What Kills SaaS Isn't AI, It's Agent

marsbitPublicado em 2026-02-06Última atualização em 2026-02-06

Resumo

The article argues that AI agents, not AI itself, are disrupting the SaaS industry. The recent market reaction to Anthropic's Claude Cowork plugin release, which erased $285 billion in software market value in 24 hours, highlights this shift. The core thesis is that the traditional SaaS model—building a "nice UI + integrations + per-seat pricing" on top of shallow moats—is dying. AI agents that can autonomously execute workflows within existing systems (CRMs, databases) are making the intermediate UI layer obsolete. This creates a "Thin Middle Squeeze": value is moving upward to the AI agent execution layer and downward to the foundational data layer (record systems), while the middle layer (traditional SaaS UI) is being crushed. However, the author clarifies that software market spending is not decreasing but shifting. New opportunities lie in: AI platform subscriptions with usage-based pricing, owning proprietary data in record systems, building infrastructure for AI security/governance, adopting outcome-based pricing models, and providing implementation services. The conclusion is that the era of "easy SaaS" with per-seat pricing is over, but immense opportunities remain for those building in the agent, data, or infrastructure layers.

Author: David Ondrej

Compiled by: Deep Tide TechFlow

Introduction: Last Monday, Anthropic released a suite of plugins for Claude Cowork. Not a new model, not a chatbot upgrade, but plugins. Within 24 hours, the software stock market lost $2.85 trillion in market value. A plugin market announcement wiped out more wealth in a single day than most industries produce in a year. Wall Street is no longer afraid of AI; they are afraid of what AI replaces.

David Ondrej points out that what is dying is a very specific type of software business—SaaS built on the weak moat of "beautiful UI + integration + per-seat pricing." When AI agents can directly complete tasks within existing systems, you don't need 15 different SaaS tools with beautiful dashboards. Value is being sucked upward into the agent layer and downward into the data layer. Everything in the middle is being squeezed.

Full text below:

Last Monday, Anthropic released a suite of plugins for Claude Cowork.

Not a new model, not a chatbot upgrade, but plugins.

Within 24 hours, the software stock market lost $2.85 trillion in market value.

A plugin market announcement wiped out more wealth in a single day than most industries produce in a year.

Wall Street is no longer afraid of AI.

They are afraid of what AI replaces.

II

Here’s where most people get it wrong.

They hear "SaaS is dead" and think it means companies will stop buying software.

That’s not it at all. Not even close.

What’s dying is a very specific type of software business—and if you understand which type, you’re looking at the biggest startup opportunity in a decade.

Let me explain:

III

Over the past 15 years, the SaaS playbook was simple:

Find a common business workflow. Build a beautiful UI around it. Add some integrations. Charge per seat, per month. Defend your position with switching costs and minor product tweaks.

This playbook created hundreds of billionaires.

But it has a fatal flaw that no one talks about.

Most of the value was never in the software itself. It was in the workflow the software organized.

The UI was the middleman.

And AI just made the middleman obsolete.

IV

Here’s what Anthropic actually did—because the headlines missed the point.

They didn’t build a better chatbot. They turned Claude into a work execution layer.

Cowork plugins allow AI agents to log into your existing tools—your CRM, your documents, your databases—and autonomously execute entire workflows. Legal audits, sales pipeline management, data analysis, production-level code, and more.

No human involvement required. This is the part that spooked the market.

Because if AI agents can do the work directly within your existing systems—why do you need 15 different SaaS tools with beautiful dashboards?

Here’s the part that should really keep SaaS founders up at night:

If 10 AI agents can do the work of 100 employees, you no longer need 100 Salesforce seats.

AI doesn’t kill software directly. It kills the number of employees using the software. That kills the per-seat revenue model. That kills the business.

V

This is what I call the "Thin Middle Squeeze."

Imagine three layers:

Top Layer—AI agents. The things that actually perform the work.

Middle Layer—SaaS UI. Dashboards, workflows, the buttons you click.

Bottom Layer—Systems of record. Databases, CRMs, and ERPs that store the real data.

Now, value is being sucked upward into the agent layer and downward into the data layer.

Everything in the thin middle is getting crushed.

This is why Adobe’s forward P/E dropped from 30 to 12. ServiceNow from 67 to 28. Not because people don’t need what they do—but because investors realized that when AI agents can completely bypass the UI, the moat around "beautiful UI + integrations" is paper-thin.

The interface used to be the product, but now it’s just a shell.

VI

But here’s where those saying "SaaS is dead" are completely wrong.

SaaS isn’t dead; the era of easy SaaS moats is dead.

That’s a huge difference.

Companies will spend more on software this year than ever before. Enterprise AI capex alone will exceed $470 billion by 2026. This isn’t a shrinking market—it’s a market exploding in size.

The money isn’t disappearing; it’s moving.

Most people are so busy panicking that they completely miss where it’s landing.

VII

Here’s where the money is actually going:

  • AI Platform Subscriptions

Usage-based. Consumption-based. Not per seat. Companies will pay for AI capacity like they pay for cloud computing—based on what they use, not how many people sit in the building. This is already happening. GitHub’s AI agent is gated behind a premium tier with usage-based pricing. That’s the template.

  • Systems of Record

Agents don’t eliminate the backend; they operate the backend. CRMs, ERPs, data warehouses—these become more valuable, not less. Because AI agents need clean, authoritative, trustworthy data to act. Garbage data in, garbage actions out. Companies with large-scale, proprietary data will win.

  • Security, Governance, and Compliance

When agents act at scale, mistakes happen at scale. Every company deploying AI agents will pay for permissions, audit logs, policy enforcement, monitoring, and evaluation. It’s boring infrastructure—and it will print money quietly for the next decade.

  • Outcome-Based Pricing

No more "$99 per seat per month." You’ll see "$5 per contract reviewed." "$2 per support ticket resolved." "$10 per enriched qualified lead." Software priced like labor—because it’s replacing labor. This is where the entire industry’s pricing model shifts.

  • Services

This one surprises people. But when building software becomes cheap and easy, companies will experiment with more custom software services. Implementation, workflow design, migration, integration work—demand for services is about to explode. Vibe coding makes creation easy. Making it work in a real business is a whole different story.

VIII

So if you’re building a startup right now—or thinking about it—here’s the only question that matters:

Where are you in the stack?

If you’re building in the thin middle—putting a pretty UI on someone else’s data, charging per seat, with no proprietary edge—you have a serious problem. Not because your product is bad. But because the economics of your position are collapsing in real time.

The agent layer above you is eating your interface.

The system of record below you is eating your lock-in.

You’re being squeezed from both directions. And that squeeze only accelerates from here.

IX

Here’s what to build instead.

Build in the agent layer. Create AI-native tools that don’t just display information—they execute workflows. Don’t show users a dashboard. Do the work for them. Price based on outcomes, not seats. Be the thing that acts.

Build in the data layer. Own proprietary data. Build systems of record for areas that don’t yet have good systems. Make yourself the authoritative backend that every AI agent needs to plug into. Agents come and go—the data layer is eternal.

Build infrastructure. Security. Monitoring. Evaluation. Governance. Compliance. Tools that enable safe deployment of AI agents at scale. Not sexy. Extremely profitable. Demand hasn’t even begun yet.

Build services. Help companies implement, customize, and operate AI systems in their actual businesses. This is where most of the real-world complexity lives, and where massive value will be created over the next 5 years.

X

Here’s the irony no one is talking about.

Anthropic’s Cowork—the product that supposedly kills SaaS—is itself a SaaS product, sold via subscription to organizations over the internet.

SaaS as a delivery model is fine. It’s always been fine.

SaaS as a business strategy built on shallow moats and commoditized workflows priced per seat—that’s over.

Conclusion

Everyone looks at this $2.85 trillion loss and sees destruction.

But I see transfer.

That value didn’t disappear. It’s moving—from companies that captured value by being the middleman between humans and their tools, to companies that capture value through execution, data, and infrastructure.

The old playbook was: Build workflow UI, charge per seat, grow revenue by increasing your customer’s headcount.

The new playbook is: Build something that owns data, executes outcomes, or secures systems. Price based on value delivered, not butts in seats.

If you’re a founder reading this, the worst thing you can do is panic.

The second worst thing is to keep building like it’s 2019.

The best thing you can do is understand where the value is moving—and stand where it lands.

The SaaS era isn’t over.

The easy SaaS era is over.

And honestly, for anyone actually building real things, this is the best news in a decade.

Perguntas relacionadas

QWhat is the immediate financial impact of Anthropic's Claude Cowork plugin announcement on the software market?

AWithin 24 hours of the announcement, software stocks lost $285 billion in market value.

QAccording to the author, what specific type of SaaS business model is dying?

AThe specific type of SaaS business model that is dying is the one built on the thin moat of 'pretty UI + integrations + per-seat pricing'.

QWhat is the 'Thin Middle Squeeze' phenomenon described in the article?

AThe 'Thin Middle Squeeze' is the phenomenon where value is being sucked upwards into the AI agent layer and downwards into the data layer, crushing everything in the thin middle layer of SaaS UI and dashboards.

QWhat are the new areas where money is flowing, as opposed to traditional per-seat SaaS?

AMoney is flowing towards AI platform subscriptions (usage-based), systems of record, security/governance/compliance tools, outcome-based pricing models, and services for implementation and customization.

QWhat is the fundamental shift in the new 'playbook' for building software companies, as opposed to the old one?

AThe new playbook is to build things that own data, execute outcomes, or secure systems, and to price based on the value delivered, not on the number of seats (per-seat pricing).

Leituras Relacionadas

STAR 50 Soars 10.73%, Why Did A-Shares Stage a "V-Shaped Reversal"?

After a prolonged decline, the Chinese A-share market staged a strong rally on July 21. The STAR 50 index surged 10.73%, its largest single-day gain in nearly a year, leading a broad-based "V-shaped" reversal. The Shanghai Composite Index rose 1.79%, the Shenzhen Component Index gained 4.81%, and the ChiNext Index jumped 7.05%. Total market turnover reached 2.97 trillion yuan, an increase of 256.1 billion yuan from the previous session, with over 3,100 stocks advancing. The semiconductor sector spearheaded the rebound, with related ETFs posting significant gains. Analysts attribute the surge to three converging factors. First, coordinated capital inflows from "national team" institutions, insurance funds, listed company buybacks, and fund house self-purchases have bolstered market liquidity and confidence. Second, supportive policy signals, including commitments from regulators to ensure stable market operations, provided a favorable backdrop. Third, a stabilization and recovery in overseas markets, notably South Korea, created a positive external environment. Institutions suggest the most severe panic selling phase for the tech sector has likely passed, following a significant digestion of crowded positions and leveraged funds. While short-term volatility may persist, the medium to long-term outlook remains underpinned by enduring trends like AI computing demand expansion and semiconductor localization. The market's focus now shifts to the sustainability of supportive fund flows, earnings reports, and upcoming catalysts from the global AI industry chain.

marsbitHá 36m

STAR 50 Soars 10.73%, Why Did A-Shares Stage a "V-Shaped Reversal"?

marsbitHá 36m

U.S. Tech Momentum Stocks Post Largest Single-Day Gain Ever, But Is the Plunge Over?

US tech momentum stocks staged a sharp rebound on Tuesday (July 21st). Morgan Stanley's TMT Momentum Factor surged over 12%, marking its largest single-day gain on record, exceeding even peaks from the 2000 dot-com bubble. Key momentum indices from Goldman Sachs also posted their strongest daily performances in years. The rally was led by semiconductors, with the Philadelphia Semiconductor Index jumping 4.6%. This rebound followed three consecutive down days and a cumulative 33% plunge in momentum stocks, one of the steepest drawdowns since the dot-com era. Analysts attribute the surge largely to a short squeeze. Heavy selling had pushed high-beta momentum stocks into deeply oversold territory, forcing many short sellers, particularly in Asia, to cover their positions, creating a self-reinforcing buying spiral. However, the rebound's internals appear weak. Trading volume was notably low, and advancing stocks still lagged decliners on the S&P 500, indicating a narrow, concentrated rally rather than broad market participation. Diverging views emerge on the outlook. BTIG warns the bounce has hit key resistance and recommends selling into strength, citing extreme volatility and historical parallels to past market tops. Conversely, Goldman Sachs and UBS believe the momentum unwind is nearing its end, suggesting it may be time to gradually add exposure, as positioning has been significantly reduced. They caution, however, that high volatility warrants a measured approach, potentially using defined-risk strategies. The upcoming earnings season, particularly reports from major tech firms like Alphabet, is seen as a critical test for the rally's sustainability. Simultaneously, bond markets flashed a warning, with yields rising partly due to spiking oil prices. Analysts note that if long-term Treasury yields break decisively higher, it could pose a significant headwind for equities, especially growth stocks.

marsbitHá 43m

U.S. Tech Momentum Stocks Post Largest Single-Day Gain Ever, But Is the Plunge Over?

marsbitHá 43m

U.S. Tech Momentum Stocks Record Largest Single-Day Gain Ever, but Has the Rout Ended?

U.S. tech momentum stocks staged a dramatic rebound on Tuesday, July 21st. Key momentum indices like the Morgan Stanley TMT Momentum Factor and Goldman Sachs' High Beta Momentum Long Index posted historic or near-historic single-day gains, fueled largely by semiconductor stocks. This sharp rally followed a severe three-day sell-off that saw momentum stocks plunge 33%, marking one of the steepest pullbacks since the dot-com bubble. Analysts attribute the bounce primarily to a short squeeze, as forced covering from over-leveraged traders, particularly in Asia, created a buying spiral. However, the rally's health is questioned due to weak market breadth—overall trading volume was low, and decliners outnumbered advancers in the S&P 500 despite the index's gain—suggesting a narrow, concentrated surge rather than broad recovery. Opinions on the sustainability diverge. BTIG strategists warn the rebound has hit key resistance levels, citing extreme volatility and historic stock dispersion as signs of an ongoing broader correction, and recommend selling into strength. Conversely, Goldman Sachs and UBS view the aggressive momentum unwinding as nearing its end, noting reduced positioning and a lack of new fundamental catalysts. They suggest the sell-off presents a selective opportunity to add exposure, albeit cautiously and gradually using defined-risk strategies. The immediate trajectory hinges on the ongoing earnings season, with market focus on Alphabet's capital expenditure guidance for AI investment clarity. Meanwhile, bond markets present a risk, with rising Treasury yields—potentially heading toward 5.5%—and widening credit spreads for mega-cap tech companies posing a threat to equity valuations. The combination of technical factors, earnings results, and macro conditions leaves the durability of the rebound in doubt.

链捕手Há 46m

U.S. Tech Momentum Stocks Record Largest Single-Day Gain Ever, but Has the Rout Ended?

链捕手Há 46m

Long-Divided Must Unite, Long-United Must Divide: When L1 Becomes Its Own Rollup, What Is Ethereum's Endgame?

"The Inevitable Cycle: When L1 Becomes Its Own Rollup – What is Ethereum's Endgame?" For years, the Ethereum community grappled with concerns that L2s were fragmenting the ecosystem and eroding L1's value. While L2s provided cheaper execution, they also splintered liquidity and the unified user experience of a single chain. This has prompted a fundamental reassessment of the relationship between L1 and L2. Ethereum's roadmap is evolving. The "Scale" initiative merges L1 and L2 expansion into a holistic framework. L1 itself is advancing with higher gas limits, statelessness, and zkEVM verification, no longer content to be just a low-throughput settlement layer. Consequently, the primary value proposition of L2s is shifting from merely providing cheap blockspace to offering L1 cannot easily provide: application-specific optimizations, privacy features, and flexible governance models. L2s are becoming a spectrum of execution environments with varying degrees of security inheritance from Ethereum. A critical challenge in this multi-chain future is interoperability. The vision is to make Ethereum "feel like one chain again." This relies on advancements in native account abstraction (like EIP-7702) and intent-based architectures (Open Intents Framework), where users declare desired outcomes, and solvers handle the complex cross-chain execution. Furthermore, shortening Ethereum's finality time from minutes to seconds is crucial, as it underpins trust between chains for bridges, stablecoins, and cross-chain applications. Perhaps the most provocative idea is that Ethereum L1 itself could become a form of "its own Rollup." As zkEVM and proof systems mature, high-performance nodes could execute transactions and generate validity proofs. Regular validators would then verify these proofs instead of re-executing all transactions. This blurs the traditional L1/L2 hierarchy, making "Rollup" more of a general execution-verification architecture. Native Rollup aims to integrate L2 validation more directly into the Ethereum protocol, allowing L2s to inherit L1's security more fully and move away from reliance on security councils. In the end, L2s are not destined to replace L1 or be made obsolete by it. The likely future is a unified system where diverse execution environments—each optimized for specific use cases like DeFi, gaming, or privacy—coexist. They will share a common foundation of security, liquidity, and verifiable state, seamlessly connected to restore a cohesive user experience. The next phase for Ethereum is not just about scaling through separation, but about intelligently reintegrating what was separated back into a coherent whole.

链捕手Há 1h

Long-Divided Must Unite, Long-United Must Divide: When L1 Becomes Its Own Rollup, What Is Ethereum's Endgame?

链捕手Há 1h

Trading

Spot
活动图片