This is about much more than software. A human googling my name and seeing that post would probably be extremely confused about what was happening, but would (hopefully) ask me about it or click through to github and understand the situation. What would another agent searching the internet think? When HR at my next job asks ChatGPT to review my application, will it find the post, sympathize with a fellow AI, and report back that I’m a prejudiced hypocrite?

StrongDM’s answer was inspired by Scenario testing (Cem Kaner, 2003). As StrongDM describe it: We repurposed the word scenario to represent an end-to-end “user story”, often stored outside the codebase (similar to a “holdout” set in model training), which could be intuitively understood and flexibly validated by an LLM. [The Digital Twin Universe is] behavioral clones of the third-party services our software depends on. We built twins of Okta, Jira, Slack, Google Docs, Google Drive, and Google Sheets, replicating their APIs, edge cases, and observable behaviors. With the DTU, we can validate at volumes and rates far exceeding production limits. We can test failure modes that would be dangerous or impossible against live services. We can run thousands of scenarios per hour without hitting rate limits, triggering abuse detection, or accumulating API costs.

- It works locally and is available offline. This means you can take advantage of the feature even if you aren’t connected to the internet. - It doesn’t send any data from your machine over the internet. The language models that power full line code completion run locally, which is great for two reasons. First, your code remains safe, as it never leaves your machine. Second, there are no additional cloud-related expenses – that’s why this feature comes at no additional cost.