Fix Your First Project tutorial parts 1-3

Part 1:
- Update "Online" → "Live" (UI terminology)
- Update "Attributes" → "JSON Configuration" (UI terminology)
- Remove redundant "Registry tab" step

Part 2:
- Simplify data verification section
- Remove redundant filter instructions

Part 3:
- Integrate machine address steps into test connection flow
- Improve step formatting and indentation

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: shannonbradshaw

docs/operate/hello-world/first-project/part-1.md

@@ -22,7 +22,7 @@ Before starting this tutorial, you need the can inspection simulation running. F
 2. Create a machine in Viam and get credentials
 3. Start the container with your Viam credentials
 
-Once you see "Can Inspection Simulation Running!" in the container logs and your machine shows **Online** in the Viam app, return here to continue.
+Once you see "Can Inspection Simulation Running!" in the container logs and your machine shows **Live** in the Viam app, return here to continue.
 
 {{< alert title="What you're working with" color="info" >}}
 The simulation runs Gazebo Harmonic inside a Docker container. It simulates a conveyor belt with cans (some dented) passing under an inspection camera. viam-server runs on the Linux virtual machine inside the container and connects to Viam's cloud, just like it would on a physical machine. Everything you configure in the Viam app applies to the simulated hardware.
@@ -78,7 +78,7 @@ After adding the camera component, you will see two items appear under your mach
 
 To configure your camera component to work with the camera in the simulation, you need to specify the correct camera ID. Most components require a few configuration parameters.
 
-1. In the **Attributes** section, add:
+1. In the **JSON Configuration** section, add:
 
    ```json
    {
@@ -141,10 +141,9 @@ The **ML model service** loads a trained model (TensorFlow, ONNX, or PyTorch) an
 Configure the `model-service` ML model service you just included in your configuration.
 
 1. In the `model-service` configuration panel, click **Select model**
-2. Click the **Registry** tab
-3. Search for `can-defect-detection` and select it from the list (a model that classifies cans as PASS or FAIL based on defect detection)
-4. Click **Choose** to save the model selection
-5. Click **Save** in the upper right corner to save your configuration
+2. Search for `can-defect-detection` and select it from the list (a model that classifies cans as PASS or FAIL based on defect detection)
+3. Click **Choose** to save the model selection
+4. Click **Save** in the upper right corner to save your configuration
 
 {{< alert title="Your own models" color="tip" >}}
 For a different application, you'd train a model on your specific data and upload it to the registry. The registry handles versioning and deployment of ML models across your fleet.

docs/operate/hello-world/first-project/part-2.md

@@ -69,27 +69,14 @@ Right click on **Data** to open in a separate tab.
 2. Click on an image to see the detection results for that image
 3. Click on a few other images to see how detection results vary for cans labeled `PASS` versus `FAIL`
 
-{{<imgproc src="/tutorials/first-project/data-tab-images.png" resize="x1100" declaredimensions=true alt="Data tab showing a grid of captured images from the inspection camera." class="imgzoom shadow">}}
+   {{<imgproc src="/tutorials/first-project/data-tab-images.png" resize="x1100" declaredimensions=true alt="Data tab showing a grid of captured images from the inspection camera." class="imgzoom shadow">}}
 
-**Verify the data includes:**
+   This captured data serves multiple purposes:
 
-- **Detection results**—Each row shows label (PASS/FAIL) and confidence score
-- **Camera images**—Click any row to see the image that was analyzed
-- **Timestamps**—When each capture occurred
-- **Machine ID**—Which machine captured it (matters when you have multiple stations)
-
-**Filter the data:**
-
-1. Click **Filter** and select your machine: `inspection-station-1`
-2. Set time range to "Last hour"
-3. You can also filter by component to see only vision service results or only camera images
-
-This captured data serves multiple purposes:
-
-- **Compliance**—Auditable record of every inspection
-- **Quality trends**—"FAIL rate increased 20% this week"
-- **Model improvement**—Export images of cans to retrain your ML model
-- **Incident review**—"Show me all FAILs from Tuesday's shift"
+   - **Compliance**—Auditable record of every inspection
+   - **Quality trends**—"FAIL rate increased 20% this week"
+   - **Model improvement**—Export images of cans to retrain your ML model
+   - **Incident review**—"Show me all FAILs from Tuesday's shift"
 
 ## 2.3 Summary
 

docs/operate/hello-world/first-project/part-3.md

@@ -143,14 +143,6 @@ The generated CLI creates your service with empty dependencies—fine for testin
 
 Why is this valuable? Traditional embedded development requires: edit code → build → deploy → test → repeat. With module-first development: edit code → run locally → see results on real hardware. The iteration cycle drops from minutes to seconds.
 
-**Get your machine address:**
-
-1. In the Viam app, go to your machine's **Configure** page
-2. Click the **Online** dropdown
-3. Click **Remote address** to copy your machine address
-
-{{<imgproc src="/tutorials/first-project/machine-address.png" resize="x1100" declaredimensions=true alt="Live dropdown showing Remote address option with machine address visible." class="imgzoom shadow">}}
-
 ### Step 1: Connect to Your Machine
 
 The generated `realMain` function creates your inspector with empty dependencies—useful for testing in isolation, but it can't access your remote machine. We'll replace it with code that:
@@ -200,25 +192,31 @@ func realMain() error {
 
 **Test the connection:**
 
-```bash
-go run cmd/cli/main.go -host YOUR_MACHINE_ADDRESS
-```
+1. In the Viam app, go to your machine's **Configure** page
+2. Click the **Online** dropdown
+3. Click **Remote address** to copy your machine address
 
-You'll see WebRTC diagnostic output as the connection is established. Look for these messages confirming the connection:
+   {{<imgproc src="/tutorials/first-project/machine-address.png" resize="x1100" declaredimensions=true alt="Live dropdown showing Remote address option with machine address visible." class="imgzoom shadow">}}
 
-```text
-Connecting to your-machine.abc123.viam.cloud...
-...
-successfully (re)connected to remote at address
-...
-Connected successfully!
-```
+4. ```bash
+   go run cmd/cli/main.go -host YOUR_MACHINE_ADDRESS
+   ```
+
+   You'll see WebRTC diagnostic output as the connection is established. Look for these messages confirming the connection:
+
+   ```text
+   Connecting to your-machine.abc123.viam.cloud...
+   ...
+   successfully (re)connected to remote at address
+   ...
+   Connected successfully!
+   ```
 
-If you see an error, verify:
+   If you see an error, verify:
 
-- Your machine is online (check the Viam app)
-- You're logged in (`viam login`)
-- The address is correct
+   - Your machine is online (check the Viam app)
+   - You're logged in (`viam login`)
+   - The address is correct
 
 ### Step 2: Access Remote Resources