How One Engineering Team is Scaling AI Agents Using AI Observability

New Relic's internal engineering and data science team has transitioned from manual debugging to using New Relic AI Monitoring (AIM) for intelligent observability of AI agents, significantly enhancing their ability to scale and optimize agent performance and costs. This shift allowed the team to automate telemetry tracking, streamline debugging, and optimize costs through continuous observability across staging and production environments. By leveraging AIM, the team improved their workflows, managed AI agent performance, and ensured cost-effective solutions by monitoring token usage and response times, thus enabling them to focus on developing the next generation of AI agents. The adoption of AIM also facilitated faster development processes with automated tracking and out-of-the-box metrics, allowing the team to move away from building custom tools and concentrate on innovation.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.