| (DTU creator here) I did have an initial key insight which led to a repeatable strategy to ensure a high level of fidelity between DTU vs. the official canonical SaaS services: Use the top popular publicly available reference SDK client libraries as compatibility targets, with the goal always being 100% compatibility. You've also zeroed in on how challenging this was: I started this back in August 2025 (as one of many projects, at any time we're each juggling 3-8 projects) with only Sonnet 3.5. Much of the work was still very unglamorous, but feasible. Especially Slack, in some ways Slack was more challenging to get right than all of G-Suite (!). Now I'm part way through reimplementing the entire DTU in Rust (v1 was in Go) and with gpt-5.2 for planning and gpt-5.3-codex for execution it's significantly less human effort. IMO the most novel part to this story is Navan's Attractor and corresponding NLSpec. Feed in a good Definition-of-Done and it'll bounce around between nodes until it gets it right. There are already several working implementations in less than 24 hours since it was released, one of which is even open source [0]. [0] https://github.com/danshapiro/kilroy |
Why the switch from Go to Rust?