Datadog has launched more than 100 new capabilities at DASH 2026, its annual product event held in Singapore on 9-10 June 2026, centred on making its Bits AI platform fully autonomous and introducing new defences against AI agent attacks.

The headline announcement is the expansion of Bits AI — Datadog’s suite of agents for automating development, security, and operational workflows — into what the company describes as truly autonomous operations. Bits AI can now automatically detect, investigate, and remediate issues by scanning infrastructure around the clock, surfacing problems, recommending fixes, and resolving them within pre-defined guardrails. New capabilities include Bits Detection, Agent Evals, Infrastructure, Code, Release, Data Analysis, Testing, and Chat. The platform is available on Slack and Claude.

AI Guard blocks agent prompt injection attacks

A second major announcement targets the security of AI agents themselves. Datadog’s new AI Guard uses a combination of deep agent telemetry tracing and AI-native stateful behavioural anomaly analysis to detect and block prompt injection and agent poisoning attacks — threats that stateless prompt-and-response evaluation systems miss. The product addresses a gap where AI agents operating with elevated privileges and external communications access can be hijacked by malicious instructions hidden within seemingly innocuous prompts.

Bring Your Own Cloud and Agent Console

Datadog also announced Bring Your Own Cloud (BYOC), which deploys the Datadog platform into a customer’s own cloud environment so that log data is processed and indexed in their own storage — addressing the cost and data sovereignty concerns arising from exponential AI-driven log volume growth.

Bits Agent Builder allows teams to create custom AI agents inside Datadog for remediation and operational automation. Agent Console provides centralised monitoring for AI agents and agentic developer tools including Claude Code, Cursor, and GitHub Copilot, giving engineering leaders visibility into how agents are being used, where they perform well, and how their output correlates with spend.

“AI has created new operational challenges where code development has outpaced human-scale management and malicious actors now use AI to attack critical systems. But AI didn’t create this complexity — it accelerated what was already there. The companies that win on AI won’t just build better models, they’ll build operational control around them,” said Olivier Pomel, co-founder and CEO at Datadog.