# Hook derivation — worked OBSERVE → INFER → BRIDGE → PROVE chains

The four-line bridge (SKILL.md → "Deriving the hook") is the method. This file shows it executed across industries so you can pattern-match the *shape* of a good INFER line — the one step that separates a one-to-one email from a mail-merge wearing a name tag.

Read these for the INFER line specifically. Notice that in every good example the inference is something the recipient privately knows but didn't expect a stranger to. That recognition — not flattery, not a value prop — is what earns the reply.

## The test every chain must pass

After drafting the INFER line, ask: **"Would this sentence be FALSE for a competitor in the same situation?"**
- If it's true of everyone in the industry → it's a platitude. Go back, pick a sharper OBSERVE fact.
- If it's true only because of *this* specific signal → it's a hook. Ship it.

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## 1. DevOps / infra tooling

- **OBSERVE:** 3 SRE roles open on their careers page for the full quarter.
- **INFER:** unfilled for a quarter means the current rotation is thin and absorbing the pages — recruiting isn't keeping up with on-call load.
- **BRIDGE:** we reduce page volume so a short-staffed rotation survives without the missing hires.
- **PROVE:** ~40% fewer alerts for two infra teams your size, month one.
- *Why it passes:* a competitor with a fully staffed team wouldn't feel this. The pain is specific to the unfilled-reqs signal.

## 2. B2B SaaS selling to RevOps

- **OBSERVE:** they just announced a Series B and a new VP of Sales on LinkedIn.
- **INFER:** post-B2 + new sales leader means the number tripled and the existing pipeline reporting won't survive the new board's scrutiny.
- **BRIDGE:** we make pipeline forecasts the new VP can defend in week one, not month three.
- **PROVE:** [named comparable] cut forecast variance from 30% to under 10% in a quarter.
- *Why it passes:* a flat company with a tenured VP doesn't have the "defend the number to a new board" pain. The funding + hire combination creates it.

## 3. E-commerce / DTC brand

- **OBSERVE:** their site runs a specific subscription app you can see in the page source / their checkout flow.
- **INFER:** that stack has a known involuntary-churn leak at card-expiry — they're losing ~5-8% of subscribers monthly to failed payments, not to cancellations.
- **BRIDGE:** we recover the failed-payment cohort before it churns.
- **PROVE:** [comparable DTC brand] recovered 6% of MRR that was bleeding to dunning failures.
- *Why it passes:* the inference is tied to a *detectable tech detail*, so it's true of them specifically, not "all DTC brands churn."

## 4. Professional services (agency → mid-market CMO)

- **OBSERVE:** they published a case study landing page but their blog hasn't shipped since Q3.
- **INFER:** the content engine stalled — likely the one person who owned it left or got pulled onto launches, and the pipeline that content fed is now thinning silently.
- **BRIDGE:** we keep the demand-gen content shipping without the headcount they just lost.
- **PROVE:** kept [comparable]'s organic pipeline flat through a content-team gap.
- *Why it passes:* the gap between "has case studies" and "blog stopped" is the specific, observable evidence of a stall — not a guess.

## 5. Fintech / regulated

- **OBSERVE:** a new compliance regulation with a known enforcement date hits their license type in 6 months.
- **INFER:** their compliance team is now triaging which controls to retrofit first, and the audit-trail gap is usually the one that surfaces late and panics legal.
- **BRIDGE:** we close the audit-trail gap so the deadline is a checkbox, not a fire drill.
- **PROVE:** [comparable] passed the equivalent audit with zero findings on first pass.
- *Why it passes:* the deadline is real and dated; the inference about *which* control bites last is the insider-grade detail that earns trust.

## 6. When the only signal is weak (the honest fallback)

Sometimes you genuinely cannot find a strong signal — the company is quiet, no hiring, no news. Do NOT fabricate. Two legitimate moves:

- **Use a category-level trigger honestly framed as a hypothesis, not a fake observation.** "Most [role]s at [company size] in [industry] are hitting [specific pain] right now — if that's you, [ask]. If not, ignore me." This is weaker than a real signal (expect reply rates at the low end of the band) but it's honest and still binary.
- **Kick it back to targeting.** If you keep landing on companies with no signal, the list is the problem, not the copy — that's a `lead-gen` ICP/timing gap. The fix is a better-segmented list with built-in triggers (recently funded, recently hiring, recently launched), not a cleverer sentence.

Never close the gap with an invented "I loved your recent post" — a signal the recipient knows is false destroys the contact on the first line.

## Anti-examples — INFER lines that FAIL the test

| Generic INFER (platitude) | Why it fails | Sharper version |
|---|---|---|
| "...so you probably want to grow revenue" | True of every company alive | Tie growth to the specific signal (new funding round → "defend a 3x number") |
| "...so you care about efficiency" | Vacuous; everyone claims this | Name the specific inefficiency the signal implies |
| "...AI is transforming your industry" | A trend, not a fact about *them* | Drop it; find a fact you can screenshot |
| "...I imagine scaling is a challenge" | Hedged guess, no observed basis | Only say it if a hiring/funding signal makes it observable |

The pattern: a failing INFER line is true regardless of the OBSERVE fact. A working one is true *because* of it.
