Dive Brief:
- Oracle built an AI-powered coding tool to help software developers accelerate processes and improve code consistency, the cloud company said Tuesday.
- The tool, called Oracle Code Assist, is optimized for Java, SQL and application development on Oracle Cloud Infrastructure. Businesses can tailor the assistant to match best practices based on internal code bases, libraries and policies. Oracle Code Assist can also help developers with context-specific suggestions, code analysis, test coverage generation and faster code reviews.
- Oracle developers are actively using Oracle Code Assist internally to build the company’s products and services, the company said. The tool will roll out to customers “in the future.”
Dive Insight:
Oracle is the latest provider to join an established trend among enterprise technology vendors. The rise of generative AI enthusiasm led to a proliferation of coding tools powered by large language models.
The coding companion push hasn’t fully percolated throughout industries, but analysts expect that will change. While 10% of enterprise software developers deployed AI-powered coding tools early last year, around 75% will use the tools by 2028, Gartner predicts.
AI coding assistants have raised questions about the skills and training needed to support software development.
“Having a crisp mental model around a problem, being able to break it down into steps that are tractable, perfect first-principle thinking, sometimes being prepared (and able to) debate a stubborn AI — these are the skills that will make a great engineer in the future, and likely the same consideration applies to many job categories,” Marco Argenti, CIO at Goldman Sachs, said last month, writing in the Harvard Business Review.
There are already signs that junior back-end and full-stack developers are growing dependent on AI to get work done, according to a Docker report published last month.
With tool usage set to grow, organizations are sifting through the hype to identify roadblocks and necessary risk mitigation techniques.
Some industry experts believe it’s too early in the AI coding adoption cycle to know whether the tools will meet mounting expectations. But experts agree organizations that choose to move forward should do so with caution by proactively addressing security risks and adapting data protocols.
Guardrails are key for the more than half of businesses that encounter insecure, AI-powered coding suggestions sometimes or frequently, according to a Snyk survey.
