Jordan Carroll

I chose Datadog because it gave me strong observability out of the box with minimal setup, which was important for moving quickly. Through their startup program, I also had access to credits and support, making it a practical choice early on. It lets me monitor and improve reliability without spending time building internal tooling.

I chose GitHub because it’s where developers already work. Pull requests are the natural place where decisions get made, so integrating directly into that workflow meant RaptorCI could deliver value without changing behaviour. It also gave me immediate distribution through the GitHub App ecosystem, which is critical at an early stage.

I chose AWS because I already had deep experience with it, which let me move quickly without needing to learn new tooling. Through AWS Activate, I also had access to credits and support, which made it a very practical choice at an early stage. It gave me a scalable, reliable foundation without slowing down development.

I chose Codex CLI because it fits how I like to build — fast, direct, and execution-focused. For RaptorCI, I needed something that could quickly generate, modify, and test code in tight loops. Codex leans towards autonomous execution and speed, which made it ideal for rapidly shipping the first version and iterating on real usage. Claude Code is great for deeper reasoning and structured collaboration, but I found Codex better suited for quickly turning ideas into working systems.