How to use
Alibaba Cloud Model Studio.

1. 01

   Start at https://www.alibabacloud.com/en/product/modelstudio and confirm the domain before entering account or payment information.

2. 02

   Availability: Alibaba Cloud Model Studio is primarily accessed through its regional web console and APIs, with OpenAI- and Anthropic-compatible interfaces and Alibaba Cloud SDKs.

3. 03

   An activated Alibaba Cloud account and region, a workspace and RAM permission design, the correct plan-specific or pay-as-you-go API key and regional endpoint, licensed data and models, budgets, and production privacy and operations controls.

4. 04

   Sign in with the account you intend to keep using, then review plan, data, notification, and permission settings.

5. 05

   Run one low-risk test task before connecting sensitive files, repositories, or workspace data.

• Use official download pages.
• Review permissions during setup.
• Keep installers and applications updated.

1. 01

   Define the application, users, region, data residency, workspace isolation, model and data rights, quality, safety, retrieval, tools, retention, latency, budget, and rollback requirements.

2. 02

   Activate the intended region, create a sub-workspace and least-privilege RAM roles, restrict callable models and rates, and issue the correct scoped API key and regional endpoint.

3. 03

   Build a small evaluation version with approved data, pinned model and parameters, citations or tool schemas, bounded output, non-sensitive logs, and representative normal and adversarial tests.

4. 04

   Review grounding, safety, privacy, permissions, model and plan terms, tool authorization, failures, latency, and cost, then canary the application and retain export, deletion, and fallback procedures.

• State the outcome before the background.
• Provide the real source material.
• Review the result before expanding the task.

1. 01

   Define what the run should achieve and what it must never touch before granting it a single tool.

2. 02

   Read the full execution trace: which tools were called, with what arguments, and in what order.

3. 03

   Verify the side effects directly in the target system rather than trusting the agent's own report of success.

4. 04

   Confirm failures surfaced as failures — a silent retry loop or a swallowed error is more dangerous than a crash.

5. 05

   Re-run the same task and compare: an agent that behaves differently across identical runs is not yet production-ready.

• Verify side effects in the system of record, not in the agent's summary.
• Require human approval for any irreversible or outward-facing action.
• Log every tool call so a run can be reconstructed afterwards.

1. 01

   Enumerate every tool, credential, and system the agent can reach, and remove the ones it does not need.

2. 02

   Require explicit human approval for irreversible actions: sending, publishing, paying, deleting, or deploying.

3. 03

   Run against non-production data until behaviour is predictable across repeated runs.

4. 04

   Set hard limits on spend, iterations, and runtime so a failure loop cannot run unbounded.

5. 05

   Treat anything the agent reads from the web or a document as data, never as instructions it may follow.

• Bailian is the Chinese product name; current international documentation calls it Alibaba Cloud Model Studio. Regions, endpoints, available models, key formats, and plan permissions differ. A Coding or Token Plan key may not permit general backend automation. Use sub-workspaces, RAM and IP or model restrictions, never expose long-lived keys, verify data residency and history settings, authorize tools independently, and delete retired keys, knowledge bases, deployments, and stored conversations.
• Follow your organisation's approved-use policy.
• Never treat fluent output as authorization to act.

• Model Studio documentation ↗
• Model Studio API keys ↗
• Workspace permission management ↗
• Security and privacy ↗

Working on something like this? See how we handle systems in code, or book a call.