When the AI Narrative Repeats NFT Frenzy: Are We Trading the Same "Hysteria" Again?

特邀专栏作者

2026-02-10 10:20

This article is about 4448 words, reading the full article takes about 7 minutes

We are in the "mid-game" of a great revolution. All the extreme optimism and extreme panic are attempts to prematurely cash in on an endgame that has not yet arrived.

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Core View: The current market's panic selling over AI disrupting the software industry, much like the excessive hype on social media, commits the "endgame fallacy." This is the mistake of trying to price the final outcome during the mid-stage of a technological revolution, overlooking the complexity and gradual nature of real-world development.
Key Elements:
1. Social media amplifies extreme narratives, distorting technical discussions into performative allegiances, creating false market consensus and investment signals.
2. The market has overreacted to the "AI kills software" narrative, leading to indiscriminate selling in the software sector (e.g., the IGV ETF), which is down 22% year-to-date, hitting extremely low sentiment indicators.
3. Earnings reports from industry giants like Salesforce and ServiceNow show their AI businesses (Agentforce, Now Assist) are growing rapidly with healthy cash flow, indicating they are actively integrating AI rather than being disrupted by it.
4. The real risk is concentrated in standardized tool-type companies lacking deep integration and proprietary data, not in enterprises with platform foundations and systematic records.
5. Historical analogies (e.g., the 2022 SaaS crash, the dot-com bubble) show that when the market panics and prices in the "endgame" during the mid-stage, it often creates significant mispricing opportunities.

Original Author: market participant

Original Compilation: TechFlow

Introduction: As the new wave of AI agent hype sparked by OpenClaw and Claude Code sweeps across social media, the author keenly senses a frenzy reminiscent of the NFT era in 2021.

This article analyzes how social media amplifies technological narratives, why Wall Street is indiscriminately selling off due to the "AI kills software" bias, and why giants like Salesforce and ServiceNow are being misjudged by the market even after delivering stellar results.

The author believes we are in the "mid-game" of a great revolution, where extreme optimism and extreme panic are both attempts to prematurely cash in on an endgame that has not yet arrived.

Full text below:

This wave of hype around OpenClaw and Claude Code reminds me of the hysteria of the NFT era.

The emergence of new technology comes with utility, while simultaneously generating cultural and narrative resonance within the zeitgeist. Like every technology that captures the collective imagination at the right moment, it is being processed through the same "distortion machine"—the very machine that once turned JPEGs of monkeys into a $40 billion asset class.

The pattern is identical: genuine innovation arrives, early adopters discover real value. Then, the social layer takes over—suddenly, the conversation detaches from the technology itself and becomes a performance about "picking sides."

Declaring "this is the future" becomes a badge of insider status. Writing guides, think pieces, and exaggerating the current state's value earns social validation. The compounding speed of opinions outpaces the technology itself.

(I promise there will be a point about financial markets later).

The Cognitive Distortion Machine

X makes it worse. Social media is increasingly treated as a legitimate lens on reality, and it bends the image of truth.

The loudest voices are not representative—they are performing "conviction" for an audience that rewards it. Every major platform runs on engagement, and engagement rewards extremity. "This is interesting and useful" doesn't go viral; "This changes everything, your job is gone" does.

A hundred retweets saying "this changes everything" are not a signal, they are an echo. The echo is mistaken for consensus, consensus is mistaken for truth, and truth is mistaken for an investable thesis.

Girard would have a field day with this. When enough people perform "belief" in an outcome, the performance itself gets confused for evidence supporting that outcome. The NFT era proved this conclusively: people didn't want JPEGs, they wanted "to want what everyone else wanted" [1].

What is Real?

The latest model capabilities are astounding—far more impressive than NFTs, which had little practical utility beyond speculation and cultural signaling.

I use these tools every day. They make me more efficient in concrete, measurable ways. The underlying models are genuinely impressive, and the improvement trajectory is steep. The delta between what I could do with these tools six months ago and today is massive.

And the broader potential is limitless. AI-assisted coding, research, analysis, writing—these are not hypothetical use cases, they are happening and creating real value for those who leverage them well.

I don't want to be the person in 1998 sneering at the internet. That's not the point; I am very long-term bullish on AI. The point is the timeline, and the chasm between potential and present reality.

What is Not Yet Real

No—Claude is not going to immediately catalyze societal upheaval. It does not mean humans no longer need interfaces to manage work. It does not mean Anthropic has already won the AI war.

Think about what the most breathless takes actually require you to believe: that enterprise software—decades of accumulated workflows, integrations, compliance frameworks, and institutional knowledge—will be replaced in quarters, not years? That per-seat pricing models die overnight? That companies generating over $10B in revenue with 80% gross margins evaporate because a chatbot can write a function? [2]

Wedbush's Dan Ives put it bluntly: "Enterprises are not going to rip out hundreds of billions of dollars of software infrastructure investments to move to Anthropic, OpenAI, etc." [3]. And Jensen Huang, who has more reason than anyone to hype AI disruption, called the notion of "AI replacing software" "the most illogical thing in the world" [4].

Those most aggressively declaring "Endgame" (thanks @WillManidis for popularizing the term) are often those who stand to benefit most from your "belief": follower counts, consulting gigs, subscription fees, speaking invitations. The incentive structure rewards bold predictions with zero accountability for timing.

The Market's Mirror

What's interesting to me: the market is making the same mistake on the other side of the table.

Anthropic released its Claude Cowork plugin on January 30th. Within a week, $285 billion evaporated from software, financial services, and asset management stocks [5].

The software ETF—$IGV—is down 22% this year while the S&P 500 is up. 100 out of 110 constituents are in the red. The RSI hit 16, its lowest reading since September 2001 [6].

Hedge funds are furiously shorting software stocks and adding to positions [7]. The narrative logic: AI kills SaaS. Every per-seat software company is a "walking dead."

This sell-off is indiscriminate. Companies with completely different AI risk profiles are being traded as the same proxy [8]. When 100 out of 110 names in an index are falling, the market is no longer analyzing; it is indulging in a narrative climax.

Note: A recovery may have begun since I started writing this.

Throwing Out the Baby with the Bathwater

Look at what's actually happening inside the companies supposedly facing existential doom.

Salesforce Agentforce revenue grew 330% year-over-year, reaching an annualized run rate over $500 million, and generated $12.4 billion in free cash flow. It trades at 15x forward P/E. They just announced a $60 billion revenue target for FY2030 [9]. This is not a company being disrupted by AI—it's a company building the AI enterprise delivery layer.

ServiceNow subscription revenue grew 21%, operating margin expanded to 31%, and they authorized a $5 billion stock buyback. Their AI suite, Now Assist, reached $600 million in Annual Contract Value (ACV), targeting over $1 billion by year-end [10]. Yet its stock is down 50% from its highs.

Should these names see a modest valuation haircut for risk? Perhaps. But smart money started pricing that in years ago. As many smarter than me have pointed out: this sell-off requires you to simultaneously believe "AI capex is collapsing" AND "AI is powerful enough to destroy the entire software industry" [11]. Both cannot be true. Pick one.

Identifying Real Risk

Will some companies be genuinely displaced? Yes.

Point solutions offering standardized, single-workflow tools are vulnerable. If your entire product is just an interface layer built on non-owned data, you're in trouble. LegalZoom is down 20%—for this type of company, the concern has substance [12]. When an AI plugin can automate contract review and NDA classification, the value proposition of paying a legacy vendor for the same function becomes hard to defend.

But companies with deep integrations, owned data, and platform-level moats are a different story entirely. Salesforce is embedded in the tech stack of every Fortune 500 company. ServiceNow is the system of record for enterprise IT. Datadog's consumption-based model means more AI compute directly translates to more monitoring revenue—their non-AI business growth actually accelerated to 20% year-over-year [13].

Selling off digital infrastructure because "AI kills software" is as absurd as selling off construction equipment stocks because a building is going up.

We've Been Here Before

The 2022 SaaS crash is instructive. The sector fell over 50%. The median forward revenue multiple dropped from 25x to 7x—below pre-pandemic levels [14]. And earnings performance remained strong throughout. The subsequent rebound was dramatic—the Nasdaq was up 43% in 2023. Granted, the trigger then was more an interest rate shock than a fundamental deterioration.

The DeepSeek panic of January 2025 is more recent. Nvidia plunged on fears cheap Chinese AI models would make the entire AI infrastructure buildout pointless, then fully recovered [15]. That fear was structurally identical to today's: a single product release triggered an existential re-rating of an entire industry.

Many observers have drawn direct analogies between the current moment and the early stages of the dot-com bust—tech stocks falling while consumer staples, utilities, and healthcare rise [16]. But one thing about the dot-com bust: Amazon fell 94%, then became one of the world's most important companies. The market trying to price the "endgame" halfway through the game created one of history's greatest buying opportunities.

Deutsche Bank's Jim Reid stated the obvious truth: "Identifying the long-term winners and losers at this stage is almost pure guesswork" [17].

I'd bet he's right. And that uncertainty—the admission that we don't yet know the ending—is precisely why this indiscriminate sell-off is a mistake.

The Endgame Fallacy

The hype merchants on X and the panic sellers on Wall Street are making the same error on opposite ends of the board.

One group says AI has already won, the future is here, all institutions and job functions are rewritten from now on. The other group says AI has already killed software, subscription revenue is dead, $10 billion in free cash flow doesn't matter because the business model is obsolete.

Both are jumping to the "endgame" while the game still has many moves left. The chasm between our present and the technological horizon will be filled by messy, incremental, company-specific progress. Some software companies will integrate AI and become stronger; a few will be genuinely displaced; most will adapt—a process that is slow, uneven, and not tweetable.

The actual trajectory is more volatile and less certain than either hype or panic suggests. Those who will do well from here will be those who can tolerate that ambiguity, not those rushing to grasp a prematurely conclusive narrative.

Great operators always find a way.