AI Hype Cycle: How to Find Real and Practical vs. Shiny | OpenAI’s Louis Brandy

AI is the biggest hype cycle happening in tech right now, but how do you know what’s actually going to make an impact for your product and team vs. what’s just new and shiny?This week, LinearB COO & Co-founder Dan Lines sits down with Louis Brandy, Member of Technical Staff OpenAI and ex-VP of Engineering at Rockset. Louis shares his unique perspective on the evolution of AI, drawing from his experiences with early days AI work at Meta and now with OpenAI following their acquisition of Rockset. He shares grounded insights into the realities of AI, separating fact from fiction in an industry often clouded by buzzwords and unrealistic expectations.Listeners will learn about the practical applications of AI, the challenges and opportunities it presents, and how to go past the hype to find AI's potential. Whether you're an AI enthusiast, a skeptic, or a professional looking to understand the true impact of AI for engineering teams, this episode offers an insightful look at one of the most talked-about topics in tech today.Episode Highlights: 00:32 Louis Brandy's background with AI at Meta04:31 The current AI hype cycle13:09 How should engineering leaders think about AI and the pressure to use it?17:58 How to know if you’re falling into the hype cycle25:50 AI vs. human code34:42 Real time when it comes to AI38:36 What should an IC do about AI in their career path?Show Notes:OpenAI Acquires RocksetDownload your copy of the Essential Guide to Software Engineering Intelligence PlatformsOFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

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