Eugene Yan · Tech & AI
TIER 4 2025-04-20
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<h1 class="title">An LLM-as-Judge Won't Save The Product—Fixing Your Process Will</h1>
<p class="date">
<info datetime="2025-04-20 00:00:00 +0000">
<span class="no-italics">[
<a class='tag' href="/tag/eval/">eval</a>
<a class='tag' href="/tag/llm/">llm</a>
<a class='tag' href="/tag/engineering/">engineering</a>
]
</span> · 5 min read
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<p>Product <a href="/tag/eval/" target="_blank">evals</a> are misunderstood. Some folks think that adding another tool, metric, or LLM-as-judge will solve the problems and save the product. But this sidesteps the core problem and avoids the real work. Evals aren’t static artifacts or quick fixes; they’re practices that apply the scientific method, eval-driven development, and AI output monitoring.</p>
<p><strong>Building product evals is simply the scientific method in disguise.</strong> That’s the secret sauce. It’s a cycle of inquiry, experimentation, and analysis.</p>
<p>It starts with <em>observation</em> aka Look at The Data™. This means examining our inputs, AI outputs, and how users interact with our systems. By looking at the data, we learn where the system works well, and perhaps more crucially, where it fails. Identifying these failure modes is the starting point for meaningful improvement.</p>
<p>Then, we <em>annotate</em> some data, prioritizing problematic outputs. This means labeling samples of successes and failures to build a balanced and representative dataset. Ideally, we should have a 50:50 split of passes and fails that spans the distribution of inputs. This dataset forms the foundation for targeted evals that track performance on the issues we’ve identified.</p>
<p>Next, we <em>hypothesize</em> why specific failures occur. Perhaps our RAG’s retrieval isn’t returning the relevant context, or maybe the model struggles to follow the complex—and sometimes conflicting—instructions. By looking at data such as retrieved documents, reasoning traces, and erroneous outputs, we can prioritize failures to fix and hypotheses to test.</p>
<p>Then, we <em>design and run experiments</em> to test our hypotheses. Experiments could involve rewriting prompts, updating retrieval components, or switching to a different model. A good experiment defines the outcomes that confirm or invalidate the hypotheses. Ideally, it should also include a baseline or control condition against which to compare.</p>
<p><em>Measuring outcomes and analyzing errors</em> is often the most challenging step. Unlike casual vibe checks, this requires quantifying whether an experiment’s updates actually improved outcomes: Did accuracy increase? Were fewer defects generated? Does the new version do better in pairwise comparisons? We can’t improve outcomes if we can’t measure it.</p>
<p>If an experiment succeeds, we apply the update; if it fails, we dig into the error analysis, refine our hypotheses, and try again. Through this iterative loop, product evals becomes the data flywheel that improves our product, reduces defects, and earns user trust.</p>
<p><img style="max-width: 100%" src="/assets/eval-method.webp" loading="lazy" title="Image" alt="Image" /></p>
<p class="image-caption">Applying the scientific method to building AI products.</p>
<p><strong>Eval-driven development (EDD) helps us build better AI products.</strong> It’s similar to <a href="https://en.wikipedia.org/wiki/Test-driven_development" target="_blank">test-driven development</a> where we write tests before implementing software that passes those tests. EDD follows the same philosophy: Before developing an AI feature, we define success criteria, via product evals, to ensure alignment and measurability from day one. Here’s a secret: Machine learning teams have practiced this for decades, where we build models and systems against <a href="https://en.wikipedia.org/wiki/Training,_validation,_and_test_data_sets" target="_blank">validation and test sets</a>. The ideas are similar though they have different names.</p>
<p>In EDD, evals guide our development. We start by evaluating a baseline, perhaps a simple prompt, to get an initial benchmark. From then on, every prompt tweak, every system update, every iteration, is evaluated. Did simplifying the prompt improve faithfulness? Did updating retrieval increase the recall of relevant documents? Or did the update worsen performance?</p>
<p>Because EDD provides immediate, objective feedback, we can see what’s improving and what’s not. This cycle—write evals, make changes, run evals, integrate improvements—ensures measurable progress. Instead of relying on vague, intuition-based perceptions, we build a feedback loop grounded in software engineering practices.</p>
<p><img style="max-width: 90%" src="/assets/edd.webp" loading="lazy" title="Image" alt="Image" /></p>
<p class="image-caption">First, write some evals; then, build systems that pass those evals.</p>
<p><strong>Human oversight is still needed even with automated evaluators (aka LLM-as-judge).</strong> While automated evals help scale monitoring, they can’t compensate for neglect. If we’re not actively reviewing AI outputs and customer feedback, automated evaluators won’t save our product.</p>
<p>To evaluate and monitor AI products, we typically sample outputs and annotate them for quality and defects. With enough high-quality annotations, we can <a href="/writing/aligneval/" target="_blank">calibrate automated evaluators</a> to align with human judgment. This could mean measuring recall or precision on binary labels, or correlation when deciding between outputs via pairwise comparisons. Once properly aligned, these evaluators help scale the continuous monitoring of AI systems.</p>
<p>But having automated evaluators doesn’t remove the need for human oversight. We still need to periodically sample and annotate data, and analyze user feedback. Ideally, we should design products that capture implicit feedback through user interactions. Nonetheless, explicit feedback, while less frequent and occasionally biased, can also be valuable. (Read <a href="/writing/llm-patterns/#collect-user-feedback-to-build-our-data-flywheel" target="_blank">more</a>.)</p>
<p>Also, while automated evaluators scale well, they aren’t perfect. But neither are human annotators. Nonetheless, by collecting more and higher-quality annotations, we can better align these evaluators. Organizational discipline is crucial to maintain this feedback loop of sampling data, annotating outputs, and improving automated evaluators.</p>
<p><img style="max-width: 100%" src="/assets/ai-monitoring.webp" loading="lazy" title="Image" alt="Image" /></p>
<p class="image-caption">Automated evaluators amplify our existing annotation and feedback processes.</p>
<p class="image-caption">• • •</p>
<p>While building with AI can feel like magic, building AI products still takes elbow grease. If teams don’t apply the scientific method, practice eval-driven development, and monitor the system’s output, buying or building yet another evaluation tool won’t save the product.</p>
<p>By the way, if you want to learn more about evals, my friends Hamel and Shreya are hosting their <em>final</em> cohort of “AI Evals for Engineers and PMs” in July. Here’s a <a href="https://maven.com/parlance-labs/evals?promoCode=eugene-is-all-you-need" target="_blank">35% discount code</a>.</p>
<br>
<p>If you found this useful, please cite this write-up as:</p>
<blockquote class="blockquote-citation">
<p>Yan, Ziyou. (Apr 2025). An LLM-as-Judge Won't Save The Product—Fixing Your Process Will. eugeneyan.com.
https://eugeneyan.com/writing/eval-process/.</p>
</blockquote>
<p>or</p>
<div class="citation"><pre><code>@article{yan2025eval-process,
title = {An LLM-as-Judge Won't Save The Product—Fixing Your Process Will},
author = {Yan, Ziyou},
journal = {eugeneyan.com},
year = {2025},
month = {Apr},
url = {https://eugeneyan.com/writing/eval-process/}
}</code></pre>
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box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
#algolia-fbt .ais-FrequentlyBoughtTogether-item:last-child {
margin-right: 0; /* No margin for the last item in the row */
}
/* Styling for images within recommendation items */
#algolia-fbt .ais-FrequentlyBoughtTogether-item img {
display: block; /* Can help remove extra space below image */
width: calc(100% - 4px); /* Full width minus 2px L/R margins */
max-width: 100%; /* Ensures image does not exceed container if intrinsically smaller */
/* height: auto; -- Controlled by inline style's max-height and object-fit */
object-fit: cover; /* Ensure image covers the area, also in inline style */
margin: 2px; /* 2px margin on top, left, right. Bottom is overridden by inline style. */
/* margin-bottom: 8px; -- This is set by inline style in JS template */
}
/* Styling for the wrapper link to make the whole card clickable */
#algolia-fbt .ais-FrequentlyBoughtTogether-item a.ais-FrequentlyBoughtTogether-item-link-wrapper {
display: block; /* Make the link fill the list item */
text-decoration: none; /* Remove underline */
color: inherit; /* Use parent's text color */
}
#algolia-fbt .fbt-product-title {
font-family: 'Raleway', Helvetica, sans-serif;
font-size: 0.75em;
display: -webkit-box;
-webkit-line-clamp: 2; /* Limit to 2 lines for WebKit browsers */
line-clamp: 2; /* Standard property */
-webkit-box-orient: vertical;
overflow: hidden;
text-overflow: ellipsis;
padding: 0 7px 7px 7px; /* 0 top, 7px L/R/B for text area */
line-height: 1.5; /* Adjust for better readability */
height: 3.3em; /* Current height: 3.3em. For 2 lines with 0.75em font & 1.5 line-height, calculated height would be 2.25em. */
color: var(--c-interactive); /* Use theme's interactive color */
}
/* This container will wrap the image and score, taking the original image's layout space. */
#algolia-fbt .ais-FrequentlyBoughtTogether-item .recommendation-image-container {
position: relative; /* For positioning the score absolutely within */
display: block; /* Matches original image display and ensures proper block layout */
width: calc(100% - 4px); /* Adopts width from original image styling */
margin: 2px; /* Adopts margin from original image styling */
margin-bottom: 8px; /* Adopts specific bottom margin from original image's inline style */
line-height: 0; /* Prevents unexpected space if child elements are treated as inline */
}
/* The image itself, now filling the container */
#algolia-fbt .ais-FrequentlyBoughtTogether-item .recommendation-image-container img {
display: block;
width: 100%; /* Fill the container's width */
max-width: 20em; /* Optional: retain original max-width constraint for the image content */
height: auto; /* Maintain aspect ratio by default */
max-height: 12em; /* Constrain image height (adjust as needed) */
object-fit: cover; /* Ensures image covers the allocated space, cropping if necessary */
margin: 0 auto; /* Center image if max-width kicks in and it's narrower than container */
}
/* The score overlay box */
#algolia-fbt .ais-FrequentlyBoughtTogether-item .recommendation-score {
position: absolute;
bottom: 3px; /* Padding from the bottom edge of the container */
right: 3px; /* Padding from the right edge of the container */
background-color: color-mix(in srgb, var(--c-background) 85%, var(--green) 15%); /* Theme-aware light green */
color: var(--green); /* Theme's green color for text */
padding: 3px 6px; /* Slightly adjusted padding */
font-family: 'Raleway', Helvetica, sans-serif;
font-size: 0.75em;
font-weight: bold;
border-radius: 10px; /* More rounded corners like the example */
border: 1px solid var(--green); /* Theme's green color for border */
line-height: 1; /* Critical for small text in a small box */
z-index: 10; /* Ensure it's above the image */
box-shadow: 0 1px 2px rgba(0,0,0,0.15); /* Softer shadow */
display: flex; /* To align icon and text nicely */
align-items: center; /* Vertically center icon and text */
}
/* Styling for the SVG icon within the score box */
#algolia-fbt .ais-FrequentlyBoughtTogether-item .recommendation-score-icon {
width: 0.9em; /* Scale with score's font size */
height: 0.9em;
vertical-align: -0.1em; /* Fine-tune vertical alignment */
margin-right: 4px; /* Space between icon and score number */
fill: var(--green); /* Theme's green color for icon */
}
</style>
<script type="aa092048b4a3b41eb259d730-text/javascript">
// Function to load a script and return a promise
function loadScript(src) {
return new Promise((resolve, reject) => {
if (document.querySelector(`script[src="${src}"]`)) {
resolve(); // Already loaded
return;
}
const script = document.createElement('script');
script.src = src;
script.onload = () => resolve();
script.onerror = () => reject(new Error(`Script load error for ${src}`));
document.head.appendChild(script);
});
}
function initAlgoliaRecommendations() {
Promise.all([
loadScript('https://cdn.jsdelivr.net/npm/algoliasearch@4/dist/algoliasearch-lite.umd.js'),
loadScript('https://cdn.jsdelivr.net/npm/instantsearch.js@4')
])
.then(() => {
// Initialize the Related Products widget
initRelatedProducts();
// Initialize the Frequently Bought Together widget
initFrequentlyBoughtTogether();
})
.catch(error => {
// Handle error silently
});
}
function initRelatedProducts() {
// Ensure container exists
if (!document.getElementById('algolia-related-products')) {
// Container not found, stopping initialization
return;
}
const recSearchClient = algoliasearch(
'2XJCLEABQD',
'b61ec4cb64bd32d62c053466fccbfa43'
);
const relatedSearch = instantsearch({
indexName: 'eugeneyan.com',
searchClient: recSearchClient,
clickAnalytics: true,
insights: true, // Enable insights for click tracking on recommendations
});
relatedSearch.addWidgets([
instantsearch.widgets.relatedProducts({
container: '#algolia-related-products',
objectIDs: ['/writing/eval-process/'],
limit: 3,
queryParameters: {
attributesToRetrieve: ['title', 'url', 'image', 'score', '_score'], // Specify only needed attributes
attributesToHighlight: [], // Disable highlighting
attributesToSnippet: [] // Disable snippeting
},
translations: {
title: '', // Custom title is in _layouts/post.html
},
transformItems: function(items) {
const containerElement = document.getElementById('algolia-recs-container');
const relatedElement = document.getElementById('algolia-related-products');
// Hide the Related Products container element first if there are no items
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relatedElement.style.display = 'none';
} else if (relatedElement) {
relatedElement.style.display = 'block';
}
// Then handle the main recommendations container visibility
if (items.length > 0 && containerElement) {
containerElement.style.display = 'block';
} else if (containerElement && !document.getElementById('algolia-fbt').hasChildNodes()) {
containerElement.style.display = 'none';
} else {
}
return items;
},
templates: {
header() { // Removed unused results, html parameters
// Return a PLAIN string for the header
return '<h4 class="algolia-recs-section-header">You Might Also Like (content-based)</h4>';
},
item: function(hit, { html, sendEvent }) { // Added sendEvent to params
const itemUrl = `${hit.url || '#'}`;
const indexName = 'eugeneyan.com'; // Get index name for insights
let imageUrl;
// Ensure hit.image is not null, undefined, or an empty/whitespace string before using it.
if (hit.image && typeof hit.image === 'string' && hit.image.trim() !== '') {
imageUrl = `/assets/og_image/${hit.image}`;
} else {
imageUrl = `/assets/og_image/default-v4.jpg`; // Default image
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let scoreValue = null;
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const scoreElement = scoreValue ? `<div class="recommendation-score"><svg viewbox="0 0 24 24" class="recommendation-score-icon" xmlns="http://www.w3.org/2000/svg"><path d="M16 6l2.29 2.29-4.88 4.88-4-4L2 16.59 3.41 18l6-6 4 4 6.3-6.29L22 12V6h-6z"></path></svg>${scoreValue}</div>` : '';
const imageAndScoreTag = `
<div class="recommendation-image-container">
<img src="${imageUrl}" alt="${hit.title || 'Recommendation cover image'}">
${scoreElement}
</div>`;
const title = hit.title || 'Untitled Post';
return `
<a href="${itemUrl}"
class="ais-RelatedProducts-item-link-wrapper"
onClick="${() => {
sendEvent('click', hit, 'Related Item Clicked');
}}"
>
${imageAndScoreTag}
<div class="related-product-title">${title}</div>
</a>
`;
},
empty(results, { html }) {
const containerElement = document.getElementById('algolia-recs-container');
const relatedElement = document.getElementById('algolia-related-products');
// Hide Related Products container since there are no results
if (relatedElement) {
relatedElement.style.display = 'none';
}
// Check if the FBT widget also has no items before hiding the main container
const fbtWidgetContainer = document.getElementById('algolia-fbt');
if (containerElement && (!fbtWidgetContainer || !fbtWidgetContainer.hasChildNodes())) {
containerElement.style.display = 'none';
}
// Return an empty string to prevent rendering 'undefined'
return '';
}
}
})
]);
relatedSearch.start();
}
function initFrequentlyBoughtTogether() {
// Ensure container exists
if (!document.getElementById('algolia-fbt')) {
// Container not found, stopping initialization
return;
}
const recSearchClient = algoliasearch(
'2XJCLEABQD',
'b61ec4cb64bd32d62c053466fccbfa43'
);
const fbtSearch = instantsearch({
indexName: 'eugeneyan.com',
searchClient: recSearchClient,
clickAnalytics: true,
insights: true, // Enable insights for click tracking on recommendations
});
fbtSearch.addWidgets([
instantsearch.widgets.frequentlyBoughtTogether({
container: '#algolia-fbt',
objectIDs: ['/writing/eval-process/'],
limit: 3,
queryParameters: {
attributesToRetrieve: ['title', 'url', 'image', 'score', '_score'], // Specify only needed attributes
attributesToHighlight: [], // Disable highlighting
attributesToSnippet: [] // Disable snippeting
},
translations: {
title: '', // Custom title is in _layouts/post.html
},
transformItems: function(items) {
const containerElement = document.getElementById('algolia-recs-container');
if (items.length > 0 && containerElement) {
containerElement.style.display = 'block';
} else if (containerElement && !document.getElementById('algolia-related-products').hasChildNodes()) {
containerElement.style.display = 'none';
} else {
}
return items;
},
templates: {
header() {
// Return a PLAIN string for the header - only if we have items to display
// The header should not render if there's no content
return '<h4 class="algolia-recs-section-header">Frequently Read Together (behavioral-based)</h4>';
},
item: function(hit, { html, sendEvent }) {
const itemUrl = `${hit.url || '#'}`;
const indexName = 'eugeneyan.com'; // Get index name for insights
let imageUrl;
// Ensure hit.image is not null, undefined, or an empty/whitespace string before using it.
if (hit.image && typeof hit.image === 'string' && hit.image.trim() !== '') {
imageUrl = `/assets/og_image/${hit.image}`;
} else {
imageUrl = `/assets/og_image/default-v4.jpg`; // Default image
}
let scoreValue = null;
if (typeof hit.score === 'number') scoreValue = hit.score.toFixed(2);
else if (typeof hit._score === 'number') scoreValue = hit._score.toFixed(2);
// else if (typeof hit.your_custom_score_field === 'number') scoreValue = hit.your_custom_score_field.toFixed(2);
const scoreElement = scoreValue ? `<div class="recommendation-score"><svg viewbox="0 0 24 24" class="recommendation-score-icon" xmlns="http://www.w3.org/2000/svg"><path d="M16 6l2.29 2.29-4.88 4.88-4-4L2 16.59 3.41 18l6-6 4 4 6.3-6.29L22 12V6h-6z"></path></svg>${scoreValue}</div>` : '';
const imageAndScoreTag = `
<div class="recommendation-image-container">
<img src="${imageUrl}" alt="${hit.title || 'Recommendation cover image'}">
${scoreElement}
</div>`;
const title = hit.title || 'Untitled Post';
return `
<a href="${itemUrl}"
class="ais-FrequentlyBoughtTogether-item-link-wrapper"
onClick="${() => {
sendEvent('click', hit, 'FBT Item Clicked');
}}"
>
${imageAndScoreTag}
<div class="fbt-product-title">${title}</div>
</a>
`;
},
empty(results, { html }) {
const containerElement = document.getElementById('algolia-recs-container');
const fbtElement = document.getElementById('algolia-fbt');
// Hide FBT container since there are no results
if (fbtElement) {
fbtElement.style.display = 'none';
}
// Check if the Related Products widget also has no items before hiding the main container
const relatedWidgetContainer = document.getElementById('algolia-related-products');
if (containerElement && (!relatedWidgetContainer || !relatedWidgetContainer.hasChildNodes())) {
containerElement.style.display = 'none';
}
// Return an empty string to prevent rendering 'undefined'
return '';
}
}
})
]);
fbtSearch.start();
}
document.addEventListener('DOMContentLoaded', function() {
let recsLoaded = false;
function checkLoad() {
if (recsLoaded) return;
if ((window.scrollY + window.innerHeight) >= document.body.scrollHeight - 500) {
recsLoaded = true;
window.removeEventListener('scroll', checkLoad);
initAlgoliaRecommendations();
}
}
window.addEventListener('scroll', checkLoad, { passive: true });
checkLoad();
});
</script>
</div>
<br>
<!-- <div id="algolia-recs-container" style="display: none;">
<div id="algolia-related-products" style="margin-bottom: 2em;"></div>
<style>
/* Common styles for both recommendation widgets */
.algolia-recs-section-header {
font-family: 'Raleway', Helvetica, sans-serif;
font-size: 1em; /* Adjust as needed, smaller than default h3 */
font-weight: bold;
margin-top: 0; /* Remove or reduce top margin */
margin-bottom: 15px; /* Space between header and recommendation cards */
color: var(--c-text); /* Use theme's text color */
font-style: italic;
}
/* Related Products Widget Styles */
#algolia-related-products .ais-RelatedProducts-list {
display: flex;
flex-direction: row; /* Arrange items horizontally */
flex-wrap: nowrap; /* Prevent wrapping to new lines, if possible */
justify-content: flex-start; /* Align items to the start of the container */
padding-left: 0; /* Remove default list padding */
list-style-type: none; /* Remove list bullets */
margin: 0;
}
#algolia-related-products .ais-RelatedProducts-item {
width: 32%; /* Adjust for 3 items: 32% * 3 items + 2% * 2 margins = 100% */
margin-right: 2%;
box-sizing: border-box; /* Include padding and border in the element's total width */
/* Optional: Basic card styling (uncomment to use) */
border: 1px solid color-mix(in srgb, var(--c-background) 85%, var(--c-text) 15%); /* Theme-aware light grey border */
padding: 0; /* Remove overall card padding, will be handled by elements */
text-align: left; /* Or 'center' if you prefer */
background-color: var(--c-background);
border-radius: 4px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
#algolia-related-products .ais-RelatedProducts-item:last-child {
margin-right: 0; /* No margin for the last item in the row */
}
/* Styling for images within recommendation items */
#algolia-related-products .ais-RelatedProducts-item img {
display: block; /* Can help remove extra space below image */
width: calc(100% - 4px); /* Full width minus 2px L/R margins */
max-width: 100%; /* Ensures image does not exceed container if intrinsically smaller */
/* height: auto; -- Controlled by inline style's max-height and object-fit */
object-fit: cover; /* Ensure image covers the area, also in inline style */
margin: 2px; /* 2px margin on top, left, right. Bottom is overridden by inline style. */
/* margin-bottom: 8px; -- This is set by inline style in JS template */
}
/* Styling for the wrapper link to make the whole card clickable */
#algolia-related-products .ais-RelatedProducts-item a.ais-RelatedProducts-item-link-wrapper {
display: block; /* Make the link fill the list item */
text-decoration: none; /* Remove underline */
color: inherit; /* Use parent's text color */
}
#algolia-related-products .related-product-title {
font-family: 'Raleway', Helvetica, sans-serif;
font-size: 0.75em;
display: -webkit-box;
-webkit-line-clamp: 2; /* Limit to 2 lines for WebKit browsers */
line-clamp: 2; /* Standard property */
-webkit-box-orient: vertical;
overflow: hidden;
text-overflow: ellipsis;
padding: 0 7px 7px 7px; /* 0 top, 7px L/R/B for text area */
line-height: 1.5; /* Adjust for better readability */
height: 3.3em; /* Current height: 3.3em. For 2 lines with 0.75em font & 1.5 line-height, calculated height would be 2.25em. */
color: var(--c-interactive); /* Use theme's interactive color */
}
/* This container will wrap the image and score, taking the original image's layout space. */
#algolia-related-products .ais-RelatedProducts-item .recommendation-image-container {
position: relative; /* For positioning the score absolutely within */
display: block; /* Matches original image display and ensures proper block layout */
width: calc(100% - 4px); /* Adopts width from original image styling */
margin: 2px; /* Adopts margin from original image styling */
margin-bottom: 8px; /* Adopts specific bottom margin from original image's inline style */
line-height: 0; /* Prevents unexpected space if child elements are treated as inline */
}
/* The image itself, now filling the container */
#algolia-related-products .ais-RelatedProducts-item .recommendation-image-container img {
display: block;
width: 100%; /* Fill the container's width */
max-width: 20em; /* Optional: retain original max-width constraint for the image content */
height: auto; /* Maintain aspect ratio by default */
max-height: 12em; /* Constrain image height (adjust as needed) */
object-fit: cover; /* Ensures image covers the allocated space, cropping if necessary */
margin: 0 auto; /* Center image if max-width kicks in and it's narrower than container */
}
/* The score overlay box */
#algolia-related-products .ais-RelatedProducts-item .recommendation-score {
position: absolute;
bottom: 3px; /* Padding from the bottom edge of the container */
right: 3px; /* Padding from the right edge of the container */
background-color: color-mix(in srgb, var(--c-background) 85%, var(--green) 15%); /* Theme-aware light green */
color: var(--green); /* Theme's green color for text */
padding: 3px 6px; /* Slightly adjusted padding */
font-family: 'Raleway', Helvetica, sans-serif;
font-size: 0.75em;
font-weight: bold;
border-radius: 10px; /* More rounded corners like the example */
border: 1px solid var(--green); /* Theme's green color for border */
line-height: 1; /* Critical for small text in a small box */
z-index: 10; /* Ensure it's above the image */
box-shadow: 0 1px 2px rgba(0,0,0,0.15); /* Softer shadow */
display: flex; /* To align icon and text nicely */
align-items: center; /* Vertically center icon and text */
}
/* Styling for the SVG icon within the score box */
#algolia-related-products .ais-RelatedProducts-item .recommendation-score-icon {
width: 0.9em; /* Scale with score's font size */
height: 0.9em;
vertical-align: -0.1em; /* Fine-tune vertical alignment */
margin-right: 4px; /* Space between icon and score number */
fill: var(--green); /* Theme's green color for icon */
}
</style>
<script>
// Function to load a script and return a promise
function loadScript(src) {
return new Promise((resolve, reject) => {
if (document.querySelector(`script[src="${src}"]`)) {
resolve(); // Already loaded
return;
}
const script = document.createElement('script');
script.src = src;
script.onload = () => resolve();
script.onerror = () => reject(new Error(`Script load error for ${src}`));
document.head.appendChild(script);
});
}
function initAlgoliaRecommendations() {
Promise.all([
loadScript('https://cdn.jsdelivr.net/npm/algoliasearch@4/dist/algoliasearch-lite.umd.js'),
loadScript('https://cdn.jsdelivr.net/npm/instantsearch.js@4')
])
.then(() => {
// Initialize the Related Products widget
initRelatedProducts();
})
.catch(error => {
// Handle error silently
});
}
function initRelatedProducts() {
// Ensure container exists
if (!document.getElementById('algolia-related-products')) {
// Container not found, stopping initialization
return;
}
const recSearchClient = algoliasearch(
'2XJCLEABQD',
'b61ec4cb64bd32d62c053466fccbfa43'
);
const relatedSearch = instantsearch({
indexName: 'eugeneyan.com',
searchClient: recSearchClient,
clickAnalytics: true,
insights: true, // Enable insights for click tracking on recommendations
});
relatedSearch.addWidgets([
instantsearch.widgets.relatedProducts({
container: '#algolia-related-products',
objectIDs: ['/writing/eval-process/'],
limit: 3,
queryParameters: {
attributesToRetrieve: ['title', 'url', 'image', 'score', '_score'], // Specify only needed attributes
attributesToHighlight: [], // Disable highlighting
attributesToSnippet: [] // Disable snippeting
},
translations: {
title: '', // Custom title is in _layouts/post.html
},
transformItems: function(items) {
const containerElement = document.getElementById('algolia-recs-container');
const relatedElement = document.getElementById('algolia-related-products');
if (items.length === 0) {
if (relatedElement) relatedElement.style.display = 'none';
if (containerElement) containerElement.style.display = 'none';
} else {
if (relatedElement) relatedElement.style.display = 'block';
if (containerElement) containerElement.style.display = 'block';
}
return items;
},
templates: {
header() { // Removed unused results, html parameters
// Return a PLAIN string for the header
return '<h4 class="algolia-recs-section-header">You Might Also Like</h4>';
},
item: function(hit, { html, sendEvent }) { // Added sendEvent to params
const itemUrl = `${hit.url || '#'}`;
const indexName = 'eugeneyan.com'; // Get index name for insights
let imageUrl;
// Ensure hit.image is not null, undefined, or an empty/whitespace string before using it.
if (hit.image && typeof hit.image === 'string' && hit.image.trim() !== '') {
imageUrl = `/assets/og_image/${hit.image}`;
} else {
imageUrl = `/assets/og_image/default-v4.jpg`; // Default image
}
let scoreValue = null;
if (typeof hit.score === 'number') scoreValue = hit.score.toFixed(2);
else if (typeof hit._score === 'number') scoreValue = hit._score.toFixed(2);
// else if (typeof hit.your_custom_score_field === 'number') scoreValue = hit.your_custom_score_field.toFixed(2);
const scoreElement = scoreValue ? `<div class="recommendation-score"><svg viewbox="0 0 24 24" class="recommendation-score-icon" xmlns="http://www.w3.org/2000/svg"><path d="M16 6l2.29 2.29-4.88 4.88-4-4L2 16.59 3.41 18l6-6 4 4 6.3-6.29L22 12V6h-6z"></path></svg>${scoreValue}</div>` : '';
const imageAndScoreTag = `
<div class="recommendation-image-container">
<img src="${imageUrl}" alt="${hit.title || 'Recommendation cover image'}">
${scoreElement}
</div>`;
const title = hit.title || 'Untitled Post';
return `
<a href="${itemUrl}"
class="ais-RelatedProducts-item-link-wrapper"
onClick="${() => {
sendEvent('click', hit, 'Related Item Clicked');
}}"
>
${imageAndScoreTag}
<div class="related-product-title">${title}</div>
</a>
`;
},
empty(results, { html }) {
const containerElement = document.getElementById('algolia-recs-container');
const relatedElement = document.getElementById('algolia-related-products');
if (relatedElement) {
relatedElement.style.display = 'none';
}
// If this 'empty' template is called, it means related products are empty.
// So, the main container should also be hidden.
if (containerElement) {
containerElement.style.display = 'none';
}
// Return an empty string to prevent rendering 'undefined'
return '';
}
}
})
]);
relatedSearch.start();
}
document.addEventListener('DOMContentLoaded', function() {
let recsLoaded = false;
function checkLoad() {
if (recsLoaded) return;
if ((window.scrollY + window.innerHeight) >= document.body.scrollHeight - 500) {
recsLoaded = true;
window.removeEventListener('scroll', checkLoad);
initAlgoliaRecommendations();
}
}
window.addEventListener('scroll', checkLoad, { passive: true });
checkLoad();
});
</script>
</div> -->
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<p>I'm a Member of Technical Staff at Anthropic. I work to bridge the field and the frontier, and help build safe, reliable AI systems that scale. I've led ML/AI teams at Amazon, Alibaba, Lazada, and a Healthtech Series A, and write about LLMs, RecSys, and engineering at <a href="https://eugeneyan.com/" target="_blank">eugeneyan.com</a>.</p>
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