6 posts tagged 'automation'
Placing human approval and review at points where failure costs are high—rather than full automation—protects quality in the AI era. This hands-on guide covers criteria for intervention points, audit trails, and designing a review experience.
Full automation spreads errors quickly and recovery costs are high. By involving humans only at decisive points where failure costs are high, recording approvals and reviews as audit trails, and designing a comfortable review experience, quality is preserved.
AI-powered vibe coding goes beyond mere code writing by removing unnecessary steps from the development process itself, shortening feedback loops. This article examines the shift in development paradigm through the lens of ‘removal’ rather than automation.
Analyzing a new paradigm where AI agents apply the ASD-STE100 standard to automate technical documentation and embed documentation quality gates into vibe coding workflows.
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.
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.
