AI experiment quality

AI 실험 품질 관리

Separate the number of generated tests from validated learning.

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html
<div class="quality"><div class="qtitle">VOLUME ≠ LEARNING</div><div class="bars"><div class="track"><span>TESTS</span><i></i><b id="testcount">2</b></div><div class="track good"><span>LEARNINGS</span><i></i><b id="learncount">1</b></div></div><div class="qnote">EVIDENCE CHECK REQUIRED</div></div>
css
.quality{width:min(85%,500px);font:800 clamp(10px,max(1.8vmin,1vw),14px)/1.1 sans-serif}.qtitle{font-size:clamp(13px,3vmin,25px);margin-bottom:12px}.bars{display:grid;gap:12px}.track{display:grid;grid-template-columns:clamp(68px,16vmin,120px) 1fr 25px;align-items:center;gap:8px}.track i{height:clamp(17px,4vmin,34px);background:var(--fg);width:30%;transition:width .5s}.track.good i{background:var(--accent)}.qnote{color:var(--accent);text-align:right;margin-top:12px}
js
let n=2;const t=document.querySelector('#testcount'),l=document.querySelector('#learncount'),bars=document.querySelectorAll('.track i');function draw(){t.textContent=String(n);l.textContent=String(Math.floor(n/3));bars[0].style.width=Math.min(n*9,100)+'%';bars[1].style.width=Math.min(Math.floor(n/3)*12,100)+'%';n=n>=10?2:n+1}draw();setInterval(draw,600);

When AI drafts variants and reports quickly, test counts can rise easily. Experiment quality asks whether results are trustworthy and reusable in future decisions.

The demo's TESTS line climbs rapidly while LEARNINGS moves only after evidence checks. Count a learning when the hypothesis, data quality, and result review hold up.

Not every test needs to win. A surprising result has value if it was measured reliably and can inform the next decision.

When to use

Use it when AI increases test volume without improving decisions.

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