Glossary of Terms

A search method that reads documents for meaning rather than exact word matches — inferring what kind of professional you are from the pattern of language across your entire profile, not just whether specific keywords appear. It rewards coherence and consistency over repetition and frequency.

The older method of resume and profile scanning that looks for exact word matches — if the recruiter searches for "talent acquisition manager," the system finds profiles containing those words. It filters first and ranks early, which is why keyword optimization became an industry in the first place.

A Career Cantina framework for writing LinkedIn profiles and resumes that work for both readers — machine and human. The three elements are Nouns (identity signals for the machine), Verbs (evidence of action for the human), and Proof (the load-bearing base that serves both simultaneously).

The identity signals in your profile — job titles, function labels, domain terms, and skills — that tell the system what category of professional you are. They carry the most weight when placed in high-read fields: your headline, job titles, and skills section, not buried in paragraph text.

Action words that show what you did, not what you were responsible for — the language the human reader scans for to evaluate whether your experience holds up under scrutiny. The difference between "responsible for managing" and "built and led" is the difference between a job description and an experience.

The specificity that makes both readers believe you — not necessarily a percentage, but enough detail (scope, scale, complexity, or context) that the reader can visualize what you actually did. Proof is the load-bearing base of the Triangle because it works for the machine and the human at the same time: it anchors your category for the system and validates your verbs for the recruiter.

A Career Cantina diagnostic framework that breaks the hiring system's pre-human pipeline into three distinct stages — each requiring a different fix. Discoverability is whether you show up in searches at all; Categorization is whether you're placed in the right talent pool; Ranking is where you sit within that pool, and it is the only stage you cannot directly control.

A Career Cantina concept describing the sequenced dual audience for every LinkedIn profile and resume: the machine reads first (using semantic search to categorize and rank), and the human reads second (scanning for evidence of action and outcome). Most profiles are written for one reader and fail the other.

LinkedIn's proprietary semantic search layer, used inside LinkedIn Recruiter to match candidates to searches by meaning rather than keyword. If you have or have had a LinkedIn Recruiter seat, you've been running candidate searches through 360Brew — and your own profile is being read by the same system when other Recruiter users search for candidates like you.

The degree to which every element of your profile — headline, summary, job titles, bullets, skills — points in the same direction and tells the same story. Semantic search systems read coherence as a confidence signal: a fragmented or contradictory profile gets placed in a generic category; a coherent one gets placed precisely. Same story, two arrangements — your LinkedIn and your resume should both be telling it.