GitHub recently added telemetry to its CLI tools, and it is enabled by default. In doing so, the platform is following a broader trend in developer tools, where usage data is used to improve products more quickly and better align them with real-world use cases.
At the same time, this default setting is sparking debate, especially now that CLI usage increasingly overlaps with AI-driven workflows via tools like GitHub Copilot. GitHub states that the telemetry is necessary to gain insight into how features are used—by both developers and AI agents—and to set priorities based on that data.
The collected data is pseudonymous and consists of technical and usage-related metadata, such as executed commands, flags used, and system information. GitHub aims to use this to better understand what users are encountering and which features are resonating with them. At the same time, The Register notes that there is no fully documented overview of all possible data points, which raises questions among some users.
Criticism of the silent introduction of telemetry
GitHub does indeed make it clear that telemetry is enabled by default and offers an opt-out option. But according to The Register, the criticism is that this wasn’t widely announced and is mainly documented in release notes. As a result, it can feel to users as though it was quietly enabled, even though it’s technically described as standard. That nuance is important because in practice, the difference between opt-in and opt-out often revolves less around the technology and more around expectations and communication.
The opt-out itself is simple. Users can disable telemetry via an environment variable, through the familiar “do not track” setting, or via the CLI configuration. This ultimately gives the developer control over what is shared. According to The Register, this mitigates the impact somewhat, though the default remains that data collection is active.
With this step, GitHub underscores how important data analysis has become for the development of tooling, especially now that AI plays an increasingly significant role in software development. At the same time, the discussion shows that transparency and clear communication are just as important for maintaining developers’ trust.