New Relic Now October 2026 Round-up

AI can accelerate what we build while making it much harder to understand and operate what reaches production.

AI is helping engineering teams create software faster than ever, but faster creation doesn’t automatically mean more reliable production. As AI-generated code, applications, and agents move into the digital estate, they’re also introducing new dependencies, operational blind spots, and new forms of complexity for the teams responsible for keeping everything running. 

At New Relic Now this October, we focused on three challenges that stand between the speed of AI and confidence in production, and on the three pillars we are building to meet them. Platform Engineering needs to see everything they run, so our pillar for Platform Engineering gives them a live, self-maintaining map of services, owners, dependencies and AI components with a comprehensive infrastructure. AI requires additional ways to be proven in production. AI Observability evaluates the quality and safety of AI responses on live traffic and tracks what models and agents cost, as well as tracking model drift. Incidents need answers grounded in evidence, so Autonomous Operations grounds each investigation in a shared context and moves teams from alert to approved action, with people in command. All three pillars run on the same foundation of connected, trusted context.

That foundation becomes increasingly important as AI spans how software is built and how applications, infrastructure, AI workloads, and agents behave in production. Connected, trusted context brings telemetry, dependencies, ownership, organizational knowledge, and business context together, giving both people and AI stronger evidence to understand what’s happening, why it matters, and what should happen next.

At New Relic Now, we brought that strategy to life through three pillars.

1.  AI Observability 

Bring production trust to the AI lifecycle

Generative AI is now firmly embedded in the core of many  businesses, but the operational model surrounding isn’t keeping  pace. The challenge begins before AI applications ever reach production. Engineering teams are adopting AI coding assistants at remarkable speed, while organizations need better ways to understand how those tools are being used, what they cost, how they affect developer workflows, and whether sensitive information is being handled appropriately. 

Once AI applications reach production, the challenge expands. Traditional application health remains important, but teams also need visibility into model behavior, prompts and responses, token consumption, latency, retrieval quality, and the increasingly complex interactions among models, agents, tools, and services.

New Relic is extending observability across that AI lifecycle designed to give engineering teams a more connected view from development through production:

• AI Coding Observability: Understand how AI coding assistants are being used across engineering teams, including adoption, usage, cost, and potential security risks.
• AI Evaluation: Evaluate AI application responses for quality, relevance, and performance so teams can identify issues and improve experiences before they affect users.
• AI Agent Monitoring: Gain visibility into agent behavior, tool calls, handoffs, and workflows to understand how AI agents perform and troubleshoot problems faster.
• AI Observability for OpenTelemetry: Use OpenTelemetry GenAI telemetry to monitor AI applications and agents across models and tools while bringing that data into a connected observability experience.

Together, these capabilities give teams the context to understand AI behavior, quality, cost, dependencies, and risk, making AI innovation more observable, measurable, and trustworthy from development through production.

2. Autonomous Operations 

Turn fragmented evidence into trusted investigation

Rarely do alerts provide a complete explanation of what changed, which parts of the environment are affected, or what the team should do next; the hard work for operations teams often comes after the alert arrives. Forming hypotheses, comparing evidence, and trying to establish a shared understanding of an incident before taking action is becoming increasingly difficult. As environments become more dynamic, the consequences of operations teams acting on incomplete information multiply. 

Building a shared, trustworthy understanding of the problem is critical for operations teams when an alert arrives. New Relic Ground Truth, New Relic Autopilot, and New Relic Ground Truth CLI each help teams reach that understanding sooner. 

• New Relic Ground Truth: Brings New Relic’s trusted operational context into the developer’s terminal, giving developers and SREs access to relevant telemetry, changes, dependencies, and organizational knowledge without leaving their existing workflows. 
• New Relic Autopilot: Investigates operational issues using New Relic’s operational intelligence, evaluates the available evidence, and helps teams understand what happened, why it matters, and where to investigate next.
• New Relic Ground Truth CLI: Brings New Relic’s trusted operational context directly into the terminal, giving developers and SREs access to relevant telemetry, changes, dependencies, and organizational knowledge without leaving their existing workflows. 

Together, these capabilities help teams spend less time assembling and reconciling evidence, reach a shared understanding sooner, and make decisions with greater confidence. People remain in control of the response, while New Relic provides the context, evidence, and guidance they need to determine what should happen next. 

This trusted investigation also provides a foundation for the broader Autonomous Operations vision: as trust, governance, and AI capabilities mature, teams can progressively coordinate more operational work while maintaining human oversight and control.

3. Platform Engineering 

Build the foundation for a changing platform engineering  mandate

Platform engineering teams are now expected to help developers ship quickly and reliably while managing fragmented infrastructure, growing observability costs, disconnected inventories, governance requirements, and an expanding AI footprint. Many teams still rely on spreadsheets, CMDBs, custom portals, and disconnected views to answer basic questions about what exists, who owns it, what changed, and how systems relate. At the same time, engineering leaders want evidence that standards and observability maturity are improving across large service estates, and a clear view of where to invest next.Platform engineering  teams need a connected operational foundation that continuously reflects their environment while giving developers a simpler, more reliable path to build and operate software.New Relic delivers that foundation in two connected parts: engineering excellence at scale, and infrastructure observability at scale.

• Service Architecture Intelligence gives platform engineering teams an internal developer platform included with New Relic at no additional cost, built from live telemetry: catalogs of services and their relationships, teams and ownership, and scorecards that turn standards such as tagging and alerting coverage into an automated maturity model across services. 
• Infrastructure 360 gives platform engineering teams a unified view of their infrastructure resources. It discovers public cloud assets and flags missing coverage, maps app-to-infrastructure dependencies across Kubernetes, networks, load balancers and application gateways, and tracks configuration changes so teams can correlate them with performance issues.

Together, these capabilities help platform engineering teams move away from manually maintained inventories and fragmented operational views toward a connected experience built on live telemetry and open standards, where services and infrastructure share connected catalogs, common ownership and consistent scorecards.  Developers spend less time searching for context and navigating internal tooling, while platform teams gain greater visibility, stronger governance, and a more scalable foundation for supporting the business.Engineering leaders gain a measurable view of excellence, benchmarked against their own goals and their industry. 

Operate AI beyond human scale, with trust

For technology leaders deciding how to run AI in production while maintaining reliability and uptime across day-to-day operations, the three pillars answer one question: can your teams trust what AI helps them build, run and operate? Platform Engineering, AI Observability and Autonomous Operations each address a different part of that question and depend on connected, trusted operational context.

• Platform Engineering uses it to show what exists across the estate, how it connects, who owns it and how it is changing.
• AI Observability uses it to prove how AI behaves from development through production, including what it costs.
• Autonomous Operations uses it to turn scattered evidence into trustworthy investigation and, over time, governed and greater autonomy.

That context is the New Relic foundation. Telemetry, service relationships, changes, ownership, organizational knowledge and business context feed one intelligence foundation, and every part of the estate teams connect makes that intelligence more useful to people and to AI.

Software is moving faster, AI is becoming part of every stage of the engineering lifecycle, and the boundaries among development, platform engineering, and operations are becoming less distinct. That gives observability a larger role to play: becoming the trusted intelligence foundation connecting telemetry and operational context with developers, operators, platform teams, agents, workflows, customer experiences, and business outcomes.

The next era of AI will be measured by how much teams can trust their systems as well as by how autonomous those systems become. Trust starts with context: knowing what is running, how it connects, what changed, what the evidence shows and where human judgment still matters. With that context across the digital estate, people and AI can act with confidence today and build toward greater autonomy tomorrow.

Trusted context. Trusted AI. Trusted action. That is how New Relic helps enterprises run AI and the rest of their digital estate with confidence.

Join New Relic Now October 2026 to see Platform Engineering, AI Observability and Autonomous Operations in action, and to connect your next part of the estate.

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