Uploaded August 2026 | Updated September 2026, 1 week ago
In this episode of Ship Happens, host Per Krogslund talks with Eric Bowman, CTO of King, about how AI is changing the fundamental constraints of software development. As AI makes writing and producing code dramatically faster, Eric argues that the bottleneck is shifting: the harder problem is increasingly deciding what to build, why to build it, and whether you're building the right thing in the first place.
Eric compares AI's impact on software development to the earlier acceleration brought by open source, while exploring what happens when teams can produce software faster than ever. They discuss the risks of the “myth of instant expertise,” how AI can reinforce existing cognitive biases, and why greater coding velocity doesn't necessarily translate into better products.
The conversation also explores how AI could reshape engineering organizations, enabling smaller, more full-stack teams and pushing the platform and domain split higher in the stack. But while AI can accelerate development, Eric argues that operations, incident response, judgment, and understanding context remain deeply human.
Per and Eric dig into the importance of prioritization, flow, and learning loops in an AI-powered development environment. Eric explains why teams need to get better at predicting outcomes, creating psychological safety, and shortening the distance between shipping something and learning whether it worked. He also looks ahead at how software development could change over the next five years, including his prediction that traditional code review may largely fade—and why human creativity could remain one of the hardest things for AI to replicate.
What You'll Learn
• How AI is changing the bottlenecks in software development
• Why faster coding doesn't necessarily mean faster product development
• What AI has in common with the acceleration brought by open source
• The risks of the “myth of instant expertise”
• How AI can amplify both strong and mediocre engineering practices
• Why AI could enable smaller, more full-stack engineering teams
• How the platform/domain boundary may change as AI improves
• Why operations and incident response remain deeply human
• Why productivity metrics aren't enough to measure AI's impact
• How prioritization and flow become more important as development speeds up
• Why fast learning loops are essential for AI-powered teams
• What Eric expects software development to look like five years from now
• Why traditional code review may eventually disappear
• Why human creativity could remain difficult for AI to replicate
In this episode of Ship Happens, host Per Krogslund talks with Eric Bowman, CTO of King, about how AI is changing the fundamental constraints of software development. As AI makes writing and producing code dramatically faster, Eric argues that the bottleneck is shifting: the harder problem is increasingly deciding what to build, why to build it, and whether you're building the right thing in the first place.
Eric compares AI's impact on software development to the earlier acceleration brought by open source, while exploring what happens when teams can produce software faster than ever. They discuss the risks of the “myth of instant expertise,” how AI can reinforce existing cognitive biases, and why greater coding velocity doesn't necessarily translate into better products.
The conversation also explores how AI could reshape engineering organizations, enabling smaller, more full-stack teams and pushing the platform and domain split higher in the stack. But while AI can accelerate development, Eric argues that operations, incident response, judgment, and understanding context remain deeply human.
Per and Eric dig into the importance of prioritization, flow, and learning loops in an AI-powered development environment. Eric explains why teams need to get better at predicting outcomes, creating psychological safety, and shortening the distance between shipping something and learning whether it worked. He also looks ahead at how software development could change over the next five years, including his prediction that traditional code review may largely fade—and why human creativity could remain one of the hardest things for AI to replicate.
What You'll Learn
• How AI is changing the bottlenecks in software development
• Why faster coding doesn't necessarily mean faster product development
• What AI has in common with the acceleration brought by open source
• The risks of the “myth of instant expertise”
• How AI can amplify both strong and mediocre engineering practices
• Why AI could enable smaller, more full-stack engineering teams
• How the platform/domain boundary may change as AI improves
• Why operations and incident response remain deeply human
• Why productivity metrics aren't enough to measure AI's impact
• How prioritization and flow become more important as development speeds up
• Why fast learning loops are essential for AI-powered teams
• What Eric expects software development to look like five years from now
• Why traditional code review may eventually disappear
• Why human creativity could remain difficult for AI to replicate
