AI Skill Report Card
Recruiting Engineering Talent
Quick Start13 / 15
Given a new engineering role, run this before sourcing a single candidate:
- Analyze the role — team stage, technical stack, seniority signals, and what "great" looks like in 90 days.
- Apply the MATCH framework to score candidates against the role (see below).
- Write targeted outreach referencing something specific to the candidate's work, not a generic pitch.
- Screen for fit + trajectory, not just keyword overlap with the job description.
Recommendation▾
Add a third example showing a rejected/failed outreach or negative outcome to illustrate contrast more explicitly
The MATCH Framework
Use this to score and compare candidates consistently:
- M — Motivation: Why are they looking? Does the move make career sense (not lateral/desperate)?
- A — Ability: Can they actually do the job — verified via past work, not just resume claims?
- T — Trajectory: Is their career arc pointing toward more scope/impact, matching the seniority of the role?
- C — Culture/Stage fit: Have they operated at this company stage before (0-10 eng team vs. 200+ eng team)? Startups need different operators than big tech.
- H — Hunger: Do they show evidence of ownership, shipping, and bias to action — critical at high-growth startups where roles are underspecified?
Score each dimension 1-5. A candidate below 3 on Ability or Culture/Stage fit is a hard pass regardless of other scores — those two are non-negotiable at startups.
Workflow14 / 15
Progress checklist for filling a role:
- Step 1: Intake — interview the hiring manager to define the real problem this hire solves in the first 2 quarters (not just a generic JD)
- Step 2: Translate the JD into a MATCH scorecard specific to this role (what does "5/5 Ability" look like here?)
- Step 3: Source candidates from targeted channels (competitor companies at similar stage, alumni of strong startups, referrals)
- Step 4: Screen resumes/profiles against MATCH — reject fast on Ability/Culture-Stage misses
- Step 5: Write personalized outreach (1-2 sentences referencing their specific work/project)
- Step 6: Phone screen focused on the two weakest MATCH dimensions from resume review
- Step 7: Debrief with hiring manager using MATCH scores as shared vocabulary
- Step 8: Close — address the specific MATCH dimension that's most likely to cause them to decline (usually stage risk or comp)
Recommendation▾
Include a concrete outreach message template (actual text) rather than just describing the approach
Examples16 / 20
Example 1: Role Analysis Input: "We need a senior backend engineer" (Series B startup, 15 engineers, scaling payments infra) Output:
- Real problem: current payments system breaks at 3x current load; need someone who's scaled a similar system before, not just "senior" title
- MATCH scorecard emphasis: Ability (has scaled a transactional system past 10x growth), Culture/Stage fit (thrived at Series B-equivalent chaos, not just big tech comfort)
- Sourcing channel: engineers from fintech startups that already hit this scaling wall (Stripe-adjacent alumni, payments infra teams at similar-stage companies)
Example 2: Candidate Screen Input: Candidate with 8 years at a 5,000-person tech company, strong resume, applying for a founding engineer role at a 4-person startup. Output:
- Motivation: 4/5 — clear reasoning about wanting ownership
- Ability: 5/5 — strong technical background, verified via GitHub/take-home
- Trajectory: 4/5 — increasing scope each role
- Culture/Stage fit: 2/5 — no evidence of operating without process/support; hard pass risk
- Recommendation: Do a scenario-based screen specifically probing ambiguity tolerance before advancing. Don't advance on resume strength alone.
Recommendation▾
Add guidance on handling edge cases like career changers, non-traditional backgrounds, or remote-only candidates
Best Practices
- Build the MATCH scorecard before sourcing, not after — prevents bias from creeping in during evaluation.
- Always verify Ability with real artifacts (code, systems design walkthrough, past project deep-dive) — resumes lie, work doesn't.
- Weight Culture/Stage fit heavily for early-stage startups; it's the #1 reason strong-on-paper hires fail in the first 6 months.
- Personalize outreach using something concrete (a blog post, OSS contribution, specific past company challenge) — response rates on generic messages are low and getting lower.
- Close on the specific risk factor, not a generic pitch — most declines trace back to one unaddressed MATCH gap (usually stage risk, comp, or trajectory concerns).
Common Pitfalls
- Don't treat "years of experience" as a proxy for Ability — it isn't.
- Don't skip the intake step and source directly off a stale JD — you'll fill the wrong role.
- Don't advance candidates who score well everywhere except Culture/Stage fit — this is the single biggest predictor of early-stage startup hire failure.
- Don't use the same outreach template across company stages — a message that works for a Series C won't land with someone considering a pre-seed risk profile.
- Don't skip the debrief step — without a shared MATCH vocabulary, hiring manager feedback becomes vague ("didn't feel like a fit") and unactionable.