# Terminal-Universe: Turning Agent Trajectories into Scalable Terminal Environments Page: https://stenobird.com/podcast/daily-paper-cast-7079649/terminal-universe-turning-agent-trajectories-into-scalable-terminal-environments Text version: https://stenobird.com/podcast/daily-paper-cast-7079649/terminal-universe-turning-agent-trajectories-into-scalable-terminal-environments.md Podcast: [Daily Paper Cast](https://stenobird.com/podcast/daily-paper-cast-7079649) Published: 2026-09-04T07:39:34+00:00 Episode link: https://share.transistor.fm/s/041c078c Audio file: https://media.transistor.fm/041c078c/3871fca2.mp3 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/daily-paper-cast-7079649/episodes/terminal-universe-turning-agent-trajectories-into-scalable-terminal-environments Duration seconds: 1322 ## Resource šŸ¤— Upvotes: 23 | cs.AI, cs.CL Authors: Jie Wu, Zhenru Zhang, Beichen Zhang, Xuwu Wang, Yuhui Su, Mouxiang Chen, Peng Wang, Zhihai Wang, Que Shen, Hao Zhou, An Yang, Fei Huang, Yujiu Yang, Dayiheng Liu Title: Terminal-Universe: Turning Agent Trajectories into Scalable Terminal Environments Arxiv: http://arxiv.org/abs/2609.04148v1 Abstract: As terminal-based code agents become prevalent, agent trajectories have accumulated at scale, while realistic, executable environments remain scarce. However, environments are what agent post-training actually requires: each can be re-queried into many verifiable tasks and provides execution feedback, whereas a trajectory is a single frozen demonstration. Rather than generating environments from scratch, we observe that the tool-execution history in existing trajectories exposes the structure and contents of the environments in which they ran, making it possible to reconstruct those environments from the trajectories themselves. Thus, we introduce Terminal-Universe, a framework which turns each trajectory into a reusable environment and explores it for synthesizing new tasks and continued interactions. Specifically, Terminal-Universe replays the file operations recorded in a trajectory to restore each file before the agent modified it, yielding a partial workspace; a completion agent then supplies the missing files and dependencies. On this recovered workspace, we both reconstruct the original intent task and synthesize entirely new ones. Besides, we also scale the tasks along two complementary axes: breadth and depth. For breadth, we mine directional dependency relations between related environments and synthesize cross-workspace queries spanning multiple codebases, as developers routinely do in real-world development. For depth, we eā€¦ ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/daily-paper-cast-7079649/episodes/terminal-universe-turning-agent-trajectories-into-scalable-terminal-environments/transcription-requests` ā€” Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/daily-paper-cast-7079649/terminal-universe-turning-agent-trajectories-into-scalable-terminal-environments.md` ā€” Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.