Optimizing AI Investment and Engineering Efficiency

Is your engineering team shipping more code but creating less business impact?

We're joined by Chris Westerhold, Global Practice Director at ThoughtWorks, to confront why engineering waste is so difficult to define and eliminate. He explains that for many teams, the issue isn't a lack of tools but a lack of a clear 'North Star' to align their efforts with real business goals, diving into why so much well-intentioned work results in wasted effort and increased friction.

Chris argues that most efficiency problems are rooted in people and processes, not technology, and why a 'systems thinking' approach is crucial for real improvement. He shares insights on balancing developer freedom with platform standardization and the leadership required to build a culture of continuous improvement. Learn why focusing on better outcomes—not just more code—is the key to unlocking your team's true potential.

Check out:

• The DevEx guide to AI-driven software development
• Workshop: The AI upgrade to your SDLC

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• LinkedIn: Chris Westerhold
• Learn more at ThoughtWorks.com

Referenced in today's show:

• Atlassian research: AI adoption is rising, but friction persists
• The New Skill in AI is Not Prompting, It's Context Engineering
• Introducing pay per crawl: enabling content owners to charge AI crawlers for access 
• Meta poached Apple’s head of foundation models with $200M offer - 9to5Mac 
• OpenAI Poaches 4 High-Ranking Engineers From Tesla, xAI, and Meta | WIRED 

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