Software Stocks Plunge 20%, But I'm Heavily Invested in Adobe and Salesforce

marsbitPublicado em 2026-02-12Última atualização em 2026-02-12

Resumo

Last week, the software sector lost $1 trillion in market value, with stocks like Shopify, Atlassian, Salesforce, and Adobe plunging. The sell-off was triggered by Anthropic's release of Claude Cowork and OpenAI's similar tools, sparking fears that AI would disrupt traditional software companies. However, the author argues this reaction is irrational panic, drawing parallels to past overreactions: Google’s 40% drop after ChatGPT, Meta’s 70% decline due to TikTok, and Nvidia’s 30% fall after DeepSeek—all of which later rebounded significantly. The author believes established software firms have strong defenses: high switching costs, deep AI integration capabilities, and entrenched trust with enterprise clients. On Thursday, they bought Adobe, Salesforce, ServiceNow, and Microsoft, citing low valuations and robust fundamentals. Adobe trades at half its historical P/E, with $5B in AI revenue. Salesforce’s AI products grew rapidly, and ServiceNow’s subscriptions rose 21% last quarter. Microsoft, despite its OpenAI stake, is undervalued with the lowest P/E among Magnificent Seven stocks. The author views this as a market overreaction and a buying opportunity for high-quality companies.

Author: Ed Elson

Compiled by: Deep Tide TechFlow

Deep Tide Introduction: Last week, the software industry lost $1 trillion in market value, falling 14% in a single week and about 20% year-to-date. Major names like Shopify, Atlassian, Salesforce, and Adobe all plummeted.

Reason? Anthropic released Claude Cowork and its plugins, and OpenAI also launched similar tools. Investors panicked and sold off, believing that "AI killed software."

But Ed Elson believes this is irrational panic; we've seen this movie before: When ChatGPT emerged in 2022, Google fell 40%; when TikTok appeared, Meta dropped 70%; when DeepSeek came out, Nvidia declined 30%.

The result? These companies have since risen 630%, 270%, and 55% from their lows, respectively. On Thursday, he bought Adobe, Salesforce, ServiceNow, and Microsoft, citing high switching costs, strong AI integration capabilities, and extremely low valuations.

Full text below:

Last week, we witnessed what can be called a massacre. $1 trillion in market value was wiped out. Selling activity hit historic highs. Companies lost 10%, 20%, 30% of their value. If you were looking at your retirement account, you might not have noticed: the S&P 500 was only slightly down. That's because the slaughter happened in one very specific place—an industry that has dominated portfolios for decades and many thought was invincible: software.

All the biggest names went into free fall: Shopify, Atlassian, Salesforce, Adobe, the list goes on. The software industry lost about 14% of its value in just one week. Year-to-date, that number is now around 20%.

Why did this happen? Because of AI. A few weeks ago, Anthropic released a new AI tool, Claude Cowork. Then (last week) they released new plugins for specific fields: legal work, sales, finance, marketing, etc. OpenAI quickly released similar tools.

Investors quickly asked themselves an important question: Isn't this what every traditional software company does? After that: Did AI just kill software? Finally, their conclusion: Sell everything.

Déjà Vu

We've seen this movie before. In 2022, an AI tool called ChatGPT took the internet by storm. Investors asked themselves an important question: Isn't this what Google does? Within months, Wall Street decided search was dead. Google lost up to 40% of its value that year.

Before that, a social media app called TikTok arrived. Investors asked themselves: Isn't this what Meta does? Once Meta reported a user decline, $230 billion in market value vanished, the largest 24-hour sell-off in stock market history. Meta went on to lose up to 70% of its value.

More recently, a Chinese AI model called DeepSeek went viral. Investors asked themselves: Isn't this what OpenAI does? OpenAI isn't publicly traded, so the sell-off wasn't visible. However, the fear echoed into the public markets. Nvidia lost 30% of its value over the next few months.

Since these market-breaking events, Nvidia, Meta, and Google have risen 55%, 270%, and 630% from their lows, respectively. DeepSeek wasn't the domestic AI killer investors thought it was. After TikTok, Meta learned from it and launched its own version, Reels, which now has a 2 billion active user base. After ChatGPT, Google doubled down on AI and eventually launched Gemini, ChatGPT's fastest-growing competitor. Google is now considered the undisputed AI heavyweight champion.

The pattern here is simple. A transformative technology arrives. Investors indiscriminately decide "it's over." They aren't wrong about the technology, but they overestimate its impact. They panic-sell, assuming the game is zero-sum. Valuations plummet. Suddenly, America's greatest companies are on a 50% discount. Meanwhile, they continue to deploy armies of talent and capital to sharpen their focus and neutralize the competition. Earnings grow larger, valuations soar again. Years later we look back at the charts and think: What were we thinking? That is, all of us who sold.

There's Panic, and Then There's This

I believe what happened in the software industry last week is no different. This isn't a correction; it's a full-blown crisis. To paint you a picture: The Relative Strength Index (RSI) is a formula that captures buying and selling pressure. An RSI score of 30 means a stock is oversold. Last week, the average RSI for software stocks hit 18. I don't usually like technical analysis, but in this case, it describes what we saw well: Armageddon.

On one hand, the concerns are valid. Will AI disrupt software? Yes. Will it put pressure on margins? Absolutely. Do SaaS companies have to rethink their distribution? Without a doubt.

On the other hand, this isn't what the market told us last week. The market told us software is over—no matter who you are or what you sell. This stance is more questionable. While I was initially willing to listen, I concluded it's not coming from a place of rationality but from a place of fear. In other words: it's irrational.

Reality Check

First, nothing is stopping software companies from integrating AI. The ChatGPT vs. Google story is the perfect example. Just because OpenAI had a more exciting product doesn't mean Google is dead. Google simply enhanced their existing product with AI features (Google Search is now the primary AI interface in the US), then built their own AI chatbot. If SaaS companies were just ignoring AI, the shorts might have a point, but they're not. Software companies are embracing AI across the board.

Second, investors underestimate how massive a pain it is to cancel an enterprise SaaS contract. In more business terms: switching costs are high. The average software sales process can take over half a year to finalize and must be approved by ten different decision-makers. The process is grueling because the contracts are long. That's not to mention the associated financial costs. For example, a typical Salesforce contract can't be canceled for free—the enterprise must pay 100% of the remaining contract value. In other words, switching your software provider as a business is a very big deal. If you're going to do it, you better have an extremely compelling reason why it's worth it. Plus, all the other executives at the company have to agree with you. Painful. Really. Painful.

Finally, in enterprise software, security concerns are huge. Signing a software agreement essentially means handing all your private data to a third party and praying they don't lose, use, or misuse it. In other words, it requires trust. This is the top priority for 80% of IT leaders. More importantly, trust can't be coded out in a day. Trust has to be built over years, even decades. It requires long-term relationships and a massive track record of success. These are things traditional companies have that Anthropic does not. Trust and security are a huge moat that cannot be overlooked.

Time to Buy

By Thursday afternoon, I had seen enough. I had two voices in my head. 1) Warren Buffett, who told me to be greedy when others are fearful. 2) Mark Mahaney, who told me to find "DHQ" (Dislocated High Quality companies). I decided it was time to buy and gave myself two options.

Option 1: Buy the entire software basket. I looked at IGV, an ETF of all the big software names, and it had been crushed. There might be a few losers in there, but the average multiple had fallen to a point where I felt I really couldn't go wrong. This was the safe choice.

Option 2: Stock pick. That is, personally identify a handful of software names I believe are high-quality companies. This was the riskier option, as I risked being wrong and picking losers. Still, I chose Option 2 because I was feeling bold.

DHQ (Dislocated High Quality Companies)

On Thursday morning, I bought three stocks: Adobe, Salesforce, and ServiceNow. After that, I bought one more: Microsoft. Note: I am not a financial advisor, this is not financial advice—I'm just telling you what I did. My reasoning is as follows.

1. Adobe

Adobe currently has a P/E ratio of 16, less than half its five-year average. It's also almost half the average P/E of the S&P 500. It's incredibly cheap. The consensus is that AI will make it irrelevant, but this ignores two key facts.

1) Adobe is already heavily integrating AI. In fact, its AI features are already generating over $5 billion in annual recurring revenue, which is more than half of Anthropic's ARR.

2) Its moat is huge. Over 98% of the Fortune 500 use Adobe, and like other software solutions, the product is so deeply integrated into the entire creative workflow that it's difficult to switch solutions. It's so ubiquitous that most digital creative roles list Adobe proficiency as a job requirement. An additional tailwind is short-form video. Adobe Premiere Pro is the industry standard for video editing, and most media companies (including ours) are significantly expanding short-form video budgets as this medium continues to explode.

2. Salesforce

Salesforce is another AI-enabled company that's considered dead.

Meanwhile, the ARR for its AI agent products quadrupled last quarter, and the company continues to be rated #1 most trusted CRM in the industry. It's down over 40% in the past year, its P/E ratio is now below the S&P average, and its price-to-cash-flow ratio is about half its 5-year average.

Even if Claude has a more interesting product, I don't believe this outweighs the massive switching costs—certainly not in the time it would take Salesforce to build its own comparable product.

3. ServiceNow

ServiceNow has been hit hard this year—down about 30% in 2026.

The consensus is that growth is about to end. Meanwhile, its fundamentals tell the opposite story: subscription revenue grew 21% last quarter, total revenue grew 20%. As for its AI capabilities, ServiceNow has more than enough.

In fact, the company is on track to generate $1 billion in revenue from its AI products this year. It has also signed multi-year partnerships with OpenAI and Anthropic—more evidence that the AI revolution is not a zero-sum game.

I believe both OpenAI and Anthropic will grow significantly this year, and so will ServiceNow.

4. Microsoft

If you listened to yesterday's podcast, you'll notice I didn't mention Microsoft. That's because I hadn't bought it yet when recording.

My initial thought was that I didn't need Microsoft because my exposure was already large. (MSFT is 5% of the S&P 500.) However, upon reflection, I decided the valuation was too cheap to ignore.

At the time, Microsoft's P/E ratio was only 25, the lowest among the Mag 7. This is relatively absurd for the reasons I highlighted above, and especially absurd for another key reason: Microsoft owns nearly a third of OpenAI.

Even if Microsoft's lunch is being eaten (which I doubt), the company has contractual rights to be compensated. Few companies are better positioned in AI than Microsoft. The current price does not reflect this.

Efficient Market Hypothesis

For the most part, I believe in the Efficient Market Hypothesis—the concept that the market reflects all available information and is smarter than any individual. I have great respect for the market's predictive power (especially after they correctly predicted 93% of Golden Globe winners). I don't claim to be smarter than them.

However, I also believe that every once in a while, something extraordinary happens—a political event, a natural disaster, a global pandemic, or indeed, the arrival of a transformative technology. In these cases, I believe the market can lose its mind. When that happens, for a brief period, the Efficient Market Hypothesis fails.

I risk being wrong and losing money here. But that's what being an investor is about. Plus, if you don't take a little risk from time to time... what's the fun in that?

See you next week,

Ed

Perguntas relacionadas

QWhy did the software sector experience a significant sell-off last week, according to the article?

AThe sell-off was triggered by the release of AI tools like Anthropic's Claude Cowork and OpenAI's similar offerings, leading investors to panic that AI would disrupt traditional software companies, causing a massive drop in valuations.

QWhat historical examples does the author cite to argue that the current panic is irrational?

AThe author cites examples like Google's 40% drop after ChatGPT's release (later rising 630%), Meta's 70% drop due to TikTok (later rising 270%), and Nvidia's 30% drop after DeepSeek's rise (later rising 55%), showing past overreactions were misguided.

QWhat are the three key reasons the author believes traditional software companies are resilient against AI disruption?

A1. Software companies are actively integrating AI into their products. 2. High switching costs make it difficult for enterprises to change providers. 3. Trust and security built over decades give established companies a significant advantage.

QWhich four companies did the author invest in during the sell-off, and what was a common valuation metric mentioned?

AThe author invested in Adobe, Salesforce, ServiceNow, and Microsoft. A common valuation metric mentioned was the price-to-earnings (P/E) ratio, which was historically low for these companies.

QHow does the author view the market's efficiency in situations like the recent software sell-off?

AThe author generally believes in the efficient market hypothesis but argues that during extraordinary events (e.g., transformative technology releases), the market can become irrational and inefficient, creating buying opportunities.

Leituras Relacionadas

The 'VVV' Concept Soars 9x in Half a Year, The New AI Narrative on Base Chain

"The article explores the 'VVV' concept as the new AI-focused narrative within the Base ecosystem, centered around the token $VVV of the privacy-focused, uncensored generative AI platform Venice, led by crypto veteran Erik Voorhees. Venice has seen significant growth in 2026, with its API users surging, partly attributed to exposure from OpenClaw. The platform now boasts over 2 million total users and 55,000 paid subscribers. Correspondingly, the $VVV token price has risen over 9x this year. Key to its performance are tokenomics designed for value accrual: reduced annual emissions, subscription revenue used for buyback-and-burn, and a unique staking mechanism. Staking $VVV yields $sVVV, which can be used to mint $DIEM tokens. Each staked $DIEM provides a daily $1 credit for using Venice's API services, creating tangible utility. The article also highlights other tokens associated with the 'VVV' narrative. $POD, the token of distributed AI network Dolphin (which co-developed Venice's default AI model), saw a massive price surge. $cyb3rwr3n, a project for a Venice credit auction market, gained attention due to perceived connections to Venice's team despite official denials. Finally, $SR of robotics platform STRIKEROBOT.AI rose after announcing a partnership with Venice for robot vision-language model development. Overall, the 'VVV' ecosystem combines AI platform growth, deflationary tokenomics, and innovative utility mechanisms, driving significant investor interest and price action in related tokens."

marsbitHá 4m

The 'VVV' Concept Soars 9x in Half a Year, The New AI Narrative on Base Chain

marsbitHá 4m

Anthropic and OpenAI Have Single-Handedly Severed the Logic of Pre-IPO Stock Tokenization

The pre-IPO stock token market is experiencing significant turmoil following strong statements from AI giants Anthropic and OpenAI. Both companies have updated their official policies, declaring that any transfer of their company shares—including sales, transfers, or assignments of share interests—without prior board approval is "invalid" and will not be recognized in their corporate records. This means buyers in such unauthorized transactions would not be recognized as shareholders and would have no shareholder rights. A major point of contention is the use of Special Purpose Vehicles (SPVs), which are legal entities commonly used by pre-IPO token platforms to pool investor funds and indirectly acquire shares from employees or early investors. The companies explicitly state they do not permit SPVs to acquire their shares, and any such transfer violates their restrictions. They warn that third parties selling shares through SPVs, direct sales, forward contracts, or stock tokens are likely engaged in fraud or are offering worthless investments due to these transfer limits. This stance directly threatens the core model of many pre-IPO token platforms, which rely on SPV structures. The announcement revealed additional risks within this model, such as complex "SPV-within-SPV" layering that obscures legal transparency, increases management fees, and creates a chain reaction risk of invalidation. Following the news, tokens like ANTHROPIC and OPENAI on platforms like PreStocks fell sharply (over 20%). The market reaction highlights a divergence: while asset-backed pre-IPO tokens plummeted, purely speculative pre-IPO futures contracts, which are bilateral bets on future IPO prices with no claim to actual shares, remained relatively stable as they are unaffected by the transfer restrictions. The industry is split on the implications. Some believe the fundamental logic of pre-IPO token trading is broken if leading companies reject SPV-held shares, potentially causing a domino effect. Others, like Rivet founder Nick Abouzeid, argue that buyers of such unofficial tokens always knowingly accepted the risk of non-recognition by the company. The statements serve as a stark risk warning and a corrective measure for a market where valuations for some AI-related pre-IPO tokens had soared to irrational levels, far exceeding recent funding round valuations.

marsbitHá 1h

Anthropic and OpenAI Have Single-Handedly Severed the Logic of Pre-IPO Stock Tokenization

marsbitHá 1h

Anthropic and OpenAI Personally Sever the Logic of Pre-IPO Crypto-Stocks

The pre-IPO token market has been rocked by strong statements from Anthropic and OpenAI. Both AI giants have updated official warnings, declaring that any sale or transfer of their company shares without explicit board approval is "invalid" and will not be recognized on their corporate records. This directly targets Special Purpose Vehicles (SPVs), the common legal structure used by pre-IPO token platforms. These platforms typically use an SPV to acquire shares from employees or early investors, then issue blockchain-based tokens representing a claim on the SPV's economic benefits. Anthropic and OpenAI's position means that if an SPV's share purchase lacked authorization, the underlying asset could be deemed worthless, nullifying the token's value. Anthropic explicitly warned that any third party selling its shares—via direct sales, forwards, or tokens—is likely fraudulent or offering a valueless investment. The crackdown highlights risks in the popular SPV model, including complex multi-layered "Russian doll" SPV structures that obscure legal ownership, add fees, and concentrate risk. If one layer is invalidated, the entire chain could collapse. Following the announcements, tokens like ANTHROPIC and OPENAI on platforms like PreStocks fell sharply (over 20%). In contrast, purely speculative pre-IPO prediction contracts remained stable, as they involve no actual share ownership. The move is seen as a corrective measure amid a market frenzy where some pre-IPO token valuations (e.g., Anthropic's token hitting a $1.4 trillion implied valuation) far exceeded recent official funding rounds. Opinions are split: some believe this undermines the core logic of pre-IPO token trading if top companies reject SPVs, while others argue buyers always assumed this legal risk when accessing unofficial channels. The statements serve as a stark warning and a potential catalyst for market de-leveraging and clearer boundaries.

Odaily星球日报Há 1h

Anthropic and OpenAI Personally Sever the Logic of Pre-IPO Crypto-Stocks

Odaily星球日报Há 1h

The Waged Worker Driven to Poverty by AI Subscriptions

"AI Membership: The Hidden Cost Pushing Workers Toward 'Poverty'" The widespread corporate push for AI adoption is creating a hidden financial burden for employees. Companies, from giants like Alibaba to small firms, are mandating AI use, often tying token consumption to KPIs, but frequently refuse to cover the costs. Workers are forced to pay for subscriptions out of pocket to stay competitive and avoid being replaced. Front-end developer Long Shen spends up to 2000 RMB monthly on tools like Cursor and ChatGPT Plus, seeing it as a necessary 3% salary investment to handle 90% of his coding tasks. While it boosted his performance and led to promotions, he now faces idle time at work, pretending to be busy. Designer Peng Peng navigates strict company firewalls by using personal devices and accounts for AI image generation tools like Midjourney, spending hundreds monthly without reimbursement, while her boss demands faster, more numerous revisions. The pressure creates workplace anxiety and suspicion. Programmer Li Huahua, after a friend's experience of raised KPIs following AI success, fears being branded a "traitor" for using it yet worries about falling behind if she doesn't. The dynamic allows management to demand results without understanding the tools or covering expenses, treating employees like AI "agents." While some, like entrepreneur Jin Tu, find high value in paid AI, building entire systems and winning competitions, for most, it's a trap. Free tools like Kimi and Doubao are introducing fees, closing off alternatives. The initial efficiency gains individual advantage, but as AI becomes ubiquitous, the personal edge disappears, workloads increase, and a cycle of dependency begins. Workers like Long Shen realize they cannot maintain AI-generated code without AI, making stopping harder than continuing to pay. The tool promising liberation is instead becoming a compulsory, costly chain in the modern workplace.

marsbitHá 1h

The Waged Worker Driven to Poverty by AI Subscriptions

marsbitHá 1h

Trading

Spot
Futuros
活动图片