You know exactly what you want. You can see it. You just don't know what it's called.
So you open your AI tool and type "pixelated fade effect". Then "retro dot gradient". Then "that grainy old-computer image style". Six rounds later you have something almost right, and almost right is the most expensive kind of wrong.
The word was dithering. With it, one prompt gets you the real thing.
This gap has a shape. AI collapsed the cost of building, so the bottleneck moved: it's no longer "can the AI do it", it's "can you name it". Every field you touch as a builder has a precise vocabulary, and the words you're missing are costing you rounds of generation, wrong libraries, and vague briefs. Vocabulary is the highest-leverage thing you can pick up right now, and nobody teaches it.
Jargon Buster is the cure. It's a free reverse-lookup glossary built for exactly this moment: you describe the thing in your head, it gives you the word.
Reverse lookup: describe it, get the word
Press Cmd+K on any page and type what you'd say to a colleague, not the term:
| What you type | What you get |
|---|---|
| "the glowy circles behind them" | Bokeh |
| "the grid of differently sized cards" | Bento grid |
| "the scroll that takes over the page" | Scrolljacking |
| "grainy speckles when I turn the number up" | ISO |
| "why is my payout smaller than my sales" | Settlement |
| "the inside of the letters fills in when I bold it" | Counter |
Misspellings work too. "Ditter" lands on Dithering. That's deliberate: the fuzzy phrasings and typos people actually reach for are stored on every entry as first-class search data, not errors to correct. A normal glossary is indexed by the words you don't know. This one is indexed by the words you do.
Every entry ends prompt-ready
Knowing the term is half the loop. Each of the 2,142 entries closes the other half:
- A plain-language one-liner for the "that's the word!" moment
- A short explainer: what it is, when to reach for it, the gotcha
- A prompt-ready snippet: the concept translated into an instruction an AI model executes well, anchored to real things models latch onto (a CSS property, a Stripe API field, a named algorithm, an After Effects effect)
Copy the prompt, paste it into your tool of choice, get the thing in one shot. That last part is the whole point.
37 fields, because builders don't stay in one lane
The site maps the full territory a do-it-all builder or small team touches: design styles, typography, color, layout, motion, video, audio, 3D, frontend, backend, APIs, auth, AI, testing, i18n, performance, security, DevOps, observability, SEO, marketing, analytics, e-commerce, payments, email, legal, client ops, and more. 2,167 terms cataloged, 2,142 busted into full entries, all prerendered static pages, no accounts, no tracking walls.
Each field page shows the whole territory at once, so five minutes of skimming gives you the map of a domain you've been guessing at for years.
The cache that warms with use
Think of it as a shared vocabulary cache. Somewhere, someone already paid the twenty minutes to figure out that "the pop-in when content loads" is called layout shift. An entry stores that answer so the next person pays nothing.
And it's built to grow through cache misses. Community contributions open up soon, and the smallest useful contribution won't be writing an entry at all: it will be adding the exact phrase you searched with before you knew the word. Your old confusion, phrased honestly, makes the lookup work for the next person who has it.
The roadmap pushes the same idea further: live demo components on visual entries (a 200px working bento grid teaches more than any paragraph), and mining the site's own failed searches, so every miss becomes a candidate alias.
Try it on your own gap
Everyone has a word they spent half an hour not knowing. The scroll thing. The blurry glass effect. The reason your invoice email went to spam.
Open jargon-buster.sivaram.dev, hit Cmd+K, and describe it badly. That's what it's for.
And if the word you needed isn't there yet, tell me. It's probably the next entry.
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