Hello – When central banks, retail investors and industry all clamor for the same metal, prices don’t just rise—they can launch. Our 2026 Gold Forecast: A Perfect Storm for Demand explains why spot gold could break past $4,000 this year and provides guidance on how to position yourself before it happens. Inside, you’ll discover: -
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How rate cuts and a weakening dollar create a powerful tailwind for precious metals. -
Three practical ways to add gold—from physical bars to high-margin mining stocks paying dividends. -
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This Month's Featured Article SaaS Apocoplyse Survivor? Why Datadog Could Be a Real AI WinnerWritten by Leo Miller. Date Posted: 3/26/2026. 
Key Points - The so-called "SaaS Apocalypse" has resulted in somewhat indiscriminate, leading to opportunities and value traps.
- As AI proliferates, Datadog could be a big beneficiary, yet shares remain down almost 40% from their highs.
- Despite the stock’s year-to-date decline, analysts see DDOG rising well above the current share price.
- Special Report: The Biggest IPO Ever: Claim Your Stake Today
Over the past few months, many investors have encountered the so-called “SaaS Apocalypse”: a sell-off of software-as-a-service (SaaS) stocks driven in part by enthusiasm for new artificial intelligence (AI) tools. To some extent, markets have been indiscriminate, punishing companies with even a SaaS-adjacent business model. But AI disruption will not affect every SaaS company the same way. That divergence creates opportunities in certain SaaS names poised to benefit from AI adoption rather than being replaced by it. One tech stock that may fit that description is Datadog (NASDAQ: DDOG). While shares have recovered from recent lows, the stock is still down about 10% year-to-date in 2026 and nearly 40% off its 52-week high. Some investors think the market may be underestimating Datadog’s role in an AI-heavy enterprise environment. Understanding the Drivers Behind the “SaaS Apocalypse” One big promise of AI is that intelligent agents will be able to act autonomously within enterprise workflows. The idea is that agents could perform tasks that today require specialized — and often costly — SaaS products, allowing companies to cut expenses. That potential has been a major reason incumbent SaaS firms have seen sharp share-price declines. Another argument is that a single employee empowered by AI could replace the work of several people, leading to headcount reductions and lower costs. AI developers such as OpenAI, Anthropic and Alphabet (NASDAQ: GOOGL) pitch that businesses can deploy AI agents to save on labor expenses. But AI is imperfect and can make mistakes, which is evident even in consumer-facing chatbots and can undermine trust. Within an organization, mistakes can have larger consequences: customer impact, revenue leakage and operational disruption. Companies are therefore unlikely to adopt AI agents at scale without mechanisms to build trust and quickly diagnose failures. That is an area where observability vendors argue they can add value. Outsourcing Thinking: AI Agents Increase the Need for Observability Datadog sells observability software that collects data from companies' applications—both internal systems and customer-facing services. That data helps teams detect problems, identify root causes and resolve incidents. While deploying AI agents could reduce labor costs, they also introduce complexity and generate significantly more data. A video on Datadog’s AI Agent Monitoring tool illustrates this point. The presenter walks through a fictional personal-finance app called Budget Guru. A user asks the app to buy $500 of a stock and remind them about an overdraft fee. A human could perform that task in a few clicks and would do the internal thinking to execute it. Budget Guru, however, coordinates five separate AI agents to complete the request—effectively outsourcing the thinking a human would do. That orchestration creates a mountain of observable data on how the result was reached. AI agents produce logs, traces and events that wouldn’t exist if a human completed the same task. As the number of moving parts increases, so do potential failure points. In that context, AI agents don’t eliminate the need for monitoring—they raise the bar for it. That dynamic should increase demand for observability platforms like Datadog, turning a broad sector sell-off into a potential opportunity for companies that provide monitoring and diagnostics. Datadog: Impressive Growth, Profitability, and Analyst Support In its latest quarter, Datadog’s revenues grew 29% to $953 million. The company also generated free cash flow (FCF) of $291 million, yielding an FCF margin of roughly 31%. The Rule of 40—which combines revenue growth and profitability—is a common SaaS health check. Scores above 40 are considered strong; Datadog comes in near 60. Wall Street analysts also see upside. The MarketBeat consensus price target is near $180, implying more than 40% upside. Price targets issued after the company’s latest earnings average slightly lower, around $174. With solid growth, strong profitability, analyst support and potential tailwinds from agent-driven AI adoption, there are reasons to believe DDOG could weather the "SaaS Apocalypse" better than many peers. | 
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