Using GPT at Work

Socket has been leveraging GPT as an internal tool to aid in the triage of the npm package firehose, particularly after the introduction of ChatGPT, which has heightened enthusiasm for large language models. While these models offer significant strengths, such as providing quick summaries to prioritize auditing, they also have limitations, including susceptibility to false positives and negatives and constraints on analyzing large files due to token limits. Socket addresses these challenges by segmenting code for analysis and adjusting AI parameters like temperature to maintain a balance between accuracy and paranoia. Although GPT is not poised to replace human roles entirely due to its vulnerability to evasion tactics like misleading comments, it serves as a valuable tool for summarization and triaging, even as humans must still verify the results. The use of GPT in this context reflects a broader trend of integrating AI into existing workflows while acknowledging its current limitations and the ongoing need for human oversight.

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