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Strangler Things: How to De-risk Legacy Code Migrations
Shawna Martell discusses a case study in which they disentangled systems with no customer impact and zero downtime, how they prioritize feature migration, tooling, and backwards compatibility.
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Building a Culture of Continuous Experimentation
Sarah Aslanifar discusses leveraging continuous learning to drive efficiency, eliminate waste, and significantly improve product outcomes, covering the crucial role of Minimum Viable Products (MVPs).
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Being a Responsible Developer in the Age of AI Hype
Justin Sheehy discusses the dramatic developments in some areas of artificial intelligence and the need for the responsible use of AI systems.
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Defensible Moats: Unlocking Enterprise Value with Large Language Models
Nischal HP discusses risk mitigation, environmental, social, and governance (ESG) framework implementation to achieve sustainability goals, strategic procurement, spend analytics, data compliance.
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When AIOps Meets MLOps: What it Takes to Deploy ML Models at Scale
Ghida Ibrahim introduces the concept of AIOps referring to using AI and data-driven tooling to provision, manage and scale distributed IT infra.
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The Incident Lifecycle: How a Culture of Resilience Can Help You Accomplish Your Goals
Vanessa Huerta Granda describes how to apply resilience throughout the incident lifecycle in order to turn incidents into opportunities, looking at real-life examples.
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Fast, Scalable, Secure: WebAssembly and the Future of Isolation
Tal Garfinkel discusses the isolation technologies that underlie WebAssembly, and the limitations of the current state-of-the-art.
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Reach Next-Level Autonomy with LLM-Based AI Agents
Tingyi Li discusses the AI Agent, exploring how it extends the frontiers of Generative AI applications and leads to next-level autonomy in combination with enterprise data.
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Kubernetes without YAML
David Flanagan discusses using programming languages to describe Kubernetes resources, sharing constructs to deploy Kubernetes resources, and making Kubernetes resources testable and policy-driven.
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Building a Successful Platform: Acceleration, Autonomy & Accountability
Smruti Patel discusses successful platform adoption. She explores topics including failed platform-building efforts, the three pillars of a successful platform, and more.
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Lessons Learned from Building LinkedIn’s AI Data Platform
Felix GV provides an overview of LinkedIn’s AI ecosystem, then discusses the data platform underneath it: an open source database called Venice.
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Unpacking How Ads Ranking Works @Pinterest
Aayush Mudgal discusses social media advertising, unpacking how Pinterest harnesses the power of Deep Learning Models and big data to tailor relevant advertisements to the pinners.
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