Jemiah Sius
New Relic | Senior Director, Developer Relations
Miami, Florida, United States
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I am a Full-stack Engineer turned DevRel Engineer at New Relic. With a background in software engineering and marketing direction, my experience involves: designing and developing user interfaces, addressing customer/client pain points, marketing automation, and community development.
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Mastering Problem Solving in Engineering with Observability
Are you an engineer tasked with developing and tackling issues in modern applications? Discover how a strategic approach to problem-solving can enhance your efficiency. This session draws on insights from New Relic’s observability teams and their experiences with distributed systems, providing a structured blueprint for excelling in problem resolution. Learn about the critical tools and methodologies that have proven effective in diagnosing and resolving complex problems in production environments, enabling you to solve challenges more swiftly, effectively, and intelligently.
HOW WE BUILD SOFTWARE: A DEVELOPMENT AND COLLABORATION WORKFLOW TO MINIMISE CONTEXT SWITCHING
We'll start the workshop with a brief overview of CodeStream and the services it integrates with. We'll also take this time to help any attendees who want to work with us during the workshop through the initial CodeStream installation and set-up.
Then we'll begin our typical development day!
First up, we will walk through the most common workflow; grabbing a ticket with a known solution, writing some code, and creating a PR.
Next up, we'll triage a bug report. We'll see how you can view production errors and explore their stack traces from within your editor and how it can help you quickly identify the source of bugs. We'll also see how CodeStream's "request feedback" functionality, as well as its ability to share code directly to Slack and other messaging services, makes it easy to collaborate on complex code changes.
Once we've squashed the bug, it's time to perform a code review! We'll use CodeStream to view an open PR and perform our review. We'll also look at how viewing changes within the context of an entire codebase gives a better understanding of the wider implications of each merge.
Finally, we'll look at how CodeStream combines with other extensions to supercharge your development process. We'll finish the workshop by inviting some of our New Relic colleagues to join us in a remote mob programming session, which we'll coordinate and launch without ever leaving our IDE.
Throughout the workshop, attendees will be given the opportunity to practice with CodeStream by helping our host by pairing, reviewing their PRs, and providing code feedback within their editor
How to cure generative AI hallucinations with observability
Generative AI (GenAI) applications are known to “hallucinate,” or confidently respond with false or made-up information. Hallucinations are one of the biggest drawbacks to using this tech and are also famously hard to detect, prevent, and fix. But, researchers and engineers are racing to solve this problem as GenAI adoption increases.
So, for a DevOps team adopting this tech now, what’s the best way to tell when hallucinations happen, and most importantly, why?
Engineers, and the company’s bottom line, need a way to trace the path of the response—from the user’s prompt and integration with a large language model (LLM) to work by agents, API calls, and back to the end user. By monitoring every step, engineers can learn where hallucinations originate and apply a potential fix, like adding more context to the prompt or ensuring the LLM is re-summarizing responses accurately, so they can quickly take action and improve the quality of their results.
In this session, Jemiah Sius, Senior Director of Developer Relations at New Relic will explain how companies can use observability to help prevent GenAI hallucinations and share ways DevOps teams can improve their LLM integrations with context, agents, chained models, and more—with a focus on how to do it affordably.
In his role, Jemiah leads a global team focused on solving friction points for engineering teams—keeping them at the center of New Relic’s innovation strategy—so they can more easily find and fix issues before they impact their business and customers.
With that, he understands the challenges DevOps teams face and how, if deployed strategically, GenAI solutions can help solve those challenges.
Seeing the Unseen: How AI Observability Is Redefining Control in the Autonomous Enterprise
This session breaks down what true AI observability demands in high-stakes enterprise environments. We will explore how New Relic delivers deep, real-time insights into distributed AI pipelines, bridging the gap between model behavior, data flows, and infrastructure health. Attendees will learn actionable strategies to detect anomalies before they impact end users, along with a practical framework for implementing AI observability to build trust in autonomous decision-making systems.
- How modern enterprises are evolving toward autonomy, and why traditional monitoring tools can’t keep up.
- What “AI observability” really means in the context of mission-critical operations.
- How New Relic enables deep, real-time insights across distributed, AI-powered environments.
- Detecting anomalies, system state drift, and performance degradation before they impact customers.
- Practical steps to implement AI observability and build confidence in autonomous decision-making systems
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