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Will AI decimate these software stocks?

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In early 2026, the software sector entered what analysts have dubbed the “SaaS-pocalypse.” The primary driver is a shift from “SaaS” (Software as a Service) to “AaaS” (Agents as a Service), where autonomous AI agents perform tasks that previously required human users to log into a dashboard.

This shift has created a “Seat Compression” crisis: if AI can do the work of five people, companies no longer need to pay for five software “seats” or licenses.

1. Customer Relationship Management (CRM) & Sales

These companies are at the center of the “seat compression” narrative because AI can now autonomously draft emails, update records, and qualify leads.

  • Salesforce (CRM): Despite launching Agentforce, Salesforce hit 52-week lows in February 2026. Investors fear that “AI Agents” will eventually eliminate the need for the thousands of human sales reps who currently use the platform.
  • HubSpot (HUBS): Similar to Salesforce, HubSpot has seen its valuation reset. While they have pivoted to a “usage-based” model to combat seat loss, the market remains skeptical that AI “credits” will fully replace the high margins of per-user subscriptions.
  • Zendesk (Private/Competitor): Though private, Zendesk is frequently cited in analyst notes as a “canary in the coal mine,” as AI chatbots now resolve over 70–80% of customer tickets without a human agent.

2. Creative & Design Software

The concern here is that generative AI allows non-experts to create professional-grade content, threatening the “pro-tool” moat.

  • Adobe (ADBE): Adobe hit a fresh 52-week low in April 2026. Despite its Firefly AI, investors are worried that specialized AI video tools (like OpenAI’s Sora or Luma) and “one-click” design platforms will erode Adobe’s dominance among creative professionals.
  • Unity (U): Facing competition from AI-driven game engines that can generate 3D environments from text, reducing the need for specialized developers and complex seat-based tooling.

3. Enterprise Workflow & IT Service Management (ITSM)

These platforms manage the “plumbing” of a company. AI is now “self-healing” many IT issues before a ticket is even created.

  • ServiceNow (NOW): Recently downgraded by major firms like UBS in April 2026. The threat is twofold: Salesforce’s Agentforce is directly attacking their IT service niche, and AI automation is reducing the human “troubleshooters” who use the platform.
  • Atlassian (TEAM): As mentioned in your earlier review, Atlassian faces “channel friction” as AI agents begin to automate project management and coding tasks (Jira/Confluence), potentially lowering the total headcount of developer teams.

4. Cybersecurity & Data Governance

AI has made “low-cost coding” possible, allowing startups to replicate complex security features that previously took years to build.

  • Varonis Systems (VRNS): Saw a significant stock drop in April 2026. Analysts are concerned that autonomous AI security systems could replace traditional data governance tools by managing permissions and threats in real-time without human intervention.
  • Okta (OKTA): Fears that AI-driven identity management will become a feature of the “operating system” or the cloud provider (Google/Microsoft), rather than a standalone software subscription.

5. Education Technology (EdTech)

This was the first sector to be hit by the “AI Replacement” concern.

  • Chegg (CHGG): After a brutal 2024 and 2025, Chegg is attempting to restructure into a “skilling” company. However, it continues to struggle as students turn to LLMs for instant, free tutoring rather than paying for Chegg’s proprietary database.
  • Duolingo (DUOL): Shares tumbled 24% in early April 2026 after the company projected lower-than-expected bookings. The concern is that AI-powered real-time translation (like Apple Intelligence or Google Translate) makes the long-term goal of “learning a language” less essential for many travelers.

Summary of the “2026 Bear Case”

Threat LevelIndustryPrimary Stock ImpactedThe AI “Replacement” Logic
CriticalEdTechChegg, DuolingoFree AI models replace paid proprietary content.
HighCRM / SalesSalesforce, HubSpotAI agents do the work, reducing “seat” counts.
MediumCreativeAdobeGenAI lowers the skill floor, commoditizing pro tools.
EmergingWorkflowServiceNow, AtlassianAutonomous IT “self-healing” reduces service tickets.

The Bottom Line: For these stocks to recover, they must prove they can monetize AI Outcomes (e.g., charging for a successfully resolved support ticket) rather than Human Access (charging per user login).

While the “SaaS-pocalypse” of early 2026 has decimated many mid-tier software companies, a clear group of “survivors” has emerged. These companies aren’t just weathering the storm; they are thriving by successfully decoupling their revenue from “human seats” and tethering it to AI outcomes.

Here are the software survivors and the strategies they used to outrun the replacement narrative.

1. The “Infrastructure Backbone”: Microsoft (MSFT)

Microsoft is the ultimate survivor because they own the “gas” that every other AI agent needs to run.

  • The Strategy: While their seat-based Office 365 revenue is vulnerable to compression, they have pivoted to Azure AI. For every customer that fires a human and hires an AI agent, Microsoft still wins through the massive compute power required to run that agent.
  • Key Stat: In FY26 Q1, Azure revenue grew 40%, significantly outpacing the market as the “World’s AI Supercomputer.”

2. The “Back-Office Orchestrator”: ServiceNow (NOW)

ServiceNow has avoided the “seat-loss” trap by focusing on operational efficiency rather than just user headcount.

  • The Strategy: Their “Now Assist” AI doesn’t just help people do work; it “self-heals” IT systems. Instead of selling 10 seats to an IT desk, they sell a platform that reduces incident resolution time by 50%.
  • The Survivor Logic: They have successfully shifted toward “Outcome-Based Pricing,” where companies pay for the value of the resolved issue, not the number of IT staff logged in.

3. The “Creative Currency” Leader: Adobe (ADBE)

After a brutal 2025, Adobe staged a massive comeback in early 2026 by reinventing how they charge for their tools.

  • The Strategy: They introduced “Generative Credits” as a new form of currency. Even if a design team shrinks, the remaining members (and their AI assistants) use exponentially more credits to generate high-resolution video and 3D assets via Firefly.
  • The Results: In Q1 2026, Adobe reported that AI-first ARR (Annual Recurring Revenue) more than tripled year-over-year.

4. The “Data Fortress”: Palantir (PLTR)

Palantir is widely considered the strongest “pure-play” survivor because they never relied on a per-seat model to begin with.

  • The Strategy: Their AIP (AI Platform) acts as a “private AI factory” for government and large enterprises. They solve the “hallucination” and “security” problems that prevent companies from using raw LLMs.
  • The Moat: Because they integrate deep into a company’s private data, the switching costs are astronomical. They are the “brains” of the enterprise, making them irreplaceable by generic AI agents.

5. The “Usage-Based” Pioneer: HubSpot (HUBS)

While still volatile, HubSpot is being labeled a survivor because they “cannibalized themselves” before the market could.

  • The Strategy: In 2025, they moved to a Usage + Seat hybrid model. They aggressively launched “AI Agents” that can work alongside humans. By making the platform the home for all customer data, they ensure that even if a sales team gets smaller, the value of the data in HubSpot gets larger.
  • Zacks Rank: As of April 2026, it holds a Rank #1 (Strong Buy) based on its resilience in moving “upmarket.”

Comparison of Survival Strategies

The “Safe Haven” Sector: Cybersecurity

Stocks like CrowdStrike (CRWD) and Palo Alto Networks (PANW) are being viewed as “structural survivors.”

The Logic: AI has made cyberattacks faster and more frequent. You cannot fight an AI-driven attack with a human-driven defense. This has created an inelastic demand for AI-native security software, protecting their business models from seat-count volatility.

Which of these “survival” tactics do you think is most sustainable for the long term: the “tax on compute” (Microsoft) or the “success-based fees” (Salesforce)?

In 2026, the AI industry has moved past the “hype” phase into a massive infrastructure and agentic era.

Published April 12, 2026

The market is dominated by a few “hyperscalers” and specialized frontier labs that control the primary compute and foundational models.

Here are the major players in AI, categorized by their role in the ecosystem:

1. The “Compute” Titans (Hardware & Infrastructure)

These companies provide the “shovels” for the AI gold rush.

  • NVIDIA: Remains the undisputed king with a ~90% market share in data center GPUs (Blackwell and Rubin architectures). NVIDIA software stack, CUDA, remains a formidable moat.
  • AMD: The primary challenger with its Instinct MI350/400 series. In early 2026, AMD secured a massive 6-gigawatt deal with OpenAI to power future training clusters.
  • The Custom Silicon Wave: Major cloud providers now design their own chips:
    • Google: Its TPU v6 (Tensor Processing Units) powers the Gemini ecosystem.
    • Amazon (AWS): Trainium 3 and Inferentia 3 chips offer high price-performance for startups.
    • Microsoft: Its Maia accelerators are now deeply integrated into Azure’s OpenAI services.

2. The Frontier Labs (Foundational Models)

These companies build the “brains” (LLMs and Multimodal models) that power everything else.

  • OpenAI: The most valuable private company in history (valued at $852B as of April 2026). Their flagship GPT-5.4 is the industry benchmark for reasoning and agentic capabilities.
  • Anthropic: Positioned as the “safety-first” alternative. Their Claude 4.6 (Opus, Sonnet, Haiku) is preferred by enterprises for its high context window and “Computer Use” features.
  • Google DeepMind: Recently released the Gemini 3 family, which is natively multimodal (processing video, audio, and code simultaneously) and powers 2 billion users via Google Search and Android.
  • Meta: The champion of “Open Weights” AI. Their Llama 4 series is the global standard for developers building local or sovereign AI applications.
  • xAI (Elon Musk): Utilizing the Colossus supercomputer (the world’s largest), xAI’s Grok 4 competes directly with OpenAI on raw reasoning power.

3. The “Agentic” & Enterprise Platforms

The shift in 2026 is away from “chatbots” and toward “agents” that do work autonomously.

  • Microsoft: Through Copilot, they have successfully integrated AI into the daily workflows of 400 million Office 365 users.
  • Salesforce (Agentforce): A major 2026 player that replaced traditional customer service with autonomous AI agents that can handle sales and support without human oversight.
  • Palantir: Dominates the defense and government sector with its AIP (AI Platform), used for battlefield intelligence and supply chain logistics.
  • Databricks & Snowflake: The “Data Giants” that allow companies to build custom AI models on top of their own private corporate data.

4. Specialized Vertical Leaders

  • AI Coding: Anysphere (Cursor) and Cognition (Devin) have revolutionized software engineering, with “autonomous coding” now handling 40% of routine enterprise code.
  • Physical AI & Robotics: Tesla (Optimus) and Figure AI are the leaders in humanoid robotics, while Waymo remains the dominant force in autonomous driving.
  • Creative Media: Runway (video), Suno/Udio (music), and Luma (3D/Video) have disrupted the film and music industries with studio-quality generative tools.

2026 Market Summary

CompanySectorKey Advantage
NVIDIAHardwareMonopoly on high-end AI chips.
OpenAIModelsFirst-mover advantage and massive Microsoft backing.
AppleEdge AIApple Intelligence runs private AI on 1B+ local devices.
Mistral AIEuropean AIThe leader in “Sovereign AI” for the EU.
Alibaba (Qwen)Asian AIDominates the Chinese market and open-source ecosystem.

The biggest trend of 2026 is the “ROI Gap”—investors are now pressuring these giants to prove that the trillions spent on chips are translating into actual corporate profits, not just cool demos.

Behind the algorithms and GPUs of 2026 are a handful of individuals whose decisions dictate the direction of global technology. The landscape has shifted recently, with several “Godfathers” of the field moving into advisory or risk-focused roles, while a new generation of “Agentic” leaders has taken over.

Here are the major players leading the AI revolution today:

1. The “Frontier” Visionaries (Lab Leaders)

These individuals lead the organizations building the world’s most powerful models.

  • Sam Altman (CEO, OpenAI): The most recognizable face in AI. In 2026, he oversees an OpenAI valued at over $850 billion. He has transitioned from simply building chatbots to focusing on “World Models” and the infrastructure required for AGI (Artificial General Intelligence).
  • Dario Amodei (CEO, Anthropic): A former OpenAI executive who now leads the primary competitor, Anthropic. Amodei is seen as the “conscience” of the industry, focusing heavily on AI Alignment and safety with their Claude models.
  • Demis Hassabis (CEO, Google DeepMind): A 2024 Nobel Prize winner, Hassabis has successfully merged Google’s massive compute power with DeepMind’s research. His focus in 2026 is “Scientific AI”—using models like AlphaFold to revolutionize medicine and material science.
  • Mustafa Suleyman (CEO, Microsoft AI): Formerly of Inflection and DeepMind, Suleyman now heads Microsoft’s consumer AI efforts. He is the primary architect of Copilot and the move toward personal AI “chiefs of staff.”

2. The “Infrastructure” Kings (The Power Brokers)

Without these individuals, the software labs would have no place to run their code.

  • Jensen Huang (CEO, NVIDIA): Often called the “Godfather of the AI Era,” Huang’s leadership has made NVIDIA the most valuable company in the world. His focus in 2026 is the Rubin GPU architecture and the creation of “AI Factories.”
  • Mira Murati (Founder, Thinking Machines Lab): After her high-profile departure from OpenAI as CTO, Murati launched her own venture in 2025. By April 2026, her “Thinking Machines Lab” has secured one of the largest hardware allocations in history to build specialized reasoning agents.
  • Lisa Su (CEO, AMD): Su has successfully positioned AMD as the only viable alternative to NVIDIA’s monopoly, specifically dominating the “Open Ecosystem” for AI hardware.

3. The “Academic & Safety” Guardians

These figures provide the intellectual and ethical framework for the industry.

  • Geoffrey Hinton (The Godfather of AI): Another 2024 Nobel Laureate. Since leaving Google, Hinton has become the leading voice warning against the existential risks of AI, frequently advising world governments on regulation.
  • Yann LeCun (Chief AI Scientist, Meta): Known for his “skeptical” but optimistic view, LeCun argues that current LLMs are not the path to true intelligence. He is leading the charge toward “World Models” that learn more like human babies do.
  • Fei-Fei Li (Stanford Professor / Founder, World Labs): The “Mother of Computer Vision.” In 2026, she leads the “Spatial Intelligence” movement, focusing on giving AI the ability to understand and interact with the 3D physical world.
  • Ilya Sutskever (Co-Founder, Safe Superintelligence Inc.): After leaving OpenAI, the legendary researcher founded SSI to focus purely on building a superintelligent system that is “provably safe” before it is ever deployed.

4. The “Sovereign & Alternative” Players

  • Elon Musk (Founder, xAI): Through xAI and the Grok models, Musk utilizes the massive data firehose of X (formerly Twitter) and the world’s largest supercomputing clusters (Colossus) to build “truth-seeking” AI.
  • Arthur Mensch (CEO, Mistral AI): The leader of Europe’s AI efforts. Mensch has become the champion of Open Source AI, ensuring that not all power resides in Silicon Valley.

Summary of Influence (April 2026)

IndividualPrimary InfluenceCurrent 2026 Project
Sam AltmanGlobal Policy & ScalingGPT-5.4 / “Stargate” Supercomputer
Jensen HuangHardware & ComputeRubin Architecture / Omniverse
Dario AmodeiSafety & EnterpriseClaude 4.6 / Scaling Laws
Yann LeCunResearch TheoryV-JEPA (Joint-Embedding Predictive Architecture)

The debate over AI is no longer just happening in research papers; in 2026, it is the primary driver of international law. The clash between Effective Accelerationism (e/acc) and AI Safety (Alignment) has created a fragmented regulatory map where a company’s “philosophy” can determine which borders it is allowed to cross.

The Great Philosophical Divide

1. Effective Accelerationism (e/acc)

  • The Philosophy: Influenced by figures like Marc Andreessen and Garry Tan, e/acc argues that any attempt to slow down AI is a “death sentence” for human progress. They believe the only way to solve AI risk is to build better AI faster.
  • Impact on Law: This philosophy has heavily influenced the U.S. Federal Framework released in March 2026. This framework aims to curb “regulatory overreach” by individual states, focusing on market competition and minimizing the compliance burden on startups to prevent “regulatory capture” by giants like OpenAI.

2. AI Safety & Alignment (The “Safety-First” Bloc)

  • The Philosophy: Led by Dario Amodei (Anthropic) and the “Godfathers” (Hinton and Sutskever), this group argues that frontier models pose existential risks (CBRN threats, autonomous cyberwarfare).
  • Impact on Law: Their fingerprints are all over California’s 2026 Safety Frameworks. Even though the famous SB 1047 failed in its original form, the new laws enacted in January 2026 require developers of large models ($100M+ training cost) to provide “certification of safety” and incident reporting.

How 2026 Global Laws Reflect These Clashes

The global regulatory landscape has split into three distinct “legal zones” based on these philosophies:

RegionPrimary PhilosophyCurrent Legal Status (April 2026)
United Statese/acc / Pro-GrowthA “tug-of-war” between the Federal pro-growth framework and California’s safety mandates. The Remote Access Security Act (RASA) also recently passed to control GPU access to foreign entities.
European UnionHuman-Centric / Risk-BasedThe EU AI Act is now in full force for “High-Risk” systems. The new Digital Omnibus proposal (late 2025) is currently being used to bridge the gap between AI innovation and strict GDPR privacy rights.
Global South (India/ASEAN)Sovereign AILed by the India AI Impact Summit (Feb 2026), these nations are rejecting “Western-centric” safety rules in favor of laws that prioritize domestic infrastructure and local language models.

The “Open Source” Wildcard

Yann LeCun (Meta) and Arthur Mensch (Mistral) have successfully lobbied for a “third way.” They argue that transparency through open-source is the only way to prevent a global AI monopoly.

By April 2026, this has resulted in “Transparency Shields” in several jurisdictions (including parts of the EU), where open-weight models receive certain liability exemptions as long as their training data and safety protocols are fully public. This is a direct challenge to OpenAI’s “closed-loop” safety model.

The Geopolitical Stall

The ultimate impact of these philosophies on global law was supposed to be codified at the Trump-Xi Summit in March 2026. However, due to the escalating Iran conflict, this summit has been pushed to May. For now, the world remains in a state of “Regulatory Arbitrage,” where companies choose their headquarters based on whether they prioritize raw speed (U.S. Federal) or verified safety (EU/California).

What is inflation psychology?

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Published April 11, 2026

Inflation psychology is the collective belief among consumers and businesses that prices will continue to rise indefinitely. It is often described as a “self-fulfilling prophecy” because when people expect inflation, they change their behavior in ways that actually cause it.

As of April 2026, this concept has returned to the forefront of economic discussion due to a sharp divergence in global markets and renewed geopolitical shocks.

1. How the “Vicious Cycle” Works

Inflation psychology turns a temporary price spike into a permanent trend through three primary behaviors:

  • Forward-Buying: Consumers rush to buy goods now (like cars, appliances, or even non-perishable groceries) to “beat” the price increases they expect next month. This surge in demand pushes prices even higher.
  • The Wage-Price-Profit Spiral: Workers demand higher wages to maintain their purchasing power. To cover these labor costs, businesses raise their prices. If businesses also raise prices to protect profit margins (a “profit spiral”), inflation becomes “sticky.”
  • Reduced Price Sensitivity: When prices for everything are rising, consumers stop “shopping around” or resisting higher costs because they assume every retailer is equally expensive. This gives businesses more “pricing power” to pass on costs.

2. The Current “Sentiment Plunge” (April 2026)

The psychological landscape shifted dramatically this month. On April 10, 2026, the U.S. Consumer Sentiment Index plunged to a record low of 47.6, down from 53.3 in March.

DriverPsychological Impact in 2026
Geopolitical TensionConcerns over the Iran conflict have spiked energy expectations, making consumers feel that “the worst is yet to come.”
Tariff LagMany businesses are only now passing on the costs of 2025 tariffs as their old inventories run out, creating a “second wave” of price shocks.
“Salient” PricesHouseholds are ignoring aggregate stats (CPI) and focusing on “salient” items—eggs, gas, and home repairs—which remain highly volatile.

3. The Cognitive Biases Involved

Economics isn’t just math; it’s brain chemistry. Two main biases are driving the 2026 outlook:

  • Anchoring: Consumers are still “anchored” to the lower prices of the early 2020s. Every trip to the grocery store feels like a “loss” compared to that mental anchor, leading to Uncertainty Fatigue.
  • Loss Aversion: Research from early 2026 shows that the “pain” of a price increase is felt twice as intensely as the “joy” of a price drop. This makes consumers more likely to hoard goods or demand aggressive raises to avoid the feeling of falling behind.

4. Regional Cross-Currents

Inflation psychology is currently diverging by region:

  • The U.S.: Expectations are becoming “unanchored.” Core inflation is projected to accelerate toward 4% as the “buy now” mentality takes hold again.
  • Canada & Europe: Sentiment is more “cautious” than “panicked.” In Canada, consumers have shifted to Intentional Spending—prioritizing value and loyalty programs rather than mass forward-buying.

The Central Bank Dilemma

Central banks, like the Bank of Canada and the Fed, are terrified of “unanchoring.” Once people believe 4% inflation is the new normal, it is incredibly difficult to bring it back to the 2% target without causing a severe recession. Their main tool right now isn’t just interest rates—it’s communication, trying to convince the public that these shocks are temporary to break the psychological loop.

Some trades ahead of Trump policy moves raise questions

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Published by Reuters April 9, 2026

My comments: This is most likely the tip of the iceberg. None will be prosecuted. The Trump team has undermined the integrity of the whole financial system.

By Utkarsh Shetti

April 9 (Reuters) – Some of U.S. President Donald Trump’s major policy decisions have been preceded by well-timed bets, leading some experts to raise questions about whether information had somehow leaked ahead of time. 

Here is a list.

April 7, 2026 – IRAN CEASEFIRE ANNOUNCEMENT:

Traders placed a roughly $950 million bet on oil prices falling just hours before the announcement of a ceasefire between the U.S. and Iran.

A combined 8,600 lots of Brent and U.S. crude futures were sold at 1945 GMT on Tuesday, according to LSEG data. At around 2230 GMT, Trump announced a two-week ceasefire with Iran, knocking crude futures down by some 15% to below $100 a barrel at the start of ​Wednesday’s official trading session.

Separately, the Associated Press reported that a group ‌of new accounts on prediction market platform Polymarket made timely bets on whether a ceasefire would be reached on April 7. Prediction ​markets offer tradable yes-or-no contracts that let users wager on a broad array of real-world events.

The news agency cited publicly available blockchain data from Polymarket using crypto analytics platform Dune, which showed at least 50 accounts, or wallets, placed “Yes” bets before Trump’s post.

One wallet, created around 10 am ET on the ‌same day, profited $200,000 after betting roughly $72,000, while another user joined the platform on April 6 and won $125,500. A third wallet ⁠was created just 12 minutes before Trump’s announcement, raking in an estimated $48,500 after betting $31,908.

Polymarket did ​not respond to a Reuters request for comment.

March 23, 2026 – IRAN ATTACK PAUSE:

An unidentified trader or traders bet $500 million on Brent and WTI crude futures in a one-minute period shortly before Trump announced a five-day delay to attacks on Iran’s energy infrastructure, after which oil prices crashed 15%, exchange data and Reuters calculations showed.

LSEG data shows 5,100 lots changed hands between 1049 and 1050 GMT, with selling dominating volume. When Trump’s social media post announcing the move hit at 1105 GMT, over 13,000 lots — equivalent to 13 million barrels — traded in 60 seconds, causing Brent to fall to $99 per barrel from $112 and sending WTI down to $86 per barrel from $99. 

February 28, 2026 – IRAN STRIKES THAT KILLED ‌SUPREME LEADER AYATOLLAH ALI KHAMENEI 

Wagers placed on platforms including Polymarket before the killing of Iranian Supreme Leader Ayatollah Ali Khamenei intensified scrutiny of prediction markets, with Democratic lawmakers calling for a ban on bets tied to military actions that could reward those with privileged information. Kalshi is facing a lawsuit for failing to pay $54 million to people who bet that Khamenei would leave office before March 1. ‌The company says it does not offer markets that settle on death.

According to a Reuters review of Polymarket’s website at the time, about $529 million ‌was wagered on a range of contracts tied to the timing of U.S.-Israeli strikes on Iran, while another $150 million was staked on Khamenei’s ‌removal as supreme leader.

Analytics firm Bubblemaps identified six accounts that made a combined $1.2 million profit from Polymarket bets that were funded in the hours immediately before the raids, which took place on February 28. U.S. Representative Mike Levin of California flagged one specific ‌Polymarket ‌bet placed shortly before the Iran strikes.

Separately, despite hotter-than-expected inflation data that would typically prompt investors to sell long-dated Treasuries, traders moved in the opposite direction on February 27, pushing yields on the benchmark 10-year note below 4%. Analysts said such a pronounced shift into the safe-haven asset would usually be driven by a negative macro event – or a strong expectation that one ⁠was imminent. 

Shares of U.S. airlines also fell that day as oil prices rose, with the Dow Jones U.S. Airlines Index slipping ‌5.13%.

January 3, 2026 – U.S. CAPTURE OF FORMER VENEZUELAN PRESIDENT NICOLAS MADURO:

An unknown trader pocketed a profit of roughly $410,000 after wagering on the ouster of Venezuelan President Nicolas Maduro in January. 

The trader’s account on Polymarket built up positions ‌in contracts tied to Maduro’s removal on terms that implied long odds before the weekend raid ⁠of Maduro’s compound in Caracas by U.S. special forces. Those wagers, worth about $34,000 prior to his capture, surged ‌in value after news of the U.S. military operation emerged on January 3.

April 9, 2025 – TARIFF PAUSE:

Unidentified options traders staked millions of dollars on a U.S. stock market rebound in the minutes before Trump’s tariff pause announcement triggered a massive rally in April last year, according to trading data.

Trump’s Truth Social post pausing tariffs came at 1:18 p.m. ET on April 9, setting off a 9.5% jump for the S&P 500. Market data shows certain options contracts logging a spike in trading activity ahead of it. Some 5,105 SPY call options traded at around 1 p.m. ET for an ‌average price of $4.20.

When stocks rallied, those calls soared as high as around $42, turning $2.14 million into about $21.44 million on paper. 

Similarly, other SPY calls betting on the ETF rising above $509 traded at around 1:10 p.m. ET; their value jumped to about $10 million by end of day, up from $624,000. 

Reuters could not determine whether the ‌calls were all purchased or sold by one trader or several and whether they closed the position for a gain.

White House ⁠spokesman Kush Desai said government ethics guidelines bar federal employees from profiting off nonpublic information. “Any implication that Administration officials are engaged in such activity without evidence is baseless and irresponsible,” he said in an email statement.

Some trades ahead of Trump policy moves raise questions By Reuters

In the world of fundamental analysis, “Total Debt” is often a bit of a moving target

Published April 5, 2026

Should you include lease liabilities?

For a standard Debt-to-Equity (D/E) calculation in 2026, the short answer is yes—you should generally include lease liabilities.

Since the implementation of accounting standards IFRS 16 (and ASC 842 in the U.S.), almost all leases are now recognized on the balance sheet. Because these represent a legal obligation to make future cash payments, most analysts treat them as a form of debt.

What is Included in “Total Debt”?

To calculate a robust D/E ratio, you aggregate all interest-bearing obligations and contractual payment liabilities. This typically includes:

  • Short-Term Debt: Bank overdrafts, commercial paper, and notes payable due within one year.
  • Current Portion of Long-Term Debt: The amount of principal on long-term loans that must be paid in the next 12 months.
  • Long-Term Debt: Bonds issued, term loans, and mortgages.
  • Lease Liabilities: Both the current and non-current portions of your lease obligations.

The Formula

The comprehensive formula for the ratio looks like this:

$$Debt-to-Equity = \frac{\text{Short-Term Debt} + \text{Long-Term Debt} + \text{Lease Liabilities}}{\text{Total Shareholders’ Equity}}$$

Why Including Leases Matters

Including lease liabilities can drastically change the profile of a company, especially in sectors that rely heavily on physical footprints.

  • Retail & Restaurants: Companies like Loblaw or Canadian Tire have massive lease liabilities for their storefronts. If you exclude these, their leverage looks artificially low.
  • Airlines: Most planes are leased. Excluding these liabilities would ignore the primary financial risk of the business.
  • The “Debt vs. Liabilities” Distinction: Be careful not to use Total Liabilities in the numerator. Total Liabilities include “Accounts Payable” and “Deferred Revenue,” which are operational obligations, not financial debt. Using Total Liabilities gives you the Total Liabilities-to-Equity ratio, which is a different (and much higher) metric.

Pro-Tip for Active Traders

If you are comparing a company’s current D/E to its historical levels from 10 years ago, remember that the “jump” in debt you might see around 2019–2020 is often just the accounting change (bringing leases onto the balance sheet), not necessarily a sudden spending spree.

When looking at TSX-listed stocks, most Canadian companies report under IFRS, so the lease liabilities will be clearly broken out in the “Liabilities” section of the balance sheet.

For the 2025–26 fiscal year, the Canadian federal budget projects total spending of $585.9 billion

Published April 2, 2026

This represents a significant increase from previous years, driven largely by new military outlays, housing initiatives, and rising debt-servicing costs.

The following table breaks down the major spending categories by dollar amount and their approximate percentage of the total budget.

Federal Spending Breakdown (FY 2025–26)

CategoryAmount ($ Billions)% of Total Budget
Direct Program Expenses$257.043.9%
Major Transfers to Persons$158.027.0%
Major Transfers to Provinces & Territories$110.318.8%
Public Debt Charges (Interest)$55.69.5%
Net Actuarial Losses$5.00.8%
Total Federal Spending$585.9100%

Key Line Items and Sub-Categories

To provide a more granular view, here are the specific costs for the most significant programs within those major categories:

1. Major Transfers to Persons ($158.0B)

  • Elderly Benefits (OAS/GIS): $85.5 billion (14.6%). This remains the largest single program expense due to Canada’s aging demographic.
  • Canada Child Benefit (CCB): $31.2 billion (5.3%).
  • Employment Insurance (EI): $27.8 billion (4.7%).
  • Canada Disability Benefit: $13.5 billion (2.3%).

2. Major Transfers to Other Levels of Government ($110.3B)

  • Canada Health Transfer (CHT): $54.7 billion (9.3%).
  • Fiscal Equalization: $27.3 billion (4.7%).
  • Canada Social Transfer (CST): $17.1 billion (2.9%).

3. Direct Program Expenses ($257.0B)

This category covers the operations of all federal departments and new strategic investments.

  • National Defence: $35.2 billion (6.0%). Spending has ramped up following the 2025 Arctic Sovereignty mandate.
  • Indigenous Services: $25.2 billion (4.3%).
  • Build Canada Homes Initiative: $13.0 billion (2.2%). A key pillar of the 2025-26 fiscal strategy to address housing supply.

Fiscal Health Indicators (2026 Context)

As an active participant in the Canadian markets, you may find the following “bottom-line” figures relevant to the current trading environment:

  • Budgetary Revenues: $507.5 billion.
  • Annual Deficit: $78.3 billion (restated at 2.5% of GDP).
  • Federal Debt-to-GDP: 42.4%.
  • Interest Outlook: Public debt charges are now consuming nearly 10 cents of every dollar the government collects, which is a major factor in the current “hard-nosed” approach to departmental budget cuts (targeting a 10% reduction in the federal workforce by 2028).

Canadian GDP update by sector

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Published March 30, 2026

As of early 2026, Canada’s economy is navigating a period of modest growth, with real GDP expanding by 1.6% in 2025 and projected to grow by approximately 0.7% to 1.1% in 2026.

The economy is currently characterized by a “two-speed” performance: strong growth in energy and commodities-producing provinces, contrasted by significant headwinds in manufacturing-heavy regions like Ontario and Quebec due to trade friction and tariffs.

Canadian GDP Breakdown by Sector (2025–2026)

The following table outlines the approximate contribution of major industrial sectors to the Canadian economy and their recent performance trends.

SectorApprox. % of GDP2025–2026 Performance Trend
Real Estate, Rental & Leasing~13.5%Stable at record highs; residential cooling in ON/BC.
Manufacturing~10.0%Contracting (-2.6% in 2025); facing U.S. trade tariffs.
Mining, Oil & Gas Extraction~9.0%Strong Growth (+4.0% in 2025); upside from oil price shocks.
Finance & Insurance~7.5%Growing (+4.0% in 2025); supported by interest margins.
Healthcare & Social Assistance~7.5%Consistent growth (+2.6% in 2025); driven by demographics.
Construction~7.0%Rebounding in engineering/infra; weak residential starts.
Public Administration~6.5%Modest growth (+1.1%); strong federal spending.
Professional & Tech Services~6.0%Resilient; tech remains a significant $120B+ industry.
Wholesale & Retail Trade~10.5%Volatile; impacted by shifting consumer confidence.

Key Economic Drivers in 2026

1. The Energy Surge

Energy-producing provinces—Alberta, Saskatchewan, and Newfoundland and Labrador—are outperforming the national average. Recent supply disruptions in the Middle East have pushed oil price forecasts up significantly. Combined with the expanded capacity of the Trans Mountain and Enbridge systems, the sector is seeing material upside in production and revenue.+1

2. Manufacturing and Trade Headwinds

The manufacturing sector remains the largest detractor from national growth. Trade uncertainty and tariffs (particularly on steel, aluminum, and lumber) have led to a third consecutive year of contraction in some sub-sectors. While a U.S. Supreme Court ruling recently struck down some broad 2025 tariffs, specialized duties on automotive and metal products continue to weigh on Central Canada.

3. Housing and Construction Bifurcation

The construction sector is seeing a split in performance:

  • Engineering & Infrastructure: GDP reached roughly $170 billion in late 2025, driven by massive government projects in clean energy and transit.
  • Residential Construction: High borrowing costs and inventory backlogs have slowed new housing starts to near two-decade lows in markets like Toronto and Vancouver.

4. Services-Producing Industries

The services sector (accounting for roughly 70% of total GDP) remains the economy’s anchor. Finance, healthcare, and education have provided steady gains that helped Canada avoid a technical recession in 2025, even as the goods-producing side of the economy struggled.

The service sector, also known as the tertiary sector, includes all economic activities that produce “intangible” value rather than physical goods. Instead of extracting raw materials (primary sector) or manufacturing products (secondary sector), the service sector focuses on providing specialized skills, experiences, and logistical support to consumers and businesses.

In modern developed economies, the service sector typically accounts for 70% to 80% of total GDP.

Major Categories of the Service Sector

The sector is incredibly broad, ranging from a neighborhood coffee shop to a global data analytics firm. It is generally divided into several key categories:

CategoryDescriptionIndustry Examples
Trade & DistributionThe movement and sale of physical goods.Retail, Wholesale, Warehousing, e-commerce.
Consumer ServicesServices provided directly to individuals.Restaurants, Hotels, Tourism, Hair salons, Gyms.
Financial ActivitiesManaging, investing, and protecting money.Banking, Insurance, Real Estate, FinTech.
Professional ServicesSpecialized expertise for businesses.Legal, Accounting, Management consulting, Marketing.
Information & TechManaging data and digital communication.Software (SaaS), Telecommunications, AI services.
Public & SocialServices essential for society’s functioning.Healthcare, Education, Public safety, Government.

The Evolution: Quaternary and Quinary Sectors

As economies become more advanced, the service sector is often subdivided into two “knowledge-based” extensions:

1. The Quaternary Sector (The Knowledge Economy)

This involves the gathering, processing, and distribution of information. It is the “brain” of the economy.

  • Examples: Research and Development (R&D), Data Analytics, Scientific Research, and Advanced IT.
  • 2026 Trend: A major driver here is Agentic AI—autonomous systems that perform complex business processes without constant human oversight.

2. The Quinary Sector (High-Level Decision Making)

This represents the highest levels of organization and decision-making in society.

  • Examples: Government leaders, CEOs of multinational corporations, and top-tier scientific innovators.
  • Non-Profit: This also includes non-profit organizations and unpaid domestic labor (caregiving) which provide immense social value but are often excluded from traditional GDP calculations.

Key Characteristics of Services

To distinguish a service from a good, economists look for four specific traits:

  • Intangibility: You cannot touch or store a service. You are buying the result (e.g., a clean house or a legal defense).
  • Perishability: Services cannot be saved for later. An empty seat on a flight or an unbooked hotel room is “lost” revenue that can never be recovered.
  • Inseparability: The service is often produced and consumed at the same time (e.g., a haircut or a live concert).
  • Inconsistency: Unlike a factory-made phone, the quality of a service can vary based on who provides it and when.

Update for March 31, 2025: The Canadian gross domestic product expanded by 0.2% from the previous month in February of 2026, according to a flash estimate. This was supported by higher output in manufacturing, mining, and quarrying, and financial services, which offset contractions for agriculture and forestry. The expansion is set to extend the 0.1% growth rate from January, which was upwardly revised from the initial estimate of a stall. Growth was carried by goods producing industries (0.2%) as higher construction (2.2%) and mining and quarrying (1.2%) offset the drop for manufacturing (-1.4%). In turn, services producing industries stalled. Output increased in finance and insurance (0.5%), and retail trade (0.8%), offsetting the contraction for wholesale trade (-1.2%) and transportation and warehousing (-0.7%), which was pressured by extreme weather conditions that prevented logistics. source: Statistics Canada

The 2008 oil spike was a perfect storm as WTI hit a record of $147.27

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Published March 30, 2026

The 2008 oil price spike, which saw West Texas Intermediate (WTI) crude hit an all-time record of $147.27 per barrel in July, was a “perfect storm” of economic, geopolitical, and financial factors. It wasn’t caused by a single event, but rather a collision of supply and demand that many at the time called the “Third Oil Shock.”

WTI crude long-term chart back to the year 2000

Here is the breakdown of what drove prices into the stratosphere:

1. The “Demand Shock” (Emerging Giants)

The single biggest driver was the rapid industrialization of China and India.

  • The Awakening: These two nations were growing at nearly 10% GDP, shifting millions of people into the middle class who were buying cars and using electricity for the first time.
  • Inelasticity: Global demand was growing so fast that it didn’t matter if prices went up; these emerging economies needed the fuel to keep their factories running, creating a “bidding war” for every available barrel.

2. Stagnant Global Supply

While demand was skyrocketing, the world’s ability to pump more oil had hit a wall.

  • Spare Capacity: Historically, Saudi Arabia kept enough “spare capacity” to flood the market if prices got too high. By 2008, that cushion had dwindled to almost nothing.
  • Non-OPEC Struggles: Production in places like the North Sea and Mexico was in natural decline, and new projects (like deep-water drilling) were taking years longer than expected to come online.
  • Peak Oil Fears: This was the era where the “Peak Oil” theory went mainstream—the fear that the world had already reached its maximum physical production limit.

3. Geopolitical Risk Premium

Investors added a “fear tax” to the price of oil due to constant instability in key producing regions:

  • The Middle East: Continued fallout from the Iraq War and rising tensions with Iran over its nuclear program led to fears of a closure of the Strait of Hormuz.
  • Nigeria: Militant attacks on pipelines in the Niger Delta frequently knocked hundreds of thousands of barrels per day offline.
  • Venezuela: Political friction between the U.S. and Hugo Chávez’s government led to concerns about supply reliability from one of the U.S.’s biggest providers.

4. The Weakening U.S. Dollar

Oil is priced globally in U.S. Dollars ($USD$). In 2008, the dollar was losing value rapidly against the Euro and other currencies.

  • The Hedge: When the dollar weakens, oil prices usually rise to compensate.
  • Foreign Buyers: For a buyer in Europe using Euros, oil didn’t actually feel as “expensive” as it did to an American, because their currency was stronger. This kept global demand high even as prices in dollars soared.

5. Financial Speculation (“The Bubble”)

This is the most debated cause. Many analysts believe the “financialization” of commodities played a role.

  • Index Funds: Huge amounts of pension fund and hedge fund money flowed into “commodity index funds.” These investors weren’t buying oil to use it; they were buying it as a financial asset.
  • The Momentum: This created a feedback loop—as prices rose, more speculative money flowed in, pushing prices even higher until the bubble finally burst during the Great Financial Crisis later that year.

Comparison: 2008 vs. Today

Factor2008 Peak ($147)2026 Context
Main DriverChina’s IndustrializationGeopolitical Conflict (ME/Ukraine)
SupplyPhysical Scarcity FearsSufficient Supply (Shale/OPEC+)
US DollarRecord WeaknessGenerally Stronger
DemandRapidly RisingTransitioning (EVs/Renewables)

The spike ended abruptly in late 2008 when the global financial system collapsed. Demand vanished almost overnight, and oil plummeted from $147 to under $40 in just six months—one of the most violent “price destructions” in history.

Considering the recent spikes we’ve seen in WTI and HOU.TO, do you think today’s geopolitical tensions are creating a similar “fear premium” to what we saw in 2008?

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Technical Analysis is about trading with the trend

Note: This technical analysis is for educational purposes. Please conduct your own analysis or consult a financial advisor before making investment decisions. The author of this article may hold long or short positions in the featured stocks or indexes. The article was written with the help of AI and was reviewed by an editor.

© 2026 TradeOnline.ca InvestOnline.ca ChartAnalysis.ca

Alphabet (GOOG) will test 200-day simple moving average

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Analysis: This is an educational rear-view mirror post. What was an early indicator of the impending short-term downtrend? You can see the negative divergence on the RSI indicator as a early warning of the short-term downtrend. Can Google hold major support around the 200-day moving average? I say yes, but the market will have the finale say. We can easily be trumped.

Google 4-year candlestick chart showing negative divergence on the RSI.

_____________

Technical Analysis is about trading with the trend

Note: This technical analysis is for educational purposes. Please conduct your own analysis or consult a financial advisor before making investment decisions. The author of this article may hold long or short positions in the featured stocks or indexes. The article was written with the help of AI and was reviewed by an editor.

© 2026 TradeOnline.ca InvestOnline.ca ChartAnalysis.ca

Canadian Phoenix pay system boondoggle

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Published March 23, 2026

The Phoenix Pay System epitomizes Government incompetency and the hubris of so-called IT experts.

The Minister of Public Services and Procurement who authorized the final rollout and release of the Phoenix pay system was Judy Foote. She knew nothing about IT systems but neither did her advisors. They are all retired now on government pensions.

While the project was initiated under the previous Conservative government, the final decision to “go live” happened in early 2016 under the Liberal government.

Key Timeline of Authorization:

  • Initial Approval (2009–2015): The “Transformation of Pay Administration” initiative began under Prime Minister Stephen Harper. Ministers including Rona Ambrose and Diane Finley oversaw the earlier development and the move of the pay centre to Miramichi, New Brunswick.
  • The “Go-Live” Decision (February 2016): After the 2015 election, Judy Foote was appointed Minister of Public Services and Procurement. Despite warnings from unions and reports of technical “bugs,” the department proceeded with the release.
  • Two-Phase Rollout: * Phase 1: Launched in February 2016 for 120,000 employees.
    • Phase 2: Launched in April 2016 for the remaining 170,000 employees.

The Aftermath

Shortly after the second phase, it became clear that thousands of federal employees were being underpaid, overpaid, or not paid at all. In 2017, Judy Foote resigned from cabinet for personal reasons, and the file was eventually handed to Carla Qualtrough, who began the long process of attempting to stabilize the system and searching for a replacement (the “Dayforce” project).

As of 2026, the government is still in the process of transitioning away from Phoenix to the Dayforce system, a project currently overseen by Minister Joël Lightbound.

What companies were behind the Phoenix boondoggle?

The company primarily behind the Phoenix pay system is IBM Canada.

While IBM built and implemented the system, the project was a massive undertaking involving several different entities and software components. Here is the breakdown of the “who’s who” behind the system:

1. IBM Canada (The Prime Contractor)

IBM was awarded the contract in June 2011 to design, customize, and implement the system.

  • The Contract: What started as a $5.7 million contract famously ballooned. By 2026, the total paid to IBM for Phoenix-related work (including years of “stabilization” efforts) has exceeded $780 million.
  • The Defense: IBM has historically maintained that they were the “builders” following the government’s instructions. They testified in 2018 that they actually recommended the government delay the rollout in 2015 because the system wasn’t ready, but were overruled by government bureaucrats.

2. Oracle / PeopleSoft (The Software)

Phoenix was not built from scratch; it was based on PeopleSoft, a commercial “off-the-shelf” payroll software owned by Oracle Corporation.

  • The disaster wasn’t necessarily the software itself (which is used by many large corporations), but rather the heavy customization required to handle the federal government’s 80,000+ complex pay rules and dozens of different collective agreements.

3. Public Services and Procurement Canada (The Architect)

The government department (PSPC) acted as the project manager.

  • They made the critical decision to eliminate 700 experienced pay advisor jobs before the system was fully functional, moving operations to a centralized hub in Miramichi, New Brunswick. This “points of failure” move left the government without a safety net when the software began to glitch.

4. Other Consultants

Several other high-profile firms were brought in at various stages to audit, advise, or try to fix the mess:

  • PricewaterhouseCoopers (PwC): Conducted early studies that helped build the original business case for the system.
  • Gartner Consulting: Hired to perform a “readiness review” just before the 2016 launch (their warnings were largely downplayed).
  • McKinsey & Company: Later brought in to help with “pay transformation” and stabilization strategies.

The Current Shift: The government is now moving away from IBM’s Phoenix system toward a new provider, Dayforce (formerly Ceridian), as part of the “NextGen” pay initiative.

Read the following story: Replacing Phoenix pay system will cost at least $4.2-billion, Auditor-General report says – The Globe and Mail