Turn a GTM opening into a scorecard before you post it.
“I am about to post an AE role and I cannot say what a great hire does in the first 90 days. Where do I start?”
The outcomes the role must hit, the competencies that predict them, questions per competency, and a shared rubric.
What this skill does
Takes the role you are hiring for and builds the thing you should have before the first interview: a scorecard. It writes the outcomes the person must hit in their first stretch, the competencies that predict those outcomes, a set of interview questions mapped to each competency, and a rubric so every interviewer scores the same candidate on the same scale. You hire against evidence instead of a gut read at the end.
Inputs
- Works today with: the role, the level, the motion it sells into, and a rough sense of what "great in year one" looks like. Paste a job description or just describe it.
- More powerful connected to a CRM: it reads what your current strong performers in the role actually do, so the outcomes are grounded, not generic.
- Sharper with an ATS: it can align the scorecard to your stages and keep every interviewer scoring in one place.
- Sharper with a meeting or notes tool: it can turn interview debriefs into rubric scores instead of loose impressions.
How it works
- 1Outcomes first
Before competencies, the scorecard names 3 to 5 outcomes the hire must produce inside the RAMP_WINDOW, written as results, not activities. "Sourced pipeline covering quota by day 90," not "does prospecting." Outcomes are what you are actually buying. Everything else predicts them.
- 2Competencies that predict the outcomes
For each outcome, name the 1 or 2 competencies that predict it, drawn from a library: prospecting rigor, discovery depth, deal control, multi-threading, forecasting honesty, coachability, customer empathy, commercial judgment. Cap the list at 5 or 6. A scorecard that weights everything weights nothing.
- 3Questions per competency
Each competency gets 2 or 3 interview questions, behavioral and past-tense, plus what a strong answer sounds like and what a weak one sounds like. Behavioral because past behavior predicts, and the "strong vs weak" note keeps interviewers from grading on charisma.
- 4Scoring rubric
A shared rubric on the SCORE_SCALE, with each competency defined at each level so a 3 means the same thing to every interviewer. An even scale forces a call and kills the safe middle. Each interviewer scores only the 1 or 2 competencies they own, so the debrief is coverage, not repetition.
- 5Interviewer assignment
The kit assigns competencies across the loop so every one is covered by someone and no candidate is graded twice on the same thing. The hiring manager owns outcomes fit. Coverage over consensus.
Output format
SCORECARD · Mid-Market AE · judged at day 180
Outcomes:
1. Self-sourced pipeline at 3x quota by day 120
2. First closed-won by day 90
3. Forecast within 15% by second full quarter
Competencies (weighted):
Prospecting rigor -> outcome 1 (owner: SDR manager)
Discovery depth -> outcome 2 (owner: hiring manager)
Deal control -> outcome 2 (owner: peer AE)
Forecasting honesty -> outcome 3 (owner: sales leader)
Coachability -> all (owner: hiring manager)
Sample question (Discovery depth):
"Tell me about a deal you lost. When did you first know, and what
had you not asked?"
Strong: names the missing question, owns it, changed their process.
Weak: blames budget, timing, or the champion leaving.
Rubric: 1-4 per competency. Advance only on avg >= 3 with no 1s on
a weighted competency.
Tips
- Outcomes are written as results with a date, never as activities.
- Competencies are capped at 5 or 6, each tied to an outcome it predicts.
- Every question is behavioral and past-tense, with a strong-answer and weak-answer note.
- The rubric scale is even, so no interviewer can hide in the middle.
- Every competency is assigned to a named seat in the loop.
Walk into the forecast call with a number you can defend.
Sorts each deal into commit, best-case, or pipeline by evidence, flags one risk, and scripts what to press each rep on.
Run a pipeline review that finds problems, not recites them.
Coverage vs target, stage aging, week-over-week movement, stuck deals, and the question to ask per deal.