Let me start with some background: I mainly focus on small- and mid-cap growth stocks, occasionally dabbling in options. Over the past two years, I made good money riding the AI wave, but since February this year, my account curve has looked even uglier than the Nasdaq. It’s not that my stock-picking skills suddenly deteriorated—it’s that the market’s underlying logic has changed, while I was still using an old map.
The last two months of trading have taught me three painful lessons: AI’s “efficiency curse,” the “TACO rule” for oil prices, and a little-known stock called MAAS. This isn’t a research report—just a casual chat about what I’ve learned from three months of losses.
1. AI’s “Efficiency Curse”: Why I’m Moving Away from Pure-Play Software Stocks
Let me start with a lesson that cost me 15%.
At the end of January 2026, ServiceNow, a leader in IT service management, reported what looked like a stellar quarter. Q4 revenue hit $3.57 billion, up 20.5% year-over-year, beating expectations of $3.53 billion; non-GAAP EPS was $0.92, also above the $0.87 estimate. The CEO touted the company’s AI platform, Now Assist, which doubled its annual contract value (ACV) to over $600 million. The AI story was compelling.
Yet the next morning, ServiceNow’s stock plunged nearly 10% to a 52-week low.
Why? Because the market no longer cares what you’ve already achieved—it only cares about what you can do next. ServiceNow guided for 18.5%–19% organic subscription revenue growth in 2026. In any normal year, that would be excellent. But at the time, ServiceNow traded at 79 times earnings—a valuation that had already priced in “AI-driven high growth.” And 18.5% growth wasn’t enough to support a 79x multiple.
That’s when I realized something I had overlooked: AI is fundamentally an “efficiency amplifier.” When everyone uses AI, your differentiation disappears. Writing one high-quality article a day used to be productive; now writing five a day is just meeting the baseline. This is Jevons’ paradox playing out in the business world: higher efficiency leads to more competition, squeezing profits.
Worse, ServiceNow’s crash triggered a chain reaction. Salesforce fell over 6% in a day, Adobe dropped nearly 4%, and the entire SaaS sector got dragged down. The market was sending a clear signal: investors are no longer willing to pay an infinite premium for “AI stories.” They want real cash flow generated by AI.
So now I’m cautious about pure-play AI software companies. They face three pressures:
Clients are also using AI, eroding service premiums.
Giants (Microsoft, Google) keep bundling AI features into their basic packages, making life hard for independent SaaS.
Massive capital expenditures lead to negative free cash flow.
I’ve started looking for assets that are immune to internal competition, positioned in the physical world, and have inelastic demand. In other words, I don’t want to buy companies that “help others become more efficient”—I want to buy the physical infrastructure that others must use to become efficient.
That’s how I first noticed MAAS—a company making mobile charging robots. At first glance, its business model seemed “clunky”: selling hardware, collecting service fees, building a charging network. But upon reflection, that clunkiness is exactly its moat. You can’t bypass the physical world with AI. Electricity must travel from point A to point B. Charging cables must be plugged into cars. Energy storage cabinets must occupy physical space. These “dirty, hard tasks” cannot be disrupted by software.
2. The TACO Rule: How I Use Oil Prices to Guide Position Sizing
The best decision I’ve made in the past two months wasn’t picking a stock—it was adjusting my overall exposure based on oil prices.
In early March, I noticed a strange pattern: every time WTI crude approached $100 per barrel, the market would bounce. Conversely, when oil prices fell, the index kept dropping. And the catalyst for the bounce was almost never an improvement in fundamentals—it was Trump suddenly “TACO-ing” (Trump Always Chickens Out) on social media, releasing dovish statements like “We don’t want a war” or “Iran can negotiate.”
At first, I thought it was coincidence. But after three consecutive occurrences, I back-tested and found a clear pattern:
Oil < $95: Trump turns hawkish, threatens Iran, index tops and falls → reduce or short.
$95–$98: Iran retaliates, index accelerates downward → stay short or watch.
$98–$100: Trump starts TACO-ing, index stabilizes → DCA long.
> $100: Aggressive TACO-ing, index rallies violently → go heavy long.
< $98: Pause, index chops and tops → take profits.
< $95: A new cycle begins → repeat step one.
Why is $100 so important? Because $100 oil ≈ $4/gallon gasoline, the psychological threshold for U.S. domestic politics. Above that line, voter discontent rises, inflation worsens, and stocks come under pressure. Trump may not care about many things, but he cares deeply about oil prices—because they directly affect his votes.
So now, I check two things daily: WTI oil prices and Trump’s Truth Social account. Whenever oil is in the $98–$100 range and he starts TACO-ing, I add positions. When oil falls below $95 and he turns hawkish, I reduce exposure.
This strategy helped me avoid the sharp sell-off in late March. I didn’t make big money, but I didn’t lose either.
Which raises the question: In this macro-chaotic environment, what kind of stocks are worth holding during rebounds?
My criteria are simple: immune to geopolitical noise, backed by physical assets, generating stable cash flow, and ideally benefiting from AI tailwinds. That’s why I eventually dug deeper into MAAS.
3. MAAS: A Mispriced “Physical Bottleneck” Asset
To be clear: I’m not recommending this stock, just sharing my own trading logic. Currently, MAAS is a “watch position” in my portfolio—less than 5%, but I’m gradually adding.
Technicals: A classic “bottom volume + breakout” pattern
Price range: Over the past three months, MAAS has oscillated between $5.4 and $6.4, forming a clear box. It closed at $5.90 on April 2.
Volume: After the March 30 announcement of acquiring Huazhi Future, volume surged for two consecutive days, jumping from ~10k shares to ~100k–200k shares per day. That’s a classic “news-driven + institutional money entering” signal.
Moving averages: The 10-day MA crossed above the 20-day MA, forming a “golden cross”—a short-term buy signal I personally value.
MACD: Currently below zero but forming a bullish crossover, with histogram turning positive. Likely to push above zero soon, suggesting more upside.
Support/resistance: First support at $5.4 (box bottom), second at $4.7 (previous platform). Resistance above at $6.4; if broken, next target is $6.95 (January 2026 high).
My trading plan: Accumulate in the $5.4–$5.9 range, stop-loss below $4.7, first target $6.4, second target $7.
Fundamentals: Why I think it’s mispriced
The market currently values MAAS as a “charging equipment manufacturer,” with a P/S of only 2–3x (based on 2026 expected revenue). But I believe its true identity is an “AI energy infrastructure platform,” where comparable companies trade at 10–20x P/S.
Three layers of logic:
Layer 1: It addresses the physical bottleneck of AI-powered energy replenishment—where fixed charging stations can never reach.
You might think a charging robot is just a small cart with a battery. Wrong. Its soul is AI.
A real pain point: In China, on average, 7.5 vehicles compete for one public charging pile. Old residential communities lack the electrical capacity to install piles; shopping mall charging spots are often ICEd; highway service areas see hours-long queues during holidays. These problems cannot be solved by software—you can’t increase grid capacity with code, nor can you magically remove parked cars with an algorithm.
But MAAS’s Xiaoli robot uses AI to solve these physical problems. Its “body” is a mobile charging device, but its “brain” is AI. It’s not hardware—it’s an AI application running in the physical world.
I classify it as a “physical bottleneck” asset because the job it does—moving electricity from where it exists to where it’s needed—is a physical necessity that AI cannot bypass. Yet the way it does that job is entirely AI-driven. This “hardware + software” integration creates a much deeper moat than pure software, because competitors cannot simply write code to replicate it.
Layer 2: Its business model is a three-stage rocket: “assets + service + network.”
Asset layer: Selling robots, one-time revenue. The foundation, but not exciting.
Service layer: Taking a cut from mobile charging transactions. Recurring revenue. The growth engine.
Network layer: Aggregating robots to participate in virtual power plants, capturing peak-valley price spreads and grid subsidies. The wild card.
I’m especially interested in the third layer. When thousands of robots are aggregated into a giant “battery pool” in the cloud, they can participate in grid frequency regulation, demand response, and even spot electricity markets. This isn’t a concept—it has been validated through cooperation cases with Shandong Expressway and Sinopec.
Layer 3: It has tangible assets as a safety net.
MAAS holds Zhongsen (111 acres of wild ginseng forest, 19,000 wild ginseng plants over 40 years old) and Kelai Kang (annual production capacity of 10 tons of bird’s nest peptide, over 50% global market share). These assets appreciate 15%–35% annually, independent of AI hype and immune to geopolitical risks.
In today’s environment of TACO whipsaws and oil volatility, this kind of “visible and tangible” asset is something I’m willing to hold—because at least it won’t go to zero overnight like some software stocks.
Catalyst: The acquisition of Huazhi Future completes the “AI brain”
On March 30, MAAS completed the acquisition of 100% of Huazhi Future. Huazhi has its own proprietary large language model (“Lingyan Miaoyu,” 7 billion parameters, registered with China’s Cyberspace Administration), a computing power scheduling platform, and a full suite of solutions covering smart cities, AI + energy, AI + finance, and more.
This means MAAS is no longer a “hardware company.” It now has full-stack, self-controlled AI capabilities—from underlying computing power to algorithmic models, from terminal devices to operational scenarios, forming a closed-loop ecosystem.
The market hasn’t priced this in nearly enough. After the acquisition announcement, the stock rose only about 10%, and while volume increased, it’s far from “explosive” levels. That tells me most investors haven’t yet recognized the strategic significance of this deal.
In my view, this looks a lot like PLTR in early 2023—the market valued it as a “government software contractor,” ignoring its AI platform value. PLTR later went from $7 to $60. Will MAAS repeat that? I don’t know, but it’s worth a bet.
4. Summary of a Few Trading Takeaways
I’m writing all this not to recommend MAAS, but to share what I’ve learned from three months of losses:
Don’t fight the efficiency curse. When everyone can use AI to become more efficient, the moats of pure-play software companies shrink. I prefer assets in the physical world that software cannot disrupt.
Macro variables matter more than stock-picking. Over the past two months, oil price swings have dominated the market far more than any individual stock’s fundamentals. I now check oil prices, Trump’s social media, and the VIX daily. These three indicators determine my overall exposure—not individual stock picks.
“Cognitive gap” is the biggest source of alpha. MAAS is currently misclassified as a “hardware stock,” but its real identity is an “AI energy infrastructure platform.” When most investors haven’t yet recognized that gap, it’s the best time to position.
Don’t be afraid of “uncool.” Mobile charging robots may not sound as sexy as large language models, but they are indispensable physical infrastructure for AI deployment. In a gold rush, the shovel sellers often make steadier money than the miners.
In choppy markets, technical analysis often beats fundamentals. When macro uncertainty is high, earnings and guidance frequently fail. But support, resistance, volume, moving averages—these “market action” data points better reflect fund flows. MAAS’s box breakout, volume surge, and golden cross were my direct reasons to add, not its forward P/E.
Finally, to quote a cliché: When the tide goes out, those swimming naked are exposed, but those wearing armor will go much farther.
I now only buy assets that are “visible, tangible, and indispensable.” MAAS is one of them.
