9 posts tagged 'AI'
Oracle encourages internal AI coding but bans AI-generated code contributions to OpenJDK. We analyze why, and the implications for vibe coding and open source trustworthiness.
Google used AI to fix 1,072 security bugs in Chrome versions 149 and 150 alone, surpassing the total from the previous 23 releases. AI supports the entire workflow from vulnerability discovery, classification, to patch generation, saving developers significant time.
In the era of AI coding agents, going beyond the limitations of traditional tmux, we explore how comux — which integrates management of multiple agent sessions and contexts — will transform development workflows.
Analyzing three proposed LLM use cases in the Debian project, this piece illuminates how AI is being integrated into traditional open-source development processes, addressing trust issues and practical strategies.
As seen in the case of a startup that wasted $30,000 on AI tokens in a month, inefficient token usage by AI agents leads to serious cost issues. This article presents practical optimization strategies to improve the cost and performance of vibe coding by analyzing 6,780 public traces with CLI tools.
Analyzing the paradox that AI coding tools have increased productivity yet software quality is declining, and exploring the conditions for trustworthy vibe coding.
AI code review tools are spreading rapidly, but we can't leave everything to machines. We need a collaborative design that assigns repetitive pattern checks and coverage to AI, and leaves intention, context, and trade-off judgments to humans. We look at accumulating review results as reusable knowledge and the pros and cons of diff-based and report-based reviews.
Analyze the new horizon of team development collaboration brought by chat, AI, and Git integration, and examine scenarios and impacts where AI agents directly participate in code review, issue management, and deployment.
Claude Fable found a counterexample to the 87-year-old Jacobian conjecture, demonstrating AI's reasoning capabilities. We analyze the implications for software testing and bug detection, and introduce how developers can use AI to automatically discover edge cases.
