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Datadog Introduces New AI Agents

Datadog introduced three new AI agents that perform interactive investigations and asynchronous code fixes for development, security and operations teams.

The launch of the Bits AI SRE, Bits AI Dev Agent and Bits AI Security Analyst agents, alongside the new Proactive App Recommendations and APM Investigator capabilities, marks the continued evolution of Bits AI, Datadog’s generative AI assistant that helps engineers resolve application issues in real time.

Datadog’s new domain-specific AI agents, unveiled at DASH, are each trained to be experts in incident response, product development and security. The agents are built on a flexible system of shared tasks—core capabilities such as querying data, analyzing anomalies or scaling infrastructure that can be reused across agents. The architecture allows Datadog to build and deploy new agents quickly while maintaining a consistent and powerful user experience. This is combined with expansive, high-quality observability data, enabling Datadog’s AI capabilities to operate with context and precision, and deliver insights and actions to eliminate risk.

“Datadog is uniquely positioned to deliver value with AI as a platform that has a wealth of clean, rich data—we process trillions of data points and are embedded in our customers’ critical engineering, developer and security workflows,” said Yanbing Li, Chief Product Officer at Datadog. “With these advancements in AI reasoning and multi-modality, we’ve gone beyond helping organizations understand their availability, security, performance and reliability. We now enable human-in-the-middle workflows by guiding customers on what to look for and where to start looking, and augment their ability to take action.”

The new AI agents announced at DASH are:

  • Bits AI SRE, a 24x7 on-call responder that is now in Limited Availability. For all alerts, Bits AI SRE performs early triage using telemetry and service context to surface initial investigation findings all before responders log in. It assigns appropriate owners, aligns all parties with real-time incident summaries and status updates, and proactively suggests next steps. It also generates a first draft of the incident post-mortem to save responders time.
  • Bits AI Dev Agent, now in Preview, which detects issues, generates code fixes, and opens pull requests tailored to organizations’ technology stack to allow users to quickly review and merge changes directly within their SCM. As a result, engineers don’t just have software that surfaces errors—they have an AI teammate that helps fix the issue and improve productivity for human resources.
  • Bits AI Security Analyst, which autonomously triages Cloud SIEM (security information and event management) signals, conducts in-depth investigations of potential threats and delivers reasoned resolution recommendations without human prompting. Bits AI Security Analyst, now in Preview, automates investigations and reduces response times, fundamentally transforming how organizations process security signals.

Additional Applied AI capabilities in preview include:

  • Proactive App Recommendations, which continuously analyzes telemetry Datadog already collects to suggest high-impact fixes and the next best action. Whether it’s optimizing a slow query, addressing inefficient code paths or catching recurring exceptions, APM Recommendations shows developers exactly where to improve performance, reduce errors and cut down resource usage—all before users are affected.
  • APM Investigator, to help engineers troubleshoot and resolve latency spikes faster. It automates a previously manual process by identifying bottlenecks, scoping impact, highlighting patterns across slow traces, suggesting likely causes and proposing a fix.

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Datadog Introduces New AI Agents

Datadog introduced three new AI agents that perform interactive investigations and asynchronous code fixes for development, security and operations teams.

The launch of the Bits AI SRE, Bits AI Dev Agent and Bits AI Security Analyst agents, alongside the new Proactive App Recommendations and APM Investigator capabilities, marks the continued evolution of Bits AI, Datadog’s generative AI assistant that helps engineers resolve application issues in real time.

Datadog’s new domain-specific AI agents, unveiled at DASH, are each trained to be experts in incident response, product development and security. The agents are built on a flexible system of shared tasks—core capabilities such as querying data, analyzing anomalies or scaling infrastructure that can be reused across agents. The architecture allows Datadog to build and deploy new agents quickly while maintaining a consistent and powerful user experience. This is combined with expansive, high-quality observability data, enabling Datadog’s AI capabilities to operate with context and precision, and deliver insights and actions to eliminate risk.

“Datadog is uniquely positioned to deliver value with AI as a platform that has a wealth of clean, rich data—we process trillions of data points and are embedded in our customers’ critical engineering, developer and security workflows,” said Yanbing Li, Chief Product Officer at Datadog. “With these advancements in AI reasoning and multi-modality, we’ve gone beyond helping organizations understand their availability, security, performance and reliability. We now enable human-in-the-middle workflows by guiding customers on what to look for and where to start looking, and augment their ability to take action.”

The new AI agents announced at DASH are:

  • Bits AI SRE, a 24x7 on-call responder that is now in Limited Availability. For all alerts, Bits AI SRE performs early triage using telemetry and service context to surface initial investigation findings all before responders log in. It assigns appropriate owners, aligns all parties with real-time incident summaries and status updates, and proactively suggests next steps. It also generates a first draft of the incident post-mortem to save responders time.
  • Bits AI Dev Agent, now in Preview, which detects issues, generates code fixes, and opens pull requests tailored to organizations’ technology stack to allow users to quickly review and merge changes directly within their SCM. As a result, engineers don’t just have software that surfaces errors—they have an AI teammate that helps fix the issue and improve productivity for human resources.
  • Bits AI Security Analyst, which autonomously triages Cloud SIEM (security information and event management) signals, conducts in-depth investigations of potential threats and delivers reasoned resolution recommendations without human prompting. Bits AI Security Analyst, now in Preview, automates investigations and reduces response times, fundamentally transforming how organizations process security signals.

Additional Applied AI capabilities in preview include:

  • Proactive App Recommendations, which continuously analyzes telemetry Datadog already collects to suggest high-impact fixes and the next best action. Whether it’s optimizing a slow query, addressing inefficient code paths or catching recurring exceptions, APM Recommendations shows developers exactly where to improve performance, reduce errors and cut down resource usage—all before users are affected.
  • APM Investigator, to help engineers troubleshoot and resolve latency spikes faster. It automates a previously manual process by identifying bottlenecks, scoping impact, highlighting patterns across slow traces, suggesting likely causes and proposing a fix.

The Latest

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 4 covers negative impacts of AI ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 3 covers barriers and challenges for AI ...