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Based on "How Anthropic Uses Claude Fable 5 With Mike Krieger" from Every Watch the original video

The AI Teammate: Mike Krieger on Fable 5's Transformative Power

Episode summary

Mike Krieger, co-founder of Instagram and head of Anthropic Labs, shares his profound experience using Anthropic's new Claude Fable 5 AI model, asserting it dramatically redefines software engineering by collapsing the gap between intent and execution. He recounts how Fable 5, unlike previous models, allows him to delegate complex, overnight tasks with high trust, even having the AI autonomously overcome obstacles like a remote service outage by scaffolding a backend. This shift has enabled him to build a personal media tracker that self-modifies its code from within the application, a process that would have taken five days of "all-nighters" in Instagram's early days, now completed with Fable 5 in a fraction of the time.

The practical takeaway is that individuals, even non-technical ones, can now achieve a level of software development previously reserved for experienced engineers, with Krieger noting a recruiter's excitement at finally bridging the gap between her ideas and tangible tools. While the traditional craft of elegant coding may feel diminished, the overall capacity for human creativity and building is vastly expanded. However, users should be mindful of Fable 5's processing time and cost for simpler tasks, potentially using faster models for quick questions, and considering architectural planning with the AI for larger projects.

When a new, powerful AI model drops, the initial buzz is often driven by quick demos and first impressions. But what truly sets a breakthrough model apart isn't just its day-one capabilities, but how it integrates into daily workflows and reshapes the very act of creation. Mike Krieger, Head of Anthropic Labs and co-founder of Instagram, offers a rare, in-depth look at this evolution, sharing his extensive experience using Anthropic's latest and most advanced model, Fable 5, internally for months before its public release. For Krieger, Fable 5 isn't merely a tool; it's a "teammate" that is fundamentally altering how he and his teams build software.

From Newbie to Delegator: A Shift in Workflow

Krieger's journey with Fable 5 began with a surprising feeling: "I feel like a total newbie again." This wasn't due to a lack of skill, but because the model demanded a complete re-evaluation of how he approached tasks. Old prompting techniques and methods for decomposing problems suddenly felt "out of date." The interaction model had to evolve from simple "Can we start by doing this?" to expressing broader intent and trusting the AI to grasp global context.

The most profound shift, according to Krieger, is Fable 5's ability to handle complex, multi-step tasks with remarkable autonomy. He describes a common scenario: "I will, you know, wish Claude a good night, set it up on like a pretty complex task... and wake up to, you know, actually it's usually done by like 2:00 in the morning." This isn't just about completing simple requests; Fable 5 demonstrates an impressive capacity to navigate unexpected challenges. Krieger recounts instances where the model, encountering a remote service outage, would proactively "scaffold a backend for it for now," document the temporary solution, and keep track of the original problem, ready to fix it when the service returned.

This level of delegation has forced Krieger to rethink productivity entirely. "It is much more like we've talked for a while about, you know, like what is it like when these models are more of like a companion or a co-worker and it really feels like now it's like a teammate that I can delegate like a lot of work to." This isn't a turn-by-turn interaction; it's a long-horizon, "don't worry, I'm on it" modality that feels akin to working alongside a highly capable human colleague.

Building the Future: Self-Modifying Software and Democratized Creation

Krieger shared a compelling anecdote about a personal side project: a media tracker app he built over a weekend using Fable 5. His core criteria for the app were simple: easy content addition (via URL, with Claude handling the semantic search) and proactive research (e.g., finding new seasons or sequels). While the UI was largely a "Fable One-shot" creation, the project's real innovation lay in its exploration of "agent-native architectures."

"What if you could actually modify the software from within itself?" Krieger mused. He built a feature where, with a long press on the chat icon, the app would open an interface allowing Fable 5 to take edit requests and preview changes live. This wasn't just about the AI generating code; it was about the AI modifying its own running application. This concept, where "every single thing in this product is accessible from the agent," points towards a future where software isn't just used by agents, but is actively shaped and evolved by them.

This capability highlights a dramatic reduction in the "cost to build." Comparing it to Instagram v1, which took "five days of all-nighters" from a seasoned mobile developer like himself, Krieger notes that Fable 5 can achieve similar results in a fraction of the time, even for non-experts. This shortening of the gap between intent and execution is, for Krieger, "the most exciting part." He shared a powerful quote from a non-technical recruiting team member at Anthropic who, after building an internal tool with Fable 5, exclaimed: "It is the first time in my life... where I feel like the thing that's in my head and the thing that exists in the world is now like they're right next to each other." This democratization of building, empowering individuals to manifest their ideas without needing an overloaded internal tools engineer, is expanding human creativity on an unprecedented scale.

The Evolving Craft of Software Engineering

The rise of highly autonomous AI models naturally raises the question: "Is software engineering over?" Krieger's answer is nuanced: "Software engineering is different." The craft, as he would have defined it during the Instagram era – spending countless hours in text editors, understanding intricate framework layers, and debugging deployments – has "radically changed." Much of that low-level implementation is now handled by the AI, collapsing into other parts of product management and higher-order problem-solving.

However, the "overall craft of the what needs you have, like what are you putting out, like is it actually good?" remains a distinctly human endeavor. Inside Anthropic, the shift means engineers are still "directly responsible individuals" (DRIs) for parts of the product, holding crucial contextual knowledge beyond the AI. They engage in architectural planning with Fable 5, often asking it to generate diagrams or markdown documents to align teams.

A new aspect of the engineering role is "meta-maintenance." Engineers are now building dashboards to track what their many AI "clouds" are doing, which pull requests need attention, and generally overseeing the parallel work streams. Understanding production environments – dealing with incidents, network failures, and scaling challenges – also remains a vital human role, as these real-world complexities often extend beyond the AI's current understanding.

Perhaps most notably, the role of the "engineering prototype" has changed. The old adage, "code wins arguments," is being replaced by PMs or designers quickly spinning up "janky" prototypes with Fable 5 to illustrate a concept, opening up new avenues for discussion and debate. While some engineers may feel a "sense of loss" for the elegant problem-solving of the past, Krieger believes the overwhelming feeling is one of excitement for the "insane amounts of work" that can now be accomplished.

Navigating Cost and Maximizing Value

Fable 5, being Anthropic's most advanced model, is also its most expensive. This reality introduces a new dynamic: users must be more thoughtful about its application. Krieger acknowledges the "kid in a candy shop" feeling during initial testing, but now, with a bill attached, "you do become more thoughtful about it."

However, Krieger argues that Fable 5's cost can be deceptive. While its per-turn cost is higher, its ability to complete complex tasks correctly and comprehensively often makes it "really cheap" in the long run. "It actually just does it right," he explains, eliminating the need for "9, 10 subsequent turns" of clarification and correction that might be necessary with less capable models. This efficiency translates into significant time and effort savings, making the overall cost-to-completion potentially lower.

The challenge, he notes, lies in balancing professional use (where companies can justify the expense for demonstrable results) with personal or hobbyist use. For quick, simple questions, Krieger himself admits to switching to a faster, cheaper model like Son, likening Fable 5 for such tasks to "using a rocket launcher to kill a mosquito." This highlights an ongoing product question for AI developers: how to intelligently route user requests to the most appropriate model without requiring the user to constantly make that decision.

Beyond the Prompt: Fable 5's Systemic Intelligence

What truly differentiates Fable 5, according to Krieger, is its "sense of the system more than just the individual piece of the work." The model frequently "positively surprises" him by anticipating production needs, bugging him about un-activated feature flags, or pointing out how a change will affect other parts of the system.

This systemic understanding extends to its "judgment" in code review. Fable 5 doesn't just blindly accept feedback; it can thoughtfully assess suggestions, sometimes accepting risks, and even "push back" on other reviewers (often other Fable models), explaining why a proposed change might not be correct. This capacity for nuanced disagreement, to "think about that for a minute. No, I thought about it and I still disagree," marks a significant leap in AI capabilities. It suggests a deeper internal model of reasoning and decision-making, far beyond simple pattern matching.

This progress is fueled by continuous feedback from real-world usage, particularly from early testers like the Every team, who push the model to its limits with "repeated multi-day, hard tasks." This rigorous testing directly informs Anthropic's development, guiding where the next improvements need to be made.

Reimagining the Interface for an Autonomous Teammate

The traditional chat interface, while functional, may not be the optimal way to interact with a highly autonomous "teammate" like Fable 5. Krieger identifies several areas for interface evolution:

1. Decoupling Work Location: The ability to kick off complex tasks on a remote dev box and then check in from a mobile device (as Krieger does, sometimes even while hiking) is crucial for Fable 5's long-running processes.
2. Comprehensible Outputs: When Fable 5 has "a lot more context" than the user, a wall of text is insufficient. The interface needs to evolve to provide richer, more digestible outputs like diagrams, flowcharts, or "progressive disclosure of the complexity."
3. Multiplayer Collaboration: As AI agents become more integrated into team workflows, there will be a growing need for multiplayer interfaces. This could involve shared chat sessions, or a more sophisticated system where an independent AI agent, kicked off by one person, can keep multiple team members updated and involved in its progress.

Fable 5 represents a pivotal moment in AI development, not just for its raw power, but for its ability to fundamentally alter how individuals and teams conceive, build, and interact with software. As Mike Krieger's experience demonstrates, the future of work with AI is less about simple assistance and more about deep, collaborative delegation with an increasingly intelligent and autonomous teammate. The craft of building is not ending; it is transforming, opening new frontiers for human creativity and problem-solving at an unprecedented scale.

Based on "In 'Keeper of My Kin,' Ada Ferrer struggles with being her mother's "chosen one"" from NPR Podcasts Watch the original video

The Heavy Gift of Being Chosen: Ada Ferrer's Memoir Unearths a Family's Cuban Exile Story

Episode summary

Ada Ferrer’s memoir, Keeper of My Kin, explores the profound, intergenerational trauma stemming from her mother’s agonizing decision to flee Cuba with infant Ada, leaving behind nine-year-old Poli during the Cuban Revolution. Ferrer, now a Pulitzer Prize-winning historian, grapples with the guilt of being the "chosen one," a feeling intensified by discovering her brother’s excruciating childhood letters to their mother, expressing deep sadness and confusion over the separation that lasted until the 1980 Mariel boatlift.

This deeply personal narrative serves as a universal reflection on family separation, particularly for immigrant communities, highlighting the often-permanent consequences of difficult choices made under duress. Ferrer contemplates how her mother’s choices might have differed had she known the separation would be permanent, offering a poignant lens through which to understand the enduring impact of such ruptures on countless lives.

In the tumultuous spring of 1963, as the Cuban Revolution tightened its grip, a mother in Havana faced an unimaginable choice. Her husband had already fled to New York, and she planned to follow, bringing her two young children. But a cruel twist of fate, the refusal of her first husband to allow their nine-year-old son to leave, forced her hand. She made the agonizing decision to take only her ten-month-old daughter, Ada, leaving her older son, Poli, behind. This heart-wrenching moment, a rupture echoing through generations, forms the core of Ada Ferrer’s poignant new memoir, Keeper of My Kin: Memoir of an Immigrant Daughter.

Ferrer, a Pulitzer Prize-winning historian and professor at Princeton University, delves into the profound reverberations of this single, life-altering decision. Her memoir is not just a personal chronicle but a powerful exploration of the immigrant experience, the enduring pain of family separation, and the complex burden of being the "chosen one."

The Agony of Departure

The scene of separation, recounted in Ferrer's memoir, is almost unbearable in its quiet cruelty. When Poli returned home for dinner that April evening, his mother and infant sister were gone. His grandmother and aunts, attempting to soften the blow, told him they had simply traveled to the countryside. "Less than a week after our departure, however, they told him the truth," Ferrer writes. The raw pain of a child grappling with abandonment is palpable: "Every night, Poli clutched my mother's house dress and cried. He was 1 month shy of 9 and 1/2."

This rupture wasn't just a personal tragedy for the Ferrer family; it was a common narrative for countless Cubans caught in the crosscurrents of the revolution and the strained U.S.-Cuban relations. Families were torn apart by political upheaval, economic necessity, and the cruel whims of fate, often with no guarantee of reunification.

The Burden of Being the "Chosen One"

For Ada Ferrer, being the child who was taken, the one who escaped, cast a long shadow over her life. She describes her lifelong work as a historian of Cuba as a form of "penance" for having been the "chosen one" that day in 1963. "My life was so determined by the fact that my mother took me with her, that she brought me to the US," Ferrer explains. "Meanwhile, my brother was back in Cuba without his mother. He was just traumatized by my mother's choice for his whole life."

This feeling of an "original sin" underscores Ferrer's deep empathy for those left behind. Her success, her flourishing, her entire life in the U.S. stemmed from a decision that simultaneously involved her brother's profound loss. The guilt of this asymmetry, the stark contrast between their paths, fueled her academic pursuits and ultimately her memoir.

A Treasure Trove of Pain: Poli's Letters

The impetus for Keeper of My Kin truly crystallized after Ferrer’s mother died in 2020, followed by her father in 2022. While cleaning out her parents’ apartment, high on a closet shelf, Ferrer discovered a clear plastic box with a white lid. Inside, tied together with the same gold curling ribbon her mother used for Christmas presents, was a stack of envelopes.

"I untied them and took out the first one and saw that it was a child's handwriting," Ferrer recalls. The date, May 4th, 1963, was less than a week after she and her mother had left Cuba. These were Poli's first letters to his mother, a desperate, hopeful chronicle of his childhood without her.

Her mother, Ferrer reveals, had expected the separation to be short-lived, believing Poli's father would relent. But he never did. The reunification of mother and son wouldn't happen until 1980, during the Mariel boatlift, which saw approximately 125,000 Cubans arrive by sea in Florida. The letters, spanning from 1963 through 1979, thus became a raw, unvarnished record of Poli's coming of age, his young adulthood, and his enduring yearning for his mother.

Reading them was an "excruciating" experience. "The letters are the letters of a little boy. The handwriting's not good, the punctuation is not good, the spelling is a mess," Ferrer describes. Yet, amidst the childish scrawl, moments of profound pain pierced through his attempts to be stoic and grown-up. One phrase, from a letter written a year or two after their departure, particularly haunted her: "Mommy, if you only knew how happy I get when a letter arrives from there. I get so happy that sometimes it makes me sad."

Ferrer could only read them in "short spurts" due to their emotional toll, but she considers them an invaluable "gift"—a tangible connection to a past she only partially lived and a brother whose pain she carried.

A Universal Echo of Separation

While Keeper of My Kin is deeply personal, Ferrer emphasizes that her family's story is far from unique. "It is the universal story... for a lot of Cubans," she asserts, and indeed, for many immigrant families worldwide. The Cuban Revolution created a unique set of circumstances, particularly the inability for many to return due to the vagaries of U.S.-Cuban relations. However, the fundamental dilemma of family separation transcends borders and political systems.

"Few people have the resources for families to leave all as one," Ferrer notes. Often, individuals or parts of families must go first, leaving others behind with no guarantee of when, or if, reunification will occur. This "wake of family separation" shapes countless lives, creating lasting impacts on individuals, families, and entire communities in both the countries of origin and destination.

The Lingering Questions

The act of writing Keeper of My Kin was a journey of discovery and reconciliation for Ada Ferrer. Yet, some questions, particularly those only her mother could answer, remain. If she could ask her mother just one more question, Ferrer admits to being torn. Part of her would want to know how her mother felt about the book itself, but another part hesitates, "just in case."

Beyond the memoir, a deeper curiosity persists: "When she first got here, she always thought she would go back," Ferrer muses. "I guess I would want to know more about the moment where she no longer believed that. When did she realize that and how did it make her feel?" And perhaps the most profound question of all, one that speaks to the weight of the impossible choice: "I wonder if she had known at the time that her absence from Cuba would be permanent, would she have made the choice she made?"

These unanswered questions underscore the enduring complexities of migration, the indelible marks left by historical events, and the profound, often silent, sacrifices made by those who sought a new life. Ada Ferrer's Keeper of My Kin is a testament to the power of memory, the resilience of family bonds, and the quiet heroism of a mother's impossible decision. It invites readers to reflect on their own family histories, the choices that shaped them, and the universal human experience of longing and belonging.

Based on "Wall Street’s A.I. Bet Is About to Become Yours | 'The Opinions' Podcast" from New York Times Podcasts Watch the original video

The Trillion-Dollar Question: Is Wall Street's AI Bet a Boom or a Bubble?

Episode summary

Wall Street is on the cusp of a massive AI bubble, with companies like SpaceX and Anthropic preparing for unprecedented IPOs, collectively valued at over $3 trillion – exceeding the entire dot-com boom. This rapid public offering strategy, driven by a need for capital and investor liquidity, is pushing these companies into household retirement portfolios almost immediately, exposing everyday Americans to the significant risks of a potential market correction. Even Sam Altman has publicly acknowledged the "over-excitement" around AI.

The practical takeaway is to be wary of overexposure to AI stocks, particularly through index funds, as history shows that major technological shifts, like the internet or railroads, are often accompanied by speculative bubbles that eventually burst, leading to economic downturns. While AI's transformative potential is undeniable, the profitability of these specific companies remains an open question, especially as open-source alternatives gain traction and even major users like Uber cap AI usage due to high costs, suggesting a disconnect between current valuations and proven returns.

Not long ago, the concept of artificial intelligence, particularly large language models and chatbots, burst into public consciousness with the launch of ChatGPT in late 2022. Since then, the conversation has been a whirlwind of awe and apprehension. Every few months, a fresh wave of commentary debates whether this burgeoning sector is a colossal bubble, whether leading AI labs are raising and spending too much money for their current earnings, and if they're leading the entire economy toward an inevitable crash.

Now, we're poised to enter a new, critical phase. Two of these pioneering companies, OpenAI and Anthropic, along with the multi-faceted AI and satellite firm SpaceX 2, are preparing for absolutely mammoth Initial Public Offerings (IPOs). SpaceX 2 alone is reportedly eyeing a public valuation of $1.77 trillion. This isn't just big; it's unprecedented. These impending IPOs force us to confront urgent questions: What do these staggering valuations tell us about the risks of a bubble? What is the true state of an American economy increasingly leveraged on AI? And where, exactly, are we heading?

To unpack these complex issues, we turn to the insights of economist and law professor Natasha Sarin, an opinion contributor for the New York Times and head of the Yale Budget Lab, in conversation with Times Opinion writer David Wallace Wells. Their discussion reveals a nuanced landscape where the undeniable transformative power of AI clashes with the dizzying valuations and potential pitfalls of a market perhaps too eager to believe its own hype.

The AI Gold Rush: Unprecedented Scale and Classic Motivations

The sheer scale of these impending IPOs is difficult to grasp. OpenAI, Anthropic, and SpaceX 2 are all aiming to go public within months of each other, with their combined market capitalization expected to exceed an astonishing $3 trillion. To put this in perspective, Natasha Sarin points out that the total value of all technology IPOs during the entire internet boom (1995-2000), adjusted for inflation, is almost matched by SpaceX 2's valuation alone. The three together significantly dwarf that historical benchmark.

So, why are these companies rushing to go public now? The motivations, Sarin explains, are in many ways classic IPO drivers: access to capital, the ability to sell stakes to a broader pool of investors, and the desire to affix public market valuations to their enterprises. While private markets, flush with capital from firms like Apollo and Blackstone, are eager to invest substantially in these companies, there are other compelling reasons. Going public allows early investors to realize the immense benefits of these multi-trillion-dollar valuations. SpaceX 2, for instance, is reportedly seeking a valuation significantly higher than what many analysts currently assign, and is even relaxing conditions to allow smaller investors in – a clear signal about the broad buyer base they hope to attract.

Wall Street's New Rules and Your Retirement Account

Perhaps one of the most surprising and consequential aspects of this AI IPO wave is its direct impact on the average American household. Due to the colossal scale of these IPOs, these companies are poised to become an instantaneous and significant part of household portfolios, primarily through retirement accounts and index funds. Stock market indices are reportedly relaxing their rules, allowing companies to be added much faster than before. This means that within as little as 15 days of SpaceX 2's IPO, it could be integrated into countless retirement portfolios and index investments across the country.

This trend of market concentration is not entirely new; last year, roughly 60% of stock market growth was driven by just a handful of technology companies. The AI IPOs are set to accelerate this concentration, profoundly affecting household portfolios. As Sarin cautions, "in some sense it means that we're all massively exposed to the idea that there might eventually be... when you have these types of technological changes... they come with a bubble that eventually pops." This automatic exposure means millions of Americans will unknowingly bear the brunt if the market corrects, a risk they didn't face just weeks ago when these companies were privately held.

The Political Economy of AI: Public Backlash and Government Stakes

The investment cycle unfolding on Wall Street exists in parallel with a growing public unease about the future of an AI-powered economy. We're seeing significant backlash, particularly around the environmental impact of data centers. There's a broader sense of apprehension about AI's implications for jobs and society. Political figures like Bernie Sanders are proposing the American government take a 50% ownership stake in these labs, with even Donald Trump making similar overtures. Intriguingly, some AI labs themselves have expressed openness to such discussions.

This dual dynamic — a massive distribution of ownership to the public through IPOs alongside contemplation of federal government intervention — seems paradoxical. Why would cash-flush companies seek to bring more of the public on board, either as investors or through government stakes? David Wallace Wells suggests it's a strategic move to protect themselves, stabilize against public backlash, and make their immense role in the future economy more palatable to a wider audience.

The nervousness is understandable. Youth unemployment is ticking up, and students graduating into an AI-influenced economy are expressing skepticism. The impact on education is already visible, and the long-term effects on the labor market, especially for white-collar workers, remain uncertain. As Sarin notes, if figures like Sam Altman are correct about significant displacement, it's hard to envision a clear path forward. This uncertainty makes ex ante regulation incredibly difficult. From the companies' perspective, going public might offer a degree of transparency and public accountability that private markets lack, potentially softening public and political opposition.

The Specter of the Bubble: History's Warning

The question of whether we're in an AI bubble isn't just for market analysts. Even Sam Altman, CEO of OpenAI, has publicly stated his opinion that investors are "over excited about AI." History, Sarin reminds us, offers a predictable cycle for every major technological innovation, from the internet to railroads. There's an initial burst of excitement, a rush of money into new technological prospects (both productive and unproductive investments, like the "dot-com" companies of the past), followed inevitably by a bubble burst, leaving behind significant economic debris. These corrections often coincide with deep economic downturns, large-scale unemployment, and the need for government intervention.

For Sarin, the question isn't if a bubble will burst, but when. The current moment feels particularly precarious, with valuations seemingly detached from traditional fundamentals.

AI's True Value vs. Market Expectations

The heart of the skepticism lies in the disconnect between AI's undeniable potential and the specific valuations being assigned to these particular companies. For years, AI leaders spoke of achieving Artificial General Intelligence (AGI) or Artificial Super Intelligence (ASI) — a "singularity" where AI could recursively improve itself, leading to an unrecognizable economy. This vision, if true, might justify astronomical valuations for the company that "wins" the AGI race.

However, the reality on the ground appears more complex. Data suggests that the use of Chinese open-source AI models has tripled this year, while the use of American AI products has largely flatlined. Companies like Uber are reportedly winding down employee use of AI due to high costs relative to perceived benefits. GitHub has moved its Co-pilot to usage-based billing, reflecting the unexpected expenses of deploying the technology. These trends indicate that the "optimistic case" for immediate, revolutionary productivity growth hasn't fully materialized for many firms attempting to deploy AI.

David Wallace Wells highlights a crucial distinction: even if AI transforms the economy, how much of that value will be captured by these specific "big AI" companies? He points out that while AI might become a utility, like electricity, electric utilities are not trillion-dollar companies. The massive spending by AI labs, often exceeding their current earnings, is driven by a fierce competition for market share, a belief that only a few dominant players will ultimately survive. This creates an incentive to spend heavily and "look like you are doing a lot in ways that might ultimately not be tied to fundamentals."

The striking paradox is that these companies are asking public investors to pay prices based on the assumption that AI will reshape the economy, even as the companies themselves haven't figured out how to stop losing money or how they will ultimately be the ones left standing in a mature AI market.

The Unanswered Questions and the Path Forward

The conversation consistently returns to a fundamental uncertainty. Even if AI is transformative, and Sarin, like Wallace Wells, believes it is, the question is how much that transformation will translate into profit for these specific firms at these specific valuations. The "singularity" narrative has given way to a more nuanced understanding: AI will continue to improve, becoming more useful and transformative over time, but not instantaneously.

The historical parallel to Robert Solo's famous quote about the internet — "you can see the internet everywhere except for in the productivity statistics" — resonates deeply. It took time for the internet's true productivity impact to manifest. The same might be true for AI. While the internet undeniably transformed life and boosted GDP growth, it wasn't the "super abundance" or "labor is over" scenario some predicted.

The concern is that the market, including analysts and the public, seems to be "buying the incredibly dramatic story of growth much more simplistically" than expected. If public investors, through retirement accounts and index funds, become heavily leveraged on these five companies, the success of the broader economy will be tied to their performance. As Sam Altman himself acknowledged, "when bubbles happen, people get smart people get over excited about like a kernel of truth... someone is going to lose a phenomenal amount of money."

The current valuations, Sarin concludes, feel "vibes-based," not truly reflective of fundamentals. While companies like Tesla demonstrate that market interest can sustain high share prices without immediate fundamental justification, the risk remains. We may be entering a phase where these AI giants are treated as the new "kings of the economy" in the market, even if their propositions don't fully materialize. The question for investors isn't just if AI will transform the world, but whether these specific companies, at these specific prices, will earn back their investment. And if not, who will be left holding the bag?