Performance-based Hiring
The No BS Guide to Evaluating HR Tech · Free

Know what any HR tech vendor is really selling you — before you sign.

The vendor brings a data scientist to the demo.
You bring this.

A free, buyer's-side evaluation of any hiring tool — measured against current selection-validity science and against employment law in every market you hire in. Paste the result into ChatGPT, Claude, or Gemini. 90 seconds.

Checks every claim against the science · Maps your legal exposure by jurisdiction · Puts the burden of proof on the vendor

The tool — build your evaluation

Which vendor is across the table?

Name the vendor. The generator builds an evaluation prompt for that specific tool. Paste it into any AI chat with web search enabled and you'll walk away with the questions the vendor can't dodge, the science behind their claims, and your legal exposure by market.

Try with a specific tool, not a vendor's whole platform — more focused = sharper evaluation.

Examples: Juicebox Phenom HireVue Plum SeekOut Eightfold LinkedIn Hiring Assistant
Your prompt for
Next steps: Copy the prompt above. Open ChatGPT, Claude, or Gemini with web search enabled. Paste and run. In about 90 seconds you'll have a buyer's-side evaluation at the depth of a paid analyst report — bring it to your next vendor meeting.

Saving your report: The prompt asks the AI to put the report in a document or canvas when it can. In Claude, click the document's name, then Export to save it as Word or PDF. In ChatGPT or Gemini, use the Canvas panel's export or share option. If the report appears in the chat instead, copy it into Word or Google Docs; headings, bold text, and lists carry over, and tables may need light tidying.
What it does for you

Make the vendor prove it

The sales deck is built to survive your questions. This is built to outlast their answers. The evaluation hands you the exact disclosures a serious vendor can produce and a weak one can't: the validity coefficient against measured performance, on what sample, against what base rate; the auto-rejection rate, and whether anyone ever measured how the rejected candidates performed; every path where the tool rejects a human with no human in the loop.

Ask those questions and one of two things happens. The vendor produces the data — and your evaluation just got stronger. Or the vendor can't — and the silence is the finding. Either way, the burden of proof has moved to the side of the table that should have been carrying it all along.

Why you can trust it

Judged by the science — not the sales deck

"4× more accurate." "Reduces bias." "AI-powered." Every claim gets checked against the published selection-validity literature instead of repeated back to you. The benchmark isn't the vendor's white paper — it's the same meta-analytic evidence I/O psychologists use to rank selection methods, anchored to Sackett, Zhang, Berry & Lievens (2022).

Updated belief = Starting belief × Strength of evidence Behind the analysis is the Diagnostic Ratio — the same Bayesian math that runs modern AI, turned on the vendor's tool. A DR of 1.0 is a coin flip. A résumé keyword filter sits near 1.1×. A referral from a trusted former colleague reaches 4–6×. Almost no vendor will tell you where their tool actually lands. This does.
See the math behind the Diagnostic Ratio →
What it protects you from

Compliant everywhere you hire

A hiring tool that's defensible in one country can be a lawsuit in the next. The evaluation reads each vendor against the employment law that actually governs your markets — and tells you where your exposure sits before you sign, not after a complaint lands. It also checks current case law, where courts now treat screening vendors as the employer's agent — so the vendor's risk becomes yours.

U.S. Uniform Guidelines (1978) Title VII / ADA / OFCCP EU AI Act (2024) GDPR Article 22 UK Equality Act 2010 Canadian BFOR Australian Fair Work Act U.S. state & local AI-hiring laws Vendor-as-agent liability
The error other guides miss

Two ways a tool fails you — most buyer's guides check one

Every evaluation asks whether a tool picks badly — the bad hire you can see. Almost none ask the harder question: whose best candidates is it throwing away before anyone looks? That's the Type II error, and it's invisible by design — rejected candidates leave no performance data, and the vendor's own bias audit won't catch it.

A keyword screen barely better than a coin flip isn't just weakly diagnostic — at a typical cutoff it also misses roughly two-thirds of the strong candidates in the pool. Stack three such filters and the misses compound: career changers, returners, fast learners with fewer years on paper, anyone who doesn't match the historical pattern — screened out before a single interview. Adding screening tools to a résumé-based process barely improves who you pick, and steadily worsens who you never see.

Common Stack
  • Credential-based job description
  • AI sourcing on keywords
  • Resume keyword screening
  • Personality assessment
  • Unstructured interviews
  • Generic onboarding
Cumulative DR ≈ 1.2–1.8×
Evidence-Based Stack
  • Outcome-objectives job definition
  • Relationship-based sourcing (warm referrals, internal)
  • Structured screen with past-accomplishment probe
  • Work sample + structured panel
  • Evidence-based debrief (no marginal hires)
  • Structured 30-60-90 day launch plan
Cumulative DR ≈ 8–12×

The evaluation makes both error types explicit for every vendor you run — the hire you'd regret, and the hire you'll never know you missed.

What you get back

One evaluation, three depths

Every conclusion is on the first screen. It opens by stating exactly what was evaluated, then gives you the verdict — and holds up when the vendor pushes back.

60 Seconds
The scorecard. What was evaluated, realistic and best-case DR, how many strong candidates the tool misses, legal exposure, and a bottom line you can quote in a meeting.
3 Minutes
The action items. The exact tests to run on your own data, and the questions to put to the vendor in your next conversation.
Analyst-Grade
The defense. Full mechanism, validity, legal, and Type II analysis — enough to defend the call to your CHRO, your CFO, or the vendor's own experts.

Whether you're running the demo or signing the contract, you read only as far as you need.

Next step

You just audited one vendor. Now audit the whole process.

The evaluator pressure-tests a single tool. The Kaizen Hiring Audit turns the same lens on your entire operation — sourcing through onboarding — and shows where your hiring decisions are being made well and where decision quality is leaking out.

Run a complete audit of your hiring process →