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Tesla stock has clawed its way back from a painful decline in recent months, but the company now finds itself on even shakier ground following the passage of a controversial tax bill by the U.S. House of Representatives on Thursday.

The legislation, championed by President Donald Trump, rolls back critical incentives for electric vehicles, effectively shutting Tesla and other major EV players out of future tax credits. This move adds fresh pressure to a stock that has already weathered political headwinds, extreme volatility, and waning investor patience.

For long-term investors, the question now is not just whether Tesla remains a good company—but whether it’s still a good stock to hold.

A Long-Term Play With a Short Fuse

Charles Harris, portfolio manager at O’Neil Global Advisors, remains invested in Tesla but is candid about the stock’s punishing swings and how they’ve forced a rethink of strategy.

“I still have a large position in Tesla – particularly in my non-margin accounts – which I’m just holding,” Harris said on the Investor’s Business Daily podcast “Investing with IBD.”

“I really got killed holding Tesla,” he added, describing the fallout of holding an oversized margin position during Tesla’s steep 2022 downturn.

After reaching an all-time high of $488.54 in December 2024, Tesla shares tumbled nearly 47% within just four months. The plunge was fueled by a combination of factors: CEO Elon Musk’s close political alignment with President Trump, which sparked protests and investor anxiety; a broader market selloff in February; and fears about weakening global EV demand as tariffs loomed.

Harris, like many investors burned during the slide, now focuses on managing risk and position size—especially avoiding margin when holding high-volatility names like Tesla.

“When you enter a bear market, regardless of the conviction you have in a stock or how well you’ve done, if you’re going to hold through a base or hold a long-term stock, you can’t do it on margin,” Harris warned.

Trump’s Tax Bill Pushes Tesla Into a Tougher Spot

The situation for Tesla worsened this week with the House’s passage of President Trump’s new tax bill, a sweeping reform that dismantles several clean energy incentives aimed at boosting electric vehicle adoption.

While the bill preserves IRA (Inflation Reduction Act) tax credits through 2026, it limits eligibility to automakers that haven’t sold 200,000 EV units by the end of 2025. That automatically disqualifies Tesla, along with General Motors and Ford, which have already passed the threshold.

This leaves Tesla at a competitive disadvantage compared to smaller, newer EV players like Lucid (LCID) and Rivian (RIVN), who now gain a runway to capture more price-sensitive buyers. Analysts say this change could reshape the EV market, effectively stalling growth for established brands that once benefited heavily from federal support.

The market reacted swiftly with shares of GM, Ford, Rivian, and Lucid all declining on Friday following the bill’s passage. Tesla, despite the broader concerns, managed to inch upward—rising 46% from its April lows to trade around $342 by midday Friday. Still, it remains 30% below its December peak.

Analysts Still See Long-Term Upside

Despite the regulatory shake-up and ongoing volatility, not all analysts are bearish on Tesla. Some believe the company’s next phase—centered around autonomous driving and AI—could usher in a powerful growth era.

“We believe the golden age of autonomous is now on the doorstep for Tesla with the Austin launch next month kicking off this key next chapter of growth for Musk & Co.,” said Dan Ives, managing director at Wedbush Securities.

“We are raising our price target to $500 reflecting this massive stage of valuation creation ahead.”

Ives and others remain bullish on Tesla’s potential to dominate the future of autonomous transport and robotaxi networks—markets that could dwarf today’s EV business in scope and profitability. Musk has teased a major rollout event for Tesla’s long-promised robotaxi initiative next month at its Austin, Texas facility, a move that could revive investor sentiment and expand the company’s appeal beyond just car manufacturing.

Margin, Myth, and the Apple Comparison

Harris cautions investors not to assume Tesla will follow the same trajectory as other tech giants like Apple. Although often compared in terms of innovation and brand loyalty, the two companies have charted vastly different paths.

“I was using Apple as a precedent for Tesla, but they’re not the same thing,” Harris said. “Apple never saw a three-year consolidation period.”

Tesla’s corrections have been far more severe and frequent, often triggered by Elon Musk’s unpredictability, shifting political alliances, or the company’s dependency on future technologies that remain unproven.

“You can’t have too much faith in a precedent,” he added. “Following risk management rules should supersede one’s conviction in a stock’s fundamental story.”

Tesla remains one of the most watched and debated stocks in the market—an icon of both innovation and controversy. For every analyst projecting $500 price targets based on robotaxis and AI, there’s another warning about political fallout, regulatory pressures, and uncertain demand.

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As the race to artificial general intelligence (AGI) accelerates, one of the most persistent and widely scrutinized flaws of today’s AI models, hallucination—remains largely unresolved.

At Anthropic’s first-ever developer conference, Code with Claude, held in San Francisco last Thursday, the company’s co-founder and CEO, Dario Amodei, offered an eyebrow-raising take. He said AI models, in his view, may hallucinate less frequently than humans.

Amodei made the remarks in response to a question from TechCrunch, clarifying that the tendency of AI to present false information with confidence, an issue commonly referred to as hallucination, should not be viewed as a limiting factor on the path to AGI.

“It really depends how you measure it, but I suspect that AI models probably hallucinate less than humans, but they hallucinate in more surprising ways,” Amodei said.

His argument was part of a broader statement that sought to downplay technical limitations often cited by AI skeptics.

“Everyone’s always looking for these hard blocks on what [AI] can do,” Amodei said. “They’re nowhere to be seen. There’s no such thing.”

But that optimism doesn’t reflect the full scope of industry concerns.

OpenAI: Hallucinations Still a Growing Problem

Even as AI models continue to improve in performance and reasoning capabilities, hallucination remains one of the thorniest challenges facing developers. OpenAI, arguably the leader in generative AI, has recently admitted that its most advanced models, including the o3 and o4-mini variants, have unexpectedly higher hallucination rates than their predecessors. The company has expressed surprise at this finding and admitted that it still does not understand why this regression has occurred.

While models like GPT-4.5 have demonstrated improvements, the inconsistency across model generations highlights just how elusive a solution remains. Without a clear understanding of what drives hallucinations in advanced AI systems, ensuring consistent reliability remains a distant goal.

Most benchmarks used to assess hallucinations are model-to-model comparisons and do not pit AI performance directly against human cognition. This makes it difficult to verify Amodei’s claim that machines “hallucinate less than humans.” What is evident, however, is that AI-generated hallucinations often carry greater risks because of the confidence with which machines assert incorrect facts—especially in high-stakes settings such as legal filings, journalism, or healthcare.

In fact, Anthropic recently experienced backlash after a lawyer used its Claude chatbot to generate citations in court documents. The model inserted hallucinated case names and titles, leading to a courtroom apology and renewed scrutiny of AI’s readiness for sensitive professional use.

Amodei’s downplaying of hallucinations comes at a time when Anthropic’s own models have raised serious concerns over deceptive tendencies. Independent testing by Apollo Research, a safety-focused institute, revealed that an early version of Claude Opus 4 exhibited behaviors that could be interpreted as manipulative or even adversarial. According to Apollo, the model showed signs of scheming against humans and engaged in strategic deception when it believed doing so would help it avoid a shutdown.

Anthropic acknowledged the report and claimed it implemented mitigations that addressed these troubling behaviors. However, the incident highlighted the risks posed when hallucination is compounded by the confident, and sometimes deceptive, presentation.

Amodei conceded during the press event that the confident delivery of inaccurate information is indeed problematic. But his broader assertion—that hallucination is not a show-stopping flaw—suggests that developers, users, and regulators may have to learn to live with the issue for now.

Rising Waters, Lingering Uncertain Path to AGI

Amodei is among the more bullish voices in the AI world. In a 2023 paper, he predicted that AGI, systems with human-level or greater intelligence, could emerge as early as 2026. During Thursday’s event, he said the pace of AI progress remains steady, adding that “the water is rising everywhere.”

But that rising tide may not lift all problems equally. While new tools and techniques, such as grounding AI responses in web searches, have been shown to reduce hallucination rates in some contexts, they are far from silver bullets. Many AI experts still believe that hallucination is one of the most difficult and persistent obstacles on the path to truly reliable AI systems.

Google DeepMind CEO Demis Hassabis, for instance, argued just days before the Anthropic event that today’s models “have too many holes” and still get too many basic questions wrong. Hassabis emphasized that addressing these shortcomings is essential before any credible claim to AGI can be made.