Boolean Search (Definition): A search method that uses logical operators such as AND, OR, NOT, and quotation marks to combine or exclude keywords in order to narrow or expand search results. Commonly used in recruitment, database querying, and research, Boolean search allows users to filter information with precision by creating logical relationships between search terms.
Example: (“Java Developer” OR “Backend Engineer”) AND (“Cape Town”) NOT (“Intern”)
There’s something beautifully frustrating about Boolean search.
It feels like trying to summon a genie with just the right combination of words, except your wishes are resumes, and the genie is a rigidly literal parser that punishes your every imprecision. But when it works, it works like magic. Not the stage kind. The real kind. The kind that makes you wonder why more people don’t take the time to learn it properly.
And yet, for all its power, Boolean search is increasingly misunderstood, misused, and dismissed as outdated, tossed aside in favor of shiny AI filters that promise to “think” for you. But here’s the inconvenient truth: Boolean search isn’t just a technique. It’s a mindset. A way of asking smarter questions in a world flooded with mediocre answers.
Especially in startup hiring, where you’re battling budget, urgency, and obscurity all at once, Boolean isn’t optional. It’s your leverage.
The Logic Behind the Madness
Boolean search is a logic-based search method that uses a specific set of operators, AND, OR, NOT, parentheses, and quotation marks, to filter and combine terms. Think of it as algebra for recruiters, only the Xs are people and the equations are resumes.
Why should you care? Because most hiring platforms, especially LinkedIn Recruiter, Google, GitHub, and job boards, still rely on some flavor of Boolean. And when you don’t speak the language properly, you get lost in translation.
Boolean Isn’t Just for “Tech” Roles
One of the biggest misconceptions? That Boolean search is only useful if you’re hiring developers or data scientists. False.
Boolean shines anywhere there’s complexity, whether it’s filtering for just the right kind of creative director in Cape Town, or trying to find that rare paid media strategist with Shopify experience and agency background but without an ego the size of a billboard.
Why Founders Should Care
Hiring is basically applied decision-making under pressure. And Boolean, at its core, teaches you how to think more clearly about your criteria.
It forces you to articulate what you really want, not just buzzwords, but actual, testable logic.
You want someone with startup experience or FAANG, but not both? Boolean can do that.
It’s a mirror. It shows you what you’re really asking for. And sometimes that’s the most valuable thing of all.
LinkedIn Recruiter
Most recruiters think they know how to use LinkedIn Boolean. Few actually do. Because LinkedIn isn’t a neutral Boolean engine, it has quirks.
•
AND is implied (e.g. Java Python)•
OR must be capitalized•
NOT excludes terms (not -)• Use quotes for phrases (e.g.
"machine learning")• Parentheses group logic (e.g.
(Java OR Python) AND ("machine learning"))Boolean strings are how you build your own algorithm. Not trusting LinkedIn’s black-box filters, writing your own logic.
What Happens When Boolean Fails
Boolean isn’t perfect. Sometimes you’re just guessing what keywords a good candidate might use. Sometimes people don’t write detailed profiles. And sometimes the best talent isn’t on LinkedIn at all.
There’s also the danger of being too precise. Overfilter, and you risk screening out great candidates. That’s where Boolean becomes a trap, precision without perspective.
Boolean vs AI: A False Dichotomy?
AI sourcing tools are getting smarter. They use NLP and semantic matching to surface candidates you didn’t think to search for.
So is Boolean dead?
LinkedIn’s AI filters might suggest good profiles, but Boolean gives you direct control. You don’t rely on “maybe.” You define “must-have.”
Most People Never Learn to Think in Boolean
The irony? Most of the “low quality candidates” recruiters complain about… are the result of bad searches.
Boolean teaches you that.
And yes, it’s slow. And frustrating. And sometimes infuriating. But like most valuable things, it pays off in clarity, not just in clicks.
So Where Do We Go From Here?
Boolean search isn’t dead. It’s just neglected.
In a world obsessed with speed and “smart” tech, Boolean quietly asks us to think more clearly. To interrogate our assumptions. To define what we mean before we search.
It’s not just a syntax. It’s a philosophy. And once you’ve mastered it, you’ll realize:
You’re not just sourcing candidates. You’re practicing precision thinking, in a profession that too often rewards shortcuts.
FAQs
What’s the fastest way to get better at Boolean?
Trial and error, paired with curiosity. There’s no hack faster than running a search, inspecting the results, tweaking the string, and trying again. Boolean is less about memorizing rules and more about learning how small changes impact your outcome. You’ll get better simply by paying attention.
If you want a shortcut, here it is: Start thinking in questions, not keywords.
Do I really need Boolean if I’m already using filters on LinkedIn Recruiter?
Yes, if you care about relevance. Filters are helpful, but they’re blunt. Boolean lets you stack logic inside those filters with way more nuance. Think of filters as mass-market presets. Boolean is manual mode, and it’s how you get your search to do what you actually mean, not what LinkedIn thinks you mean.
What if I’m getting too few results?
That’s not a problem. That’s feedback. Boolean search is like tuning a radio, if you hear static, adjust the frequency. Too few results usually means your string is too narrow. Open it up with more synonyms (use OR), simplify role titles, or remove unnecessary filters. Then re-test.
Also worth checking: Are you using terms candidates actually write in their profiles? People don’t always describe themselves the way job specs do.
Can I use Boolean across multiple platforms the same way?
Not exactly, but the core logic carries over. The principles are universal, but each platform has its quirks. For example:
LinkedIn Recruiter auto-applies “AND” between terms.
Google supports
site:searches and needs explicit operators.Job boards might limit the use of parentheses or complex strings.
Learn the rules of each platform the way you’d learn different keyboards—they all type letters, but the shortcuts change.
Should I teach Boolean to my whole team?
If they source, even a little, then yes. You don’t need every team member writing 7-layer nested strings. But a basic understanding of Boolean helps everyone ask better questions, run smarter searches, and challenge lazy assumptions. Plus, it makes for great team debates (“Wait, shouldn’t that be in parentheses?”).
It’s like giving them a compass. You still set the direction, but now they can help navigate.
Isn’t AI going to replace all of this?
Probably not. And if it does, it’ll still need you to define the question. AI can surface candidates. It can analyze job descriptions. But it’s not going to understand your hiring nuances, the weird mix of “must-haves” and “definitely-nots” that make a hire actually work in your business. That’s on you. Boolean isn’t about resisting AI. It’s about thinking clearly before you outsource the thinking.
