The Build vs. Buy Debate, GenAI and Section 174 | Kelly Vaughn

On this week’s episode, our hosts Dan Lines and Conor Bronsdon are joined by long-time friend of the show, industry expert, and Director of Engineering at Spot AI, Kelly Vaughn. Together they tackle a range of topics, including how tax laws are impacting engineering teams, the evolving role of AI in software development, and the great build vs. buy debate.The conversation starts with Kelly and Dan’s takes on Section 174, which poses a looming threat to US tech companies. From there, they pivot to GenAI to discuss how you can measure its impact, leadership’s role in the process, and the importance of navigating this implementation wisely. They conclude by talking about Kelly’s recent article on the debate of building software in-house vs. buying third-party solutions, and why the answer isn’t black or white.Episode Highlights01:35 Section 174's impact on US tech companies08:01 Why intention matters for remote vs. in-person work12:46 Kelly and Dan’s take on what’s causing layoffs in tech18:21 What should leaders be doing to encourage Gen AI tool knowledge?24:28 How are we tracking the impact of Gen AI?31:50 How should organizations set up standardization?33:55 The great build vs. buy debate39:47 How the engineering leaders’ role has changed in recent yearsShow Notes:Lesson in Engineering Leadership | Kelly Vaughn | SubstackMeasuring Impact: GenAI Code | LinearBFoundation (Chronological Order) Series by Isaac AsimovWatch Foundation - Apple TV+OFFERS 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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