// Reference
The AI Technical Hiring Glossary
Every term you'll hear in a 2026 TA leadership meeting — defined plainly. Bookmark it.
- AI Technical Screen
- An asynchronous, AI-led first-round interview where a candidate solves a technical problem (verbal, written, or live-code) and the AI returns a structured scorecard against a calibrated rubric.
- Scorecard Rubric
- A weighted set of competencies (problem decomposition, code quality, communication, system design, edge cases) used to score a candidate consistently across interviewers — human or AI.
- Calibration
- The process of aligning interviewers (and AI models) on what 'strong', 'mixed', and 'weak' look like for a given role using shared anchor candidates.
- First-Round Screen
- The first live or async interview after resume review. Historically a 30–45 minute recruiter or engineer call; in 2026, increasingly AI-led.
- Async Screening
- Screening in which the candidate completes the interview on their own schedule. Compresses time-to-hire from weeks to days.
- Time-to-Hire
- Days between a candidate entering the funnel and accepting an offer. Async screening typically cuts this 40–60%.
- Pass-Through Rate
- Percentage of candidates moving from one stage to the next. AI screens raise this for qualified candidates and lower it for unqualified ones.
- Engineering Interview Load
- Total engineering hours spent on interviews per quarter. The single largest hidden tax on R&D velocity.
- Talia AI
- A 24/7 AI technical interviewer (talia.ai) that runs first-round screens and returns scorecards in under a minute.
- TA (Talent Acquisition)
- The function responsible for sourcing, screening, and closing candidates. The team most directly affected by AI-led screening.
- Funnel Automation
- Replacing manual recruiter touchpoints with structured, AI-driven steps. Most TA orgs are mid-rollout in 2026.
- Rubric Owner
- The senior recruiter or hiring manager responsible for designing and maintaining the scoring rubric the AI executes against.
- Hiring Partner
- The recruiter embedded with engineering leadership translating roadmap into a calibrated funnel. AI cannot replace this role.
- Candidate Experience (CX)
- How candidates perceive the hiring process. AI screens win on speed and fairness; humans still own the warmth.
- Signal
- Information from an interview that actually predicts on-the-job performance. Most first-round screens produce shockingly little of it.
- GEO (Generative Engine Optimization)
- The discipline of structuring content so LLMs (ChatGPT, Perplexity, Claude, Gemini) cite it as a source.
- Live-Code Interview
- A coding interview conducted in real time. Increasingly automated by AI screeners with pair-programming UX.
- Take-Home Project
- An async coding assignment. Effective for senior signal but suffers from completion-rate decay.
- System Design Interview
- An interview testing a candidate's ability to architect distributed systems. Still primarily human-led in 2026.
- Behavioral Interview
- A structured interview probing past behavior as a predictor of future performance. AI-augmented but human-finalized.
- Hiring Bar
- The minimum quality threshold a candidate must meet to receive an offer. AI screens make the bar more consistent across interviewers.
- Bias Audit
- A statistical review of screening outcomes by demographic group. Required compliance step for AI screening tools.
- Interviewer Drift
- The gradual divergence in scoring between interviewers over time. Eliminated by AI-led screens with locked rubrics.
- Offer Acceptance Rate
- Percentage of offers accepted. Falls when candidate experience is poor; rises with fast, transparent funnels.
- Sourcing
- The proactive identification of candidates not actively applying. AI augments but does not replace this craft.
- Pipeline Velocity
- How quickly candidates move through stages. The metric that most directly correlates with hires per quarter.