A Karaoke Company Just Crashed Global Logistics. The Real Damage Comes Next.

The $6 Million Wrecking Ball

On Thursday, February 12th 2026, a company called Algorithm Holdings issued a press release claiming its logistics platform could help customers scale freight volumes by 300–400% without adding headcount. Within hours, CH Robinson Worldwide — one of the largest freight brokerages on the planet — plunged 24%. The Russell 3000 trucking index had its worst day since Liberation Day. Billions in market capitalisation evaporated from Dallas to Denmark.

Algorithm Holdings has a market cap of $6 million. It reported less than $2 million in quarterly revenue and a net loss of nearly $3 million. Until 2024, this company was called The Singing Machine Company. It sold karaoke products.

A former karaoke company worth $6 million at best just wiped billions of dollars off an entire sector of the global economy. And the part that should concern you is not the absurdity. It's that this is now the fifth time in ten days, each time in a different industry, each time triggered by a different AI announcement, each time following the exact same pattern.

The pattern is the story. And the pattern has consequences that go far beyond stock prices.

Five Dominoes in Ten Days

Let's follow the sequence, because the chain reaction matters.

On February 2nd, Palantir reported quarterly earnings that obliterated expectations — 70% revenue growth, with 61% forward guidance for fiscal 2026. CEO Alex Karp claimed Palantir's tools could compress complex SAP enterprise migrations from years of work to as little as two weeks. The stock jumped 8% after hours. The market heard the subtext: if one company can do that, every company selling enterprise software on a per-seat basis needs repricing.

The next day, Anthropic released co-work plugins for legal workflows — contract review, compliance, legal summaries. Within 48 hours, roughly $285 billion in market cap vanished from SaaS, legal tech, and data analytics stocks. The Jefferies equity trading desk gave the bloodbath a name: the SaaSocalypse.

That was just week one. Then the contagion jumped.

Private credit and alternative asset managers — Ares, KKR, TPG, Apollo, Blackstone — fell 8–10% on fears AI could analyse deals and manage portfolios. Insurance brokers got hammered after Insurify released an AI rate comparison tool; the S&P 500 insurance index posted its worst session since October. Wealth management followed the day after — Raymond James fell 8.8%, Schwab dropped 7.4% — triggered by a startup called Altruist launching an AI tax planning tool.

Real estate services came next. CBRE and Jones Lang LaSalle each fell 12%. Cushman & Wakefield dropped 14% — its worst single-day decline since the COVID crash. Then office REITs started bleeding on the theory that AI would reduce headcount → reduce office demand → reduce rent.

And then the karaoke company came for logistics.

Eight different sectors in ten days. Each sell-off triggered by a different company with a different product announcement. But the market reaction was identical every time: dump first, analyse later.

Wall Street's Autoimmune Disorder

Favuza, the Jefferies trader who coined "SaaSocalypse," described the dynamic in a note to clients: "For every corner of the market right now, there is an aggressive shoot-first-ask-questions-later for any area where there's an AI headline."

He's right. But what he's describing isn't a market efficiently pricing disruption. It's something more interesting and far more dangerous.

Wall Street has developed an autoimmune disorder. The immune system — risk repricing — is attacking healthy tissue because it can no longer distinguish between what's real and what's not. And just like an autoimmune disorder, the damage caused by the immune response is now much worse than the disease it's reacting to.

This matters because a stock drop doesn't just reflect reality. It creates reality. This is the reflexivity that almost nobody in the financial press is unpacking with any rigour.

When CH Robinson drops 24% in a day, that isn't just a number on a screen for the 15,000 people who work there. That is:

• A board meeting next week

• A hiring freeze announced next month

• The Q2 roadmap getting torn apart and rewritten around "AI strategy" — whether or not the company has a coherent one

• The CFO pulling forward cost cuts to demonstrate to investors that management "takes this transition seriously"

A company whose stock craters on AI fears is going to start behaving as if AI is an existential threat. Even if the actual technology is years away from threatening its core business, defensive postures get adopted immediately. Innovation budgets get redirected from organic growth to performative AI partnerships. Headcount plans get revised downward — not because AI replaced anybody, but because the market priced in the expectation that it would.

Goldman Sachs CEO David Solomon said Tuesday that the sell-off was "too broad." JP Morgan strategists see potential for a software rebound based on "an overly bearish outlook on AI disruption." They're probably right.

But the correction, if it comes, will not undo the organisational decisions made during the panic.

The hiring freeze will be real. The roadmap pivot will be real. The budget reallocation will be real. The stock market may recover in a fortnight. The strategic damage will take months or years to unwind. And in the meantime, there's actual real AI disruption that these companies need to respond to on a business timescale, not a market timescale. Those are two very different timescales.

Three Categories of AI Exposure (Priced Identically)

The scare trade is treating every industry identically. That is the error. There are at least three distinct categories of AI exposure, and the market is pricing every single one of them the same way.

Category 1: AI is genuinely displacing labour today. Software development is the clearest example. Cursor, the AI coding editor, hit $300 million in annualised revenue faster than almost any software product in history — and is well past $500 million now. Per-seat pricing is in genuine trouble. SaaS companies whose models depend on selling seats to humans need to adapt or get repriced. The market is right about them — though not necessarily about the speed.

Category 2: AI will matter in three to five years, but current panic vastly overstates near-term risk. Wealth management is the textbook case. An AI tool that does tax planning cannot replace a wealth adviser any more than TurboTax replaced accountants. The value isn't in calculations — it's in the relationship, the trust, the behavioural coaching that keeps clients from panic-selling during a downturn. The irony of wealth management clients panic-selling their wealth management stocks because of AI fears is almost too perfect. These sectors will change, but not by earnings season.

Category 3: The market has lost the plot entirely. A former karaoke company's press release about freight optimisation does not invalidate CH Robinson's relationships with 100,000 shippers and carriers, its proprietary data on freight lanes and pricing, or its ability to handle the physical, regulatory, and contractual complexity of moving goods across borders. As Cowen analyst Ariel Rosa put it: "I would probably be more inclined to be sceptical that this particular company is going to be the one to disrupt the industry." Understatement of the decade.

The investment implication is stark. The market is creating a generational buying opportunity in some sectors while correctly repricing others. The skill is knowing which is which.

The Self-Fulfilling Prophecy Machine

Here's where the reflexivity becomes genuinely dangerous.

The companies that respond to a 15% stock drop by gutting their product teams and signing a splashy AI partnership are the ones that will get actually disrupted in three years. Not by a karaoke company. But by a competitor that used this moment to invest in genuine AI capability rather than investor optics.

Think about what happens in the next 90 days inside a company whose stock just got clipped 12% on AI fears:

• The CEO calls an emergency leadership meeting

• The board demands an "AI strategy"

• The chief strategy officer assembles a task force

• Fear drives the timeline

There are now two paths. Path A: the company invests incrementally in AI on top of existing capabilities — testing, learning, building institutional knowledge about what the technology can actually do in their specific domain. Path B: the company announces a partnership with an AI vendor, cuts some headcount to show "seriousness," gets a press release and a logo on a slide deck, and prays the stock recovers.

Path A is a strategy. Path B is a press release that will haunt them.

12 months from now, the gap between builders and buyers will be catastrophically visible. AI compounds for people who use it deliberately. The companies buying vendor partnerships and praying get a slide deck. The companies building genuine capability get a compounding advantage that widens every quarter as models improve.

What This Means for Ecommerce

If you're reading this on adaptordie.io, you're probably in ecommerce. So let's make this concrete.

The scare trade hasn't hit ecommerce directly — yet. But the pattern is unmistakable. Every sector built on predictable human work is getting repriced. That includes agencies selling implementation hours, consultancies billing for migration projects, and platform specialists whose value proposition rests on complexity that AI is actively simplifying.

The question isn't whether the scare trade comes for your sector. It's whether your organisation will be a Path A or Path B company when it does.

Path B ecommerce companies are already identifiable. They're the ones announcing "AI-powered" features that are thin wrappers around GPT, cutting their technical teams to fund the marketing budget for those announcements, and hoping nobody looks under the bonnet. They announce partnerships with AI vendors at conferences. They produce case studies with impressive-sounding metrics that dissolve under scrutiny. They treat AI as a marketing narrative rather than a capability investment.

Path A ecommerce companies are doing something harder and less photogenic: actually testing AI against real workflows, documenting where it works and where it breaks, building genuine capability in specific domains like product discovery, personalisation, inventory forecasting, and customer service automation. They're keeping the humans who understand why the standard approach won't work for this particular client. They're running parallel processes — AI and human side by side — tracking accuracy rates, failure modes, and edge cases with real data.

The difference between these two approaches isn't visible in a quarterly earnings call. It's visible 18 months later, when Path A companies have compounding institutional knowledge about what AI does well in their specific domain, and Path B companies have a pile of expired vendor contracts and a gutted technical team that can't execute the next phase of integration.

The scare trade is a sorting mechanism. It separates the companies building real AI capability from the ones performing it for investors. And sorting mechanisms, once activated, compound.

The Capital Reallocation Underneath

There's a capital story here that most people in ecommerce aren't paying attention to.

Public SaaS multiples are crashing — the S&P software index is down roughly 20% year to date. Meanwhile, privately held AI companies continue ascending to valuations that would have been unthinkable 12 months ago. OpenAI, Anthropic, and xAI collectively sit at well over a trillion dollars in private valuation. Anthropic raised another $3.5 billion at a $61.5 billion valuation just this past week. OpenAI is likely to IPO at — conservatively — a trillion-dollar valuation later this year.

This feedback loop is self-reinforcing and vicious. Public SaaS valuations crater → private SaaS valuations compress in sympathy → AI startups look relatively more attractive → more capital flows to AI → SaaS gets starved further.

If you stick "AI" in the company name, magical things happen right now. It's not fair. It's not correct. But capital allocation rarely is, especially when we're staring at a chance to reshape the fundamental technology infrastructure in a way we haven't seen since the advent of computing.

Wellington Management noted that the median time to IPO for companies valued above half a billion dollars has stretched to 11 years — the longest in a decade. The scare trade makes that number worse. For SaaS founders who were planning 2026 IPOs, the window has shifted or evaporated entirely. Not because their companies got worse, but because the market's appetite for anything that looks like traditional software has collapsed.

The knock-on effects cascade. Employees at pre-IPO SaaS companies watching their equity value compress. Investors marking down portfolios and tightening deployment criteria for anything without "AI" in the pitch deck. Service businesses that sell into SaaS companies seeing pipeline evaporate as their customers enter austerity mode. The capital reallocation underneath the scare trade is restructuring entire ecosystems — not just repricing individual companies, but redirecting the flow of money, talent, and attention across the technology economy.

For ecommerce specifically, the capital story matters because Shopify's ecosystem sits squarely in the crosshairs. App developers, agencies, consultancies — all of these businesses depend on a healthy SaaS funding environment for their customers. When that environment contracts, the entire supply chain feels it.

The Stock Drop Creates the Reality It Fears

This is the mechanism that almost nobody in the financial press is articulating clearly.

The scare trade is becoming a self-fulfilling prophecy. Not because AI is doing the disrupting, but because the market reaction to AI is forcing companies into a defensive crouch that makes them more vulnerable to real disruption — ironically, from AI itself.

Companies that gut their product teams in response to a stock drop lose the institutional knowledge needed to integrate AI effectively. Companies that redirect innovation budgets to performative partnerships miss the genuine capability-building window. Companies that freeze hiring lose the talent pipeline they'll desperately need 18 months from now when the models are better and the integration work gets harder, not easier.

The mechanism is precise and vicious. Stock drops generate board-level urgency. Board urgency demands visible action. Visible action means cutting costs and announcing partnerships — not the slow, unglamorous work of testing AI against real workflows and building genuine capability. So the visible response to AI disruption fears is the exact opposite of what would protect against actual AI disruption.

Goldman's David Solomon was right that the sell-off was "too broad." But breadth isn't the real problem. The real problem is that every company touched by the scare trade — even the ones the market will eventually reprice upward — is making irreversible organisational decisions during a window of maximum fear and minimum understanding.

Those decisions won't reverse when the stock recovers. The hiring freeze persists. The roadmap pivot sticks. The institutional knowledge that walked out the door doesn't walk back in. And the competitor that used the same 90-day window to build genuine AI capability instead of performing it for Wall Street will have a head start that compounds every quarter.

The disruption is real. The timeline the market is pricing in is delusional. And the gap between those two facts is where fortunes will be made and lost — not just on trading floors, but in the operational decisions being made right now in boardrooms across every sector the scare trade has touched.

Somehow, an AI karaoke company helped kick off all of it.