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Challenge 4: Go Live

Recap:

In Challenge 3, your project context file changed everything. AI knew your project from the first word of every conversation, and you used that speed to build ambitious features: integrating new data, adding domain-specific logic, and whatever your team chose to push toward. Your app went from displaying real data to being genuinely useful.

Then in Lesson 4, you zoomed out. You learned what deployment means: moving your app from your private Environment to a live URL that anyone can visit. You saw that your Save & Sync habit has been building toward this moment all along, that the deployment pipeline is already set up, and that going live is one prompt away. You ran the pre-flight check and made a game plan for this final sprint.

You also learned some important truths about AI-built software: the two-week cliff (things break when they interact), the validation gap (AI says it's done before you've verified it works), and why authoritative data sources matter more than AI-generated explanations. Those aren't reasons to hold back. They're reasons to ship thoughtfully.

This is it. Your final sprint. Time to ship.

The Challenge

Deploy your Vessel Traffic Dashboard to a live URL. Then add the capability the NTSB said VTS needs most: detection.

In 2016, the NTSB examined six VTS-area accidents and found a pattern: "action was not taken or need for action was not recognized" as collision risk developed. The watchstanders had the data. They didn't see the pattern in time. Your dashboard can help close that gap.

Deploy first. Get the URL working. Then use the remaining time to make the dashboard proactive: it should flag things that need attention before the watchstander has to notice them.

What to Build

Deploy first, then build detection capabilities.

  • Your Vessel Traffic Dashboard is deployed to a live URL: tell your AI coding assistant to deploy the project and get back a working URL that anyone can visit from any device
  • Fix any issues from the pre-flight check: if something was broken or outdated when you checked in Lesson 4, fix it now
  • Hazard correlation: the watchstander can see which vessels are near active navigational hazards (wrecks, light outages, pipeline operations, restricted areas). Your project has navigational warnings and broadcast warnings data. Cross-reference those with vessel positions so the watchstander doesn't have to check every warning against every vessel manually.
  • Vessel behavior detection: the dashboard flags vessels showing inconsistent or concerning data. A vessel reporting "Under way using engine" but showing zero speed. A vessel whose navigational status doesn't match its behavior. These are the patterns that precede incidents, and the dashboard should surface them.
  • Your live version reflects your latest work: save and sync so the live URL shows everything you've built

These are options for teams that finish the baseline capabilities. Your team can also define your own stretch goals.

  • Prioritized attention view: combine all flagged items (hazard proximity, behavior anomalies, weather impacts from Challenge 3, clearance issues from Challenge 3) into one ranked view. The watchstander sees the highest-priority situations first, not a flat list.
  • Combined risk assessment: pull together every signal the dashboard knows about and produce a per-vessel or per-situation risk summary. When the incoming watch takes over, they can read the risk picture in seconds.
  • Mobile-friendly: test your live URL on a phone. A watchstander might check the dashboard from a tablet on the watch floor. Tell your AI assistant to make the layout responsive if it isn't already.
  • About page: add a section explaining what the Vessel Traffic Dashboard is, who built it, and where the data comes from
  • Share it: share the live URL with someone and ask what they think. That's the ultimate test of whether what you built is useful.

Final Growth Check-in

There is a final growth check-in on the next page. Make sure to navigate there and fill it out before the final reflection begins.

Tips

  • Deploy first, detect second. Don't try to perfect everything before you deploy. Get the URL, confirm it works, then use the remaining time for detection capabilities. You can redeploy as many times as you want.
  • Use the game plan you made in Lesson 4. Your team already discussed what to tackle first. Stick to the plan, or adjust it now that you're in the sprint.
  • Test the live URL, not just the Live Preview. Open it in a new browser window or on a teammate's phone. Check the things that matter most: Do the assessments from Challenge 3 still work? Does the hazard correlation flag the right things? Do behavior anomalies surface correctly?
  • Detection is about patterns. Ask your AI assistant: "What patterns in our vessel data might indicate something needs attention? Look at speed versus navigational status, positions relative to hazard warnings, and any inconsistencies." Let it explore the data and propose what to flag.
  • If deployment fails, don't panic. Ask your AI assistant: "The deployment didn't work. Can you investigate why and fix it?"
  • Save and sync after each change. Make a change, verify it, then save and sync. The pipeline updates the live version automatically.

Go build. That's the brief. Spend the rest of this session block working on your challenge with your team. Your Facilitator will let you know when it's time for the Reflection.