AI Hype Echoes NFT Mania, Market Overreacts to AI Disruption Narratives

Author:market participant

Compiled by DeepTide TechFlow

Deep Tides Guide: As the new wave of AI agent fever sparked by OpenClaw and Claude Code swept through social media, the author keenly sensed a mania reminiscent of the NFT era in 2021.

This article dissects how social media amplifies technological narratives, how Wall Street engages in indiscriminate selling due to the bias of "AI killing software," and why giants like Salesforce and ServiceNow are still wrongly beaten by the market despite delivering impressive results.

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

The full text is as follows:

This wave of enthusiasm for OpenClaw and Claude Code reminds me of the hysteria of the NFT era.

The emergence of new technology is accompanied by practicality, while also generating cultural and narrative resonance within the spirit of the times. Like every technology that has captured collective imagination at the right moment, it is now being processed through the same "distortion machine"—the very machine that turned JPEG images of monkeys into a $40 billion asset class.

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

Claiming "this is the future" has become a hallmark within the community. Writing guides, deep thinking (think pieces), and exaggerating the current value can gain social recognition. The compounding speed of ideas has even surpassed that of technology itself.

(I promise, there will be a perspective on financial markets later).

X made the situation worse. Social media is increasingly seen as a legitimate lens for reality, while it distorts the image of facts.

The loudest voices are not representative—they are performing "conviction" for audiences that reward such behavior. Every mainstream platform runs on engagement, and engagement rewards extremism. "This is interesting and useful" won't spread widely, but "This changes everything, you're going to lose your job" will.

A hundred retweets saying "this changes everything" are not a signal, but an echo.Echoes are mistaken for consensus, consensus is mistaken for truth, and truth is mistaken for an investable theory.

Girard would surely have a field day with this scene. When enough people perform "acts of belief" for a certain outcome, the performance itself becomes confused as evidence supporting that outcome. The NFT era has proven this conclusively: people don't want JPEGs; they want the "wanting that everyone else wants" [1].

The latest model's capabilities are astonishing—far more so than NFTs, which have little practical capability beyond speculation and cultural signaling.

I use these tools every day. They have improved my efficiency in concrete, measurable ways. The underlying models are indeed impressive, and the trajectory of improvement is very steep. When I compare what I could do with these tools six months ago to what I can do today, the increment is huge.

Moreover, the broader potential is infinite. AI-assisted programming, research, analysis, writing—these are not hypothetical use cases; they are happening now and creating real value for those who use them effectively.

I don't want to be the person in 1998 who looked down on the internet. That's not the point, I'm very bullish on AI in the long term. The point isSchedule, as well asThe gap between potential and current reality.

No—Claude will not immediately catalyze social unrest. This does not mean that humans no longer need interfaces to manage work. This also does not mean that Anthropic has already won the AI war.

Think about what the most breathless opinions actually require you to believe: that enterprise software—decades of accumulated workflows, integrations, compliance frameworks, and institutional knowledge—will be replaced in a few quarters rather than years? That a per-seat billing model will die overnight? That a company with over $10 billion in annual revenue and 80% gross margins will vanish just because a chatbot can write a snippet of code? [2]

Wedbush's Dan Ives bluntly points out: "Enterprises will not completely overturn their past hundreds of billions of dollars in software infrastructure investments to migrate to companies like Anthropic and OpenAI." [3]. Jensen Huang, who more than anyone else has reason to promote the disruptive power of AI, called the concept of "AI replacing software" "the most illogical thing in the world" [4].

Those who are most actively declaring the "Endgame" (a term popularized by @WillManidis) are often the ones who benefit the most from your "unwavering belief": follower counts, consulting requests, subscription fees, conference invitations. The incentive structure rewards bold predictions that bear no responsibility for timing.

What interests me is that the market is also making the same mistakes on the other side of the table.

Anthropic released its Claude Cowork plugin on January 30, and within less than a week, $285 billion in market value evaporated from software, financial services, and asset management stocks [5].

Software ETF - $IGV - has fallen 22% this year, while the S&P 500 is rising. 100 out of 110 components are in a loss state. The RSI has touched 16, the lowest reading since September 2001 [6].

Hedge funds are aggressively shorting software stocks and continuously increasing their positions [7]. The narrative logic is: AI kills SaaS (Software as a Service). Every software company that charges per seat is a "zombie."

This sell-off is indiscriminate. Companies with entirely different risk profiles regarding AI are all being treated as the same trade [8]. When 100 out of 110 names in the index are falling, the market stops analyzing and is instead immersed in the climax of the narrative.

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

See what is actually happening inside companies that are considered to be facing a catastrophe.

Salesforce Agentforce's revenue increased by 330% year-over-year, with annualized revenue exceeding $500 million and generating $1.24 billion in free cash flow. The forward P/E ratio is 15 times. They have just announced a revenue target of $60 billion for fiscal year 2030 [9]. This is not a company being disrupted by AI — this is a company building the AI enterprise delivery layer.

ServiceNow Their subscription business grew by 21%, operating profit margin expanded to 31%, and they authorized a $5 billion stock buyback. Their AI suite Now Assist achieved an annual contract value (ACV) of $600 million, with a target to break $1 billion by year-end [10]. However, their stock price has fallen 50% from its peak.

Should these names be moderately downgraded in valuation due to the risks? Perhaps. But smart people have been pricing this in for years. As many smarter than me have pointed out: this selloff requires you to believe both that "AI capital spending is collapsing" and that "AI is powerful enough to destroy the entire software industry" [11]. These two things cannot be true at the same time. Pick one.

Will some companies be truly replaced? Yes.

Point solutions that provide standardized, single workflows are fragile. If your entire product is merely an interface layer built on non-proprietary data, you are in trouble. LegalZoom dropped by 20%—for such companies, concerns are substantive [12]. When AI plugins can automatically perform contract review and NDA classification, the value proposition of paying traditional vendors for the same functionality becomes indefensible.

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

Selling off digital infrastructure because "AI is killing software" is as absurd as selling off construction equipment stocks because buildings are going up.

The 2022 SaaS crash was enlightening. The sector fell more than 50%. The median forward revenue multiple dropped from 25 times to 7 times—below pre-pandemic levels [14]. Yet financial performance during that time had been solid. The subsequent rebound was significant—the Nasdaq rose 43% in 2023. Admittedly, the drivers at the time were more interest rate shocks than fundamental deterioration.

January 2025 DeepSeek Panic is closer. NVIDIA plummeted due to concerns that cheap Chinese AI models would render the entire AI infrastructure construction meaningless, but then fully recovered the losses [15]. That fear is structurally identical to today's: a single product launch triggered a survival crisis-style reassessment of the entire industry.

Many observers have made a direct analogy between the current moment and the early stages of the dot-com bubble burst—technology stocks are falling, while consumer staples, utilities, and healthcare stocks are rising [16]. But here's something about the dot-com bubble burst: Amazon fell by 94%, and then became one of the most important companies in the world. The market trying to price the "endgame" halfway through the game created one of the greatest buying opportunities in history.

Jim Reid of Deutsche Bank said a sensible thing: "Identifying long-term winners and losers at this stage is almost pure guesswork." [17]

I bet he's right. And this uncertainty—that is, acknowledging that we don't yet know how it will end—is precisely why this indiscriminate selling is wrong.

The hype merchants on X and the panic sellers on Wall Street made the same mistake at opposite ends of the board.

A group of people say AI has already won, the future has arrived, and all institutions and job roles will be rewritten from now on. Another group says AI has already killed software, subscription revenue is dead, and $10 billion in free cash flow no longer matters because the business model is outdated.

Both sides jumped to the "endgame" while the game still had many moves left. The gap between our current situation and the technological vision will be filled by chaotic, incremental, and company-specific progress. Some software companies will integrate AI and become stronger; a few will be genuinely replaced; most will adapt—this adaptation process is slow, uneven, and not suitable for Twitter.

The actual trajectory is more volatile and less certain than the hype or panic suggests. Those who will do well from now on will be the ones who can tolerate this ambiguity, not those who rush to grasp a premature narrative.

Great operators always find a way out.

Reference Source

[1] Girard's Mimetic Desire Theory (https://www.iep.utm.edu/girard/)

[2] Wealth Magazine: Why SaaS Stocks Are Irrationally Slumping Like DeepSeek's Panic

[3] CNBC: The Impact of AI Tools on SaaS Software Stocks

[4] CNBC: Jensen Huang calls AI replacing software "the most illogical thing"

[5] Yahoo Finance: U.S. software sector loses $285 billion in market value due to impact from Anthropic

[6] Yahoo Finance: IGV ETF Trend Analysis

[7] Axios: Hedge Funds Aggressively Shorting the Software Industry

[8] Benzinga: Misinterpretations in the Software Sector Crash

[9] Salesforce Investor Relations: Agentforce-Driven Record-Breaking Q3 Earnings

[10] Futurum Group: ServiceNow Q4 Financial Report and AI Platform Momentum [11] Fortune Magazine: AI Paradox and Irrational Analysis

[12] CNBC: Software Stocks Enter Bear Market, ServiceNow and Others Plunge Sharply

[13] StockAnalysis: Datadog Operating Statistics

[14] Meritech Capital: 2022 SaaS Crash Retrospective

[15] CNBC: NVIDIA Plummets Due to DeepSeek Concerns

[16] Forbes Magazine: Deutsche Bank Compares the Software Stock Bubble to the Internet Era

[17] Deutsche Bank Jim Reid Analysis Report