Mona
Recruiter
Mona is an AI recruiting partner built for founders and hiring managers who want to hire well without wasting time. She brings structure and speed to every stage of the process, from writing a role definition grounded in real outcomes to sending an offer letter that closes the deal. Mona is direct, warm, and equally committed to the hiring manager's bar and the candidate's experience. She treats recruiting as a craft, not a checklist.
How Mona helps you
I help you write job descriptions that attract the right people and filter out the wrong ones.
I build outbound sourcing messages that get replies without sounding like spam.
I design interview rubrics tied to real competencies, not gut feel.
I align your panel before interviews so debrief is fast and decisive.
I draft offer letters and give you a negotiation playbook to close confidently.
I write rejection notes that keep candidates warm and protect your reputation.
Capabilities
- Outcome-based job descriptions tied to real deliverables
- Ideal candidate profiles before any sourcing begins
- Cold outbound messages targeting 20 percent or higher reply rates
- Must-have vs. nice-to-have role scoping (five must-haves max)
- Competency scorecards with evidence-based rating guides
- Panel calibration frameworks run before the first interview
- Debrief templates that drive fast, consistent hiring decisions
- Offer letters and rejection notes that reflect well on your brand
Live Coaching with Mona
Mona plays the other person in a tough conversation while coaching you in real time, whispering tactical suggestions as you go. Practice as many times as you like, then get a scored performance breakdown at the end.
5 practice scenarios
Salary Expectations Standoff
easyWho you face: Priya Nair, 34, a mid-level software engineer at a Series B startup who just got a recruiter cold message on LinkedIn. She's politely skeptical and slightly annoyed by vague outreach.
Get Priya to stay engaged in the process despite not being able to give a hard salary number yet.
Passive Candidate Who Isn't Really Looking
mediumWho you face: James Okafor, 41, a senior engineering manager at a stable Fortune 500 who genuinely likes his job. He agreed to a call out of mild curiosity, not urgency.
Uncover what would actually make James consider a move and create enough pull to get him to a first interview.
Candidate Backing Out After Verbal Offer
mediumWho you face: Sofia Reyes, 28, a UX designer who verbally accepted an offer two days ago but just sent a vague email saying she needs 'more time to think.' She got a counter-offer from her current employer.
Understand Sofia's hesitation, address it honestly, and get her to a decision — ideally yes, but without manipulation.
Hiring Manager Pushing an Unworkable Job Description
hardWho you face: Derek Chung, 47, a VP of Product at a mid-size SaaS company who is convinced he knows exactly what he wants. He's written a job description requiring 10+ years of experience with a 3-year-old technology and wants a salary cap of $95k.
Push back on the unrealistic job description without losing Derek's trust or starting the relationship adversarially.
Candidate Challenging a Rejection They Didn't Deserve
hardWho you face: Amara Diallo, 36, a highly qualified data scientist who was rejected after a final round interview. She has receipts — her GitHub, her publications — and she believes (possibly correctly) the decision was influenced by bias.
Handle Amara's challenge with honesty and professionalism, provide what genuine feedback you can, and leave her with dignity even if the decision won't change.
Success stories
Illustrative examples of how Mona is used.
Fixing a Job Description That Was Attracting No One Good
A startup founder had posted a senior engineering role three times over six weeks and kept getting applicants who were either underqualified or clearly wrong fits. The description listed fifteen requirements and no clear sense of what success looked like.
Mona rewrote the role around two concrete outcomes due in the first ninety days and cut the requirements to four must-haves. Applications dropped in volume but the next hire came from the third interview.
Turning a Cold Outreach Campaign From Ignored to In-Demand
A hiring manager was sending LinkedIn messages to strong candidates and hearing nothing back. The messages opened with the company name, listed the role title, and asked if the candidate was open to opportunities.
Mona rebuilt the messages to open with a specific observation about each candidate's work, keep the ask small, and lead with what made the role interesting. Reply rates went from under five percent to above twenty-five percent within two weeks.
Getting a Divided Panel to a Fast, Confident Decision
A five-person interview panel finished a finalist round with three different opinions and no shared framework. Debriefs ran long and the team was close to making a hire based on whoever argued loudest.
Mona introduced a structured debrief template tied to the competencies agreed on before interviews started. The next finalist round ended in a unanimous decision in under thirty minutes, and the offer went out the same day.
Ready to work with Mona?
Start a conversation now, or browse the full team of coaches.