WorkSeptember 18, 2026via InfoQ AI/ML
Presentation: Complexity and Creativity in Software Engineering
Why it matters
As AI code generation shifts engineering toward 'write-only' software, traditional workflows collapse. Leaders need new mental models—decoupling intent from implementation, automating reviews, building self-healing systems—to keep teams productive and creative rather than drowning in AI-generated code.
Key signals
- Shift to 'write-only software' driven by AI code generation
- Traditional pull request workflows breaking under AI velocity
- Decoupling intent from implementation as a management strategy
- Automating code reviews as a scaling lever
- Self-healing architecture as a complexity-management pattern
- Presenter: Phillip Mortimer (engineering leadership focus)
- Audience: senior engineering and architecture teams
- Shift toward 'write-only' software driven by AI code generation
- Traditional pull request workflows identified as broken for AI-assisted development
- Decoupling intent from implementation as core strategy for managing complexity
- Automation of code review processes as emerging practice
- Self-healing architecture as enabler for distributed AI-driven development
- Target audience: senior engineering and architecture teams adapting to AI workflows
The hook
Pull requests are broken. Here's how engineering leaders are rethinking code review in the age of AI generation.
Phillip Mortimer discusses the shift toward write-only software driven by AI code generation. He explains why traditional pull requests are broken and shares how engineering leaders can manage complexity by decoupling intent from implementation, automating code reviews, and building self-healing arc…