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This work shows that reasoning traces are not a prerequisite: skills distilled from non-reasoning trajectories alone remain competitive with skills distilled from paired reasoning/non-reasoning corpora, with domain-dependent differences between the two sources.
It is shown that format choice remains important even after fine-tuning; models learn more efficiently with specific formats rather than adapting to any format; this finding allows format selection to be done via inference alone, avoiding costly trial-and-error fine-tuning runs.
A prototype of a Plan Mode for spreadsheet programming is built and evaluated against a non-planning baseline and it is found that using Plan Mode led to a reduction in refinement and a better perception of the tool across dimensions of creativity support and human-machine collaboration.
A three-level taxonomy inspired by autonomous driving that distinguishes degrees of autonomy along a roadmap from today’s AI-assisted development workflows to fully autonomous software development in which AI systems autonomously identify demands and design, implement, verify, and maintain software without human oversight is introduced.