After Checkout, Get the First NoInfra Agent Running

Most agent projects lose momentum after the buyer says yes. The plan is selected, the account is created, and then the team falls into work that does not prove the agent: cloud accounts, server choices, provider keys, token budgets, firewall rules, deployment scripts, and a long list of responsibilities that appear before the first useful conversation.

That is the wrong order for an early agent experiment.

After checkout, the first milestone should be simple: get into a hosted workspace, choose the right runtime, confirm setup state, send a real first message, and decide whether the workflow deserves more investment. NoInfra is built around that sequence. It gives builders a product path where the checkout handoff points toward the agent, not a pile of infrastructure tickets.

Here is the practical checklist for the first session after checkout.

1. Start from the agent, not from the plan page

The first screen that matters is the workspace where the agent will run. A plan is only useful if it turns into a working loop, so do not spend the first session debating every possible future workload.

For a first NoInfra run, start with OpenClaw unless you already know you need a different runtime profile. OpenClaw is the straightforward choice for direct hosted agent use: give it a concrete job, inspect how it responds, and use that evidence to decide what comes next.

Hermes and NemoClaw are useful names to keep in mind, but they should not become day-one indecision. Hermes fits delegated longer-running workflows. NemoClaw fits secure Builder environments. Those distinctions matter once the workload shape is clearer. The first checkpoint is whether one real task can run in a hosted workspace without dragging the team into server setup.

2. Confirm the setup state before debugging the prompt

The most common post-checkout mistake is treating every failure as a prompt problem. Sometimes the prompt is fine and the environment is not ready yet.

Before rewriting instructions, check the workspace state:

• The selected agent exists in the workspace.
• The runtime setup has moved past initial provisioning.
• The first-run path is asking for the next user action, not silently waiting on setup.
• The page still points at the expected agent instead of sending you back to plans.

This is why visible deployment progress matters. A hosted agent can be created, provisioned, and nearly ready while still not being able to answer the first useful message. That difference should be visible to the operator. If the product says the runtime is still being prepared, wait for the setup path to finish. If it says the agent is ready, move to the response-path checks.

3. Check starter tokens before bringing provider keys

The point of starter tokens is to avoid making provider-key ownership the first blocker. NoInfra starts builders with managed starter tokens so the first experiment can happen before a team decides whose API key, billing account, quota policy, and spend controls should own the workload.

That does not mean tokens are invisible. A serious first run still needs a token sanity check:

• Is the workspace showing starter-token availability?
• Is the agent allowed to use the managed token path?
• Does the first message look like a normal request, or does it fail before the model call?
• If the task is large, can you shrink it into a smaller first proof?

The goal is not to burn through the largest possible request. The goal is to learn whether the agent can complete a representative loop. A short, concrete task is better than a vague essay prompt because it produces evidence quickly and makes failures easier to classify.

4. Send a first message that proves the loop

A useful first message is not "what can you do?" That prompt produces a tour, not proof.

Pick a task with a real input, a clear expected output, and a short completion window. Examples:

• "Summarize this support thread into the three decisions we need to make."
• "Turn this deployment note into a launch checklist with blockers first."
• "Review this onboarding text and identify the parts that would confuse a first-time agent user."
• "Draft the first reply to this customer using only the facts in the message."

The test should reveal whether the hosted agent can read the instruction, operate inside the expected context, produce usable output, and return control to the user. If the first message is too broad, you will not know whether a weak answer came from the prompt, the runtime, missing context, or an oversized task.

5. Classify the first failure precisely

If the first run fails, do not collapse every issue into "the agent is broken." Classify the failure.

Setup failure: the workspace or runtime is not ready, so the agent cannot start. Wait for provisioning or use the setup state to identify what is missing.

Access failure: the user is in the wrong account, the agent is not attached to the workspace, or the create-agent return path did not land where expected.

Token failure: the request cannot use starter tokens, the workspace has exhausted its allocation, or a token path needs attention before the model call.

Prompt failure: the agent answered, but the instruction was vague, overloaded, or missing the source material needed for the job.

Runtime fit failure: the job is better suited for a different runtime profile than the one selected for the first test.

This classification keeps the next action practical. A setup problem needs a setup fix. A prompt problem needs a smaller or sharper task. A runtime-fit problem needs a runtime decision. Those are different paths.

6. Decide what the second run should prove

The second run is where the experiment becomes useful. Once the first response works, resist the urge to jump straight into a giant workflow. Instead, choose the next proof boundary:

• Repeatability: can the agent do the same class of task twice with consistent output?
• Context: can it use the files, messages, or instructions the team actually relies on?
• Handoff: can a human review and act on the output without translating it?
• Runtime fit: is OpenClaw still the right runtime, or is the workload pointing toward Hermes or NemoClaw?
• Cost shape: is the task small enough to keep experimenting before committing more budget?

That second run tells you whether you have an agent worth improving or just a successful first response.

What checkout should not become

Checkout should not become a detour into cloud setup. It should not start with provider-key politics. It should not require a builder to decide the whole future architecture before one workflow has run.

The right post-checkout experience is narrower and more useful: create the hosted agent, watch the setup state, confirm starter tokens, send a concrete first message, classify any failure, and run the next proof.

That is how an agent experiment earns the next hour.

Create an agent on NoInfra and use the first session to prove one hosted loop before you buy more infrastructure or write more glue code: Create an agent.