CLI coding agents rise, with Docker isolation to tame risk
Open-source, CLI-first coding agents are getting easier to use while new tools add Docker isolation to reduce security risk in real projects. Developers have more terminal-native options as open-source agents like OpenCode, Cline, and Aider gain traction for everyday coding flows, according to The New Stack’s overview of the space ([OpenCode, Cline, and Aider](https://thenewstack.io/open-source-coding-agents-like-opencode-cline-and-aider-are-solving-a-huge-headache-for-developers/)). A recent video argues for a terminal-based “Pi” coding agent that promises more user control than GUI assistants ([Pi Coding Agent](https://www.youtube.com/watch?v=hv0V0GJpC78&pp=ygUYQUkgY29kaW5nIGFnZW50IHdvcmtmbG93)). CLI momentum is also visible in a new community project, term-llm, a simple but rich command-line interface for working with LLMs ([term-llm](https://community.openai.com/t/new-project-term-llm-a-simple-and-rich-cli-for-using-llms/1371422)). Another video makes the case that agents pair naturally with text-first workflows like CLIs, Markdown, and JSON ([AI Agents LOVE CLIs](https://www.youtube.com/watch?v=-QznXY_pJvw&pp=ygUYQUkgY29kaW5nIGFnZW50IHdvcmtmbG93)). Security is catching up too: The New Stack highlights NanoClaw, which runs each agent in its own Docker container to contain tool-use and secrets exposure, addressing issues seen with OpenClaw’s looser model ([NanoClaw](https://thenewstack.io/nanoclaw-containerized-ai-agents/)). The pattern suggests a practical path to production: CLI agents plus per-agent container sandboxes.