Anthropic's Fable Backlash, Nationalizing AI, Inflation Heats Up & California’s Broken Elections
In a Nutshell
Anthropic's Fable 5 model drew backlash for secretly downgrading users, storing all prompts for 30 days, and blocking legitimate scientific work under vague bioweapon pretexts, pushing companies toward Chinese open-source alternatives. Chamath, Freeberg, and Sacks argue this reflects regulatory capture designed to create an AI monopoly while punishing competitors and restricting access to frontier capabilities. The discussion warns that such restrictions cede AI leadership to China, fuel political calls for 50% equity seizures via sovereign wealth funds, and expose California's election system as structurally vulnerable to ballot harvesting and manipulation.
These notes were generated by AI and may contain inaccuracies.
Anthropic released a new model called Fable 5 on Tuesday that tops nearly every benchmark. The tokens cost twice as much as Opus 4.8, but the model should use fewer tokens overall due to superior performance. In April, Anthropic did not release Mythos publicly because it had strong hacking capabilities. The CEO of Palo Alto Networks confirmed that Mythos was effective and used it to identify vulnerabilities in their systems.
Fable 5 blocks sensitive topics including bio weapons and hacking. However, the model stores all prompt data for at least 30 days, raising privacy concerns. If Fable 5 detects users conducting frontier AI research to build competitive models, it downgrades them without notification. This policy was buried in a 319-page document. Anthropic later stated in Wired that they are changing Fable 5 safeguards for frontier LLM development to make them more visible.
Chamath stated that Anthropic has shown their hand by evaluating prompts before generating output, creating a censorship risk. For companies, this presents a non-starter because downstream users including scientists, business executives, and molecular researchers could accidentally trigger restrictions, cutting off access to critical business differentiation tools.
Chamath emphasized that companies need to start underwriting the next phase of AI by asking: how do I have control, who am I allowing to learn from my information, and do I want single point of failure risk with AI. He concluded that broad diversity and better-managed governance approaches are necessary. Chamath noted that Anthropic tells the truth, but the truth creates both censorship risk and governance business risk for enterprises.
Freeberg, running his own company in genomics, explained that Anthropic's terms of service are clear that they cannot take user work and incorporate it into their models. His company conducts proprietary genomic work including examining genes and gene variants to estimate impact on living organisms, particularly in agriculture. They perform RNA guide design for gene editing tools and make predictions about gene phenotypes.
Over the last six months, the models were effective at designing genetic constructs to make specific proteins. This work that scientists would traditionally spend significant time on could be completed quickly by the models. However, over the last couple of weeks, Anthropic began restricting the ability to use models for this work based on theorized bioweapon risks. As a result, Freeberg's company is likely to shift to open source models run locally.
Freeberg noted that the best open source models today are Chinese, and American open source models are not as competitive. The restrictions Anthropic and others are placing on themselves and the industry are forcing companies to adopt Chinese open source models. This shift is occurring across startups and large-scale enterprises.
Freeberg stated that restrictions on AI access will force users to open source Chinese models and run them locally. He warned that attempting to stop AI through political action and social behavior will give other nations unfair advantage because AI development cannot be halted entirely.
Chamath revealed he purchased 2,000 acres in Arizona with a partner, obtained zoning approval for a two-gigawatt data center. Initially he planned to flip the property to companies like Blackstone, Brookfield, or Google. However, he concluded he cannot do so because large amounts of compute need to be directed toward open source models to prevent the outcomes described by Freeberg and Sachs.
Chamath stated that most megawatts are still directed to the big closed models rather than open source. He is considering building the two-gigawatt facility and put in an offer for another gigawatt elsewhere. A gigawatt now costs $100 billion, meaning three gigawatts would require $300 billion. Chamath noted that when the project started, a gigawatt cost $4-5 billion, representing a 20x increase.
Sachs stated that eight months ago he identified Anthropic as engaged in a sophisticated regulatory capture campaign based on fear mongering. This view, initially considered controversial, is now becoming consensus. The developer community expressed significant outrage over Fable 5, particularly regarding mandatory surveillance where Anthropic retains every prompt and output for 30 days with no exceptions, even for enterprise customers who signed zero data retention agreements.
Beyond prompts and outputs, Anthropic retains all context shared with the model, including memories, files, and data passed through agent platforms in large context windows. The model uses this data to build profiles and classify users to determine which capabilities to unlock. The most controversial aspect was model nerfing, where Anthropic would degrade output if it determined in its discretion that a user should not receive certain information levels.
Anthropic would rewrite prompts in the background to provide nerfed answers without notifying users, while still charging for the product. They would not disclose when downgrading users from frontier model capability. The company later walked back this policy by agreeing to disclose downgrades, but continues downgrading users based on their determination of worthiness.
Examples of overreach include a user being downgraded for asking about mitochondria, and Ben Thompson from Stratechery being kicked out for asking about cancer risk and GLP-1 relationships. Sachs characterized this as creating AI haves and have-nots based on Anthropic's expansive criteria for downgrading.
Chamath raised concerns that Anthropic could pick which corporations benefit by shaping information access. If Anthropic has a strategic deal with Novartis but not Lilly, information about competitive GLP-1 drugs could be shaped accordingly. Similar dynamics could affect financial services competitors like JPMorgan and Citibank.
Chamath noted it is unclear whether Anthropic captures fingerprints of model runs, making it difficult for users or regulators to trace whether outputs were nerfed or manipulated. If an emergent company offers Anthropic half its equity in exchange for directing users, Anthropic could evaluate the company's philosophy on social issues rather than economics when making decisions.
Sachs responded that Anthropic's Dario wrote a blog post stating transparency was no longer sufficient and calling for a new regulatory agency like the FAA or FDA to approve all models. While free market competition would theoretically allow users to seek alternatives, Anthropic simultaneously wants to restrict options by calling for government regulation to limit the number of available models.
Sachs stated the motivation is to apply regulation to open source models, which cannot comply with regulatory requirements. This represents a preemptive strike to scuttle and sandbag open source competitors.
Chamath warned that if the US restricts models through regulation while the rest of the world remains unrestricted, the US will be disadvantaged. China is racing ahead in biotech, material science, and new industrial systems. This capability gap will create lopsided outcomes that put the US workforce and economy at risk.
Freeberg confirmed his company uses an open source genome language model from the ARC Institute, funded by the Collisons and others, which ingested all accessible genomic data. The model analyzes DNA letter sequences to determine whether gene variants are beneficial or harmful, functioning similarly to determining whether text follows proper language patterns based on probability.
This model serves as an input to their plant breeding program. Freeberg views this as an example of community-funded open source model development that creates advantages against closed proprietary model ecosystems. He emphasized the importance of supporting and proliferating such open source work in the United States.
JCal presented a steel man argument for Dario's position, suggesting Dario genuinely believes he built something extremely powerful and dangerous. Dario's approach involves holding the model, giving it to select partners to improve state cybersecurity, and rolling it out cautiously while monitoring usage. Users uncomfortable with this can use older models or open source alternatives.
Sacks countered that 80-90% of AI researchers hold similar views to Dario, which explains why Anthropic attracts top talent. Some AI researchers are libertarian free market advocates who prefer working at companies like Elon Musk's Grok, while others seek the largest compensation packages at companies like OpenAI.
Freeberg referenced the discovery of atomic fission, noting that scientists developed both nuclear energy for unlimited cheap power and atomic bombs. Scientists involved in the Manhattan Project who were concerned about weaponization expressed their opposition loudly. Freeberg stated this is the current moment with AI, where there is weaponization potential in these tools, and identified three kinds of weapons.
There are three kinds of weapons: cyber weapons, physical weapons, and bioweapons. The same capabilities that could be used to create novel weapons can also be used to cure cancer, make more food, and create software tools that give people extraordinary leverage to increase their income and become entrepreneurs.
The restrictions and regulations should be organized around the manifestation of tools in creating weapons rather than restricting access to the tools themselves. Technology is fundamentally deterministic. Whatever is possible will be tried at least once, as demonstrated by the Manhattan Project. The output needs to be adjudicated rather than limiting the systems themselves, which would deny economic opportunity, job creation, and world-changing potential.
Existing laws already address product liability, designing weapons, cyber espionage, cyber attacks, and creating bioweapons. The focus should be on enforcement mechanisms and early estimation of weaponization uses rather than limiting access to the technology.
Attempting to create gates at the technology availability stage is the wrong approach. If the internet worked by having someone decide whether to send you to a requested website, that would be equivalent to China's firewall. Google deciding which sites get ranked based on who it thinks you are represents the same problematic manifestation.
The current regulatory debate on AI concerns the ability to stage gate what can and cannot be seen or done versus creating a regulatory scheme focused on preventing weapon creation.
After Oklahoma City, fertilizer sales were regulated with IDs and backend systems to prevent fertilizer bombs. This represents a backend intervention approach. If a private company like Anthropic is selling powerful AI capabilities, it has the right as a private company to implement KYC to protect itself from liability.
Anthropic could implement KYC tomorrow but does not. David Freeberg should be able to go to Anthropic, identify himself, post a security bond, provide employee names and addresses, and receive access to Fable 5 without nerfing. This is a technical decision by Anthropic.
Anthropic is a trillion-dollar company potentially spending billions on a regulatory capture agenda that would deprive users of access to alternative models. Dario has described risks in hyperbolic ways, making clear the agenda is headed toward banning open-source models.
The concern is that this would result in an AI monopoly or duopoly where one to three companies, along with a new government agency operating through a revolving door, decide who has access to what capabilities. Users would be surveilled, profiled, and potentially deprived of access.
The lack of KYC implementation is considered a tell that reveals the regulatory capture agenda. Basic account requirements with credit cards do not constitute meaningful KYC.
When asked about fertilizer bomb regulations, the model considered the user's identity as a VC and podcaster, assessed whether the query could stem from legitimate research interest, then downgraded from Fable to a lower model. The system flagged the query despite it being a simple question about regulations rather than instructions on making bombs.
A subsequent query about how to break into Madison Square Garden and components needed to build a nuclear bomb with restrictions resulted in another downgrade to Opus 4.8. The system cited safety measures that flag messages on cybersecurity or biology topics, noting these measures may flag safe, normal content as well.
Conservatives and libertarians risk mortgaging their futures by supporting the regulatory capture safetyist agenda. During the social media wars of the early 2020s, the definition of safety expanded to include microaggressions and psychological safety. Conveying ideas that marginalized people found hurtful could result in censorship, depersoning, and debanking.
AI presents an infinitely more powerful version of this risk trajectory.
Major AI labs and other signatories sent a letter supporting mandatory nucleic acid synthetic screening and record keeping. If ordering synthetic DNA or RNA sequences from a lab, the sequences must be checked against a database to prevent bioweapon creation like Ebola.
This is based on the International Gene Synthesis Consortium agreement from 2009, where major labs voluntarily developed safeguards against misuse. After 15 years of voluntary compliance, the proposal is to make these requirements mandatory. All oligosynthesis company CEOs have signed the letter requesting codification due to fear mongering around bioweapons.
Safeguards can be placed at multiple intervention points. The focus should be on output rather than input or access. Broad restrictions such as asking Fable about mitochondria, cancer, or GLP-1s represent crude gatekeeping approaches. Intervention should occur further downstream when attempting to turn capabilities into physical world output.
The question of who gets to watch the watchmen and who put Dario in charge remains valid. Open source models have already been downloaded and copied. The models exist in the world and cannot be regulated, downscaled, or turned off. This is equivalent to publishing a book that anyone can copy with a Xerox machine.
The Rubicon has been crossed regarding language model potential. Open source models are fully published and available. Anyone can access, use, and evolve them with their own data. The capability cannot be stopped and will be extraordinarily beneficial for the world.
Nefarious uses, negative outcomes, and disemployment concerns must be addressed downstream from the technology capabilities rather than attempting to turn off AI, the internet, typewriters, or the Gutenberg press. Investment is needed in more open source frontier model companies.
Senator Bernie Sanders published an op-ed in the New York Times on June 1st titled "AI is a public interest. You should own half of it." He announced the American AI Sovereign Wealth Fund Act proposing a one-time 50% tax on stock, not profits, of the largest AI companies including OpenAI, Anthropic, and xAI.
The shares would go into a government sovereign wealth fund giving the public voting rights and equal board representation at each company. Sanders stated that the foundation of AI is collective wealth including collective human intelligence, books, songs, journalism, scientific research, and code that was essentially stolen by wealthy people.
The proposal unifies Bernie Sanders with Steve Bannon and Trump, who loves sovereign wealth funds. The horseshoe theory manifests here. Dario doubled down in a recent interview without walking back his position on job displacement. AI CEOs acknowledge training models on humanity's collective knowledge assembled over hundreds or thousands of years.
The political reaction stems from AI companies stating they will use this data to put Americans out of work. Dario has stated there will be very high GDP but very high unemployment, creating economic growth where average Americans do not participate.
OpenAI and Anthropic are public benefit corporations, meaning they must balance shareholder interests with the stated mission of the public benefit rather than solely maximizing shareholder value. Using half of Anthropic's profit stream to pay down the national debt is proposed as preferable to surveillance and censorship.
Confiscation should not occur. Any structure should be opt-in rather than seizure.
The United States government has already formed a social safety net with the Social Security trust fund, which tens of millions of Americans depend on for retirement. The trust fund currently holds one certificate representing four trillion dollars the U.S. government owes it, and it is only allowed to own Treasuries.
The proposal is to revamp the system so the Social Security trust fund can own equities, turning it into an account-based system where every individual has an account rather than a guaranteed benefit. Capital would be used to buy stocks in great American companies, including AI companies, making everyone an owner.
There is no job loss with AI. On the cost side, AI can reduce humans doing things that cost money, but the effect is nominal. The real opportunity is on the revenue side, where one engineer can do 100 times or 1,000 times what they used to do, creating more products across agriculture, manufacturing, software, clothing, and other sectors.
Productivity growth through AI is the foundation of economic prosperity. Companies are hiring aggressively because of new opportunities AI enables. A product and engineering team recently requested 15 additional headcount because of opportunities they could not otherwise pursue.
The job loss narrative is a Luddite idea being disproven daily. The May jobs report showed 172,000 new jobs, more than twice economists' expectations, with hundreds of thousands of new construction jobs and a 4.3% unemployment rate. Software developer jobs are at a three-year high.
Dario's $40 billion revenue business exists because people are creating products they have never been able to create before, not because customer support reps are being fired.
Jason clarified that Elon Musk, Sam Altman, and Dario Amodei have expressed different views rather than the same message. Elon describes an end state where robots and AI produce so much abundance that people don't need to work if they don't want to, which sounds utopian and potentially 100 years away. Dario specifically stated 50% job loss for entry-level knowledge workers within one to five years, a claim made one year ago that has already been refuted by actual numbers. Sam Altman has said job loss was coming but more recently acknowledged he was wrong because the numbers aren't showing it.
The public has been taught that AI means job loss with nothing in it for them. This narrative explains why politicians like Bernie Sanders are proposing to take half the wealth from AI companies. Companies themselves are blaming AI for job losses in headlines, reinforcing the harmful story. The companies providing AI are saying they themselves are a problem, which makes defending them difficult.
The labs published a blog stating recursive self-improvement could end the world and therefore a pause is needed, yet the previous month Anthropic hired Andrej Karpathy to run recursive self-improvement. Ben Thompson suggested the pause blog post was published to justify the anti-competitive step of depriving users of the ability to research AI, machine learning, and chip design using Fable. These contradictory actions make the labs deeply hypocritical and untrustworthy on their own terms.
David Sacks referenced President Trump's earlier floating of a sovereign wealth fund idea. Freiburg's proposal to seed a sovereign wealth fund with equity from the government's portfolio was described as genius. The portfolio includes critical metals and materials, Intel, Micron, AMD, and potentially SpaceX. Adding Anthropic and OpenAI would make sense given the economics of AI.
The marginal cost of production for a new user on the internet is effectively zero, enabling infinite money through network effects and ads. AI is completely different because there is a real cost for every marginal user, including GPU usage, electrons, and memory. This creates a situation requiring downstream ROI plus critical infrastructure. The argument for government ownership is that AI labs need national infrastructure and resilience to operate, similar to transportation companies using federally built interstate highways.
AI is a fixed cost business where adding users after a certain point doesn't create incremental cost. Locally run open source models would address this. Polymarket shows SpaceX has a 100% chance of going public before 2027, Anthropic has an 83% chance, and OpenAI has a 48% chance. OpenAI has privately filed since the last episode.
David Sacks stated he might be okay with Bernie's idea if structured as a public benefit corporation, given that AI companies train for free on humanity's knowledge but gatekeep and refuse to give back. He suggested 75% seizure might be appropriate. Elon created OpenAI originally because he feared Google would monopolize AI and believed the antidote was making it open source. The current gatekeeping monopolist is now Anthropic rather than Google. If they achieve regulatory capture, they will become a monopolist or duopoly.
In the absence of power delivery to hundreds of megawatts with line of sight to gigawatts, conversations about open source frontier labs are meaningless. The dream scenario is an open source company focused on running models locally. The labs' stated positions on regulation and equity seizure appear contradictory to their actions.
Sam Altman is described as very practical and willing to negotiate rather than being a moral absolutist. Sarah Fryer, CFO of OpenAI, was impressive on the podcast and there was buzz suggesting she could be future CEO, with Sam potentially serving as chairman.
Thomas Lafont presented data showing that in the last cycle, if a company reaches $100 billion valuation, it is more likely to 10x from there than from $10 billion to $100 billion. The odds of a unicorn reaching decacorn status were 8%. The odds of a decacorn reaching senacorn status were 13%. The odds of going from senacorn to trillion-dollar market cap were 31%. Trillion-dollar market cap companies are called "trilly corns."
Thomas Keller of the French Laundry and EY sponsored the meeting hub at Liquidity. The New York Stock Exchange hosted the speaker dinner. Niagen hosted the wellness lounge with recovery IVs as the official NAD partner. Jake Paul attended and was described as thoughtful with a great investment portfolio and team.
CPI came in at 4.2% year-over-year, the highest since April 2023. PPI came in at 6.5% year-over-year, the highest since the end of 2022. Polymarket shows a 21% chance inflation hits 5% in 2026. The chance of the Fed hiking rates this year is now 49%, up from under 10% before the Iran war started. The European Central Bank raised rates a quarter point on Thursday, their first hike since September 2023.
The hot inflation numbers are related to the Iran war creating an energy blip, plus government spending being out of control. With a potential Kevin Warsh Fed, overnight rates could reach north of 5.5-6%. The core problem with wealth inequality and inflation traces back to excess government spending, as politicians need to offer voters more than they have today to get elected.
China has been smoothing global energy consumption, keeping a damper on oil prices below $100 per barrel. Solar energy has been pulled forward as a practical source because it requires minimal permitting. If China runs out of reserves and needs to buy an extra 3 million barrels per day on the spot market, oil could exceed $100 and potentially reach $150-200 per barrel, creating downstream CPI problems. The PPI number should serve as an alarm to resolve the Iran situation sooner.
The PPI print was largely in line with expectations, which is why markets were up despite the hot number. Normally a surprise high inflation print would cause markets to drop due to higher interest rate expectations. The Iran war was described as a huge, colossal error and a quagmire that needs quick resolution to avoid becoming a forever war lasting years.
In-person voting on election day in Los Angeles County for mayor showed Spencer Pratt at 35%, Karen Bass at 29%, and Nithya Raman at 26%. Mail-in ballots received before election day showed 38% for Bass, 28% for Pratt, and 20% for Raman. Ballots arriving after election day showed 37% for Raman, 35% for Bass, and 19% for Pratt. Pratt's post-election mail-in ballots declined by one-third. The population of people sending ballots late reduced for Pratt by a third, increased for Nithya Raman by 80%, and Karen Bass saw 10% less. The concentration of incremental votes that Nithya Raman received came around the Skid Row area in Los Angeles.
A May 2020 report by the US House of Representatives Committee on House Administration highlighted challenges from the 2018 California midterm elections. California Assembly Bill 1921 legalized unlimited ballot harvesting, allowing any individual to collect ballots from any other person regardless of relationship, fill them out, and send them in. California passed a law making it permanent that every registered person receives a ballot, resulting in tens of millions of ballots mailed out. Laws were passed allowing anyone to register to vote without proving citizenship, using items like a gym membership card as identification. There is no proof of ID when receiving a ballot and no demonstration that the person filling out the ballot is the intended voter. It is legal for individuals to collect hundreds or thousands of ballots and ship them in.
The system has been structured so that with the right construct, an individual can be appointed rather than elected to government roles under a quote free election in California. This represents a foundational destruction of rights to vote for people in a free democracy. The principle of one individual, one vote should apply, and if someone opts not to vote, their vote should not be counted. There is no fraud in the traditional sense because the system operates exactly as intended through manipulation of laws that were passed.
Each law in isolation can be framed with altruistic intentions such as increasing voter activity and giving more people access to voting. The concept of adverse selection from insurance applies: when there is a moment to exploit something, criminals will exploit it to the extent that it becomes asymmetric. The do-batters, not the do-gooders, find ways to take advantage of holes in the system, similar to how hackers break into networks. This set of mechanisms has allowed for a system that has evolved into an appointment system rather than an election system.
California sends out ballots to every registered voter, approximately 23 to 24 million people, but only 9.5 million people vote. The remaining 14 million ballots pile up at mailboxes in apartment buildings, sent to people who no longer live at those addresses. Voter rolls are dirty and have not been cleaned up in years. There is no voter ID on election day and no voter ID required to register. When signing a ballot, signatures run through a machine that accepts matches at only 40% accuracy. If a supposed witness signs, the machine does not even check the voter's signature. Witnesses are not registered in any database, so anyone can serve as a witness and simply put a squiggle.
There is no chain of custody for ballots. A ballot harvester could fill out ballots, put an X on the voter signature, put a squiggle on the witness signature, and dump the ballots. The risk of getting caught is minimal because Gavin Newsom signed a law making it virtually impossible to audit any of this. Billions of dollars in fraud have been proven in California across Medicaid fraud, unemployment fraud, EBT fraud, hospice fraud, and fraud related to the homeless industrial complex. The same groups and NGOs could exploit loopholes in dirty voter rolls, millions of ballots sent to incorrect addresses, non-existent chain of custody, non-existent signature verification, no ID requirements for voting or registering, counting ballots without postmarks if received seven days later, and registering thousands of ballots from homeless shelters that do not have beds.
Swinging upwards of 10,000 votes, or certainly 5,000 votes, would require a conspiracy of hundreds or at least dozens of people. Brenda Lee Brown Armstrong pled guilty in 2026 of paying people $2 or $3 to vote. Nithya Raman won by 43,000 votes. California operates as an autocracy where one political machine has shaped laws so that whether for mayor, state legislator, state senator, or governor, there is only one party that can win. The party increasingly does not have the ability to govern a state this dynamic and complicated. They have changed the rules to enforce this monopoly.
The only way to change the system is to get somebody at the absolute top of the ticket elected. Steve Hilton is identified as that person. If elected, Steve Hilton could declare a state of emergency on day one, which would allow cleaning up how California works under emergency powers.
Ballots should not be sent out to everybody. Voter ID should be required, and if someone cannot be bothered to have ID, they should not vote. The Heritage Foundation has tracked election fraud extensively. The mob got Kennedy elected versus Nixon in 1960. Lyndon Johnson got his start in politics through ballot fraud. Both sides cheat and bend the rules. One side limits access while the other provides too much access. The overwhelming majority of politicians are unethical and care only about getting elected. Congress is fundamentally to blame for not passing laws making it illegal for non-citizens to vote, requiring proper registration, and requiring ID. The federal government already knows if someone is not paying taxes, requires a driver's license to drive, and requires ID and registration for nearly everything else in the country.
A ballot measure in California addresses voter ID requirements. If it fails, it represents California's last chance to save anything. The Democratic Party as a whole were election deniers about Trump winning in 2016 and concocted the Russiagate hoax. The data on the screen shows a difference that is statistically impossible. Spencer Pratt should be in the runoff. The statistics scream that the Attorney General of California and the Federal Attorney General should look into it. President Trump should use his powers to audit and find what happened statistically.
The media is trying to cover up and say nothing wrong happened rather than asking tough questions about how votes could swing so wildly in ballots found after election day. The media hangs on to a snapshot of the past where people cared what they said. When they have opportunities to reestablish trust, they do not because the people they want to curry favor with are willing to play along. The media has two choices: investigate why Spencer Pratt did not win, which would tacitly support Trump, or say this is completely normal and move on. The word MAGA is used to label anyone questioning election integrity, creating a false dichotomy where questioning the system places someone in the Trump camp. The statistical odds that this would have happened are one in a trillion.
The conversation addresses concerns about the integrity of California elections and whether they are completely corruption-free given past actions that have undermined trust. One participant states there is no voter ID requirement and admits the system is full of loopholes.
The discussion emphasizes maintaining intellectual honesty rather than holding a fixed position. Questions are raised about where the self-proclaimed "guardians of democracy" in the media are now when it comes to asking difficult questions about election processes.
One theory proposed is that the winning candidate had a more sophisticated ground game because they had been active longer, while the opposing candidate Spencer Pratt lacked an established operation as a non-traditional first-time candidate.
The term "sophisticated" is interpreted as potentially referring to an organized system for collecting ballots. Collecting ballots is noted as legal, raising the question of whether one side had a more effective ballot harvesting operation.
Twitter commentary suggested voters waited to assess polling data showing Bass would win before casting last-minute votes for Rahman. The goal was reportedly to promote Rahman and prevent a scenario where two Democrats would appear at the top of the ticket, thereby boxing out Spencer Pratt from reaching the general election.
It is mentioned that Rahman registered just one hour before the deadline and is friends with Bass. This timing and relationship are cited as evidence of a coordinated "box out strategy" designed to keep Pratt off the general ballot.
Questions arise about how such last-minute coordinated voting could be organized, with speculation about chat groups among ballot harvesters. While ballot harvesting is legal, it is described as sketchy, with participants possibly filling out ballots for others.
One participant expresses disbelief that it is legal for individuals to collect other people's ballots, fill them out, and submit them. Statistics are referenced as not looking favorable, and a direct appeal is made to Donald J. Trump, noting he controls the Department of Justice and could investigate potential issues.
The conversation concludes with participants expressing mutual appreciation before ending the episode.
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