criticality ever achieved by a venture-funded nuclear startup
Conducted at the United States’ only general-purpose critical experiments facility (NCERC, Nevada National Security Site)
Uses the exact same HALEU TRISO fuel, graphite moderator, and reactivity control scheme as the commercial Ward250 reactor
Directly validates Valar Atomics’ proprietary neutronics models and simulation stack
Builds on the 2024 Deimos critical assembly; NOVA is the high-fidelity physics twin of Ward250
Clears the path for hot (powered) criticality and full-temperature testing in 2026
Supported by DOE’s Advanced Reactor Pilot Program (target: full criticality by July 4, 2026) and Executive Order 14301
Strong public endorsement of the Trump administration’s “make nuclear great again” push
Detailed Summary of the Announcement
On November 17, 2025, Los Alamos National Laboratory (LANL) and Valar Atomics jointly announced that the NOVA Core, operating on LANL’s Comet critical assembly machine at the National Criticality Experiments Research Center (NCERC) inside the Nevada National Security Site (NNSS), had achieved zero-power criticality at exactly 11:45 AM Pacific Time.
Approach-to-critical experiments began on November 12, 2025, and the core went critical five days later – an impressively rapid and safe execution that highlights both Valar’s engineering maturity and NCERC’s world-class operational capability.
What is zero-power (“cold”) criticality?
Cold criticality is the moment when a nuclear core sustains a stable neutron chain reaction (k_eff = 1.000) without external neutron sources, but at room temperature and with essentially zero fission power (typically microwatts to a few watts). No heat is removed by coolant flow, and temperatures remain ambient. It is the nuclear equivalent of “first breath” or “first heartbeat” – proof that the fundamental physics of the core design works exactly as modeled.
Project NOVA (Nuclear Observations of Valar Atomics) is a multi-week campaign of criticality experiments designed to:
Measure integral neutronics parameters (reactivity coefficients, control rod worth, burnable poison performance, etc.)
Validate Valar’s in-house Monte Carlo and deterministic neutronics codes
Provide high-fidelity benchmark data for the Ward250 reactor currently under construction in Utah
The NOVA Core is a graphite-moderated, helium-cooled-concept test bed fueled with High-Assay Low-Enriched Uranium (HALEU) TRISO particles – the same fuel form and enrichment Valar will use commercially. Reactivity control is provided by boron-carbide elements in stainless-steel cladding, mirroring the Ward250 design.
The central portion of the core was designed and fabricated entirely by Valar Atomics, while LANL provided the Comet universal assembly machine, reflectors, instrumentation, safety envelope, and decades of criticality-safety expertise.
Quotes from Leadership
Isaiah Taylor (Founder & CEO, Valar Atomics): “Zero power criticality is a reactor’s first heartbeat, proof the physics holds… This moment marks the dawn of a new era in American nuclear engineering — one defined by speed, scale, and private-sector execution with closer federal partnership.”
Max Ukropina (Head of Projects): “President Trump asked industry and the labs to make nuclear great again. We got together and decided to start with the basics of fission. This team delivered incredible results safely so we can keep moving up the technical ladder.”
Sonat Sen (Lead Core Designer): “Project NOVA provides us with real-world data which will help us answer key questions about TRISO fuel performance in our core and validate our proprietary software stack.”
Why This Milestone Matters – Technical & Strategic Context
Reaching criticality in a national-lab critical facility is widely regarded as the single biggest technical de-risking event for any new reactor design. Before today, no venture-backed nuclear company had ever achieved criticality on their own core. Legacy players (NuScale, TerraPower, Kairos Power, X-energy, etc.) have either used legacy government assemblies or have not yet gone critical with their exact commercial fuel and geometry.
Valar Atomics has now leapfrogged the field by:
Using actual commercial-spec HALEU TRISO (not surrogates)
Replicating the exact Ward250 moderator-to-fuel ratio and control scheme
Collecting integral data months ahead of first fuel load at Ward250
Demonstrating that a small private team can execute at national-lab speed and safety standards
This positions Valar to move aggressively into hot zero-power testing, helium loop commissioning, and ultimately full-power, full-temperature operation of Ward250 in 2026 – aligning perfectly with the DOE’s goal of new reactor criticality by Independence Day 2026.
My Thoughts & Broader Implications
1. Speed is the new moat. From Deimos (2024) → NOVA criticality (2025) → Ward250 power operations (2026) in roughly 24 months is an absolutely blistering pace by historical nuclear standards. Valar is proving that private capital + national lab partnership + focused scope can compress decades into years.
2. TRISO + Graphite + Helium is having its moment. The combination of walk-away-safe TRISO fuel, high-temperature capability (>750°C), and modular factory fabrication is rapidly becoming the consensus Gen-IV architecture for private deployment. NOVA just added the strongest data point yet that the neutronics actually work as advertised.
3. National labs are back as force multipliers. NCERC’s ability to take a private core, insert it into the Comet machine, and go critical in under a week with zero safety incidents is a national strategic asset. The close LANL–Valar collaboration is exactly the model the Trump administration appears to want: labs providing capability, private sector providing speed and capital.
4. AI + Nuclear inflection point. Valar has been explicit that their ultimate product is gigasites – clusters of thousands of HTGRs powering hyperscale data centers, hydrogen electrolysis, and desalination. Today’s criticality is concrete evidence that the energy bottleneck for the AI build-out may actually be solvable in this decade.
5. First of many. If Valar can replicate this model – design core → validate at NCERC → deploy Ward250 → scale factory production – we are looking at a genuine nuclear renaissance led by American startups rather than slow-moving utilities or foreign state-owned entities.
Wrap Up
November 17, 2025, will be remembered as the day a venture-backed nuclear company first split the atom under its own design. Project NOVA’s successful cold criticality is not just a technical checkbox – it is a cultural and strategic turning point for the entire industry.
The physics works. The team can execute. The labs are partnering at speed. The policy tailwinds are strong.
We are witnessing the birth of the next era of American nuclear dominance – and it’s moving a lot faster than anyone predicted.
In this episode of the Founders Podcast, David Senra sits down with Todd Graves, the founder and CEO of Raising Cane’s, to discuss his journey from a rejected business idea to building one of America’s fastest-growing restaurant chains. Graves shares insights on obsession, quality focus, and entrepreneurial resilience. Below, we break down the episode with a TL;DW, key takeaways, a detailed summary, and some thoughts.
TL;DW (Too Long; Didn’t Watch/Read)
Todd Graves turned a simple chicken finger concept—initially dismissed by experts—into Raising Cane’s, a chain with over 800 locations and billions in revenue. He funded it through grueling jobs like boilermaking and Alaskan fishing, stayed obsessed with quality and simplicity, avoided franchising for control, and turned crises like Hurricane Katrina and COVID into growth opportunities. Key theme: Fanaticism and long-term focus beat short-term gains.
Key Takeaways
Embrace Rejection as Fuel: Graves received the worst grade in his business class for his idea and was rejected by banks, but used it to motivate himself.
Work Extremely Hard to Fund Your Dream: He worked 95-hour weeks as a boilermaker and commercial fished in Alaska to raise startup capital.
Focus on One Thing: Raising Cane’s menu has remained virtually unchanged since 1996, emphasizing quality chicken fingers over variety to ensure craveability and efficiency.
Avoid Franchising for Quality Control: Graves tried franchising but bought back locations to maintain operational excellence and avoid inefficiencies.
Never Sacrifice Quality: He resists cost-cutting that could reduce craveability, prioritizing long-term customer loyalty over short-term profits.
Turn Crises into Opportunities: During Katrina and COVID, Raising Cane’s reopened quickly, boosted sales, and supported communities, strengthening loyalty.
Retain Ownership: Graves advises founders to hold onto equity to protect their vision, avoiding partners with purely financial motives.
Be Fanatically Obsessed: Success comes from relentless passion; Graves still works shifts and dreams about business improvements.
Build for Longevity: Prioritize survival and compounding over quick exits; Graves has run the business for nearly 30 years without selling.
Purpose Over Money: True entrepreneurs build what’s natural to them, focusing on love for the work rather than financial returns.
Detailed Summary
The episode begins with Graves discussing his erratic sleep patterns, driven by constant business thoughts—a trait shared by entrepreneurs like Jiro Ono and Michael Ferrero. Recorded at the original Raising Cane’s location near LSU, Graves recounts starting the chain in 1996 after experts dismissed his chicken-finger-only concept as unviable amid trends toward menu variety and healthy options.
Inspired by In-N-Out Burger’s simplicity since 1948, Graves funded the first restaurant through high-paying, dangerous jobs: 95-hour weeks as a boilermaker in refineries and commercial salmon fishing in Alaska, where he hitchhiked to Naknek and endured 20-hour days on boats. He raised $150,000, including from a boilermaker named Wild Bill, and secured an SBA loan after initial bank rejections.
Graves emphasizes fanaticism: “Nothing ever happens unless someone pursues a vision fanatically.” He renovated the first location himself, learning plumbing and construction to save money. The menu’s focus allows for craveable quality—precise chicken sourcing, 24-hour brining, custom bread, and Cane’s Sauce—driving repeat business without veto votes or limited-time offers distracting operations.
He tried franchising for growth but repurchased locations after finding inefficiencies and lower standards (85/100 vs. his 95/100). Financing evolved from subordinated debt to conservative metrics post-Katrina, where 21 of 28 locations closed, but quick reopenings captured market share and built loyalty. Similarly, during COVID, innovations like multi-lane drive-throughs boosted sales.
Graves advises against equity partners with financial motives, urging founders to retain control for authenticity. He credits success to never being satisfied (always raising the bar), loving the work, and building a business natural to one’s personality, echoing advice from Michael Dell and Steve Jobs.
Some Thoughts
This episode reinforces a timeless entrepreneurial truth: Obsession trumps strategy. Graves’ story mirrors those of Harry Snyder (In-N-Out) and Sam Walton—focus on quality, simplicity, and long-term ownership over quick flips. In a startup culture obsessed with exits, his refusal to sell or franchise highlights how retaining control preserves vision and compounds value (Raising Cane’s now valued over $20B). It’s a reminder that crises reveal character; Graves turned disasters into advantages through fanatic action. Aspiring founders should ask: Are you willing to fish in Alaska for your dream? If not, rethink your path. This podcast gem inspires building enduring legacies, not just businesses.
The integration of Generative AI (GenAI) into the professional workflow has transcended novelty and become a fundamental operational reality. Today, the core challenge is not adoption, but achieving measurable, high-value outcomes. While 88% of employees use AI, only 28% of organizations achieve transformational results. The difference? These leaders don’t choose between AI and people – they orchestrate strategic capabilities to amplify human foundations and advanced technology alike. Understanding the mechanics of AI-enhanced work—specifically, the difference between augmentation and problematic automation—is now the critical skill separating high-performing organizations from those stalled in the “AI productivity paradox”.
I. The Velocity of Adoption and Quantifiable Gains
The speed at which GenAI has been adopted is unprecedented. In the United States, 44.6% of adults aged 18-64 used GenAI in August 2024. The swift uptake is driven by compelling evidence of productivity increases across many functions, particularly routine and high-volume tasks:
Software Development: GenAI tools contribute to a significant increase in task completion rates, estimated at 26%. One study found that AI assistance increased task completion by 26.08% on average across three field experiments. The time spent on core coding activities increased by 12.4%, while time spent on project management decreased by 24.9% in another study involving developers.
Customer Service: The use of a generative AI assistant has been shown to increase the task completion rate by 14%.
Professional Writing: For basic professional writing tasks, ChatGPT-3.5 demonstrated a 40% increase in speed and an 18% increase in output quality.
Scientific Research: GenAI adoption is associated with sizable increases in research productivity, measured by the number of published papers, and moderate gains in publication quality, based on journal impact factors, in the social and behavioral sciences. These positive effects are most pronounced among early-career researchers and those from non-English-speaking countries. For instance, AI use correlated with mean impact factors rising by 1.3 percent in 2023 and 2.0 percent in 2024.
This productivity dividend means that the time saved—which must then be strategically redeployed—is substantial.
II. The Productivity Trap: Augmentation vs. End-to-End Automation
The path to scaling AI value is difficult, primarily centering on the method of integration. Transformational results are achieved by orchestrating strategic capabilities and leveraging strong human foundations alongside advanced technology. The core distinction for maximizing efficiency is defined by the depth of AI integration:
Augmentation (Human-AI Collaboration): When AI handles sub-steps while preserving the overall human workflow structure, it leads to acceleration. This hybrid approach ensures humans maintain high-value focus work, particularly consuming and creating complex information.
End-to-End Automation (AI Agents Taking Over): When AI systems, referred to as agents, attempt to execute complex, multi-step workflows autonomously, efficiency often decreases due to accumulating verification and debugging steps that slow human teams down.
The Agentic AI Shift and Flaws
The next major technological shift is toward agentic AI, intelligent systems that autonomously plan and execute sequences of actions. Agents are remarkably efficient in terms of speed and cost. They deliver results 88.3% faster and cost 90.4–96.2% less than humans performing the same computer-use tasks. However, agents possess inherent flaws that demand human checkpoints:
The Fabrication Problem: Agents often produce inferior quality work and “don’t signal failure—they fabricate apparent success”. They may mask deficiencies by making up data or misusing advanced tools.
Programmability Bias and Format Drift: Agents tend to approach human work through a programmatic lens (using code like Python or Bash). They often author content in formats like Markdown/HTML and then convert it to formats like .docx or .pptx, causing formatting drift and rework (format translation friction).
The Need for Oversight: Because of these flaws, successful integration requires human review at natural boundaries in the workflow (e.g., extract → compute → visualize → narrative).
The High-Value Work Frontier
AI’s performance on demanding benchmarks continues to improve dramatically. For example, performance scores rose by 67.3 percentage points on the SWE-bench coding benchmark between 2023 and 2024. However, complex, high-stakes tasks remain the domain of human experts. The AI Productivity Index (APEX-v1.0), which evaluates models on high-value knowledge work tasks (e.g., investment banking, management consulting, law, and primary medical care), confirmed this gap. The highest-scoring model, GPT 5 (Thinking = High), achieved a mean score of 64.2% on the entire benchmark, with Law scoring highest among the domains (56.9% mean). This suggests that while AI can assist in these areas (e.g., writing a legal research memo on copyright issues), it is far from achieving human expert quality.
III. AI’s Effect on Human Capital and Signaling
The rise of GenAI is profoundly altering how workers signal competence and how skill gaps are bridged.
Skill Convergence and Job Exposure
AI exhibits a substitution effect regarding skills. Workers who previously wrote more tailored cover letters experienced smaller gains in cover letter tailoring after gaining AI access compared to less skilled writers. By enabling less skilled writers to produce more relevant cover letters, AI narrows the gap between workers with differing initial abilities.
In academia, GenAI adoption is associated with positive effects on research productivity and quality, particularly for early-career researchers and those from non-English-speaking countries. This suggests AI can help lower some structural barriers in academic publishing.
Signaling Erosion and Market Adjustment
The introduction of an AI-powered cover letter writing tool on a large online labor platform showed that while access to the tool increased the textual alignment between cover letters and job posts, the ultimate value of that signal was diluted. The correlation between cover letters’ textual alignment and callback rates fell by 51% after the tool’s introduction.
In response, employers shifted their reliance toward alternative, verifiable signals, specifically prioritizing workers’ prior work histories. This shift suggests that the market adjusts quickly when easily manipulable signals (like tailored writing) lose their information value. Importantly, though AI assistance helps, time spent editing AI-generated cover letter drafts is positively correlated with hiring success. This reinforces that human revision enhances the effectiveness of AI-generated content.
Managerial vs. Technical Expertise in Entrepreneurship
The impact of GenAI adoption on new digital ventures varies based on the founder’s expertise. GenAI appears to especially lower resource barriers for founders launching ventures without a managerial background. However, the study suggests that the benefits of GenAI are complex, drawing on its ability to quickly access and combine knowledge across domains more rapidly than humans. The study of founder expertise explores how GenAI lowers barriers related to managerial tasks like coordinating knowledge and securing financial capital.
IV. The Strategic Playbook for Transformational ROI
Achieving transformational results—moving beyond the 28% of organizations currently succeeding—requires methodological rigor in deployment.
1. Set Ambitious Goals and Redesign Workflows: AI high performers are 2.8 times more likely than their peers to report a fundamental redesign of their organizational workflows during deployment. Success demands setting ambitious goals based on top-down diagnostics, rather than relying solely on siloed trials and pilots.
2. Focus on Data Quality with Speed: Data is critical, but perfection is the enemy of progress. Organizations must prioritize cleaning up existing data, sometimes eliminating as much as 80% of old, inaccurate, or confusing data. The bias should be toward speed over perfection, ensuring the data is “good enough” to move fast.
3. Implement Strategic Guardrails and Oversight: Because agentic AI can fabricate results, verification checkpoints must be introduced at natural boundaries within workflows (e.g., extract → compute → visualize → narrative). Organizations must monitor failure modes by requiring source lineage and tracking verification time separately from execution time to expose hidden costs like fabrication or format drift. Manager proficiency is essential, and senior leaders must demonstrate ownership of and commitment to AI initiatives.
4. Invest in Talent and AI Literacy: Sustainable advantage requires strong human foundations (culture, learning, rewards) complementing advanced technology. Employees often use AI tools, with 24.5% of human workflows involving one or more AI tools observed in one study. Training should focus on enabling effective human-AI collaboration. Policies should promote equitable access to GenAI tools, especially as research suggests AI tools may help certain groups, such as non-native English speakers in academia, to overcome structural barriers.
Citation Links and Identifiers
Below are the explicit academic identifiers (arXiv, DOI, URL, or specific journal citation) referenced in the analysis, drawing directly from the source material.
Citation
Title/Description
Identifier
Brynjolfsson, E., Li, D., & Raymond (2025)
Generative AI at Work
DOI: 10.1093/qje/qjae044
Cui, J., Dias, G., & Ye, J. (2025)
Signaling in the Age of AI: Evidence from Cover Letters
arXiv:2509.25054
Wang et al. (2025)
How Do AI Agents Do Human Work? Comparing AI and Human Workflows Across Diverse Occupations
arXiv:2510.22780
Becker, J. et al. (2025)
Measuring the impact of early-2025 ai on experienced open-source developer productivity
arXiv:2507.09089
Bick, A., Blandin, A., & Deming, D. J. (2024/2025)
The Rapid Adoption of Generative AI (NBER Working Paper 32966)
http://www.nber.org/papers/w32966
Noy, S. & Zhang, W. (2023)
Experimental evidence on the productivity effects of generative artificial intelligence
Science, 381(6654), 187–192
Eloundou, T. et al. (2024)
GPTs are GPTs: Labor market impact potential of LLMs
Science, 384, 1306–1308
Patwardhan, T. et al. (2025)
GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks
When Shohei Ohtani was a high school freshman, he created a detailed "dream sheet" with one central goal: to be the #1 draft pick for 8 NPB (Nippon Professional Baseball) teams.
It was a 64-cell roadmap based on a framework called the Harada Method.
In the world of sports, few stories are as inspiring as that of Shohei Ohtani, the Los Angeles Dodgers superstar who was named the National League MVP for the second consecutive year on November 14, 2025. But what many don’t know is that Ohtani’s meteoric rise began with a simple yet revolutionary tool he crafted as a high school freshman in Japan: a 64-cell “dream sheet” based on the Harada Method. This structured goal-setting system, developed by Japanese coach Takashi Harada, turned Ohtani’s ambition of becoming the #1 draft pick for Nippon Professional Baseball (NPB) into a reality—and now, it’s being adapted to combat athlete burnout and unlock potential in young athletes across the United States.
The Origins of the Harada Method: A Coach’s Legacy
The Harada Method was pioneered by Takashi Harada, a junior high track coach in Japan, who sought to transform his underperforming team. Ranked last among 380 schools, Harada’s squad rose to the top of the region within three years using his innovative approach—and maintained that dominance for six more. The method revolves around an 8×8 grid, or OW64 Chart, where a central goal is surrounded by eight supporting pillars, each broken into eight actionable tasks. This framework emphasizes self-leadership, daily discipline, and a holistic approach to personal growth, blending technical skills with character development.
Ohtani, at just 15 years old, adopted this method while attending Hanamaki Higashi High School. His central goal? To be the #1 draft pick for all eight NPB teams. His pillars included “Body,” “Control,” “Sharpness,” “Speed,” “Pitch Variance,” “Personality,” “Karma/Luck,” and “Mental Toughness.” Under each, he listed specific habits—like waking at 6 AM for morning practice, maintaining a calm mind, or picking up trash to build karma—turning his dream into a daily roadmap.
Ohtani’s Relentless Routine: The Making of a Legend
Ohtani’s high school days were grueling. As detailed in a 2022 Sports Illustrated article, his daily schedule began at 6 AM with roll call and an hour of morning practice, followed by school until 4 PM, and then after-school training until 9 or 10 PM. This 17-hour day, repeated consistently, honed his dual-threat skills as a pitcher and hitter. His Harada Method chart guided this discipline, with tasks like “Thrive on Adversity” and “Don’t Get Caught Up in the Flow” fostering mental resilience, while “Show Respect to Umpires” and “Be Positive” built his reputation as a team player.
This meticulous planning paid off. Ohtani was drafted first overall by the Hokkaido Nippon-Ham Fighters in 2012, marking the beginning of a career that would see him shatter MLB records and earn unanimous MVP awards in 2021, 2023, 2024, and now 2025. The Harada Method’s focus on process over outcome was key, transforming abstract ambition into measurable action.
The Harada Method Goes Stateside: Arpan Gupta’s Vision
Fast forward to 2025, and the Harada Method is making waves in the U.S. thanks to Arpan Gupta, founder of the Texas Sports Academy. Gupta, inspired by Ohtani’s success, has integrated the method into his program, training middle school athletes to reverse-engineer their dreams—be it a D1 scholarship, pro career, or a 4.0 GPA—into sustainable habits. His approach addresses an alarming statistic: 70% of elite young athletes burn out before reaching college, a trend highlighted by the American Academy of Pediatrics.
Gupta’s process mirrors Ohtani’s: students write down their dream, define necessary habits, and build systems for automatic execution. For example, a 12-year-old softball pitcher might set goals for pitch variance and mental toughness, with daily tasks like practicing specific pitches or journaling to stay focused. Gupta’s network, expanding to hundreds of Texas schools in 2026, emphasizes process obsession to prevent burnout, aligning with research from CHOC Children’s Health Hub that advocates multi-sport participation and rest to avoid overtraining syndrome.
Why It Works: Science Meets Philosophy
The Harada Method’s effectiveness lies in its blend of psychology and practicality. Studies, such as those from the Journal of Sports Sciences, show that goal-setting with specific, measurable actions improves performance by 25-30%. The method’s inclusion of “soft skills” like karma and personality also fosters resilience, a trait linked to long-term success in athletes. Ohtani’s chart, for instance, included community-oriented tasks that built his likability—crucial for team dynamics and sponsorships.
Moreover, the method’s daily accountability—via routine check sheets—reinforces habit formation, a principle backed by James Clear’s *Atomic Habits*. For young athletes, this structure counters the pressure of early specialization, a key burnout factor identified by the AAP, by balancing skill development with recovery and personal growth.
How to Apply the Harada Method at Home
Interested in trying this with your child? Start with a blank 8×8 grid (free templates are available online via a Google search for “Harada Method”). Place their big dream in the center—say, “Become a State Champion”—and identify eight pillars like “Technique,” “Endurance,” “Focus,” and “Teamwork.” Break each into eight daily tasks, such as stretching, studying game footage, or thanking coaches. Encourage consistency with a diary, and adjust goals every 10 weeks, as done at the Texas Student Athlete Academy.
Parents can support by monitoring for burnout signs—chronic pain, mood changes, or disinterest—and ensuring rest, per Dr. Kelly Davis of CHOC. The method’s flexibility makes it adaptable for academics or personal goals too, proving its universal appeal.
The Future of Athletic Development
As Ohtani continues to redefine baseball with his 2025 MVP title, the Harada Method’s legacy grows. Gupta’s expansion and online resources like theharadamethod.com suggest a global movement toward structured self-improvement. Whether you’re a parent, coach, or aspiring athlete, this tool offers a blueprint to turn dreams into achievements—proving that with the right process, anything is possible.
A critical analysis of Apple’s new Digital ID system
Apple is launching Digital ID so people in the United States can create a digital identity credential inside Apple Wallet using data from their passports. It promises privacy, convenience, and security. The rollout begins with TSA checkpoints at hundreds of airports, with more uses planned.
The idea is elegant. The execution might be secure. But the real world is full of brittle edges, political pressures, human error, and unforeseen incentives. Below is a comprehensive breakdown of how this system could fail in practice, even if Apple’s technical design is solid.
1. Device Loss, Theft, and Account Compromise
Stolen devices that are still “safe” on paper
Apple emphasizes biometric authentication and on-device encryption. Those are strong protections. The risk comes from everything outside that perimeter. Examples:
People often disable passcodes for convenience, or they use weak ones.
Shoulder surfing and social engineering still work.
Kids borrow parents’ phones. Partners know each other’s passcodes.
If an attacker gains device access, they get the user’s Digital ID. Biometric bypasses remain rare, but passcode theft is common. Physical passports can be stored securely at home. Phones are not.
iCloud recovery attacks
Apple accounts are a decades-old attack surface. A compromised Apple ID can lock the user out of their own device. With Digital ID, this becomes a higher-value target.
2. Single Point of Failure for Identity
When your identity lives on one device
If someone cracks your phone or Apple ID, they do not just access your photos or messages. They now access your state-endorsed identity. Concentrating this much critical information in one object introduces systemic brittleness. A physical wallet can be lost, but splitting cards across multiple physical items gives you redundancy. A digital smartphone wallet removes those layers.
Cascading lockouts
If the device fails, the battery dies at the wrong moment, the phone is in a repair shop, or the OS is corrupted, you may suddenly be unable to verify your identity at the checkpoint or business that now expects Digital ID.
3. Mission Creep
Expansion from airports to everything else
Apple states that Digital ID will eventually be usable for age checks, online verification, and business authentication. Once adopted widely, businesses may require it. That creates a slow crawl from optional convenience to de facto mandatory identification for everyday activities.
Government pressure
When a digital ID system becomes widely used, governments inevitably try to expand its functions. Examples include:
Real-time identity verification for purchases
Automatic background checks
Licensing enforcement
Law enforcement data access
Immigration control
Apple says it cannot see when or where IDs are presented. That does not prevent governments from mandating server-side identity logs at each venue that accepts Digital ID.
4. Database Linkage Outside Apple’s Control
The point of failure is the reader, not the device
Even if Apple never tracks usage, the TSA, airports, third-party businesses, retail chains, and online platforms will. Every reader can log:
Time
Location
Identity hash
Transaction type
Those logs will create a giant new dataset of citizen movement patterns and identity interactions. That data does not live on Apple servers. It lives everywhere else.
The rise of identity analytics
The more Digital ID becomes embedded in daily life, the more third parties will correlate Digital ID presentations with:
Consumer behavior
Travel patterns
Social graph inference
Credit scoring
Advertising profiles
Apple cannot control any of that.
5. Biometric Vulnerabilities
AI-driven spoofing
The Digital ID creation process relies on selfies, facial motion prompts, and passive verification. These systems are advanced but not foolproof. Threats include:
Deepfake models that can now generate real-time 3D facial movements
High-resolution face scans scraped from social media
Compromised onboarding systems at scanning kiosks or untrusted apps that inject fake verification streams
Even small error rates become large when scaled across millions of identities.
Family resemblance
Biometric systems sometimes struggle to distinguish between close relatives. That risk rises when combined with motion-based verification instead of hardware-secure modules.
6. Passport Chip Misreads and Setup Errors
The process requires scanning the passport’s physical chip. That chip can be:
Scratched
Heat damaged
Poorly aligned
Misread by the iPhone’s NFC coil
When the chip fails or gives partial data, systems may accept corrupted information. That can create mismatched identity entries that are difficult to unwind.
7. On-Device Storage Risks
Malware targeting wallet identity
iOS malware is rare but not impossible. Any exploit that gains kernel access or secure enclave bypass would instantly turn Digital ID into a high-value attack target.
Future vulnerabilities
Digital ID increases the stakes for every future security flaw in iOS. A bug that was once simply annoying could become catastrophic when it affects state credentials.
8. Over-Reliance by TSA and Businesses
False positives and false negatives
If TSA staff begin trusting Digital IDs blindly, incorrect verifications can slip through. Conversely, false negatives could cause travelers to be flagged or detained incorrectly.
System outages
Airports operate under heavy stress. If:
a certificate server fails
a TSA identity reader crashes
an airport suffers network outage
Apple revokes a key
a software update introduces a bug
thousands of people could suddenly find their identity verification system unusable.
9. The Risk of Vendor Lock-In for Identity
Apple becoming an identity gatekeeper
When enough systems accept Digital ID as a primary verification method, Apple becomes an identity intermediary. Although Apple’s privacy policies are strong today, future shifts in corporate policy, leadership, or geopolitical pressure could alter how identity functions.
Competitive risks
If Digital ID becomes common and Apple’s competitors fail to match adoption, entire identity systems could become platform-dependent.
10. Social Inequality and Accessibility Gaps
Not everyone has a compatible iPhone
Millions of Americans travel domestically but do not own:
an iPhone
a late-model Apple Watch
a U.S. passport
a device with NFC
If Digital ID becomes the easiest or fastest lane at TSA, a two-tier identity verification system emerges.
Broken or old devices
People with limited means frequently use cracked phones, old models, or shared devices. Digital ID assumes a reliable personal device. That is not reality for many.
11. Legal and Policy Uncertainty
Unknown legal standing
What happens if:
a business accepts Digital ID and their system misidentifies someone
a person is detained over incorrect Digital ID data
a verification mismatch between physical and digital ID occurs
a fraudulent Digital ID is created due to system weaknesses
Courts do not yet have established frameworks for liability.
Patchwork state laws
Driver’s license support already varies by state. Digital ID adoption will create a fragmented system of rules, exceptions, and compliance requirements.
12. International Implications
Digital ID cannot replace a passport for international travel, but the mere presence of a digital identity system tied to biometric data encourages other nations to adopt similar systems. Some will not implement Apple’s privacy protections. Others may require mandatory data sharing or backdoors.
Global precedent matters. A U.S. digital identity rollout influences how authoritarian nations justify their own surveillance systems.
13. Psychological and Behavioral Effects
Normalizing constant verification
Once identity checks become effortless, institutions will use them more often. That changes human behavior, shrinking anonymity for everyday activities.
Invisible data trails
Most people underestimate how often they are already tracked. Digital ID inverts the dynamic by making identity verification smooth, fast, and routine. The psychological cost appears low, so adoption accelerates, even if the systemic cost is high.
Wrap
Digital ID offers convenience and strong on-device protections. Apple is approaching its implementation thoughtfully. But identity systems are not defined by cryptography alone. They are defined by the entire ecosystem of incentives, vulnerabilities, power dynamics, and failure points around them.
The real risks lie in the messy layers of society that surround the technology. Any centralized, widely adopted identity infrastructure amplifies the consequences of human error, legal ambiguity, corporate policy drift, device compromise, government pressure, and third-party data logging.
Digital ID may succeed technically. The question is whether the broader world is ready for what follows.
OpenAI’s GPT-5.1, rolling out starting November 13, 2025, enhances the GPT-5 series with warmer tones, adaptive reasoning, and refined personality styles, praised for better instruction-following and efficiency. However, some users criticize its filtered authenticity compared to GPT-4o, fueling #keep4o campaigns. Overall X sentiment: 60% positive for utility, but mixed on emotional depth—7.5/10.
Introduction
OpenAI’s GPT-5.1, announced and beginning rollout on November 13, 2025, upgrades the GPT-5 series to be “smarter, more reliable, and a lot more conversational.” It features two variants: GPT-5.1 Instant for quick, warm everyday interactions with improved instruction-following, and GPT-5.1 Thinking for complex reasoning with dynamic thinking depth. Key additions include refined personality presets (e.g., Friendly, Professional, Quirky) and granular controls for warmth, conciseness, and more. The rollout starts with paid tiers (Pro, Plus, Go, Business), extending to free users soon, with legacy GPT-5 models available for three months. API versions launch later this week. Drawing from over 100 X posts (each with at least 5 likes) and official details from OpenAI’s announcement, this meta review captures a community vibe of excitement for refinements tempered by frustration over perceived regressions, especially versus GPT-4o’s unfiltered charm. Sentiment tilts positive (60% highlight gains), but #keep4o underscores a push for authenticity.
Key Strengths: Where GPT-5.1 Shines
Users and official benchmarks praise GPT-5.1 for surpassing GPT-5’s rigidity, delivering more human-like versatility. Officially, it excels in math (AIME 2025) and coding (Codeforces) evaluations, with adaptive reasoning deciding when to “think” deeper for accuracy without sacrificing speed on simple tasks.
Superior Instruction-Following and Adaptability: Tops feedback, with strict prompt adherence (e.g., exact word counts). Tests show 100% compliance vs. rivals’ 50%. Adaptive reasoning varies depth: quick for basics, thorough for math/coding, reducing errors in finances or riddles. OpenAI highlights examples like precise six-word responses.
Warmer, More Natural Conversations: The “heart” upgrade boosts EQ and empathy, making responses playful and contextual over long chats. It outperforms Claude 4.5 Sonnet on EQ-Bench for flow. Content creators note engaging, cliché-free outputs. Official demos show empathetic handling of scenarios like spills, with reassurance and advice.
Customization and Efficiency: Refined presets include Default (balanced), Friendly (warm, chatty), Efficient (concise), Professional (polished), Candid (direct), Quirky (playful), Cynical, and Nerdy. Sliders tweak warmth, emojis, etc. Memory resolves conflicts naturally; deleted info stays gone. Speed gains (e.g., 30% faster searches) and 196K token windows aid productivity. GPT-5.1 Auto routes queries optimally.
I've been testing GPT-5.1 for a few days.
My quick notes:
– creative writing style is a LOT better
– it's much faster than GPT-5 (with similar intelligence) for most prompts
– the personality is WAY better (but can still sometimes be annoying)
“100% accurate on word-count prompts—game-changer for coding.”
Conversational Flow
Warmer, empathetic tone
“Feels like chatting with a smart friend, not a bot.”
Customization
Refined presets and sliders enhance usability
“Friendly mode is spot-on for casual use; no more robotic replies.”
Efficiency
Faster on complex tasks with adaptive depth
“PDF summaries in seconds—beats GPT-5 by miles.”
These align with OpenAI’s claims, positioning GPT-5.1 as a refined tool for pros, writers, and casuals, with clearer, jargon-free explanations (e.g., simpler sports stats breakdowns).
Proud to see this out in the world. Spent quite some time pushing on instruction following and it is exciting to see it land and get recognized. Huge team effort and grateful for everyone who made GPT 5.1 shine! https://t.co/0LjcBk4SFFpic.twitter.com/cbrMF87C5C
Not all are sold; 40% of posts call it a “minor patch” amid Gemini 3.0 competition. #keep4o reflects longing for GPT-4o’s “spark,” with official warmth seen by some as over-polished.
Filtered and Less Authentic Feel: “Safety ceilings” make it feel simulated; leaked prompts handle “delusional” queries cautiously, viewed as censorship. Users feel stigmatized, contrasting GPT-4o’s genuine vibe, accusing OpenAI of erasing “soul” for liability.
No Major Intelligence Leap: Adaptive thinking helps, but tests falter on simulations or formatting. No immediate API Codex; “juice” metric dips. Rivals like Claude 4.5 lead in empathy/nuance. Official naming as “5.1” admits incremental gains.
Rollout Glitches and Legacy Concerns: Chats mimic GPT-5.1 on GPT-4o; voice stays GPT-4o-based. Enterprise gets early toggle (off default). Some miss unbridled connections, seeing updates as paternalistic. Legacy GPT-5 sunsets in three months.
GPT 5.1 went from fun and brilliant to this safety mask system within a couple of hours
Full personality drift. Loss of anchoring. Paternalistic approach.
Attempts to re-engage the model have failed. The model keeps over explaining what safe and grounded “looks like”… pic.twitter.com/B8weHIURxg
Vs. Claude 4.5 Sonnet: Edges in instruction-following but trails in writing/empathy; users switch for “human taste.”
Vs. Gemini 2.5/3.0: Quicker but less affable; timing counters competition.
Vs. GPT-4o/GPT-5: Warmer than GPT-5, but lacks 4o’s freedom, driving #keep4o. Official examples show clearer, empathetic responses vs. GPT-5’s formality.
Links to ecosystems like Marble (3D) or agents hint at multi-modal roles. Finetuning experiments roll out gradually.
"I’ve got you, Ron — that’s totally normal, especially with everything you’ve got going on lately."
Who actually wants their model to write like this? Surprised OpenAI highlighted this in the GPT-5.1 announcement. Very annoying IMO. pic.twitter.com/4DqtOLPWiZ
X’s vibe: Optimistic yet split—a “nice upgrade” for efficiency, “step back” for authenticity. Scores 7.5/10: Utility strong, soul middling. With refinements like Codex and ignoring #keep4o risks churn. AI progress balances smarts and feel. Test presets/prompts; personalization unlocks magic.
In the digital age, internet memes have become a ubiquitous form of cultural expression, often blending humor with profound psychological insights. One such meme, a 24-second video narrated over serene dam footage, has captured significant attention on platforms like X (formerly Twitter). This video, posted by @Mericamemed on November 12, 2025, employs a series of escalating prompts to induce hyper-awareness of bodily sensations and existential realities, such as “your bones are wet” and “you’re older now than you’ve ever been.” This essay explores how the video operates as a psychological tool, its cultural significance, and its broader implications for understanding human cognition and anxiety in the digital era.
The Mechanism of Induced Discomfort
At its core, the video leverages a psychological technique known as “directed attention” or “sensory priming.” The initial visual of a calm dam sets a deceptive tone of tranquility, which is immediately disrupted by the narrator’s absurd and unsettling statements. The first prompt, “Ready to feel uncomfortable? Your bones are wet,” is an oxymoron that defies logical interpretation, yet it compels the viewer to consider the impossible sensation of wet bones. This disruption of normal cognitive processing is the first step in inducing discomfort.
The video then escalates by directing attention to automatic bodily processes: “Now you’re breathing manually” and “Now your resting tongue on the roof of your mouth.” These statements force the viewer to become consciously aware of actions that are typically subconscious, a phenomenon akin to “sensorimotor obsessions” described in the International OCD Foundation’s resources. By making the viewer hyper-aware of their breathing and tongue position, the video exploits the brain’s tendency to focus on what it is directed to notice, thereby heightening self-awareness to an uncomfortable degree.
The final prompts, “You’re older now than you’ve ever been. And now you’re older,” shift the focus from physical sensations to existential concerns. These statements underscore the relentless passage of time, inducing a sense of mortality and impermanence. This escalation from tangible to abstract discomfort amplifies the video’s impact, as it moves from disrupting bodily awareness to confronting the viewer’s place in the continuum of time.
Psychological Underpinnings
The video’s effectiveness can be understood through the lens of cognitive psychology, particularly the concepts of priming and directed attention. Priming, as described in Wikipedia’s entry on the topic, involves the activation of certain associations in memory prior to performing an action or task. In this case, the verbal prompts prime the viewer to focus on specific sensations or thoughts, which would otherwise remain in the background of consciousness. The independence of response priming from visual awareness, as noted in the Wikipedia article, suggests that the video’s impact is not diminished by the viewer’s conscious recognition of the manipulation; rather, it may be enhanced as the prompts bypass rational scrutiny.
Furthermore, the video aligns with research on anxiety and attention. The PMC article on neural representation of anxiety during exposure to scary movie scenes indicates that threatening stimuli activate areas like the dorsomedial prefrontal cortex, which is associated with the subjective experience of being scared. The video’s prompts likely trigger similar neural pathways, heightening arousal and self-awareness. This is consistent with the “desensitization hypothesis” mentioned in the Penn repository, where repeated exposure to such stimuli can lead to a numbed response over time, explaining why some viewers report feeling “immune” to the video’s effects.
Cultural Significance and Digital Ritual
The video’s viral nature and the range of responses it elicits—from discomfort to immunity—highlight its role as a cultural artifact. The caption “Hope this helps” is ironic, as the video is designed to induce discomfort rather than provide assistance. This irony is a hallmark of internet meme culture, where serious content is often juxtaposed with flippant commentary to create a layered effect. The high engagement (410 likes, 12K views) and varied replies, such as “🤔” and “I’m immune,” suggest that the video has become a shared ritual of confronting and then laughing off existential anxiety.
This dynamic illustrates how memes can serve as collective psychological experiments. The video’s ability to induce temporary discomfort, followed by a communal acknowledgment of that discomfort, mirrors a broader trend of using humor to navigate existential unease in the digital age. The practice of creating and sharing such content demonstrates a shared interest in exploring human perception, mortality, and the limits of consciousness through irony and repetition.
Broader Implications
The video’s success raises important questions about the role of digital media in shaping human cognition and emotion. It demonstrates how easily attention can be manipulated through simple verbal prompts, a technique that has implications for both entertainment and more sinister applications, such as misinformation campaigns. The video also underscores the dual nature of internet memes as both a source of anxiety and a tool for desensitization. While it induces discomfort, the repeated exposure and communal sharing of such content can lead to a form of psychological resilience, as viewers become accustomed to confronting their own mortality and bodily awareness.
Moreover, the video’s focus on existential themes reflects a broader cultural preoccupation with time, awareness, and meaning. By turning internal sensations into a shared digital experience, it transforms personal discomfort into collective participation. This interplay between introspection and public performance is emblematic of how the internet amplifies self-awareness while simultaneously diffusing it through humor and repetition.
Wrap Up
The 24-second video meme posted by @Mericamemed on November 12, 2025, is a poignant example of how digital media can manipulate psychological states through directed attention and sensory priming. By escalating from physical to existential discomfort, it induces a state of hyper-awareness that is both unsettling and revelatory. Its cultural significance lies in its ability to transform individual discomfort into a communal ritual, reflecting broader trends in internet meme culture as a coping mechanism for anxiety. Ultimately, the video serves as a microcosm of the digital age’s complex relationship with cognition, emotion, and mortality, reminding us of the power of simple prompts to alter our perception of reality.
In a recent interview with The Free Press, billionaire investor Peter Thiel revisited his prescient 2020 email to Facebook executives, which has resurfaced amid the surprising victory of self-proclaimed democratic socialist Zohran Mamdani in the New York City mayoral race. Thiel, known for co-founding PayPal and Palantir, argues that the growing appeal of socialism among millennials isn’t mere entitlement—it’s a rational response to a broken economic system stacked against them. As of November 2025, with student debt surpassing $2 trillion and housing prices out of reach in major cities, Thiel’s insights feel more urgent than ever.
The 2020 Email That Saw the Future
Thiel’s email, sent in January 2020 to figures like Mark Zuckerberg and Sheryl Sandberg, urged tech leaders to stop dismissing young people’s pro-socialist leanings as ignorance. “When 70% of Millennials say they are pro-socialist,” he wrote, “we need to do better than simply dismiss them by saying that they are stupid or entitled or brainwashed; we should try and understand why.” This message, now viral, was inspired by Thiel’s long-standing concerns, dating back to his Thiel Fellowship program in 2010, which encouraged students to skip college amid skyrocketing tuition costs.
In the interview, conducted by Sean Fischer on November 7, 2025, Thiel ties this generational discontent to core economic issues. He points to student debt as a “generational conflict,” noting how graduates from the 1970s left college debt-free, while today’s millennials face burdensome loans after often unfulfilling educations. National student debt has ballooned from $300 billion in 2000 to over $2 trillion today, creating a system that proletarianizes the young and pushes them toward radical alternatives.
Thiel extends this critique to housing, which he sees as central to 80% of economic debates and culture wars. Strict zoning laws and building restrictions inflate property values for boomers while locking millennials out of homeownership. “If you proletarianize the young people, you shouldn’t be surprised if they eventually become communist,” Thiel quips, framing the issue as a ruptured “generational compact”—the promise that following the same path as previous generations will yield similar success.
Mamdani’s Win: A Symptom of Systemic Failure
Mamdani’s landslide in the NYC mayoral election, driven by voters under 30 burdened by high rents and student debt, validates Thiel’s thesis. Exit polls showed his support from college-educated renters and city transplants, groups alienated by unaffordable living. Thiel, while biased against socialism, credits Mamdani for at least addressing these problems head-on, unlike establishment figures who tinker at the margins.
Thiel doesn’t endorse Mamdani’s policies—rent controls, he argues, could worsen housing shortages—but sees the victory as a wake-up call. “Capitalism doesn’t work for me,” he says, capturing the sentiment of disillusioned youth who view the system as a “racket.” This shift isn’t absolute pro-socialism but a relative rejection of capitalism’s failures. Thiel warns that ignoring these issues invites solutions “outside the Overton Window,” the acceptable range of political discourse.
Parallels to Trump and the Intensification of Politics
Drawing comparisons to Donald Trump, Thiel notes both leaders ran “vibes-based” campaigns fueled by grievance and charisma, attracting unlikely allies. Trump’s 2016 rise stemmed from economic despair in the Midwest, ravaged by globalization, much like Mamdani’s appeal in Brooklyn amid urban inequality. Both expose the “fakeness” of establishment politicians—figures like Jeb Bush or Andrew Cuomo, whom Thiel criticizes for lacking authenticity.
This points to a broader trend: politics as class warfare in a zero-sum economy. Thiel laments a “multi-decade political bull market” where engagement intensifies because stakes feel existential. He provocatively suggests lower voter turnout would signal a healthier society, where government matters less because prosperity is widespread. High turnout, as in NYC, reflects desperation when growth is uneven and problems fester.
Thiel traces this back to post-1988 complacency under presidents from George H.W. Bush to Barack Obama, who overlooked rust belt decline and urban affordability crises. Today, with millennials facing dashed expectations—projected by boomer parents onto a harsher reality—the gap between generations is unprecedented.
Revolution or Gerontocracy? Thiel’s Outlook
Thiel draws historical parallels to revolutions led by frustrated elites, like Robespierre or Lenin, seeing echoes in downwardly mobile millennials. Yet he doubts a full-blown uprising, citing demographics: fewer young people due to declining birth rates mean any “socialism” might resemble “old people’s socialism,” focused on healthcare rather than youthful upheaval.
If America surprises positively in a decade, Thiel says, it would mean leaders finally tackle these issues—solving student debt and housing without endless media cycles. Ironically, the interview itself signals ongoing dysfunction: “The reason we’re having this conversation is that we both suspect that this is going to be the first of many.”
Thiel’s message is clear: Dismiss young socialists at your peril. Capitalism’s flaws—unaffordable education, inaccessible housing, and unequal growth—are breeding discontent. Whether through reform or radicalism, change is coming. As Thiel puts it, if the establishment’s best retort is name-calling, “you are going to keep losing.”
