Explores how AI boosts coding speed but highlights alignment as the true bottleneck in software development.
How AI accelerates code output, creating a review bottleneck, and strategies to rebalance the development pipeline.
Analysis of structural failure modes when using LLMs as security scanners in agentic workflows, with measurement ideas and evidence.
Explores how AI-generated code creates invisible cognitive debt, making code harder to understand and maintain, as flagged by Thoughtworks Technology Radar.
GitHub Copilot Rubber Duck uses a second AI model to review code plans, catching subtle errors in multi-file tasks.
How queueing theory from hospital ERs can optimize your team's pull request code review process.
Analysis of how slow code reviews silently kill team velocity, with metrics and solutions for engineering managers.
A developer shares how they use Claude Code for 90% of code in the Hegel project, emphasizing human review and design control.
How AI has reshaped the role of a great software engineer, shifting focus from writing code to reviewing AI-generated code and prioritizing business value.
Explores how AI coding agents shift programming from craft to high-level oversight, diminishing the art of detailed code.
Explores the evolving value of code review in the AI era, where AI agents generate and review code, challenging traditional human review processes.
Article discusses the true purpose of code review beyond bug-finding, emphasizing judgment, communication, and codebase health.
A Django core developer warns against over-reliance on LLMs in open-source contributions, emphasizing the need for human understanding.
A Django core developer warns against over-reliance on LLMs in open-source contributions, emphasizing the need for human understanding.
Analyzes how AI is creating challenges for junior developers, arguing that advice to 'struggle harder' ignores systemic pressures.
Analyzes the hidden costs and skill erosion of using AI for coding, emphasizing the need for human oversight.
Explores how AI-assisted coding creates a bottleneck in code review, comparing it to historical industrial constraints and questioning sustainability.
Explains how stacked pull requests can speed up development by enabling parallel work and avoiding large, hard-to-review PRs.
Explores how AI-generated code overwhelms traditional peer review processes, highlighting existing flaws and proposing deeper evaluation methods.
Explores how managing multiple AI coding agents parallels tech leadership, shifting focus from code generation to orchestration and review.
