Generative AI has become particularly relevant to developers because modern AI systems can assist with programming, debugging, documentation and software-related tasks.
At a broader level, Generative AI refers to systems that generate new content based on learned patterns and contextual input. This can include text, images, audio, video and source code.
Large language models are one important category within the broader Generative AI ecosystem. Foundation models can provide capabilities that are adapted for different applications.
For developers, however, generated code should not be treated as automatically production-ready.
Testing, code review, dependency checks, security assessment and human understanding remain essential.
The Campus Review guide explains the fundamentals behind Generative AI and covers foundation models, transformers, tokens, multimodal systems, coding applications, AI risks and responsible use.
It provides useful context for developers who want to understand not only how to use AI coding tools, but also the technology behind them.
Explore the Generative AI guide
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