Practical writing on AI screening, recruiting operations and structured interviews, for teams that want to hire faster without lowering the bar.
How to post a salary range that does its job
A good salary range filters out mismatches, builds trust, and saves you a week of awkward conversations. Here's how to set and post one.
How to screen career changers without your AI writing them off
Non-linear resumes trip up pattern-matching. Here's how to screen career changers fairly without lowering your bar.
How to interview for a skill you don't have yourself
You're hiring a specialist you can't personally evaluate. Here's how to get real signal without faking expertise you don't have.
Who owns what in a hire: a clean split between recruiter and hiring manager
Most hiring delays come from unclear ownership, not hard decisions. Here's a simple split of work between recruiter and hiring manager.
When your AI screener and your hiring manager disagree
An AI screener ranks a candidate high and your hiring manager wants them out. Here's how to treat that gap as useful signal, not a fight.
How to follow up on a vague answer without feeding the candidate the answer
The best interview signal usually comes from your second and third questions, not your first. Here's how to probe a vague answer without leading the witness.
How to reject candidates well, and keep your pipeline warm
Most teams treat rejection as an afterthought. Done well, it protects your brand, your future pipeline, and the candidates you do want to hire.
How to pilot an AI screener before you let it touch a live role
Before an AI screener ranks real candidates, prove it works. A practical way to run a backtest and a shadow pilot on roles you already know.
How to take interview notes that stand up in a debrief
Good interview decisions come from good notes. Here's how to capture evidence in the room so your debrief argues about facts, not memory.
How to run a weekly pipeline review that keeps roles moving
A 30-minute weekly review that catches stalled candidates, unblocks decisions, and keeps every open role moving forward.
Where AI should stop and you should start in screening
AI is good at reading and ranking. You're good at judgment calls it can't make. Here's how to split the screening work so neither of you wastes time.
Reference checks that actually tell you something
Most reference calls confirm what you already decided. Here's how to run one that surfaces real signal before you make an offer.
How to close a candidate without playing games
The offer stage decides whether weeks of work turn into a hire. Here's how to close strong candidates without gimmicks, pressure, or lowball first offers.
What a resume can't tell your AI screener (and how to fill the gap)
AI can read every resume in seconds, but a resume only holds part of the story. Here's what it misses, and how to catch it before you decide.
How to design an interview loop where every stage earns its place
Most interview loops repeat the same questions in different rooms. Here's how to map competencies to stages so every round tells you something new.
Interview scheduling is where good candidates go cold
Scheduling looks like admin, but the gap between yes and a booked slot is where strong candidates drift. Here's how to close it.
Should you let AI auto-reject candidates?
AI can screen and rank every application. Deciding who gets a no is a different question. Here's where to automate and where to keep a human.
How to run a screening call that respects everyone's time
A structured 25-minute screening call filters out mismatches early and gives candidates a reason to stay. Here's how to run one that holds up.
Response-time SLAs: the quiet reason good candidates say yes
The best candidates are gone in days, not weeks. Here's how to set response-time targets that keep your pipeline warm.
How to turn AI match scores into a shortlist you trust
An AI match score is a starting point, not a verdict. Here's how to set thresholds, review bands, and override rules that hold up.
How to calibrate interviewers so a 4 means the same thing to everyone
A scorecard only works if your interviewers agree on what the numbers mean. Here's how to calibrate a panel so scores are comparable, not personal.
How to measure quality of hire without a data team
Most teams track time-to-hire because it's easy. Here's how to measure whether your hires actually work out, with signals a small team can collect.
Should you tell candidates AI screened their application?
Disclosure isn't just a legal box to tick. Here's how to tell candidates AI helped screen them, without eroding trust or overpromising.
Designing a take-home assignment candidates won't resent
A practical guide to work-sample tests that predict on-the-job skill without burning candidates' evenings or your team's goodwill.
Where candidates drop off, and how to fix each leak
Most pipelines lose good people at predictable points. Here's where drop-off happens and what to do about each stage.
Write a job post your AI screener can actually rank against
An AI ranks resumes against the role you describe. Vague postings produce vague scores. Here's how to write one that sorts a pile into a real shortlist.
How to run an interview debrief that doesn't turn into groupthink
The debrief is where a good hiring process quietly falls apart. Here's how to collect scores first, argue the evidence, and reach a decision you can defend.
The intake meeting that makes the rest of the hire easier
Most hiring delays start before the first resume. A tight 45-minute intake meeting with the hiring manager prevents them.
How to screen candidates when every resume is AI-written
AI-written resumes are now the norm. Here's how to read past the polish and screen for real signal without punishing good candidates.
How AI resume screening actually works (and where it doesn't)
Parsing, matching and ranking, explained in plain terms. Plus the parts a recruiter should still do by hand.
Bias in hiring AI: what to check before you trust a score
AI can reduce bias in hiring or quietly amplify it. A practical checklist for keeping screening fair and defensible.
How to cut time-to-hire without lowering the bar
Most of the delay in hiring is not in the interviews. It is in the gaps between them. Here is where the days actually go.
Building a talent pipeline that actually gets used
Most talent pools are graveyards. Here is what separates a pipeline you actually search from a spreadsheet you forget.
The case for structured interviews (with a scorecard to steal)
Unstructured interviews mostly measure rapport. Structure is how you measure the job and compare candidates fairly.
12 interview questions that reveal real skill
Skip the brainteasers. These twelve behavioral prompts surface how a candidate actually works, not how well they rehearsed.