2 min lesson
Base-model selection is itself a research decision
Respond to "Why is choosing a strong open MoE base for Composer 2 (rather than pretraining from scratch) consistent with the role's compute-efficiency bet?" Name the reason and the detail behind it.
Step 1 of 2
Base-model selection is itself a research decision. Picking a strong open MoE and applying continued pretraining plus RL is a compute-efficiency play: you spend FLOPs where they buy the most product quality instead of re-learning what a good base already knows.
Compile 2026 updates the model story: Composer 2.5The current Composer release, better at long-running tasks and at judging when a job needs a light touch versus deep work. Press Enter for the full definition. is the available model step to study now, while Cursor says it is training a significantly larger model from scratch with SpaceX using 10x more total compute. In an interview, keep those two facts separate: shipped capability versus future training direction.
The fourth bet from the JD shows up physically as infrastructure - the stack's bottom three layers above.
The ComposerCursor's own fast coding model, tuned for the editor and priced well below frontier models; the recommended day-to-day model for executing a plan. Press Enter for the full definition. reports and the Cursor TabCursor's original autocomplete: multi-line, edit-aware suggestions you accept with the Tab key. Press Enter for the full definition. online-RL blog post are the most impactful prep you can do. Reading them lets you reason from what the team actually did - base selection, sandbox infra, online RL on Tab - instead of generic RL theory. Cite a specific choice and ask a sharp question about it and you signal you'd fit the actual work.
Don't overstate exact numbers you can't source. It's stronger to say “Composer 2Cursor's in-house agentic coding model: frontier-level coding quality at high speed and low cost, built as a software-engineering specialist rather than a general-purpose model. Press Enter for the full definition. was reported to train on top of an open ~1T-param MoE base” and “Cursor says a larger from-scratch model is in training” than to assert a future model is already available. The team is full of truth-seekers; confident wrongness costs you more than a calibrated hedge.