All-In Podcast in 3 minutes

Here is The Daily FM summary of the All-In Podcast that aired on Monday September 28th. Daniel Ek, Spotify’s co-founder and now executive chairman, joined Jason Calacanis and David Friedberg to discuss Spotify’s origins, his new preventive-health company Neko Health, and his cautiously optimistic view of AI. [1]

Ek began with Spotify’s unlikely creation during music piracy’s peak. In 2006, Sweden had fast broadband, rampant illegal downloads, and virtually no legal digital-music options. The music business was collapsing, but Ek and co-founder Martin Lorentzon saw that consumers would pay for a vastly better experience: all the world’s music, instantly accessible. The catch was licensing. Ek said he and his partner invested their own money and persuaded record labels with a clever guarantee: if Spotify failed after a year, the labels still met their financial targets; if it worked, everyone won. It took years of negotiation before Spotify launched in Sweden in 2008, then the UK, and finally the U.S. in 2011.

The larger focus was Neko Health, Ek’s eight-year-old healthcare startup. His argument is that American healthcare remains designed to react to acute illness, even though chronic diseases are the biggest cost and suffering burden. Many serious illnesses can be treated far more cheaply and effectively when found early, he said, but the system lacks enough high-quality, longitudinal patient data.

Neko’s answer is an annual, roughly one-hour health scan priced at $499. It combines 53 blood markers, cardiovascular measurements, strength testing, and more than 6,000 high-resolution skin images, followed by time with a clinician. The company has performed over 100,000 scans and says about 1 percent of members have had a serious undiagnosed condition identified. Ek stressed that most customers are healthy; the purpose is both to catch hidden risks and make lifestyle improvements more concrete.

The most striking example involved skin screening. Ek said the average Neko patient has around 950 moles, an astonishing number that drew disbelief from the hosts. Rather than relying on a doctor to notice one suspicious spot, Neko uses AI to catalog and flag lesions, then has clinicians and dermatologists review findings. On repeat visits, it can detect subtle changes over time that even an excellent physician could not remember from one year to the next.

Ek acknowledged that $499 is still meaningful money, but argued preventive care should become as routine as an annual dental visit. He said Neko’s vertically integrated model—its own clinics, equipment, software, and staff—lets it offer the service with positive unit economics. He also identified a central structural problem in U.S. healthcare: insurance is frequently tied to jobs, so insurers have little reason to fund prevention whose payoff may arrive a decade after a patient switches employers.

On AI, Ek resisted sweeping pronouncements about whether development should slow down. Instead, he argued the industry does a poor job explaining AI’s positive uses, such as early disease detection and better music personalization. He endorsed a future with both closed frontier models and open-source systems, while suggesting that access to large-scale compute may matter more for safety than trying to regulate software alone.

Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Friday September 25th. The hosts used the episode to argue that the AI debate has shifted from theoretical fears of “superintelligence” to a more practical question: should companies be held accountable for products they choose to release?

David Sacks and Chamath Palihapitiya criticized leading AI developers, especially Anthropic and OpenAI, for calling themselves “labs” while operating as enormous, profit-seeking corporations. Their central argument was that companies should not seek broad immunity or global governance schemes to avoid responsibility. Instead, they should test products, slow down releases when necessary, and face normal product-liability rules—much as Tesla, Meta, and other scrutinized technology companies do.

Sacks argued that international AI regulation would arrive too slowly to matter and could dilute accountability. Chamath’s sharper formulation was that these are not neutral research labs: they have shareholders, giant valuations, major capital needs, and should be judged accordingly. The group also pushed back on the idea that competitive markets inherently make AI unsafe. Their view was that customers do not want unreliable products, and businesses already have strong legal and financial incentives not to release dangerous software.

David Friedberg then laid out the episode’s biggest technology takeaway: open-weight AI is progressing at a startling speed. He cited a flood of recent releases from Chinese and other developers, including models capable of advanced coding, image generation, robotics, and technical reasoning that can be downloaded and run locally. In his telling, AI capability is no longer confined to a few frontier companies or giant data centers. The hosts argued that this makes calls to “ban superintelligence” increasingly unrealistic: software has already spread widely, and restrictions could simply move talent and innovation abroad.

The panel debated what that means for Anthropic and OpenAI. Chamath said model capabilities are clustering, while the real differentiation increasingly lies in the “harness” around a model—the agents, interfaces, and workflows that let it take useful action. He warned that customers will pressure companies to move from expensive premium models to cheaper open alternatives. Friedberg noted that Anthropic may retain an edge in difficult scientific and life-sciences applications, where customers could pay heavily for frontier performance. Sacks was more optimistic about both Anthropic and OpenAI, calling them a durable frontier-intelligence duopoly—but warned they must keep improving because their lead may last only six to twelve months.

Anthropic’s possible IPO became a focal point. Sacks said the company’s own public warnings about catastrophic AI risk, combined with its push for regulation and its plan to open a biological research lab, could create unusually severe investor risk disclosures. Chamath countered that CEO Dario Amodei has built a formidable company and talent magnet, but said the IPO may need a lower valuation to compensate investors for those risks.

The episode ended on a more optimistic note around Meta’s Muse and xAI’s Grokbot. The hosts described these as the first broadly accessible AI agents that could book travel, manage inboxes, identify savings, process returns, and act like free personal assistants. Their prediction: once ordinary users experience that utility, fear of AI may give way to demand for it. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Wednesday September 23rd. The episode featured Luca Ferrari, CEO of Milan-based Bending Spoons, explaining how his company turned a failed AI startup, a leftover $40,000, and a $10,000 app acquisition into one of technology’s most aggressive—and unusual—serial acquirers. [1]

Ferrari said he and his co-founders began with an AI company in 2010, but were simply too early and it failed after three years. Their investors effectively let them keep the remaining $40,000 rather than spend more on liquidation. Instead of taking the suggested vacation, the founders used it as seed capital for Bending Spoons in 2013. Their key insight was unusually candid: they were not especially good at discovering product-market fit from scratch, but had become strong at engineering, design, marketing, and monetization. So they decided to “buy product-market fit” from others, then improve it.

Their first deal was a roughly $10,000 acquisition of a lightly monetized iPhone keyboard-customization app. It had users and favorable App Store positioning, but Bending Spoons rebuilt it entirely. That basic formula has since expanded to much larger brands, including Vimeo, AOL, Eventbrite, Airtable, and Miro. Ferrari described Bending Spoons not as a holding company but as an operating platform: when it buys a company, it deeply integrates it into a shared system of more than 50 internal technologies, covering areas such as AI-model orchestration, recruitment, A/B testing, payments, and operations. [2]

The most controversial part of the model is its lean staffing. The hosts compared Bending Spoons’ post-acquisition cuts to Elon Musk’s approach at X, but Ferrari said the company learned its staffing discipline organically. Early acquisitions often came without the original team, forcing Bending Spoons to operate comparable businesses with much smaller internal teams. Its theory is that small, highly talented, highly accountable teams are more likely to produce “10 out of 10” performance than large organizations. Of about 800 core employees, roughly three quarters work in engineering, AI, product design, or product management. Ferrari said the company received 800,000 applications last year and hired fewer than 300 people.

Financially, Bending Spoons has relied mostly on reinvesting free cash flow and using debt, rather than repeatedly raising equity. Ferrari said its blended debt cost is around 9 percent, fully hedged, with maturities extending to 2031. His surprising argument was that higher rates might not be disastrous: while new borrowing would cost more, the valuations of acquisition targets could fall, creating better opportunities for a disciplined buyer with historically strong unlevered returns.

Ferrari argued Bending Spoons differs fundamentally from traditional private equity. Private-equity owners usually keep companies separate so they can resell them; Bending Spoons transforms them onto a common technical foundation and shares elite talent across the portfolio. That makes its model harder to copy, but also means it cannot simply flip assets.

The hosts also challenged the assumption that Europe lacks world-class technology talent. Ferrari acknowledged Europe’s structural problems but said its half-billion-person market, solid education, and ambitious people eager to prove themselves provide an underrated advantage. Milan remains Bending Spoons’ largest talent hub, but London, Madrid, and eventually the United States are growing. His closing message was that the company stays focused on becoming exceptional at one thing: acquiring mature digital businesses and making them materially better. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time! [3]

Here is The Daily FM summary of the All-In Podcast that aired on Tuesday September 22nd. The episode focused on California politics, featuring Republican gubernatorial candidate Steve Hilton and media personality turned Los Angeles political candidate Spencer Pratt. Their shared message was that California’s government has become an entrenched, one-party “machine” that rewards bureaucracy, special interests, and disorder while making ordinary life unaffordable.

Hilton, a British-born former tech entrepreneur, presented California as a uniquely consequential test case. In his words, California means to America what America means to the world: a place historically defined by innovation, ambition, agriculture, entertainment, and technology. Yet he argued that 16 years of Democratic control have produced the country’s highest poverty rate, unemployment, housing costs, and regulatory burden, along with a continuing exodus of residents and businesses. He blamed one-party rule for letting unions, trial lawyers, donors, and politically connected nonprofits dominate Sacramento. [1]

His economic pitch centered on lowering the cost of living. Hilton proposed cutting California’s regulatory count from more than 420,000 to below 200,000, reducing government headcount, canceling high-speed rail, ending some homelessness-related nonprofit funding, and using the savings to eliminate state income tax on the first $150,000 earned. He also pledged to reduce gasoline prices by rolling back state climate-related fuel charges and to cap annual vehicle registration at $73 by abolishing the DMV. The hosts pressed him on his difficult polling position, but Hilton said his campaign had narrowed the gap against Democrat Javier Becerra, especially among independents and financially stressed working-class voters.

Hilton’s sharpest attack was on Becerra, whom he portrayed as a career politician and a likely continuation of Governor Gavin Newsom’s policies. The conversation was more persuasive when it focused on concrete examples than personal insults: Hilton described small businesses facing illegal street vendors, excessive fees, and rising energy costs, and argued that California has inverted incentives, punishing rule-following businesses while tolerating disorder.

Spencer Pratt joined to recount his own Los Angeles campaign after losing his home in the Pacific Palisades fire. Pratt’s anger over the fire, empty reservoirs, brush-management rules, and what he sees as city incompetence drove much of the discussion. He said he entered politics to force leaders to take public safety, infrastructure, and rebuilding seriously. He also argued that viral AI-assisted campaign videos helped him break through traditional political media, though he emphasized that the message—not the technology—was what resonated.

The most contentious section concerned mail voting and ballot harvesting. Pratt alleged that California’s rules enable highly organized political groups to collect ballots and influence voters, while acknowledging he lacked evidence of specific fraud in his own race. Host Jason Calacanis repeatedly challenged him to distinguish legal ballot collection, campaign persistence, and actual criminal fraud. The exchange exposed a real disagreement: Pratt and some hosts viewed the system as structurally vulnerable, while Calacanis insisted extraordinary claims require evidence and legal action.

The episode ended on Hilton’s more optimistic note. Beyond cutting waste, he wants California to build “ten new cities,” revive housing and business creation, and reclaim its role as a place where people come to build. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Tuesday September 22nd. The episode featured Boom Supersonic founder and CEO Blake Scholl, who made an energetic case that commercial aviation has stagnated for decades—and that his startup can bring back faster-than-sound passenger travel while also becoming a major supplier of power for AI data centers. [1]

Scholl’s opening argument was deliberately provocative. In 1969, humanity landed on the Moon and flew an airliner through the sound barrier. Yet more than 50 years later, he said, neither lunar exploration nor supersonic civilian travel has maintained that momentum. Concorde’s retirement in 2003 left commercial passengers flying at essentially the same speeds as previous generations. He also criticized the aerospace incumbents, noting that Boeing’s last all-new airliner program began in 2004 and arguing that the giant has become complacent. [2]

Boom began in far less glamorous fashion: its early prototype was essentially a cardboard-and-plywood mockup with office-store seats. Scholl, formerly a software engineer and advertising executive, recalled pitching Jeff Bezos for seed funding in 2015. Bezos passed, while warning that startups could not build a composite airliner in a garage. Scholl said he took that personally. Boom later built XB-1, which it describes as the first privately developed jet to break the sound barrier, with a team of only about 50 people. [3]

The technical centerpiece was Boom’s approach to the sonic-boom problem. Rather than eliminate the boom at its source, its “boomless cruise,” or Mach cutoff, concept uses atmospheric conditions to bend the shockwave upward before it reaches the ground. Scholl compared it to a tree falling where nobody hears it. He said this enables flight around Mach 1.3 over land—about 50 percent faster than today’s commercial speeds—with no boom heard below. Over oceans, Boom’s planned Overture aircraft would fly at Mach 1.7, cutting a transatlantic trip to roughly three and a half hours.

Scholl said the longstanding U.S. ban on civil supersonic flights over land ended by executive order after Boom’s testing, and he emphasized that permanent legislation has advanced unanimously through the House and Senate Commerce Committee. The political surprise, he argued, is that supersonic travel has become a rare bipartisan cause. He praised the current administration for moving quickly, saying an invitation to the White House arrived within a day of his public campaign. [4]

The larger business surprise was engines. After a public split with Rolls-Royce, Boom decided to develop its own engine rather than outsource the task. Scholl now believes that setback may have saved the company: the same high-power turbine core needed for supersonic aircraft can be adapted into generator systems for data centers. Boom says it has demand in the tens of gigawatts and plans to test its first engine core soon. Its trailer-mounted systems could provide 42 megawatts of on-site generation without water cooling.

Asked when passengers can fly, Scholl estimated four years as the goal, though he stressed that speed matters more than predictable deadlines. He put Overture’s transatlantic break-even round-trip fare at about $3,500, with airlines likely charging more. His long-term definition of success was broader than premium travel: a future where children find a six-hour transcontinental flight as strange as they now find rockets that fail to land themselves. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Monday September 21st. The episode featured AI entrepreneur Naveen Rao, co-founder and CEO of Unconventional AI, making an audacious case that artificial intelligence’s biggest near-term constraint is not model capability but energy—and that conventional computer architecture may be fundamentally too wasteful for the intelligence systems people want to build. [1]

Rao is an AI-chip veteran who founded Nervana Systems in 2014, sold it to Intel, then led Intel’s AI group. Later, he helped build infrastructure for training large models before joining forces with Databricks. His newest company is attempting what he described as a first-principles redesign of computing, with a target of delivering 1,000 times better power efficiency within three and a half years.

His core warning was stark. Google alone reportedly processes 3.2 quadrillion AI tokens per month. Using a rough estimate of 10 joules per token, Rao said that could imply 12 gigawatts of power—against approximately 40 gigawatts currently going into all U.S. data centers. Whether the exact estimate holds, his point was that AI demand and model sizes are growing far faster than electricity supply. Data-center planning, he said, has already shifted from finding floor space, racks, or GPUs to first securing power contracts. Energy represents about half the cost of serving an AI token.

Rao argued that today’s computers waste energy mostly by constantly moving information between separate memory and compute components. GPUs remain descendants of the old von Neumann architecture: extremely fast, but designed around digital abstractions and data movement rather than efficiency. Biology provides an alternative benchmark. The human brain uses roughly 20 watts; a squirrel’s highly capable brain uses only about 8 milliwatts. Rao’s provocative ambition is not merely to imitate biology, but ultimately to “beat biology.”

Unconventional AI’s proposed answer is a “dynamical computer,” where memory and computation are integrated into physical, time-varying circuits. Rao illustrated the concept with metronomes placed on a movable board: even when started out of sync, physical interaction causes them to synchronize. His company seeks to harness similar emergent behavior in semiconductor circuits, rather than forcing every task through conventional matrix multiplication and repeated memory access.

The most notable reveal was Rao’s claim that his team has built the first physical dynamical computer. The startup began in earnest in January, sent its chip design to fabrication in June, and now has a working prototype in the lab. It generated images using approximately 500 nanojoules per image, which Rao contrasted with millijoules for conventional GPU-based computing—suggesting orders-of-magnitude lower energy use.

He also said a key breakthrough involves “sparsity”: deliberately removing many connections in a system rather than connecting every element to every other element. Counterintuitively, Rao said this can improve scalability, efficiency, and trainability all at once.

In the discussion afterward, Rao said the company expects to have a full product in about two years, beginning with data-center racks that provide tokens through a network connection while hiding radically different hardware underneath. Existing models could be adapted at the model level, although migration will require work. The team spans theorists, neuroscientists, physicists, and chip engineers—a difficult mix to coordinate—using Python-based libraries to bridge disciplines.

Rao’s closing thesis was optimistic: cheaper intelligence may increase total AI consumption through Jevons paradox, but it could also decentralize computing, enable local data centers, and make vast robotic systems economically viable. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Sunday September 20th. The hosts interviewed AppLovin founder and CEO Adam Foroughi, a low-profile executive behind one of the market’s most remarkable recent turnarounds. AppLovin began as an advertising platform for mobile-game developers, helping them monetize the enormous amount of time adults spend playing casual games. Foroughi estimated that more than a billion people play mobile games each day and that the ecosystem now generates roughly $50 billion a year in advertising spend. [1]

The company’s larger ambition is to move beyond getting players from one game to another and use its recommendation technology to introduce shoppers to products they did not know they wanted. Foroughi drew a useful distinction between search advertising and discovery advertising. Search, including advertising that may eventually appear in AI chatbots, serves someone who already knows they want dress shoes or another product and is ready to research it. Discovery advertising, like Facebook and Instagram ads or AppLovin’s newer commerce efforts, attempts to create demand by presenting a relevant product unexpectedly. He argued that this produces real economic expansion, not merely a better route to an already-planned purchase.

Foroughi described advertising as “machine learning 1.0.” Recommendation systems and large language models differ technically, but he said both grew from related research and both improve by predicting outcomes. Advertising has an unusual advantage: it gives instant feedback on whether a prediction produced a transaction, making it an extremely profitable proving ground for deep-learning systems.

One of the most notable exchanges concerned the persistent suspicion that phones are secretly listening to conversations. Foroughi rejected that idea as impractical, given the scale of data needed to record and interpret audio for ads. He suggested the eerie coincidence usually comes from more ordinary signals—searches, browsing behavior, or connections between people on social networks. The hosts raised the possibility that platforms may infer interests among nearby friends or social groups, but Foroughi’s broader point was that targeted advertising is less mysterious than it appears, and that people often prefer relevant ads to irrelevant spam.

The most dramatic part of the episode was AppLovin’s market collapse and recovery. The company went public in 2021 at about a $28 billion valuation, rose to $40 billion, then fell to roughly $3.8 billion in 2022—a 92 percent drawdown—even as its EBITDA grew from $600 million to around $1 billion. Foroughi blamed a flood of insider selling and insufficient interest from major investors during the Covid IPO boom. Rather than spend time persuading Wall Street, he told his team to become their own best investor. AppLovin spent roughly $6 billion buying back stock, retiring 20 to 25 percent of its shares; at its peak, those repurchases were worth more than $50 billion.

He said maintaining morale required an “us against the world” culture and expanded performance stock awards for key employees who had watched their expected wealth evaporate. The turnaround accelerated after AppLovin upgraded from simpler statistical models to a deep-learning system, improving advertiser performance. When Foroughi finally returned to investor meetings in 2023, he said the stock surged from about $80 to $150 in a week. It eventually ran from $9 to $750, reaching around $250 billion in market value—an equally extreme example of investor herd behavior on the upside.

On privacy, Foroughi accepted the need for clear rules, including Apple’s restrictions on precise targeting. But he argued that privacy changes can lead users to receive worse ads, even though they still spend 30 seconds watching them in exchange for an in-game reward. His view was that regulation has now stabilized and powerful models can still provide relevance with less granular data.

Finally, he argued that AI agents will automate routine purchases, such as supplement subscriptions, but will not eliminate shopping as entertainment. Most people, he said, still enjoy browsing, comparing, tracking packages, and discovering something new. AppLovin’s edge, in his telling, is intense focus: a lean company, specialized talent across Palo Alto, Beijing, and Singapore, differentiated data, and the constant assumption that giant competitors could overtake it at any time. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Friday September 18th. Legendary venture investor Bill Gurley delivered an unusually personal keynote arguing that society’s response to major disasters should follow a simple discipline: find the root cause, correct it, and prevent a recurrence. His concern was that the world has failed to apply that standard to Covid-19, despite its enormous human and economic costs. [1]

Gurley began with a tour of catastrophes where independent investigation eventually forced reform. He cited the Surfside condominium collapse, the Boeing 737 Max crashes, Hurricane Katrina, Fukushima, and the Challenger explosion. In each case, he said, a technical failure was compounded by institutional failure: bad designs, ignored warnings, regulators too close to the institutions they oversee, and organizations instinctively circling the wagons. But there were also “searchers”—reporters, whistleblowers, victims’ families, scientists, legislators, and independent investigators—who uncovered what happened and pushed governments and companies toward changes. [2]

His heroes included Richard Feynman, who cut through NASA’s evasions after Challenger by demonstrating on live television how cold could compromise an O-ring, and Japanese investigator Kiyoshi Kurokawa, whose Fukushima commission concluded that the nuclear disaster was not simply natural but “profoundly man-made” and preventable. Gurley’s broader lesson was that public scrutiny and genuine root-cause analysis matter because prevention depends on understanding the actual failure.

He then turned to Covid, which he described as vastly larger than the disasters he had just outlined—citing 15 million deaths and a $45 trillion global cost. Gurley’s central complaint was not that the answer is already certain, but that an independent, adequately resourced inquiry has never been conducted. He argued there has been no sustained major-newsroom investigation, bipartisan congressional effort, federally funded third-party inquiry, or commission comparable to those that followed much smaller tragedies.

Gurley strongly criticized prominent Covid-era scientific figures including Anthony Fauci, Francis Collins, Peter Daszak, Jeremy Farrar, and Ralph Baric. He portrayed them as conflicted “blockers,” rather than impartial investigators, particularly because of their past support for gain-of-function research. He argued that the early scientific consensus favoring animal spillover unfairly stigmatized consideration of a lab accident as conspiracy thinking, and that this chilled journalists and scientists from asking questions.

The most notable evidence he highlighted was the “DEFUSE” proposal, uncovered by the DRASTIC research group. Gurley said the document described EcoHealth Alliance collaborators proposing research that would modify bat coronaviruses, including inserting a furin-cleavage site. He argued this should be treated as a major investigative lead, not proof of any conclusion. He also pointed to China’s reported testing of tens of thousands of animals without identifying a clear intermediary host, while acknowledging that animal spillover should remain open to research.

When asked directly what he thinks caused Covid, Gurley declined to choose a definitive origin. That was his key closing point: the goal should be truth and prevention, not prosecution or partisan victory. He called for support for independent researchers, greater document disclosure from institutions such as UNC, renewed investigative journalism, and a genuinely independent commission—someone with the persistence of Feynman—to establish the root cause before another pandemic tests an already weakened public trust. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Friday September 18th. NASA administrator and private astronaut Jared Isaacman delivered an unapologetically ambitious vision for American space exploration: return astronauts to the Moon, establish a permanent lunar base, build nuclear-powered spacecraft, and ultimately send people to Mars before China can claim the defining victory of a new space race. [1]

Isaacman’s central argument was that NASA’s problem is not a lack of money, talent, or imagination, but decades of diffused priorities and poor capital allocation. With a roughly $25 billion annual budget, he said, NASA has too often tried to satisfy every congressional district, partner country, and contractor instead of executing focused missions. He criticized expensive programs that became too big to fail, highlighting a Moon rocket system he said is less efficient than the Saturn V and a Mars sample-return effort that approached the cost of an aircraft carrier before being canceled.

His remedy is a more disciplined NASA that does work industry cannot yet profitably do. Commercial companies such as SpaceX, Blue Origin, Rocket Lab, and others should handle proven services like launch, communications, and Earth observation. NASA, in his telling, should push the next frontier: nuclear power and propulsion, advanced robotics, Mars technology, radical aircraft designs, and flagship science missions.

The near-term plan is aggressive. Isaacman said Artemis III is moving toward a 2027 mission involving rendezvous and testing with vehicles from both SpaceX and Blue Origin, followed by astronauts returning to the lunar surface with Artemis IV in 2028. The objective is not a symbolic visit but a Moon base at the lunar south pole, where permanently shadowed craters may contain water ice and nearby ridges can offer nearly continuous solar power.

The urgency, he stressed, comes from China. Isaacman described the lunar south pole as a very small piece of highly valuable real estate, comparing the whole Moon to Africa but the desirable polar region to Washington, D.C. There are only a few practical “parking spots,” and heavy landings could damage them. China and Russia, he warned, are pursuing their own south-pole base and nuclear-power capabilities. His most memorable image was a future astronaut stepping onto the Moon in live high-definition video, only for the flag on the spacesuit not to be American.

The most futuristic portion of the conversation was Isaacman’s proposed “Nuclear NASA.” He argued that fission reactors could generate electricity for efficient electric propulsion, making missions farther from the Sun more practical and reducing dependence on manufacturing fuel on Mars. A planned 2028 nuclear-powered mission would fly past Mars and deploy three helicopter-like scouts equipped with ground-penetrating radar to search for subsurface ice and future landing sites.

He also made the case for human spaceflight even as robots improve. Robotics should do dangerous, repetitive work, he said, but humans will still cross oceans, climb mountains, and explore space because exploration is part of human nature—and because human missions inspire the public in ways machines do not.

The hosts were enthusiastic, joking that NASA has a much easier time making exciting presentations than agencies such as the IRS or HUD. Their broad takeaway was that Isaacman wants NASA to recover its Apollo-era confidence: less bureaucracy, more urgency, stronger partnership with private industry, and a clear national mission to ensure America leads in space. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!

Here is The Daily FM summary of the All-In Podcast that aired on Thursday September 17th. The panel hosted independent video journalist Nick Shirley, whose investigations into government waste and alleged fraud have made him both a social-media phenomenon and a target of political backlash.

The conversation opened with Shirley’s latest report on California’s high-speed rail project. He portrayed it as a monument to failed public infrastructure: after roughly 18 years and at least $15 billion spent, the system has yet to lay operational track or connect any towns. Original estimates of around $33 billion have ballooned repeatedly, with figures cited in the discussion reaching as high as $236 billion. The line’s original promise—linking Los Angeles and San Francisco—has effectively narrowed to a Central Valley segment between Merced and Bakersfield. [1]

Shirley interviewed local officials, farmers, and state senator Dave Cortese. Critics argued that the project suffers from disastrous planning: homes are still being built along the proposed route, farms could be divided by the line, and contractors have received huge delay payments when they could not work. One striking claim was that a contractor settlement exceeded half a billion dollars for delays. The hosts contrasted the project with China’s vast rail buildout and argued that California could subsidize flights between San Francisco and Los Angeles for generations for less than the projected cost of the train. [2]

Senator Cortese defended the rail program as a long-term economic-development project, saying thousands of workers are active across 21 construction sites. But his admission that completion in 20 years “might be, might not” became one of the episode’s most memorable moments. The hosts saw that uncertainty as emblematic of weak accountability: legal, procedural, and political failures that may not fit the narrow definition of fraud, but still waste public money.

The discussion then shifted to Shirley’s broader work exposing alleged misuse of social-benefit programs, particularly in California and Minnesota. He described investigating daycares, nonprofits, healthcare providers, and organizations serving immigrants that receive public funding. Shirley said California passed a law—described by critics as the “Stop Nick Shirley Act”—that could allow certain immigration-support organizations to demand he remove footage and potentially expose him to fines and legal costs. He is suing the state, arguing that the measure violates his First Amendment rights.

The panel was especially critical of the political dynamics behind the law. Shirley noted that one sponsor was an immigrant-rights nonprofit that he said had received substantial state money, while the bill’s author was identified as the state attorney general’s wife. The hosts treated this as an effort to shield publicly funded organizations from scrutiny, though Shirley acknowledged that his reporting depends heavily on local tips and viewers flagging suspicious activity.

Shirley explained that he began as a teenage YouTube prank and vlog creator, later covering migration after time spent in Chile and interviews at the southern border. He says his investigations are self-funded through his audience, not backed by an institution. Jason Calacanis praised him as a new-generation investigative reporter doing work once associated with programs like 60 Minutes and Frontline, and pledged financial support for a small research, editing, and security team.

A sobering note came when Shirley said the confrontational style that drives attention also creates real danger: he now considers security because subjects may react violently when confronted. Still, he argued that exposing fraud can produce tangible consequences, pointing to recent charges and guilty pleas connected to cases he has highlighted. His closing message was simple: young people should complain less, investigate more, and follow corruption stories through until someone is held accountable. Thank you for listening to All-In Podcast in 3 minutes from The Daily FM. See you next time!