Vighnesh Taunk: Welcome to IT Voice Tech News, Nic. It’s a pleasure to have you here today.
Nic Benders: Thank you, Vighnesh. Great to be here. I’ve been with New Relic for over 14 years now, moving between operations and software engineering roles. My journey began with the frustration of not being able to gather enough quality insights about my running systems. That’s when I decided to join New Relic in 2010—to help solve that problem. Since then, we’ve been on a mission to make life easier for engineers by not just offering visibility, but by delivering deep understanding into how systems perform in real-world scenarios.
Vighnesh Taunk: That’s a great mission. For context, I’ve also worked as a software developer and product manager in my earlier roles, so I know firsthand how much of a difference tools like New Relic make. During my time at Yodlee, part of Envestnet, we used New Relic extensively.
Nic Benders: That’s always great to hear. I love connecting with people who’ve used the platform.
Vighnesh Taunk: Let’s begin with the most pressing topic today—AI. Everyone wants to get into it, whether or not it’s relevant to their field. As Chief Technology Strategist, can you share New Relic’s vision for AI and intelligent observability?
Nic Benders: Certainly. AI is both overhyped and underappreciated at the same time. It’s a bit like when public cloud computing was introduced. Initially, people didn’t understand its full potential. But over time, it transformed how we build and deploy software. I believe AI will transform the software industry faster than the public cloud did. At New Relic, we see ourselves evolving from being purely an instrumentation and data platform provider to being a platform that delivers understanding. We’re moving into what I call the “Intelligence Era” of observability.
Vighnesh Taunk: Absolutely. From my perspective, New Relic helps facilitate confident decision-making. With AI now more accessible than ever, how do you see cost reduction accelerating AI adoption? What are the main challenges enterprises face, and how does observability help mitigate them?
Nic Benders: Cost is always a factor, especially with newer technologies like AI. I often compare it to our journey into the public cloud. The capabilities were amazing, but the bills piled up quickly. Enterprises realized they needed better visibility and governance to manage cloud costs. The same is true for AI. Without observability, companies risk runaway costs. Our observability platform brings together cost data, performance data, and usage insights to give teams confidence while embracing AI.
Vighnesh Taunk: That makes a lot of sense. AI, at its core, is machine learning—and it’s only as good as the data it’s trained on. What steps does New Relic take to ensure data privacy while also improving AI accuracy and reducing model drift?
Nic Benders: Great question. At New Relic, data privacy is a cornerstone. We have strong data isolation mechanisms, certifications like FedRAMP, HIPAA, and we work with financial and healthcare institutions globally. We don’t pool customer data for training. Instead, we leverage anonymized time-series data or work within a customer’s own environment. This keeps boundaries intact while still delivering value.
Vighnesh Taunk: That’s reassuring. I’ve also read about the 20+ AI-powered features launched by New Relic. Could you elaborate on some impactful innovations and how non-technical users can benefit from them?
Nic Benders: Sure. One of our key AI features is Incident Response Intelligence. It uses LLMs to summarize what went wrong during incidents and provides recommended actions. We also introduced scorecards that unify team information and telemetry for smarter decision-making. Other offerings include Cloud Cost Intelligence and Service Architecture Scorecards. These tools aren’t just technical; they’re designed to provide context and actionable insights, even to non-technical users.
Vighnesh Taunk: Looking forward, what do you see as the next big shift in AI-driven observability? How will it further impact IT monitoring and optimization?
Nic Benders: I expect significant gains in agentic AI—where AI not only answers questions but executes tasks like refactoring code or managing dependencies. Auto-remediation, which once required a knock engineer or runbook, is becoming automated. I also see semantic joins between structured and unstructured data becoming standard. Eventually, AI won’t just live in chatbots but will be embedded throughout your observability platform.
Vighnesh Taunk: That’s insightful. So can users now simply ask questions like, “Why is my system behaving this way?” and get AI-driven guidance?
Nic Benders: Yes—and no. We already offer integrations with Amazon Q, GitHub Copilot, and others where you can ask such questions. But our long-term goal is a fully guided interface where every element is intelligent. We’re already using AI to summarize incidents and surface related documentation like retro notes, identifying the right person to talk to and previous fixes. That level of guidance is incredibly powerful.
Vighnesh Taunk: That’s impressive. Can you give us a sneak peek into your latest AI-powered observability tools?
Nic Benders: One recent launch is our Incident Response Intelligence feature. It summarizes alerts and suggests next steps, pulling from documentation and historical incident data. We’re also working on ensuring New Relic integrates with tools like GitHub Copilot and Amazon Q, making it easier to access insights without logging into the New Relic UI.
Vighnesh Taunk: That’s excellent. As we wrap up, what’s your vision for New Relic in this AI-powered future? And what advice would you give to businesses preparing for this transition?
Nic Benders: Our vision is threefold. First, we’ll continue delivering AI-powered tools to customers. Second, we’ll help customers monitor their own AI systems—from inference latency to prompt response. Third, we’re using AI internally to enhance our own productivity. My advice? Start using AI tools now. Gain hands-on experience so you’re ready when the next opportunity arrives. The future is not yet written, and it’s up to us to shape it.
Vighnesh Taunk: One final personal question—what’s your favorite LLM?
Nic Benders: Personally, I use a mix. OpenAI for tough questions, Anthropic for general use, and on-device models like Llama 3 for experimentation. At New Relic, we use a portfolio approach: combining premium frontier models with our own self-hosted SLMs and ML techniques. There’s no one-size-fits-all.
Vighnesh Taunk: That’s a smart approach. Thank you, Nic. It was an absolute pleasure speaking with you.
Nic Benders: Likewise, Vighnesh. Thank you for the thoughtful questions and engaging conversation.
