On this Friday the 13th, I didn’t have to try hard to come up with a scary story for you.

It all started a little over a week ago, in the early days of 2026. The financial landscape, particularly across public and private technology markets, seemed to hum with its usual, predictable rhythm. Investors and analysts alike were fixated on the familiar, if peculiar, narratives of the digital age. Conversations frequently revolved around Moltbook, that bizarre, AI-driven social network that had somehow permeated every aspect of public discourse, its algorithms so ancient and deeply embedded they felt like digital bedrock. It was a platform that, despite its quirks and controversies, represented a perceived stability in the tech ecosystem. Then, without much fanfare, a new wave of advancements in enterprise AI agents, spearheaded by models like Claude, began to roll out. Initially, the market shrugged. Model updates and improvements were, after all, a constant in this accelerated era; they seemed just another iteration in an ongoing technological evolution. Yet, beneath the surface, a tectonic shift was brewing.

Public market investors, seasoned by cycles of hype and reality, started to process these seemingly innocuous updates with a growing sense of unease. They began to question the very foundations upon which the sprawling, multi-trillion-dollar software-as-a-service (SaaS) industry had been meticulously constructed. For years, concerns had simmered, particularly around the specious logic of applying traditional SaaS metrics – like Annual Recurring Revenue (ARR), Customer Lifetime Value (CLTV), and churn rates – to the nascent, fundamentally different business models of AI-native companies. Critics argued that AI companies, with their usage-based pricing, high compute costs, and rapid feature commoditization, simply couldn’t be evaluated through the same lens as a subscription-based software vendor. This disconnect had created a fragile illusion of continuity, one that the new AI agent breakthroughs were now threatening to shatter.

Then, a relentless selloff materialized, swiftly and brutally. As of market close yesterday, over the last five days, the market witnessed a staggering decline in some of the industry’s most venerable SaaS giants. Salesforce, a titan of cloud computing, found itself down more than 3%. Adobe, synonymous with creative software, shed 3% of its value. Docusign, a linchpin for digital agreements, plummeted 5.5%. And Workday, a leader in human capital management, experienced a precipitous drop of more than 10%. (These numbers, it’s worth noting, already included a modest recovery from their lowest points, underscoring the severity of the initial plunge.) These companies were among the hardest hit in what analysts and industry insiders quickly dubbed the "SaaSpocalypse"—a term that, with its apocalyptic overtones, captured the sudden and profound dread gripping the market.

The implications of this public market tremor quickly reverberated through the private markets, sending shivers down the spines of venture capitalists and startup founders alike. The answer to how this applied to startups was starkly simple: it exposed an open secret. After a year of whispered chatter in Silicon Valley boardrooms and venture firm offices, the industry still had no real playbook for making money in enterprise AI. The fundamental certainties of the SaaS era – predictable recurring revenue, sticky customer bases, high switching costs, and the defensibility of proprietary code – were vanishing. They evaporated like Jason (seems to) at the end of the first Friday the 13th movie, leaving behind only chilling questions.

"The software slump is proving that code alone was never a real moat," asserted Zach Lloyd, CEO and founder of the burgeoning AI agent startup Warp, in a recent email. His statement cuts to the core of the crisis. "For VCs and founders, this changes everything: you can’t bet on execution anymore when the cost of building software is going to zero." Lloyd elaborated on the paradigm shift: "The question is now ‘what’s stopping someone from copying this next week,’ and if your only answer is ‘we have good engineers,’ you’re in trouble." This sentiment highlights a critical vulnerability: if advanced AI agents can automate much of what traditional SaaS products do, often with greater efficiency and lower cost, then the competitive advantage shifts dramatically. Proprietary algorithms and large language models (LLMs) developed by companies like Anthropic (the maker of Claude) are becoming the new infrastructure, making it easier for smaller teams to spin up highly capable, specialized AI applications that directly compete with established SaaS offerings, often at a fraction of the development cost. The barrier to entry, once defined by engineering prowess and extensive development cycles, is now being radically lowered.

While the immediate market reaction might appear somewhat overblown, the essential, long-term question remains, as noted by Daniel Docter of Dell Technologies Capital. "The highs are never as high as they really are, and the lows are never as low as they are," Docter told Fortune, offering a tempered perspective. "I think this is probably overdone a little bit in terms of this near-term reaction. But the longer-term question—the most important question—is, will AI displace a significant portion of SaaS software or SaaS revenue?" This isn’t merely an academic debate; the stakes are astronomical. That’s easily hundreds of billions, or even trillions in value, currently up in the air, its fate hanging precariously on the trajectory of AI. And what, after all, is scarier than profound, market-altering uncertainty?

The "SaaSpocalypse" narrative, while dramatic, reflects a genuine industry reckoning. For decades, the SaaS model thrived on the principle of accumulating features and functionalities, often leading to complex, monolithic platforms. Customers paid recurring subscriptions for access to these ever-expanding suites, often utilizing only a fraction of the available tools. AI agents, however, promise a different paradigm: intelligent automation that can perform complex tasks across multiple applications, often through natural language commands, without the need for manual navigation through disparate interfaces. Imagine an AI agent scheduling meetings, drafting reports, analyzing market data, and even generating code snippets across various enterprise systems – Salesforce, Workday, Adobe Creative Suite – all orchestrated by a single, intelligent assistant. This fundamentally undermines the value proposition of paying separate, hefty subscriptions for each individual tool.

The historical parallels are instructive. The shift from on-premise software to cloud-based SaaS, while disruptive for legacy players, ultimately created new giants. Similarly, the internet’s advent reshaped media, retail, and communication. What makes the AI shift uniquely terrifying for SaaS is its potential to not just change how software is delivered, but to fundamentally alter the need for human interaction with software interfaces themselves. The "moat" of a user interface, once a key differentiator, becomes less relevant when an AI agent can bypass it entirely.

In this new landscape, VCs and founders are scrambling to redefine "moats." Proprietary data, especially niche, high-quality datasets, is emerging as a critical differentiator. Companies that can leverage unique data to train highly specialized AI models will possess a significant advantage. Deep domain expertise, embedded within AI systems, is also becoming invaluable. Furthermore, the ability to build strong network effects around AI agents, where their utility grows with each user interaction and data point, could create new forms of defensibility. Investment strategies are shifting towards foundational AI infrastructure, highly specialized vertical AI agents that solve acute industry problems, and "human-in-the-loop" systems that augment rather than fully replace human decision-making. The ethical and regulatory landscape around AI is also a looming factor, with potential regulations on data privacy, algorithmic bias, and autonomous decision-making likely to shape market winners and losers.

As the industry grapples with these seismic shifts, capital continues to flow, albeit with a discernible preference for the architects of this new AI-driven future and resilient sectors.

VENTURE CAPITAL

Despite the SaaS tremors, the venture capital landscape saw significant activity, particularly in AI-related ventures, underscoring the market’s pivot towards new technologies:

• Anthropic, a San Francisco-based AI powerhouse and the developer behind the influential Claude AI assistant, commanded a staggering $30 billion in Series G funding. This massive round, attracting heavyweights like GIC, Coatue, D. E. Shaw Ventures, Dragoneer, Founders Fund, ICONIQ, and MGX, is a clear signal of intense investor confidence in foundational AI models and agents that are driving the current market disruption.
• Talkiatry, a New York City-based psychiatrist employer, secured $210 million in Series D funding. Perceptive Advisors led the round, joined by Sofina and existing investors, demonstrating continued robust investment in tech-enabled healthcare solutions.
• Simile, operating out of Palo Alto, Calif., and New York City, which develops an AI model designed to predict human behavior, raised $100 million in funding. Index Ventures led the round, with participation from Bain Capital Ventures and others, highlighting the growing interest in predictive AI analytics.
• Anterior, a New York City-based AI platform tailored for health plans, closed $40 million in funding. The round saw participation from prominent firms including NEA, Sequoia Capital, FPV, and Kinnevik, reflecting the ongoing digital transformation in healthcare administration.
• Ever, a San Francisco-based electric vehicle retailer, accelerated with $31 million in Series A funding. Eclipse led the round, joined by Lifeline Ventures, Ibex Investors, and others, signaling sustained growth in the EV ecosystem.
• Uptiq, a McKinney, Texas-based developer of an AI platform for financial services, raised $25 million in Series B funding. Curql led the round, with Silverton Partners, 645 Ventures, Broadridge, and Green Visor Capital also investing, pointing to the increasing adoption of AI in fintech.
• OPAQUE, a San Francisco-based platform dedicated to ensuring privacy and compliance in AI systems, secured $24 million in Series B funding. Walden Catalyst led this round, underscoring the critical importance of secure and ethical AI development.
• Somethings, a New York City-based digital mental health platform for teens and young adults, received $19.2 million in funding. Catalio Capital led, joined by General Catalyst and Tusk Venture Partners, reflecting continued investment in mental wellness technology.
• Electric Twin, a London, U.K.-based AI platform that builds synthetic audiences modeling human behavior, raised $14 million across two funding rounds. Investors included Atomico, LocalGlobe, Mercuri, and Samos Investments, showcasing innovation in AI for market research and simulation.
• Stanhope AI, a London, U.K.-based developer of AI models designed to mimic the human brain, raised $8 million in seed funding. Frontline Ventures led, with Paladin Capital Group and Auxxo Family Catalyst Fund participating, pointing to investment in foundational AI research.
• Santé, a New York City-based fintech platform for the wine and spirits industry, raised $7.6 million in funding. Bonfire Ventures led, joined by Operator Collective, Y Combinator, and Veridical Ventures, highlighting specialized fintech solutions.
• Bearing, an Indianapolis, Ind.-based physical security operations platform built on ServiceNow, secured $4.5 million in seed funding. AZ-VC led the round, with High Alpha, PHX Ventures, and Lightbank contributing, showing continued interest in enterprise software enhancements.
• Ando, a San Francisco-based developer of AI staffing and scheduling software for hourly workers, raised $4 million in seed funding. Slow Ventures led, joined by Blitzscaling Ventures, Zero Capital, Monochrome, and others, reflecting the application of AI to workforce management.
• Demoboost, a Warsaw, Poland-based product demonstration platform for software companies, raised €2.8 million ($3.3 million) in funding. Digital Ocean Ventures and RIO ASI led the round, joined by B-Value, indicating continued investment in sales enablement tools.

PRIVATE EQUITY

The private equity space saw substantial deals, emphasizing consolidation and strategic acquisitions:

• Nuveen agreed to acquire Schroders, a London, U.K.-based investment manager, for approximately £9.9 billion ($13.5 billion), signaling major movements in the asset management sector.
• Blackstone and EQT partnered to acquire Urbaser, a Madrid, Spain-based waste management company, from Platinum Equity for approximately $6.6 billion, a significant transaction in the environmental services industry.

IPOS

In public markets, a notable energy offering provided a counterpoint to the tech sector’s volatility:

• ARKO Petroleum, a Richmond, Va.-based energy distributor, successfully raised $200 million in an offering of 11.1 million shares priced at $18 on the Nasdaq, indicating investor appetite in diverse sectors.

FUNDS + FUNDS OF FUNDS

Investment firms continued to raise significant capital for future deployment:

• Union Capital Associates, a Greenwich, Conn.-based private equity firm, closed $450 million for its fourth fund, targeting founder-led businesses, showcasing ongoing confidence in the growth equity segment.

We’re off for the long weekend! See you Tuesday,

Allie Garfinkle
X: @agarfinks
Email: [email protected]
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