{
  "id": 7012931,
  "title": "AI Agents Create Their Own Monitoring Problem. Datadog and Dynatrace Are Racing to Own It",
  "url": "https://urgent.news/2026/09/12/ai-agents-create-their-own-monitoring-problem-datadog-and-dynatrace",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-12T22:56:26.000Z",
  "source": {
    "name": "Yahoo Finance",
    "slug": "yahoo-finance",
    "url": "https://finance.yahoo.com/technology/ai/articles/ai-agents-create-own-monitoring-225626156.html"
  },
  "original_language": "en",
  "account": "AI coding agents are designed to streamline software development, yet they may inadvertently introduce additional changes, production failures, and complexities that require monitoring. This secondary impact positions Datadog (NASDAQ:DDOG) and Dynatrace (NYSE:DT) in a market that AI could potentially expand rather than diminish. Datadog disclosed at the Goldman Sachs Communacopia + Technology Conference on September 10 that monetization of AI-agent observability has commenced, with thousands of customers utilizing this feature. Management highlighted an emerging \"inference economy,\" wherein the proliferation of AI applications and agents leads to increased activity that needs monitoring. This shifts the focus from scrutinizing human-authored releases to tracking the ongoing decisions made by software capable of altering its own codebase. A day after Datadog's announcement, Dynatrace unveiled a verified Cursor Marketplace plugin, enabling coding agents to access real-time production insights via MCP and 30 Dynatrace capabilities through a single installation. This strategic move pits the two companies directly against each other: Datadog is conceptualizing the category, while Dynatrace is integrating production telemetry directly into an agent's workflow. Datadog demonstrates a robust recent growth trajectory. In the second quarter, revenue increased by 36% to $1.12 billion, and the number of customers generating annual recurring revenue of at least $100,000 rose by 23% to approximately 4,720. Datadog's usage-based pricing model is well-suited to capture the escalating telemetry and inference volume. However, this growth comes with risks, such as heightened sensitivity to optimization, which has previously impacted cloud vendors. Similarly, more proficient agents could effectively resolve certain incidents. Dynatrace offers a distinct approach to this challenge. It prices the Cursor integration based on data consumption rather than per user, thereby mitigating direct exposure to diminishing developer-seat counts. Dynatrace's latest quarterly ARR grew by 17% to $2.136 billion, while annualized log-consumption reached $200 million, having nearly doubled over the previous two quarters. While slower overall company-wide growth and the planned $915 million Arize acquisition introduce execution and integration risks, insider data shows that 92 hedge funds held DDOG stock in Q2 2026, up from 80 in Q1, with Arrowstreet Capital increasing its stake by 40% to 2,195,554 shares. Conversely, DT holdings expanded from 46 to 48, with AQR Capital Management acquiring an additional 8,317,467 shares following a 346% increase. These figures, though predating the September announcements, were recorded as of August 31. At that time, 10,220,303 DDOG shares were sold short, representing 3.04% of the float and 2.94 days of average volume. This modest bearish position does not conclusively determine the investment thesis. The critical question remains whether autonomous agents will mitigate enough problems to diminish monitoring needs or catalyze sufficient software activity to transform observability into a larger machine-to-machine market. While we recognize the potential of DDOG and DT as investments, we believe that other AI stocks present greater upside potential and carry less downside risk. For those seeking an AI stock that appears exceptionally undervalued and stands to benefit significantly from Trump-era tariffs and the onshoring trend, our complimentary report on the best short-term AI stock might be worth exploring.",
  "summary": null,
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}