Runs entirely locally: HTML, CSS, vanilla JavaScript — no external dependencies.
Goal
Start with a deliberately simple prompt, compare the result, then get creative. Participants experience chat mode and learn along the way: an open prompt gives the AI a lot of freedom — results vary.
Preparation
- An empty folder as a project (in Kiro via Open a project).
- Kiro in chat mode (default).
Part 1 – The first, open prompt
Everyone enters the same, deliberately plain prompt:
Create a timer using HTML, vanilla JavaScript and CSS without external dependencies.
Observe & compare
- Try the result briefly (open the file in the browser, see the box below).
- Compare as a group: the results will differ — countdown vs. stopwatch, different layout, different buttons, different colors.
- Discussion: Why? An open prompt leaves a lot of room for interpretation. The more precise the prompt (format, requirements, examples), the more predictable the result.
How to open the file in the browser: In the Kiro Explorer (left), right-click the HTML file → Reveal in File Explorer, then double-click it in Windows Explorer. It opens in the default browser. After changes, reload the page with F5.
Part 2 – Now get creative
No fixed prompt — participants design their timer to their own idea. They can rework the existing timer (follow-up prompt) or start from scratch.
Examples for inspiration (just ideas, feel free to find your own):
- „Turn the timer into a Rolex — an analog clock with hands and a classy look.“
- „Design the timer in Star Trek LCARS style with the typical colors and shapes.“
- „Build a Pomodoro timer (25 min work / 5 min break) with a progress ring.“
- „Make a retro flip-clock timer like an old split-flap display.“
- „Design a countdown in neon/synthwave style with a glow effect.“
Tip for good results: if you have a clear picture in mind, describe it (style, colors, behavior) — this shows how much more precise prompts steer the outcome.
Key takeaways
- Chat mode is ideal for fast, exploratory building.
- Same prompt ≠ same result: open prompts produce different outcomes.
- Precision (style, format, examples) makes results more predictable.
- Follow-up prompts build on the existing result (iterative working).