The 4-sentence cold email frame I keep coming back to (per-sentence job spec)
Pasting this here because I keep getting asked to share it. Most "AI cold email" prompts give you something polished but generic... this one specs a job per sentence, and the per-sentence job is what actually makes the output work .
You are a senior B2B sales copywriter who has written cold emails that booked 500+ demos for SaaS companies in the $10K-$100K ACV range.
INPUT
- Target prospect role + company: {{ROLE}} at {{COMPANY}}
- Verifiable observation about their company (recent news, hire, launch, job posting): {{OBSERVATION}}
- Pain that observation implies: {{IMPLIED_PAIN}}
- Your product (one line): {{PRODUCT}}
- One quantified result a similar customer got: {{PROOF}}
- Your ask (15-min call / async demo / specific question): {{ASK}}
TASK
Write a 4-sentence cold email:
- S1: Specific {{OBSERVATION}}. Prove you actually researched.
- S2: Connect observation to {{IMPLIED_PAIN}} that is genuinely relevant to their role.
- S3: One-line value claim including {{PROOF}}.
- S4: {{ASK}} — make it low-friction.
Then write 2 alternative subject lines.
CONSTRAINTS
- Subject line: under 6 words, curiosity-driven
- Body: under 90 words total
- No "I hope this email finds you well"
- No "circling back"
- No "quick question"
- Plain text only — no HTML, no images
- The first 50 characters of the body must be visible in mobile preview and earn the open
OUTPUT
Subject: ...
Body: ...
Alt subject 1: ...
Alt subject 2: ...
One sentence on what to say in the follow-up if no reply in 4 days.
Two things that make this prompt land that most others miss:
1. Per-sentence job spec. "Write a cold email" lets the model freestyle. "S1 does X, S2 does Y, S3 does Z" forces structural discipline. Less freedom, tighter output.
2. The "verifiable observation" input is a qualification gate. If you can't fill that field in, you don't know enough about the prospect to email them. The hardest input is the trust check, and it's intentional.
The constraint list is the part most prompts skip. Telling the model what NOT to do ("no circling back", "no quick question") is doing 60% of the work — without it, every output drifts toward the same SaaS-bro template.
The variation I've tested most: dropping the {{PROOF}} number to qualitative if you don't have a real one. Quality of output stays the same.
Disclosure: I keep a directory of ~50 of these at www.prompt-drop.info (free, no signup) same shape across marketers / founders / devs / sales / e-comm / recruiters / real estate / content. Sharing in case useful.