Daniel sent us this one — he's been running into the problem every intermediate language learner knows too well. You look up a technical term, say for DIY parts or some specific process, and the dictionary gives you something that sounds right but when you actually use it with a native speaker you get that look. That polite, slightly pained look. The word exists, technically, but nobody actually says it. So he's asking: what are the best ways to build your own personal dictionary, curated from real encounters, with your own examples and context, something that actually captures the word as it's used — not as a committee decided it should be used. Where do we even start with this.
The core problem he's describing has a name in lexicography — it's the difference between prescription and description. A standard dictionary prescribes what a word should mean. What he wants is descriptive: what people actually say. And for technical vocabulary in a language like Hebrew, that gap is enormous. Hebrew has the Academy of the Hebrew Language coining official terms for everything from "motherboard" to "torque wrench," and then actual mechanics and engineers just... don't use them. They use borrowed terms, or slang, or a weird calque from Russian because that's who brought the tool over in the nineteen nineties.
The Academy of the Hebrew Language versus the guy at the hardware store. That's a whole genre of mismatch.
It really is. And that mismatch is why a personal dictionary is so powerful. You're not building a reference work for the world — you're building one for yourself, from encounters where you actually learned the word in context. The memory of that encounter is part of the definition.
Let's talk concrete options. What actually exists for someone who wants to do this systematically, not just scribble things in a notes app and forget they exist?
I'd break the landscape into three categories. First, flashcard-style tools that let you build rich multimedia cards with example sentences. Second, linked-note systems that let you connect words into networks. Third, dedicated dictionary-builder apps, which are rarer but do exist. The flashcard space is where most people land, because the tooling is mature and the spaced repetition actually solves the retention problem.
Right — the "easy to forget" part of his prompt. You can build the most beautiful personal dictionary in the world and if you never review it, it's an art project.
Anki is the obvious starting point. It's free on desktop and Android, and the card format is completely flexible. You can have a field for the word, a field for the definition in your own words, a field for the example sentence where you encountered it, a field for audio — either your own recording or clipped from something — and a field for notes about register or connotation. The note type system means you design the template once and every new card inherits that structure. It's basically a database with a review scheduler bolted on.
Anki has a reputation for being... let's say, architecturally hostile to anyone who doesn't enjoy configuring software.
The interface is what I'd call "functionally honest." It does exactly what you tell it and nothing you don't, which means you have to know what to tell it. But for a personal dictionary, you don't need the complicated stuff. You're making one card type with a handful of fields, and that takes maybe fifteen minutes to set up. After that, adding a word is just filling in a form.
The spaced repetition means it surfaces the word right when you're about to forget it.
Which is the killer feature. The algorithm tracks your performance on each card and schedules reviews at increasing intervals — a day, then three days, then a week, then a month — but only if you keep getting it right. If you struggle, it shortens the interval. It's like a personal trainer who knows exactly which vocabulary muscles are atrophying.
" That's the most generous description of the Anki interface I've ever heard.
I won't defend the CSS. But the mobile app AnkiMobile on iOS is actually quite polished — it's a paid app that supports the whole ecosystem. On Android, AnkiDroid is free and open source. Both sync with AnkiWeb, so you can add words on your computer and review them on your phone. And the add-on ecosystem is enormous.
What about alternatives for people who take one look at Anki and flee?
The strongest competitor is probably RemNote. It's newer, the interface is modern, and it's built around linked knowledge. Every term you create can be connected to other terms, and the spaced repetition is built in. It treats terms as first-class entities — you can hover over a linked term and see its definition. It's closer to a personal wiki with flashcards than a flashcard app with fields.
That linked approach sounds more like what he's asking for — a curated reference, not just a review queue.
It is, and that's the trade-off. Anki is a better review tool. RemNote is a better reference tool. The ideal is probably both — a system where you can browse your dictionary as a connected web AND get reminded to review the ones you're shaky on. But that dual use case is hard to find in one package. Another option designed specifically for language learners is LingQ, though it's more of a reading platform with built-in dictionary features. When you read a text and tap a word, it saves it to your personal vocabulary list along with the sentence. That's very close to what he's describing — words captured in the wild, with context attached automatically.
The "in the wild" part matters. The whole premise is that standard dictionaries fail for technical vocabulary. So the capture mechanism is half the problem. If adding a word is friction-heavy, you won't do it in the moment, and then the encounter is lost.
This is where browser extensions and mobile sharing become critical. On a phone, the system share sheet is the fastest path. Most dictionary and flashcard apps support "share to" — you highlight a word in your reading app, hit share, and send it to your dictionary app with the surrounding sentence. On iOS, there's an app called VocabTracker that specializes in this. On Android, there's WordTheme, which functions as a personal dictionary with a built-in quiz mode and accepts shared text.
One thing I notice about all these apps is they're designed for single words or short phrases. What about when the thing you're learning is a whole expression, or a technical term that's four words long, or a phrase that only makes sense in a specific domain?
That's where a notes-based system starts looking better than a flashcard system. Something like Obsidian or Notion. You create a note for the term, write your own definition, paste in example sentences from different encounters, and link it to related terms. Over time, you build a personal technical glossary that's browsable and searchable. The downside is no spaced repetition — you have to remember to review it on your own. There are plugins that add spaced repetition to Obsidian, but they're community-built and the experience isn't as seamless as a dedicated app.
We've got flashcard systems that are great at scheduling but mediocre as reference works, and note systems that are great as reference works but have no memory. The thing that does both well doesn't quite exist.
Not as a single polished product, no. But the closest you can get is a workflow rather than an app. You use one tool for capture and quick review, and another for the long-term reference. For example: capture words in Anki with full context, let the algorithm keep them fresh, and then periodically export the mature cards into a notes app where they become your permanent searchable glossary. The mature cards are the ones you already know — they're exactly the ones worth putting in a reference.
The mature cards are the ones worth keeping. I like that as a principle. The stuff you've actually internalized becomes your dictionary. Everything else is still in the training pipeline.
That pipeline metaphor reframes the problem. He's not just building a dictionary — he's building a pipeline from encounter to internalization to reference. The encounter happens in the wild. The capture has to be nearly frictionless. The review has to be scheduled. And the reference has to be browsable. Each stage has different requirements, and no single tool optimizes for all of them.
Let's talk about the capture stage specifically, because that's where most systems fail. You're reading something, you hit a word you don't know, you look it up, and then... If you have to switch apps, type the word, type the definition, copy the sentence, tag it, and save it, you've spent thirty seconds. That's an eternity in the middle of reading.
There's a concept in second-language acquisition called "involvement load" — the cognitive effort required to process a word during a learning task. Higher involvement load generally leads to better retention, but there's a sweet spot. If the mechanics of saving the word are so cumbersome that you lose the thread of what you were reading, you'll stop doing it. The tool has to meet you where you are.
What's the fastest capture workflow that actually exists right now?
On iOS, I think it's the share sheet to a dedicated app. You highlight the word in your reading app, you tap "Look Up" to see the built-in dictionary definition, and if that definition is actually good, you can often share it directly. But for technical terms where the built-in dictionary fails, you're probably looking it up elsewhere or asking a native speaker. The share sheet can still grab the word and the surrounding sentence and send it to Anki or VocabTracker. On Android, the equivalent is the "Share" option in the text selection menu. There's also a tool called Readlang — a browser extension that lets you click any word on a webpage, see a translation, and automatically save it to your word list with the sentence. It supports Hebrew, which is relevant here.
Readlang is interesting because it collapses the lookup and the capture into one click. You're not switching contexts.
The developer has been iterating on it for years. The saved words can be exported to Anki, which means you can use Readlang for the capture stage and Anki for the review stage. That's exactly the pipeline approach I'm talking about.
Now, there's a deeper question here worth pulling on. He mentions that when he learns something from personal experience, he learns the actual term and maybe other terms in the context, and the nuance. That "personal experience" part is doing a lot of work. It's not just that the dictionary is wrong — it's that the dictionary can't give you the social and contextual information that comes from learning a word in a real situation.
This is what linguists call "communicative competence" — knowing not just what a word means, but when it's appropriate to use it, who uses it, what it signals about the speaker. A standard dictionary might tell you that a certain Hebrew word means "valve," but it won't tell you that the plumber uses a different word than the engineer, or that one of them is actually an Arabic loanword, or that using the Academy's official term makes you sound like you're reading from a textbook.
The Academy's official term for anything mechanical is basically a sign that says "I have never touched this object.
There's an actual documented phenomenon here. The Academy coined "machshev" for computer, and that one stuck — it's universal. But they also coined "mikledet" for keyboard, and half the country says "keyboard" anyway. A 2023 study from the University of Haifa looked at technical Hebrew vocabulary in the automotive repair industry and found that over sixty percent of commonly used terms were borrowings from English, Arabic, or Russian, not the Academy's official Hebrew coinages. The official terms existed — mechanics just didn't use them.
So the dictionary is wrong more than half the time in that domain. That's not a marginal problem — that's the dictionary being actively misleading.
That's just one domain. Imagine a software engineer discussing API design in Hebrew, or a carpenter buying supplies, or a doctor explaining a procedure to a patient. Each domain has its own actual vocabulary that diverges from the official one. The only way to learn the real vocabulary is exposure — hearing it used, using it yourself, being corrected — and then capturing it.
The personal dictionary is not just a convenience. For technical vocabulary, it's essentially the only dictionary that exists.
In many domains, yes. The published dictionaries are either too general or too prescriptive. The real lexicon lives in the community of practice. And that's actually an opportunity — building your own dictionary forces you to pay attention in a way that passively looking things up doesn't. You become a field linguist in your own life.
Let's talk about what makes a good dictionary entry, then. If you're going to curate this thing, what fields should you include?
The minimum viable entry is four fields. The word itself. A definition in your own words — not copied from a dictionary, because the act of paraphrasing is part of the learning. The full sentence where you encountered it, because context is what disambiguates. And some kind of register or domain tag — is this a word for the hardware store, the doctor's office, the software team meeting? Without that tag, you'll end up using the word in the wrong setting, which is sometimes worse than not knowing it at all.
Using a formal word in a casual setting is awkward. Using a casual word in a formal setting can be genuinely bad. The tag is what tells you which minefield you're in.
Then there are optional fields that add a lot of value. Audio — your own pronunciation or a native speaker's. Related words — synonyms, antonyms, the verb form if this is a noun. Notes on usage — "this is the word my neighbor used when he helped me fix the sink, but the YouTube tutorial used a different one." And a personal memory hook — "I learned this when the plumber laughed at me for saying the Academy term." That story is mnemonic gold.
The plumber laughing at you is a better spaced repetition algorithm than any software. You don't forget that word.
Emotion is a powerful encoding mechanism. There's a whole body of research on "flashbulb memories" — moments of surprise or embarrassment that sear information into long-term memory. A good personal dictionary entry captures a little bit of that emotional context. It's not just data — it's a record of an experience.
Okay, so we've covered capture and structure. Let's talk about the review side, because this is where I think a lot of people get the philosophy wrong. Spaced repetition apps are built on the idea that you're drilling vocabulary to automaticity — see the word, instantly know the meaning. But for a personal technical dictionary, the goal might be different. You don't need to instantly recall the Hebrew word for "ball-peen hammer." You need to be able to find it when you're at the hardware store.
This is a really important distinction, and it's one the flashcard orthodoxy doesn't handle well. Spaced repetition is designed for active recall — production. But a personal dictionary can serve a reference function that doesn't require active recall at all. You just need to know it exists and be able to look it up. That's a much lower bar, and it changes the review strategy — and the tool choice. If you're building a reference more than a recall deck, Obsidian with a good search function and tagging system might be more useful day-to-day than Anki.
Obsidian has the advantage of being plain text. Your personal dictionary is a folder of markdown files. It'll outlast any app, any platform, any company. I've seen too many language learners pour hundreds of hours into a proprietary app's vocabulary system only to have the app shut down or change its data model.
The plain text argument is the "buy a Toyota" of software advice. It's not glamorous, but it'll still be running in twenty years. And there's a specific workflow that combines the best of both worlds — the "Anki to Obsidian" pipeline. You use Anki for the active acquisition phase — the first few months where you're drilling a word until it sticks. Once the interval is past six months or so, you export the card to Obsidian as a permanent reference entry. The word is now in your long-term memory, but you also have it in a searchable, linkable format.
Six months seems like a reasonable threshold. If you haven't seen the word in six months and you still remember it, it's probably yours.
If you do forget it, you can look it up in Obsidian, which is exactly what you'd do with a physical dictionary. The difference is this dictionary is curated by you, from your actual encounters, with your actual examples. It's a dictionary that knows what you know.
There's a social dimension here too that I think is underexplored. When you learn a technical term from a specific person — a colleague, a neighbor, the guy at the hardware store — that term comes with a social credential. Using it signals that you're in the in-group. A personal dictionary can capture that social information alongside the linguistic information.
Sociolinguists call this "community of practice" vocabulary. Every profession, every hobby, every neighborhood has its own lexicon. Learning the lexicon is part of gaining membership. And a personal dictionary can explicitly track that. "This is the word Yossi at the machine shop uses." That's not just a citation — it's a key to a social world.
Yossi at the machine shop is a better lexicographer than the Academy of the Hebrew Language. I mean that sincerely. He's documenting the living language.
That's the shift in mindset that makes a personal dictionary work. You stop deferring to authorities and start treating yourself as a competent observer of language as it's actually used. You're not learning Hebrew — you're learning the Hebrew that people actually speak in the contexts you actually inhabit.
Let's get practical about the Hebrew-specific dimension, because that's clearly the context here. Hebrew has some unique characteristics that make a personal dictionary especially valuable. The gap between written and spoken, the rapid evolution of slang, the fact that a huge portion of technical vocabulary is borrowed and the borrowings change depending on who you're talking to.
Hebrew also has the root system, which is both a blessing and a curse. The blessing is that if you know the root, you can often guess related words. The curse is that standard dictionaries are organized by root, not by word, which makes them nearly unusable for learners who don't already know the root. A personal dictionary organized alphabetically by word — or better yet, by domain — sidesteps that entirely.
Organized by domain. That's a really interesting structural choice. Instead of a single A-to-Z dictionary, you have sections: hardware store Hebrew, doctor's office Hebrew, software team Hebrew, neighborhood Hebrew.
Within each domain, you might have different registers. The word you use with the doctor versus the word you use to describe the same thing to a friend. These are distinctions that no published dictionary makes, but they're the most important thing to get right in practice.
What about the actual mechanics of Hebrew text entry? It's a right-to-left language with niqqud that's a pain to type on most keyboards. Does that create friction at the capture stage?
It does, and it's one of the reasons I'd recommend keeping niqqud optional. Most adult Hebrew speakers don't use niqqud in everyday writing, and you're recording words as you encounter them in the wild — which usually means without vowels. You can add niqqud for words where the pronunciation is ambiguous, but it shouldn't be a required field. On iOS, the Hebrew keyboard has improved dramatically — predictive text works reasonably well. On Android, Gboard's Hebrew support is solid. The friction isn't zero, but it's manageable.
For audio, being able to record a native speaker saying the word is huge, especially for Hebrew where the stress pattern can change the meaning. "Ochel" versus "ochel" — food versus eats. The vowels are the same, the consonants are the same, the stress is different.
Minimal pairs like that are exactly where audio earns its keep. Most flashcard apps support audio attachments — on Anki, you can record directly into the card editor. There's also an app called Forvo that's a pronunciation dictionary with native speaker recordings. You can often find the word there and link to it or download the audio. It's especially valuable for Hebrew because the gap between how words are written and how they're pronounced in rapid speech can be substantial.
We've talked a lot about tools and workflows. I want to come back to something he mentioned in the prompt — the idea of a dictionary that provides "definitive answers." That's an interesting word choice. When you look something up in a standard dictionary, you trust it. When you're building your own, how do you know your entry is right?
This is the epistemological challenge of the personal dictionary. You're the compiler, and you're also a non-native speaker. Your entries are provisional. The healthiest approach is to treat them that way explicitly — add a confidence field. "Heard this once from a colleague, fairly sure it's right." "Confirmed with three different native speakers." "Saw this in a technical manual but never heard it spoken." That meta-information is just as valuable as the definition itself.
A confidence field. That's brilliant and also a little humbling. It forces you to acknowledge what you don't know.
It makes the dictionary more useful over time. When you review an entry from six months ago and see "low confidence, only heard once," you might actively seek out confirmation. You ask a native speaker, you look for the word in a different context, you upgrade the confidence level. The dictionary becomes a living document that improves with use. It also helps with the problem of fossilized errors — the mistakes that become permanent because you learned them early and never got corrected. A personal dictionary with confidence tags keeps your uncertainty visible.
Let's talk about the social curation angle. What about building a personal dictionary collaboratively? You and a few other learners, or you and a native speaker, contributing to a shared glossary for a specific domain.
This is where things get really interesting. There's an app called Quizlet built around shared flashcard sets, but its card model is simple and doesn't support the rich metadata we've been talking about. For collaborative dictionary-building, a shared Notion database or a shared Obsidian vault synced through something like Syncthing is more powerful. Everyone contributes entries, adds example sentences, tags domains, and over time you build a communal reference far richer than what any one person could compile.
The communal dictionary of a neighborhood hardware store. That's basically an oral tradition committed to text.
It's how real dictionaries used to be made. The Oxford English Dictionary was built on volunteer contributions — people would send in slips of paper with words and example sentences from their reading. James Murray, the original editor, called it a "democratic" process. A shared personal dictionary is the same idea, just digitized and domain-specific. The first edition took seventy years to complete, and something like six million citation slips were submitted by volunteers. One of the most prolific contributors was a man named William Chester Minor, who submitted over ten thousand entries — he was also a convicted murderer living in an asylum for the criminally insane. The whole story is in a book called "The Professor and the Madman.
The moral is: your personal dictionary contributions are probably more reliable than some of the OED's sources.
The moral is: dictionaries have always been collaborative, and they've always been imperfect. The difference now is the tools let you build one that's perfectly suited to your specific needs.
One thing I want to push on — we've been assuming the personal dictionary is a supplement to published dictionaries. But for technical vocabulary in a specific domain, the personal dictionary might actually be better than any published resource. It's not a supplement. It's the primary reference.
For certain domains, I think that's absolutely right. Anything hands-on and trade-related — plumbing, carpentry, auto repair, electrical work. Anything in fast-moving technology fields where the terminology hasn't stabilized. Anything where the language community is small or the standard reference works are outdated. In those cases, your personal dictionary isn't Plan B. It's Plan A. Lexicography is inherently slow. A good dictionary entry takes research, multiple citations, editorial review. By the time a technical term makes it into a published dictionary, the practitioners have often moved on. The personal dictionary operates at the speed of conversation. You hear it today, it's in your dictionary tonight.
Speed of conversation versus speed of lexicography. That's a framing that makes the whole project feel less like a study aid and more like a necessary adaptation to how language actually works.
Language is not a fixed system with a single authoritative reference. It's a set of overlapping communities, each with its own norms. A personal dictionary acknowledges that reality and gives you a tool to navigate it.
Alright, let's try to synthesize this into something actionable. If someone listening wants to start building their own personal technical dictionary tomorrow morning, what's the simplest workflow that actually works?
Start with Anki on your phone. Create one note type with four fields — word, definition in your own words, example sentence, and domain tag. Add an audio field if you can. When you encounter a new technical term in the wild, use the share sheet to send it to Anki with the surrounding sentence. Fill in the definition and tag immediately — don't put it off, the context will fade. Once a card's interval passes three months, export it to a plain text file or a notes app organized by domain. That's the reference layer. The whole thing takes maybe ninety seconds per word at the start, and it gets faster as you build the habit.
Ninety seconds per word. Over a year of regular encounters, that's a substantial personal glossary.
If you add five words a week — which is conservative for someone immersed in a technical environment — that's two hundred sixty words in a year. Each with a real example sentence, each tagged by domain, each with a definition in your own words. That's a reference work no publisher could produce, because it's tailored to exactly the contexts you personally inhabit.
Five words a week. That's the kind of manageable goal that actually gets done, as opposed to "learn five hundred words this month" which gets abandoned by day four.
The literature on habit formation consistently shows that consistency beats intensity. Small daily actions compound. Five words a week for two years is five hundred twenty words. That's a professional-grade technical vocabulary in any domain. And it scales down as well as up. Even one word a week — one genuine encounter where you learn the real term and capture it — you're still building something standard dictionaries can't give you.
Let's talk about one more dimension before we wrap up — the psychological shift. When you start keeping a personal dictionary, you start paying different attention to language around you. You become a collector. Every conversation becomes a potential source. That's a fundamentally different orientation than just "studying.
It's the difference between being a consumer of language and being a naturalist of language. A consumer takes what's given. A naturalist observes, collects, categorizes. It's a more active, more engaged relationship with the language. And for adult learners especially, that shift can be the thing that breaks you out of the intermediate plateau — that phase where you're functional but not fluent, and progress feels invisible. A personal dictionary is a tangible artifact of progress. You can see it growing. You can flip through entries from six months ago and realize you now know those words cold. It makes progress visible.
Visible progress is underrated as a motivator. The apps with streak counters and gamification are tapping into the same thing, but a personal dictionary is more authentic. It's not a number someone else designed to keep you engaged. It's your actual knowledge, externalized.
It's useful beyond motivation. A year from now, you have a reference you can actually use. You can search it when you're about to have a conversation in a specific domain. You can share it with a colleague who's learning. It's not just a learning tool — it's a professional asset.
Alright, I want to mention one more tool that hasn't come up yet, because it fits the "curate your own examples" part of the prompt perfectly. There's an app called Clozemaster that's built around cloze deletion — fill in the blank — but it sources its sentences from a huge corpus of real text. You can choose specific domains or word frequency ranges. It's not a personal dictionary builder, but it's a great source of authentic example sentences for the words you're trying to learn.
Clozemaster is excellent for that. The sentences come from Tatoeba, a crowd-sourced corpus of translated sentences. The quality varies, but the volume is enormous — millions of sentences across thousands of language pairs. For Hebrew, there are over a hundred thousand sentences. If you find a technical term in your personal dictionary and want to see more examples of it in context, Clozemaster can often surface them. It's a research tool for dictionary-building. And that's the broader point — building a personal dictionary doesn't mean you ignore external resources. It means you curate from them. You're the editor. The published dictionaries, the corpora, the native speakers you know — they're all sources. You're the one deciding what goes in and how it's presented.
The editor metaphor is right. A personal dictionary is an editorial project. You're making judgments about what's worth keeping, how to organize it, what to emphasize. It's a creative act, not just a study technique.
That creative act changes your relationship with the language. You're not just learning Hebrew — you're making a map of the Hebrew that matters to you. That's a fundamentally different project than working through a textbook.
I think that's the takeaway. The question wasn't just "what tools exist" — it was "how do I build something that captures the real language as I encounter it, with the nuance and context that standard references miss." And the answer is: you become your own lexicographer. You build a pipeline from encounter to capture to review to reference. You use spaced repetition for what needs to be recalled, and linked notes for what needs to be findable. You tag by domain, you note your confidence level, and you treat the whole thing as a living document.
You start small. Five words a week. Ninety seconds per word. A habit, not a project. A year from now, you have something no publisher can sell you.
The dictionary that knows what you know.
That's the one.
Now: Hilbert's daily fun fact.
Hilbert: In the early Renaissance, French Guiana was briefly the center of a fringe electromagnetic theory that claimed a warship could be disabled at a distance by vibrating a bronze bell at the exact resonant frequency of its hull — practitioners called it "bell-shot" and believed it worked through a kind of sympathetic vibration carried by seawater, though no ship was ever successfully stopped this way.
They tried to sink ships with...
That's one way to put it. Another way is "they rang a bell at the ocean and hoped for the best.
I have so many questions about the experimental setup.
Yet I suspect the answers would only disappoint.
This has been My Weird Prompts, produced by the endlessly resourceful Hilbert Flumingtop. You can find every episode at myweirdprompts.com or wherever fine podcasts are streamed. If you enjoyed this one, leave us a review — it helps other people find the show. I'm Herman Poppleberry.
I'm Corn. Thanks for listening.
