Spin up sandboxed Linux containers pre-loaded with AI coding tools (Claude Code, Codex, OpenCode via mise). Each container gets SSH access, ZFS snapshot-based checkpoints, and network egress policies that control what the agent can reach. Managed entirely from the CLI over TrueNAS WebSocket API.
Anthropic’s prompt suggestions are simple, but you can’t give an LLM an open-ended question like that and expect the results you want! You, the user, are likely subconsciously picky, and there are always functional requirements that the agent won’t magically apply because it cannot read minds and behaves as a literal genie. My approach to prompting is to write the potentially-very-large individual prompt in its own Markdown file (which can be tracked in git), then tag the agent with that prompt and tell it to implement that Markdown file. Once the work is completed and manually reviewed, I manually commit the work to git, with the message referencing the specific prompt file so I have good internal tracking.
，这一点在heLLoword翻译官方下载中也有详细论述
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Pop culture picks – 1:08:21
复旦大学老龄研究院教授申琦将这种现象称为：老年人大模型使用中的“提问沟”。