#ai-code-generation

#ai-code-generation

There are these people that write software the old way, and the old way is going to go away. They call it 'vibe coding.' I think vibe coding is a slur. What's wrong with the term is that it implies ease. They don't understand that it's a skill.

This is a state where we see that the teams that move fastest will be the ones with clear tests, tight review policies, automated enforcement and reliable merge paths. Those guardrails are what make AI useful. If your systems can automatically catch mistakes, enforce standards, and prove what changed and why, then you can safely let agents do the heavy lifting. If not, you're just accelerating risk,

Company CEO David Mytton said the release of v1.0 of its Arcjet JavaScript SDK makes it possible for developers to address many of the issues as applications are being developed that DevOps teams would otherwise need to address later in the software development lifecycle (SDLC). Additionally, Arcjet is beta testing a similar SDK for Python developers, who often have even less application security expertise, added Mytton.

Using AI to help download photos so we can consolidate all our images into one place. Over the years, [Audrey](https://audrey.feldroy.com) and I have accumulated photos across a variety of services. Flickr, SmugMug, and others all have chunks of our memories sitting on their servers. Some of these services we haven't touched in years, others we pay for but rarely use. It was time to bring everything home.

Frontends are no longer written only for humans. AI tools now actively work inside our codebases. They generate components, suggest refactors, and extend functionality through agents embedded in IDEs like Cursor and Antigravity. These tools aren't just assistants. They participate in development, and they amplify whatever your architecture already gets right or wrong. When boundaries are unclear, AI introduces inconsistencies that compound over time, turning small flaws into brittle systems with real maintenance costs.

Generating code using AI increases the number of issues that need to be reviewed and the severity of those issues. CodeRabbit, an AI-based code review platform, made that determination by looking at 470 open source pull requests for its State of AI vs Human Code Generation report. The report finds that AI-generated code contains significantly more defects of logic, maintainability, security, and performance than code created by people.

Based on over 4,400 Java tasks, the report finds that depending on which of the four levels of reasoning capabilities that OpenAI now makes available, the overall quality of the code, especially in terms of the vulnerabilities generated, significantly improves. However, the overall volume of code being generated per task also substantially increases, which creates additional maintenance challenges for application developers that are not going to be familiar with how code might have been constructed in the first place.

Code Feedback MCP Server provides AI with real-time feedback necessary to ensure that code meets quality standards before it is deployed.