Datadog unveils 100+ features at DASH, pushing Bits AI toward autonomous operations

Datadog Expands Platform With Autonomous AI Operations

Datadog unveiled more than 100 new capabilities at its annual DASH conference, marking a significant expansion of its observability platform focused on autonomous AI operations and enhanced security controls1

1

. The company, which invests approximately 30% of revenue into research and development, centered its announcements around addressing two critical pressures reshaping enterprise technology: code being generated faster than humans can manage it and attackers using artificial intelligence to target critical systems2

2

.

Bits AI Gains True Autonomy Across Development Lifecycle

The centerpiece of the announcement involves major enhancements to Bits AI, Datadog's suite of agents built to automate development, security and operational workflows. Previously focused on investigating root causes, Bits AI now includes modules for Detection, Agent Evals, Infrastructure, Code, Release, Data Analysis, Testing and Chat3

3

. These additions enable the agents to detect, investigate and remediate problems by scanning infrastructure around the clock, recommending fixes and resolving them under predefined guardrails. The new Agent Eval feature allows Bits AI to debug and generate fixes for AI agents themselves, extending automation beyond traditional systems. Bits AI operates across the software development lifecycle by following each release and pull request from code change through staging, rollout and production, validating functionality at every step. Teams can access these capabilities through tools they already use daily, including Slack and Anthropic's Claude1

1

.

AI Guard Tackles Prompt Injection and Agent Poisoning Threats

To manage AI and security complexity, Datadog introduced AI Guard, a product specifically designed to counter prompt injection and agent poisoning attacks. "With AI agents operating with elevated privileges, accessing sensitive data and communicating externally, a single malicious prompt hidden in an innocuous-appearing prompt can turn a well-intended agent into a malicious actor leaking sensitive information," explained Tim Knudsen, vice president of security products at Datadog2

2

. AI Guard combines deep agent telemetry tracing with AI-native stateful behavioral anomaly analysis to detect and block attacks that stateless prompt-and-response checks miss, addressing sophisticated techniques attackers use to hide malicious instructions across multiple steps of agent behavior3

3

.

Custom AI Agent Creation and Monitoring Tools

Datadog also announced Bits Agent Builder, enabling custom AI agent creation inside the platform to automate incident remediation, generate tailored reports and enforce standards across environments within customer-defined controls1

1

. Complementing this, Agent Console provides centralized monitoring for AI agents and agentic developer tools like Claude Code, Cursor and GitHub Copilot. The console addresses a critical visibility gap, helping teams understand which users adopt agents most heavily, which tasks agents perform best, where they struggle, and how agent-produced work correlates with spending2

2

.

Bring Your Own Cloud Addresses Exploding Log Volumes

As AI volumes increase, log generation grows exponentially, forcing companies to choose between retaining data and absorbing costs or deleting it and losing visibility. Datadog's Bring Your Own Cloud deploys the platform inside a customer's own environment, processing and indexing data in their cloud object storage rather than moving it out3

3

. Co-founder and CEO Olivier Pomel framed the launches as a strategic bet: "The companies that win on AI won't just build better models, they'll build operational control around them." The releases signal Datadog's view that operational control and automation, rather than model quality alone, will determine which organizations succeed as AI agents take on more critical roles with elevated privileges across infrastructure.