Local agents can do far more than you think
Once a cloud agent is connected to your computer, it can use your real devices, intranet, local data, logged-in tools and GPU. Here is a collection of use cases that best show the benefits of running locally, each with an example you can use as-is.
少inMachine上Sign in AI Account: 用一个云端 agent Security地管很多电脑
每电脑都装一份 AI 工具, Sign in一次Account, 凭据散落各处, 容易被盗用, 也容易因as异常Sign in被风控. 用 dwb-bridge 让Account只留in一个地方, 合规又省心.
新Machine上 3 分钟让 agent 开工: 不用Install Codex, Claude Code
新服务器, 临时虚机, 同事的电脑......不用装 Node, 不用装任何本地 agent, 不用Sign in AI Account, 只装一个小程序, 云端 agent 就能直接in那Machine上干活.
Let a cloud agent debug on the real Android phone on your desk
There is no phone in a cloud sandbox. Once connected to your machine, the agent can install packages, read logs, take screenshots and reproduce crashes via adb, closing real-device issues on the spot.
Use your locally logged-in kubectl and cloud CLIs to let the agent manage cloud resources
No need to hand kubeconfig or AccessKey to any cloud environment. The agent reuses the CLI tools already logged in on your computer; checking clusters, viewing status and making changes all happen right in front of you.
Tens of GB of footage and a local GPU, handed to the agent without uploading
Moving large videos, model weights and huge logs to the cloud is slow and costly. Let the agent use the local GPU and disk on your workstation directly, with the results right at hand.
During live alerts, let the agent troubleshoot with you using your intranet access
Cloud agents can't reach the company intranet. Connect the on-call engineer's computer and it can use the local jump host tools, monitoring and log platforms to investigate, reaching a conclusion in minutes.
Local multi-service integration: have the agent run the whole environment for end-to-end tests
One feature touching three repos and five services? Have the agent bring up the whole environment with docker compose on your computer, change code across services and run end-to-end tests.
Hand repetitive computer tasks to the agent: file organizing, format conversion, weekly report generation
Batch renaming, archiving invoices by month, extracting info from a pile of documents, writing weekly reports from commit history... describe it once and the agent writes and runs a script on your computer.
Private dependencies, huge repos: let the agent refactor in your local repo
Can't pull dependencies from the company's private server, or the repo is too big to upload? The agent changes code, builds and runs tests directly in your local working copy and verifies results on the spot.
Let the agent analyze sensitive data without it leaving your machine
Customer lists, financial reports and user logs can't be uploaded to the cloud? Let the agent read, compute and chart them right on your computer; the raw data never leaves your machine.