Author: Market Participant
Compiled by: TechFlow TechFlow
Original title: Nothing new in the market; the current AI craze reminds me ofNFTs.
TechFlow Dive: As OpenClaw and Claude Code sparked a new wave of AI agent fever that swept social media, the author keenly sensed a frenzy reminiscent of the NFT era of 2021.
This article analyzes how social media amplifies the technology narrative, how Wall Street indiscriminately sells off stocks due to the "AI kills software" bias, and why giants like Salesforce and ServiceNow are still unfairly punished by the market despite delivering amazing results.
The author argues that we are in the "mid-game" of a great revolution, and all the extreme optimism and extreme panic are attempts to prematurely exhaust the yet-to-arrive endgame.
The full text is as follows:
This wave of popularity for OpenClaw and Claude Code reminds me of the hysteria of the NFT era.
The emergence of new technologies is accompanied by practicality, while simultaneously generating cultural and narrative resonance within the zeitgeist. Like every technology that captures the collective imagination at the right time, it is being processed through the same "twisting machine"—the same machine that once transformed JPEG images of monkeys into a $40 billion asset class.
The pattern is identical: genuine innovation arrives, and early adopters discover the real value. Then, the social layer takes over—suddenly, the conversation detaches from the technology itself and becomes a performance about "taking sides."
Declaring "this is the future" has become a hallmark of those in the industry. Writing guides, producing "think pieces," and exaggerating the value of the status quo garner social approval. The compounding effect of these ideas even outpaces that of the technology itself.
(I promise there will be a view on the financial markets later.)
Cognitive Distortion Machine
X makes things worse. Social media is increasingly seen as a legitimate lens through which reality is viewed, and it distorts the image of the truth.
The loudest voices aren't representative—they're performing "unwavering conviction" for the audience rewarding this behavior. Every major platform operates on engagement, and engagement rewards are extreme. "This is fun and useful" won't spread widely; "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. The echo is mistaken for consensus, consensus is mistaken for truth, and truth is mistaken for an investable theory.
Girard would certainly be thrilled to see this. When enough people put on a show of faith in a result, the show itself can be mistaken for evidence supporting that result. The NFT era proved this point: people didn’t want JPEGs, they wanted “what everyone else wants” [1].
What is real?
The latest modeling capabilities are astonishing—far more impressive than NFTs, which have little practical use beyond speculation and cultural signals.
I use these tools every day. They improve my productivity in concrete, measurable ways. The underlying model is truly impressive, and the trajectory of improvement is very steep. The incremental improvement is enormous when I compare what I could do with these tools six months ago to what I can do today.
Moreover, the broader potential is limitless. AI-assisted programming, research, analysis, and writing—these are not hypothetical use cases; they are happening and creating real value for those who use them effectively.
I don't want to be the person who looked down on the internet in 1998. That's not the point; I'm very bullish on AI in the long term. The point is the timeline and the gap between potential and the current state.
What isn't real?
No—Claude won't immediately catalyze social unrest. This doesn't mean humans no longer need interfaces to manage work. Nor does it mean Anthropic has won the AI war.
Consider what those most breathtaking arguments actually require you to believe: Will enterprise software—the workflows, integrations, compliance frameworks, and institutional knowledge built up over decades—be replaced in a few quarters rather than years? Will the per-seat billing model die out overnight? Will a company with annual revenue exceeding $10 billion and a gross margin of 80% simply vanish because a chatbot can write a function? [2]
Wedbush’s Dan Ives bluntly stated: “Companies will not completely overturn their past investments of hundreds of billions of dollars in software infrastructure in order to migrate to companies like Anthropic and OpenAI” [3]. Jensen Huang, who has more reason than anyone to advocate the disruptive power of AI, called the concept of “AI replacing software” “the most illogical thing in the world” [4].
Those who most actively proclaim the "Endgame" (thanks to @WillManidis for popularizing the term) are often the ones who benefit most from your unwavering conviction: increased followers, inquiries, subscriptions, and conference invitations. Incentive structures reward bold predictions that bear no responsibility for timing.
The Market Mirror
What's interesting to me is that the market makes the same mistakes on the other side of the table.
Anthropic released its Claude Cowork plugin on January 30, and in less than a week, $285 billion of stocks in the software, financial services and asset management sectors evaporated.[5]
The software ETF, $IGV, has fallen 22% this year, while the S&P 500 has risen. 100 of its 110 constituent stocks are in the red. The RSI index hit 16, its lowest reading since September 2001.[6]
Hedge funds are aggressively short software stocks and continuing to increase their holdings[7]. The narrative is: AI kills SaaS (Software as a Service). Every software company that charges per seat is a “walking dead”.
This sell-off is indiscriminate. Companies with completely different risk profiles affected by AI are all treated as the same trading targets[8]. When 100 out of 110 names in the index are falling, the market has stopped analyzing and is indulging in the climax of the narrative.
Note: The recovery may have already begun since I started writing this article.
Throwing away the bathwater also means losing the child.
Let's take a look at what's really happening inside those companies that are thought to be facing annihilation.
Salesforce’s Agentforce revenue grew 330% year-over-year, with annualized revenue exceeding $500 million and generating $12.4 billion in free cash flow. The forward P/E ratio is 15. They have just announced a revenue target of $60 billion for fiscal year 2030.[9] This is not a company being disrupted by AI—it is a company building an AI enterprise delivery layer.
ServiceNow’s subscription business grew by 21%, its operating margin expanded to 31%, and it authorized $5 billion in stock buybacks. Their AI suite, Now Assist, has an annual contract value (ACV) of $600 million, with a target of breaking $1 billion by the end of the year.[10] However, its stock price has fallen by 50% from its peak.
Should these names be downgraded due to risk? Perhaps. But smart people started pricing this out years ago. As many smarter people than I have pointed out: this sell-off 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. Choose one.
Identify the real risks
Will some companies actually be replaced? Yes.
Point solutions that provide standardized, single-workflow tools are vulnerable. If your entire product is just an interface layer built on top of non-proprietary data, you're in trouble. LegalZoom fell 20%—and for companies like that, the concerns are real.[12] The value proposition of paying traditional vendors for the same functionality becomes hard to defend when AI plugins can automatically perform contract review and confidentiality agreement (NDA) classification.
But companies with deep integration, proprietary data, and platform-level foundations are a completely different story. Salesforce has penetrated the technology stack of every Fortune 500 company. ServiceNow is the system of record for enterprise IT. Datadog’s consumption-based model means that more AI computing directly translates into more monitoring revenue—their non-AI business growth has actually accelerated to 20% year-over-year growth. [13]
Selling off digital infrastructure stocks because "AI is killing software" is as absurd as selling off construction equipment stocks because buildings are springing up.
We have experienced these things.
The SaaS crash of 2022 was instructive. The sector fell by more than 50%. The median forward revenue multiple dropped from 25x to 7x—below pre-pandemic levels[14]. Meanwhile, earnings had been strong. The subsequent rebound was remarkable—the Nasdaq rose 43% in 2023. Admittedly, the trigger was more interest rate shocks than a deterioration in fundamentals.
The DeepSeek panic of January 2025 is even closer. Nvidia crashed due to concerns that cheap Chinese AI models would render the entire AI infrastructure construction meaningless, but subsequently recovered all its losses.[15] That fear was structurally similar to today's: a single product launch triggered a survival crisis reassessment of the entire industry.
Many observers have drawn a direct analogy to the early stages of the dot-com bubble burst—when tech stocks fell while consumer staples, utilities, and healthcare stocks rose.[16] But there is one thing about the dot-com bubble burst: Amazon fell 94 percent and then became one of the world’s most important companies. The market’s attempt to price in the “endgame” halfway through the game created one of the greatest buying opportunities in history.
Jim Reid of Deutsche Bank made a very true statement: "Identifying long-term winners and losers at this stage is almost pure guesswork." [17]
I bet he's right. And this uncertainty—the admission that we don't yet know how it will end—is precisely what makes this indiscriminate selling a mistake.
End fallacy
Speculators on X and panic sellers on Wall Street made the same mistake at opposite ends of the chessboard.
One group says AI has won, the future is here, and all institutions and job functions should be rewritten now. Another group says AI has killed software, subscription revenue is dead, and $10 billion in free cash flow is irrelevant because the business model is obsolete.
Both sides jumped to the "endgame" when there were still many moves left in the game. The gap between our present state and the technological vision will be filled by chaotic, incremental, and company-specific progress. Some software companies will integrate AI and become more powerful; a few will actually be replaced; most will adapt—a slow, uneven process that is not suitable for tweeting.
The actual trajectory is more volatile and uncertain than hype or panic suggests. Those who will do well from now on will be those who can tolerate this ambiguity, not those who are eager to grasp at a narrative that is prematurely settled.
Great business leaders always find a way out.
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