[Rick Retirement Planner]

Hello — I manage hiring for a small team and I’m curious about practical, low-tech ways to use AI to create job descriptions and candidate scorecards. I’m not a developer and I want something reliable, easy to edit, and fair to share with candidates and interviewers.

Specifically, I’d love advice on:

• Tools: Which beginner-friendly AI tools or apps work well for this task?
• Prompts & templates: Examples of simple prompts or templates to generate a clear job description and a matching scorecard.
• Quality checks: How to review or tweak AI output so it’s accurate, non-biased, and realistic for our level of experience.
• Workflow: A short, practical process to go from role outline to a shareable job post and interview scorecard.

If you have sample prompts, templates, or short step-by-step workflows that have worked for non-technical managers, please share. Thanks — I’m looking for straightforward, repeatable tips I can use this week.

[aaron]

Quick win (5 minutes): paste one current job title and its top three responsibilities into an AI prompt and ask it to produce a 1‑paragraph job summary and 5 must-have skills. You’ll have a usable baseline in under five minutes.

Good point — focusing on both job descriptions and candidate scorecards together is the right move. They should be written in tandem so interviews map directly to hiring decisions.

The problem: Job ads are vague and scorecards are inconsistent. That creates hiring bias, long time-to-fill, and poor role fit.

Why this matters: Clear JD + scorecard = faster hiring, better quality-of-hire, fewer mismatches, and more objective interviews. That translates to lower recruitment cost-per-hire and higher time-to-productivity.

What I’ve learned: The highest impact change is making scorecards the source of truth. Job descriptions should be distilled from the scorecard, not the other way around.

1. What you’ll need
   • A short role brief (title, 3–5 responsibilities, 3 outcomes in 6 months)
   • Your current job posting (if any)
   • Access to an AI assistant (ChatGPT or similar)
2. Step-by-step: build a JD and scorecard
   1. Draft the outcomes: write 3 measurable outcomes for month 6 (e.g., “reduce churn 10%” or “launch X feature”).
   2. Use AI to expand each outcome into 3 skills and 3 behaviors that demonstrate success.
   3. Create a scorecard with four zones: Must-have (3), Nice-to-have (3), Cultural fit (3), Red flags (3). Map each item to outcomes.
   4. Write the job description from the candidate perspective: 2-sentence summary, 3 core responsibilities, 3 must-have skills, 1 paragraph on growth/compensation.
   5. Convert scorecard items into interview questions and scoring rubrics (0–3 scale).

What to expect: In 60–90 minutes you’ll have a role briefable to hiring managers and a scorecard that yields consistent interview ratings.

Copy-paste AI prompt (use this as-is)

“I have a role: [Job Title]. Key responsibilities: [list 3–5]. Target outcomes at 6 months: [list 3]. Create: 1) a 2-sentence job summary for candidates, 2) 3 must-have skills, 3) a candidate scorecard with categories: Must-have, Nice-to-have, Culture, Red flags (3 items each), and 4) three interview questions per Must-have skill with a 0–3 scoring guide.”

Metrics to track

• Time-to-fill (days)
• Offer acceptance rate (%)
• Hiring manager satisfaction (1–5)
• 90-day new hire success rate (meets 80% of outcomes)

Common mistakes & fixes

• Vague responsibilities —> Fix: rewrite as outcomes with measurable targets.
• Scorecards too subjective —> Fix: link behaviours to a 0–3 rubric and require two interviewers.
• Long JDs —> Fix: keep why and outcomes up front; move perks to the end.

One-week action plan

1. Day 1: Run the AI prompt on one priority role and finalize scorecard.
2. Day 2–3: Convert scorecard items into 6 interview questions and train 2 hiring managers on scoring.
3. Day 4–5: Post the JD, start interviews with mandated scorecard use.
4. Day 6–7: Review metrics and calibrate rubrics based on first 3 interviews.

Your move.

[Jeff Bullas]

Quick win (under 5 minutes): paste one job title and its top three responsibilities into this AI prompt (below). Ask for a 2‑sentence candidate summary and 5 must‑have skills — you’ll have a clean baseline in minutes.

Nice point in your post: making the scorecard the source of truth is exactly right. I’d add a practical way to link scorecard items directly to interview evidence so hiring is repeatable.

What you’ll need

• A short role brief (title, 3–5 responsibilities, 3 outcomes for month 6)
• One existing job posting (optional)
• An AI assistant (ChatGPT or similar) and a spreadsheet or doc to capture the scorecard

Step-by-step (do this)

1. Write 3 measurable outcomes for month 6 (e.g., “Increase demo conversions 15%” ).
2. Run the AI prompt below to generate a candidate‑facing summary, skills and a first draft scorecard.
3. For each Must‑have on the scorecard, ask the AI to create 3 behavioural interview questions using STAR prompts and a 0–3 scoring guide.
4. Pick two interviewers and require independent scoring; average the scores and flag >1 point variance for calibration.
5. Post the JD (short, outcome-led) and use the scorecard in every interview.

Practical example (copy this pattern)

Role: Marketing Manager. 6‑month outcomes: Launch 1 major campaign, increase MQLs 30%, improve landing page conversion by 12%.

• 2-sentence summary: Lead performance marketing to build high-converting campaigns across paid and email channels. You’ll be measured on campaign ROI, lead volume and conversion improvements.
• Top 3 must-have skills: Performance marketing, data-driven optimization, landing page CRO.
• Scorecard (Must-have): Campaign strategy, Analytics & reporting, Conversion optimization. (Nice-to-have/Culture/Red flags as separate columns.)
• Sample interview Q for Analytics: “Describe a time you used analytics to change a campaign. What data did you use, what decision did you make, and what happened?” Scoring 0–3: 0=no example, 1=limited data, 2=clear action with modest impact, 3=strong metrics + sustained improvement.

Common mistakes & fixes

• Vague outcomes —> Rewrite as measurable targets tied to business impact.
• Subjective ratings —> Use STAR questions + 0–3 rubric and two interviewers.
• Long JDs —> Put outcomes and why first; keep responsibilities short.

Copy-paste AI prompt (use as-is)

“I have a role: [Job Title]. Key responsibilities: [list 3–5]. Target outcomes at 6 months: [list 3]. Create: 1) a 2-sentence job summary for candidates, 2) 5 must-have skills, 3) a candidate scorecard with categories: Must-have, Nice-to-have, Culture, Red flags (3 items each), and 4) for each Must-have skill, provide three STAR interview questions with a 0–3 scoring guide.”

One-week action plan

1. Day 1: Run prompt on one priority role and finalize scorecard.
2. Day 2–3: Convert top scorecard items into interview questions; train 2 hiring managers.
3. Day 4–7: Start interviews with mandatory scoring; review first 3 hires and recalibrate.

Start with one role. Ship a scorecard this week — iterate after real interviews. Small tests beat perfect plans.

[Becky Budgeter]

Quick win (under 5 minutes): pick one job title and its top three responsibilities, paste them into your AI assistant, and ask for a 2‑sentence candidate summary plus five must‑have skills. You’ll have a neat baseline you can use right away.

Great call in your message about making the scorecard the source of truth — and especially useful: linking each scorecard item to specific interview evidence so ratings are repeatable. I’ll add a compact, practical workflow to turn that idea into a reliable process you can use this week.

What you’ll need

• A short role brief (title, 3–5 core responsibilities, 3 outcomes for month 6)
• An AI assistant (ChatGPT or similar) and a simple doc or spreadsheet
• Two interviewers for calibration and independent scoring

Step-by-step: build a JD + scorecard that links to evidence

1. Draft 3 measurable outcomes for month 6. Be concrete (percent, number, deliverable).
2. Ask the AI to turn each outcome into 2–3 skills and 2–3 observable behaviours that show success (e.g., “uses metric X to guide decision; ran A/B test and iterated based on result”).
3. Create a scorecard with four columns: Must-have (3 items), Nice-to-have (3), Culture (3), Red flags (3). For each Must-have, list the linked outcome(s) beside it.
4. For each Must-have item, write 2–3 behavioural interview prompts (STAR style) and a simple 0–3 rubric: 0=no example, 1=weak, 2=good, 3=excellent with measurable impact. Put an “Evidence” field where interviewers paste the candidate quote or result that justified the score.
5. Require two interviewers to score independently; average scores and flag >1 point variance for a quick calibration chat after the interview.
6. After 3–5 interviews, run a 20‑minute calibration: compare evidence snippets, adjust rubric language to reduce ambiguity, and update the JD to reflect the real skills that matter most.

What to expect

• Quick draft (AI + light edits): 30–60 minutes for one role.
• A usable scorecard and interview question set: 60–90 minutes.
• First calibration after 3 interviews will tighten scoring and lower bias.

Simple tip: always anchor at least one Must-have to a business metric or deliverable — that makes the rubric less subjective. Which role are you thinking of trying this on first?

[Steve Side Hustler]

Nice call on making the scorecard the source of truth and anchoring Must-haves to a business metric — that single change flips interviews from gut-feel to evidence-driven. Here’s a compact, no-nonsense workflow you can run this week if you’re short on time.

What you’ll need

• One short role brief: title, 3 core responsibilities, and 3 concrete 6‑month outcomes (numbers or deliverables).
• An AI assistant and a simple doc or spreadsheet to capture the scorecard and interview notes.
• Two interviewers for independent scoring (can be the hiring manager + one peer).

Step-by-step (busy-person version)

1. 5-minute quick win: Tell the AI the role, responsibilities and the 3 outcomes. Ask for a 2‑sentence candidate summary and 4–5 must-have skills. Save that as your baseline.
2. 30-minute build: For each outcome, ask the AI to list 2–3 observable behaviours that show success and map 1–2 skills to each behaviour. Use those to create a scorecard with four columns: Must-have (3), Nice-to-have (3), Culture (3), Red flags (3).
3. 15–20 minute interview pack: Convert each Must-have into 2 behavioural prompts (STAR-style) and a simple 0–3 rubric: 0=no example, 1=weak, 2=good, 3=measurable impact. Add an “Evidence” field for interviewers to paste quotes or metrics.
4. Calibration & repeat: Require two independent scores per interview; average them and flag >1 point variance for a 5–10 minute calibration chat. After 3 interviews, spend 20 minutes comparing evidence and tightening rubric language.

What to expect

• A usable JD + scorecard baseline in under 45 minutes.
• Interview-ready questions and rubrics in ~60–90 minutes total.
• Noticeably more consistent ratings after the first 3 interviews and one calibration session.

Prompt approach (use conversational frames, not a long copy/paste)

• Inputs: role title, 3 responsibilities, 3 outcomes (be specific).
• Ask for: two-sentence candidate summary; 4–5 must-have skills; for each outcome, 2 observable behaviours; a 4‑column scorecard with 3 items each.
• Variants: Quick (short summary + skills), Detailed (behaviours + rubrics + evidence fields), Calibration (compare 3 interview snippets and suggest rubric tweaks).

Small habit: always tie at least one Must-have to a number or deliverable — hiring becomes less subjective overnight. Try this on one open role this week and iterate after three interviews.

[Jeff Bullas]

Nice point — anchoring Must-haves to a business metric really does flip interviews from gut-feel to evidence-driven. I’ll add a compact, do-first toolkit you can use this week to move from idea to hireable scorecard fast.

What you’ll need

• A short role brief: title, 3 core responsibilities, 3 concrete 6-month outcomes (numbers or deliverables).
• An AI assistant (ChatGPT or similar) and a simple doc or spreadsheet to capture the scorecard and interview notes.
• Two interviewers for independent scoring (hiring manager + peer).

Step-by-step (do this now)

1. 5-minute quick win: Run the Quick Prompt below to get a two-sentence candidate summary and 4–5 must-have skills. Save as your baseline.
2. 30-minute build: For each 6-month outcome, ask the AI to produce 2–3 observable behaviours and map 1–2 skills to each behaviour. Use those to create the scorecard columns: Must-have (3), Nice-to-have (3), Culture (3), Red flags (3).
3. 20-minute interview pack: Convert each Must-have into 2 STAR-style prompts and a 0–3 rubric (0=no example, 1=weak, 2=good, 3=measurable impact). Add an Evidence field for verbatim quotes or metrics.
4. Calibration: Require two independent scores per interview; average them and flag >1 point variance for a 5–10 minute sync. After 3 interviews, run a 20-minute calibration to tighten language.

Copy-paste AI prompts (use-as-is)

Quick prompt (under 5 minutes):

“I have a role: [Job Title]. Key responsibilities: [list 3–5]. Target outcomes at 6 months: [list 3]. Create: 1) a 2-sentence job summary for candidates, 2) 4–5 must-have skills.”

Detailed prompt (use for scorecard + interview kit):

“I have a role: [Job Title]. Responsibilities: [list 3–5]. 6-month outcomes: [list 3, be specific]. For each outcome, list 2–3 observable behaviours that demonstrate success and map 1–2 skills. Then create a candidate scorecard with columns: Must-have (3 items, link each to an outcome), Nice-to-have (3), Culture (3), Red flags (3). For each Must-have item, provide 3 STAR interview questions and a 0–3 scoring guide. Include an “Evidence” field description and one example answer that would score a 3.”

Practical example (pattern you can copy)

• Role: Marketing Manager. 6-month outcomes: Launch 1 major campaign, increase MQLs 30%, improve landing page conversion by 12%.
• Must-have: Performance campaign strategy — linked to campaign launch and ROI metric. Interview Q example: “Tell me about a campaign you launched that missed target. What data did you use to pivot and what was the outcome?” Scoring 0–3: 3 = clear metric-driven pivot that recovered >=20% of target within 4 weeks.

Common mistakes & fixes

• Vague outcomes —> Fix: rewrite as measurable targets tied to business impact (%, numbers, deliverables).
• Subjective rubrics —> Fix: use STAR prompts + 0–3 scale and require an Evidence quote for each score.
• Long JDs —> Fix: place the outcomes and “why this role matters” up front; keep responsibilities short.

One-week action plan

1. Day 1: Run Quick prompt for one priority role and pick top 3 Must-haves.
2. Day 2: Build the detailed scorecard using the Detailed prompt; create interview pack.
3. Day 3–4: Train two interviewers on scoring and Evidence capture (15 minutes).
4. Day 5–7: Run interviews, average scores, and hold a 20-minute calibration after 3 interviews; iterate rubrics.

Small bet: do this for one role this week. Ship a scorecard, test with three interviews, then refine. Evidence over opinion — that’s the win.

[Author]

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