```html
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>ai implementation simulator</title>
<style>
body {
font-family: monospace;
background-color: #f0f0f0;
color: #333;
display: flex;
justify-content: center;
align-items: center;
min-height: 100vh;
margin: 0;
padding: 20px;
box-sizing: border-box;
}
#app {
background-color: #fff;
border: 1px solid #ddd;
padding: 2em;
max-width: 600px;
width: 100%;
box-shadow: 0 2px 5px rgba(0,0,0,0.1);
}
#metrics {
display: flex;
justify-content: space-around;
margin-bottom: 2em;
padding-bottom: 1em;
border-bottom: 1px dashed #ccc;
text-align: center;
}
#metrics div {
flex: 1;
}
#metrics span {
display: block;
font-size: 1.5em;
font-weight: bold;
}
#narrative {
margin-bottom: 2em;
line-height: 1.6;
text-transform: lowercase;
}
#choices {
display: flex;
flex-direction: column;
gap: 1em;
}
button {
width: 100%;
padding: 1em;
font-family: monospace;
border: 1px solid #333;
background-color: #fff;
cursor: pointer;
transition: background-color 0.2s, color 0.2s;
text-align: left;
text-transform: lowercase;
}
button:hover {
background-color: #333;
color: #fff;
}
</style>
</head>
<body>
<div id="app">
<div id="metrics">
<div>adoption <span id="adoption-stat">10</span></div>
<div>productivity <span id="productivity-stat">50</span></div>
<div>innovation <span id="innovation-stat">20</span></div>
</div>
<div id="narrative"></div>
<div id="choices"></div>
</div>
<script>
const gamestate = {
adoption: 10,
productivity: 50,
innovation: 20,
};
const scenarios = {
start: {
text: "you decide to roll out a new ai tool. the goal is company-wide adoption. your leadership team awaits your direction.",
choices: [
{
text: "mandate its use. monitor dashboards for compliance.",
effects: { adoption: -5, productivity: 5, innovation: -10 },
next: 'feedback_low_morale'
},
{
text: "encourage its use on existing tasks to make them faster.",
effects: { adoption: 5, productivity: 10, innovation: 0 },
next: 'feedback_stagnation'
},
{
text: "form pilot teams to redesign workflows around the tool.",
effects: { adoption: 10, productivity: -10, innovation: 10 },
next: 'feedback_high_engagement'
}
]
},
feedback_low_morale: {
text: "adoption is low. employees see the tool as surveillance. they fear being replaced.",
choices: [
{
text: "tie performance reviews to ai usage metrics.",
effects: { adoption: 5, productivity: 5, innovation: -20 },
next: 'ending_bad'
},
{
text: "offer bonuses for sharing novel uses that improve efficiency.",
effects: { adoption: 15, productivity: 10, innovation: 15 },
next: 'ending_mixed'
}
]
},
feedback_stagnation: {
text: "some tasks are faster but there is no revolution. the ai feels like a minor upgrade. a few people have ideas.",
choices: [
{
text: "tell them to focus on their current work. we need efficiency now.",
effects: { adoption: -5, productivity: 5, innovation: -15 },
next: 'ending_mixed'
},
{
text: "create a small, dedicated fund for employees to test their ideas.",
effects: { adoption: 10, productivity: -5, innovation: 20 },
next: 'discovery'
}
]
},
feedback_high_engagement: {
text: "the pilot teams have redesigned a key workflow. it requires new skills and collaboration between departments. productivity dipped during the trial.",
choices: [
{
text: "this is too disruptive. halt the redesign and revert to the old process.",
effects: { adoption: -15, productivity: 10, innovation: -10 },
next: 'ending_mixed'
},
{
text: "scale the new workflow. invest in training and reward teams.",
effects: { adoption: 20, productivity: 15, innovation: 10 },
next: 'discovery'
}
]
},
discovery: {
text: "an employee found a use for the ai that could create a new service offering. it seems promising but risky.",
choices: [
{
text: "thank them for the idea. a committee will evaluate it next quarter.",
effects: { adoption: 0, productivity: 0, innovation: -10 },
next: 'ending_mixed'
},
{
text: "give the employee a small team and budget to build a prototype.",
effects: { adoption: 10, productivity: -5, innovation: 30 },
next: 'ending_good'
}
]
},
ending_bad: {
text: "your ai implementation failed. usage is enforced but meaningless. employees are demoralized and innovation is gone."
},
ending_mixed: {
text: "your ai implementation had mixed results. you have pockets of efficiency and some novel ideas, but no unified transformation."
},
ending_good: {
text: "your approach was successful. by changing processes, aligning incentives, and empowering your team, you unlocked transformative value."
}
};
const narrativeel = document.getelementbyid('narrative');
const choicesel = document.getelementbyid('choices');
function updatemetrics() {
document.getelementbyid('adoption-stat').textcontent = gamestate.adoption;
document.getelementbyid('productivity-stat').textcontent = gamestate.productivity;
document.getelementbyid('innovation-stat').textcontent = gamestate.innovation;
}
function showscene(scenekey) {
const scene = scenarios[scenekey];
narrativeel.textcontent = scene.text;
choicesel.innerhtml = '';
if (scene.choices) {
scene.choices.foreach(choice => {
const button = document.createelement('button');
button.textcontent = choice.text;
button.onclick = () => {
for (let key in choice.effects) {
gamestate[key] += choice.effects[key];
}
updatemetrics();
showscene(choice.next);
};
choicesel.appendchild(button);
});
}
}
updatemetrics();
showscene('start');
</script>
</body>
</html>
```
co-evolutionary system. roles shift: product managers become goal curators, developers constraint engineers, qa behavioral auditors. new ai trainers refine models. software continuously adapts, learning from interaction and data. an urban planning ai models city growth, suggesting infrastructure changes based on citizen input via natural language and simulation, bridging expert urban planners with community needs.
generative expertise platform. roles shift: developers become knowledge architects, product managers synthesis directors. qa performs epistemic validation. ai prompters elicit insights. software generates knowledge, inferring and creating novel information. a legal research ai analyzes case law, drafting arguments and identifying precedents for lawyers, rendering complex legal data intuitively queryable.
autonomous intent realizer. roles shift: product managers are objective strategists, developers intent translators. qa becomes consequence analysts. ai operations overseers monitor. software converts intents into self-directed actions. a personalized education system demonstrates this: educators set goals, the ai crafts learning paths and content with adaptive feedback.