ars Technica AI·
Use of AI coding tools has become a convenient boogeyman for any tech issues.
Read full articleEveryone is adopting AI coding tools. Engineers are writing code faster than ever. But are organizations actually delivering value faster? That’s not obvious. I wrote Enabling Microservice Success with a big focus on engineering enablement, guardrails, automated testing, active ownership, and light touch governance. I didn’t know AI coding agents were coming, but it turns […]
Vibe coding and spec-driven development (SDD) are two emerging approaches where devops teams use AI to develop all of an application’s code. There are discussions about which approach to use for different use cases, and there are many platforms to consider with varying capabilities and experiences. Some experts question whether AI delivers reliable, maintainable applications, while others suggest that, at some point, AI can lead the end-to-end software development process. But one certainty IT organizations face is that there’s more demand for applications, integrations, and analytics than there is supply of agile teams and devops engineers. Compound this imbalance with business priorities to address application security vulnerabilities, modernize applications for the cloud, and address technical debt. It results in tough choices on what work to prioritize and where to drive efficiencies in the software development life cycle. Even before AI code generators emerged, IT leaders sought
Vibe coding and spec-driven development (SDD) are two emerging approaches where devops teams use AI to develop all of an application’s code. There are discussions about which approach to use for different use cases, and there are many platforms to consider with varying capabilities and experiences. Some experts question whether AI delivers reliable, maintainable applications, while others suggest that, at some point, AI can lead the end-to-end software development process. But one certainty IT organizations face is that there’s more demand for applications, integrations, and analytics than there is supply of agile teams and devops engineers. Compound this imbalance with business priorities to address application security vulnerabilities, modernize applications for the cloud, and address technical debt. It results in tough choices on what work to prioritize and where to drive efficiencies in the software development life cycle. Even before AI code generators emerged, IT leaders sought
iPhone maker warns about security risks as new software floods its review process
Plus: Major data breaches at a gym chain and hotel giant, a disruptive DDoS attack against Bluesky, dubious ICE hires, and more.
Learn 5 practical vibe coding best practices for Claude Code and coding agents: CLAUDE.md, planning, review agents, safer prompts, and diff review.
