i get like 40 sales emails a week and i started actually reading them recently just out of curiosity

something weird i noticed. nearly all of them are from people who also send sales emails for a living. like its one guy selling a service to another guy who sells the same service to someone else.

i replied to one last week just to see what would happen. guy got on a call with me. turns out he was trying to sell me his thing and i was kind of curious what his pitch was. halfway through we both sort of realised neither of us was actually going to buy anything from the other. we ended up just chatting about football for 20 mins. he supports arsenal, poor lad.

ive been thinking about that call all week honestly.

the people i actually know who run normal businesses, my mates dad who does plumbing, the woman who runs the cafe down the road, my uncle who has a small printing company, none of them read these emails. they have a secretary or an assistant or just a personal email they only give to family. the emails go into a void.

so who are these emails actually reaching. its just other people in the same world sending the same things to each other on monday mornings. its mental when you think about it.

i tried to figure out who was actually replying to the ones i looked at and as far as i can tell its almost always other people in tech or marketing. people who recognise what theyre looking at because they send the same stuff themselves.

i dont really have a point im just thinking out loud. one of the emails last month was from a guy in hull who clearly hit send by accident, it just said "please remove me from this list you absolute" and then nothing. i still wonder what the last word was gonna be.

been doing outbound for clients for about 5 years now. ran inboxes for B2B SaaS agencies law firms a few ecom brands. seen 4 major algorithm shifts from google and microsoft in that time. the last one in q2 2025 quietly killed a huge chunk of the cold email industry and most people still havent adjusted their setups. wanted to write something useful for the people who are past the beginner stage and wondering why their numbers are sliding

the order most people get backwards

infrastructure first then list then offer then copy. in that order. if your infra is broken your copy doesnt matter because it lands in spam. if your list is bad your offer doesnt matter because the wrong people are reading it. most beginners and honestly most intermediates obsess over subject lines while their domain is silently cooking. fix the foundation first or nothing else compounds

domain setup

primary domain (yourcompany dot com) should never send cold. ever. buy 3 to 5 secondary domains as variations. so getyourcompany dot com tryyourcompany dot com yourcompanyhq dot com etc. 2 to 3 inboxes max per domain. that gets you somewhere between 6 and 15 inboxes total. youll see people online running 8 inboxes per domain. they will get burned within 6 months. google watches volume per root domain and identical content fanning out from one source is the fastest flag

volume per inbox

20 to 30 sends per day per inbox in 2026. not 50. not 100. the old numbers from the 2022 playbooks are dead. google tightened the screws after the bulk sender rules in february 2024 and again with the q2 2025 algo change. if you push 50 a day expect a 6 to 10 month inbox lifespan instead of 18 to 24. the math on burn rate vs incremental volume rarely works out unless youre running a churn-and-burn agency model which i wouldnt recommend in 2026

the DNS records nobody sets up properly

SPF DKIM DMARC are non negotiable. the one almost everyone gets wrong is DMARC policy. start at p=none for monitoring. read the reports for 30 days. then move to p=quarantine. without proper DMARC your domain has technically been sending unauthenticated mail since the google/yahoo enforcement in early 2024. ive audited maybe 40 client setups in the last year and over half had broken or missing DMARC. its the single highest leverage fix and it takes 20 minutes

warmup truth

the auto warmup features in smartlead instantly mailreef etc are not actually replicating real engagement anymore. google can identify warmup network patterns. it doesnt always punish you but it stopped counting that traffic as positive trust signal sometime in 2024. real warmup means real conversations. send to your own inboxes friends colleagues for the first 3 weeks of any new domain. its boring it doesnt scale but it actually works. think of warmup networks as life support not a workout

reply rate is a deliverability signal not just a campaign metric

this is the one most people miss and it explains why their results decay. google tracks whether recipients reply. low reply rate equals lower trust score equals worse placement equals even lower reply rate next campaign. its a doom loop. one bad campaign with 0.1% reply can poison a domain for weeks. this is why "just send more volume" actually makes everything worse not better

what positive reply rate should actually be

depends on industry but for B2B SaaS targeting mid market expect 1 to 3% positive reply rate. positive. not total reply. anyone hitting 10%+ is either picking 50 perfect prospects per campaign (which is fine but isnt really cold email anymore its researched outreach) or theyre counting auto replies and "unsubscribe me" as positives in their numbers. dont benchmark yourself against twitter screenshots

list quality is doing 80% of the work

apollo has gotten noticeably worse since 2024. data hygiene dropped after they changed their data partnerships. ocean dot io clay enrichment and ZoomInfo for enterprise are the current best options depending on price tolerance. always verify with zerobounce or millionverifier before any send. catch all domains should never be your primary list. one bounce-heavy campaign can kill an inbox for 60 days because google reads bounce rate as a sender quality signal

copy stuff thats currently working

short. plain text only. no images no logo signatures no tracking links if you can possibly avoid them. one CTA. "worth a quick chat" is fully cooked its been pattern matched into the spam corpus. interest-based CTAs that ask a real question are pulling better. specificity in the first line beats traditional personalization. "saw you guys hired 4 AEs last quarter" outperforms "loved your linkedin post" by a wide margin because the first one shows you researched something material the second one is what every clay-and-openai stack outputs

what i'd do starting fresh today

3 secondary domains. 2 inboxes each. 6 inboxes total. start at 15 sends per inbox per day for month 1. ramp to 25 by month 2. tight ICP under 1000 contacts. zerobounce verify everything. write 3 sequence variants and run them sequentially not concurrently so you can actually isolate what works. monitor placement with glockapps weekly. expect 60 days before you have meaningful signal on what works. anyone telling you "i booked 30 meetings my first week" is either selling a course or got lucky on one campaign and will not repeat it

the part nobody likes hearing

cold email in 2026 is mostly an infrastructure and list game. copy is maybe 20% of the outcome. the people winning right now arent the best writers theyre the best operators. if you want to be in the top 10% of cold email senders you need to think like a deliverability engineer first and a copywriter second. the gurus selling courses about hooks and frameworks are 3 years behind where the channel actually is

happy to get into specifics on any of this. especially the DMARC stuff because thats the one that genuinely fixes peoples campaigns overnight when its set up right

not affiliated with anthropic, just been using it heavy since like late 2023. i'll share the actual prompts.

what i'm NOT going to tell you to do

• generate 10,000 first lines and blast them. everyone's done it. inboxes are cooked. your reply rates will be 0.3% and you'll wonder why
• use it to write your whole sequence from a "write me a cold email for X" prompt. the output is recognizable. people are trained to spot it now
• replace your researcher/SDR with it. doesn't work. you need a human checking the output or it goes off the rails in weird ways

what works is using it as a leverage tool for tasks your team is already doing but slowly. that's it. that's the whole insight.

the actual use cases (with prompts)

1. Pain point extraction from job postings

this one made us money immediately. when a company is hiring for a role, that role tells you what they care about. but reading 200 job postings sucks.

we scrape the postings (or just paste them in), and run them through Claude to extract the specific operational pain. then the SDR uses that pain in the opener.

prompt we use (cleaned up version):

Below is a job posting from [company]. I sell [your offer in 1 sentence]. 

Read the posting and extract:
1. The single biggest operational pain point implied by this role existing
2. What problem they're hiring this person to solve (in their words, paraphrased)
3. Any specific tools/processes mentioned that suggest current state
4. ONE specific angle I could use in a cold email opener that ties our offer to what they're actually struggling with

Be specific. Don't give me generic stuff like "they want to grow." If the posting says "must be comfortable in a fast-paced environment with shifting priorities," tell me that means their ops are probably chaotic and their previous person likely burned out.

Job posting:
[paste]

the "be specific. don't give me generic stuff" part is doing a LOT of work in that prompt. without it Claude gives you LinkedIn-tier observations.

example output for a Head of RevOps posting at a series B SaaS we were prospecting:

>

SDR opens with: "saw you're hiring a Head of RevOps - the 'build dashboards leadership actually trusts' line caught my eye. usually means the current ones are getting argued about in QBRs. is that the situation or am i reading too much into it?"

reply rate on that campaign was like 11%. our normal is 4-6%. the question at the end matters btw - it's a real question, not a "would love to chat" thing.

2. The "make this not sound like AI" pass

we still write our own copy. but sometimes a copywriter writes something that's a little too polished or starts every email the same way. we use Claude as a debaiifying pass.

This is a cold email. I want it to sound like a real human typed it on their phone between meetings, not like marketing copy. 

Rules:
- no em dashes (i know you love them, stop)
- lowercase first letter is fine
- short sentences. fragments are ok.
- one specific concrete detail, not vague claims
- DO NOT start with "I noticed" or "I saw" or "Hope this finds you well" 
- DO NOT use the word "leverage" or "streamline" or "solutions"
- if there's a CTA make it a real question, not "would love to chat"
- max 65 words

Here's the email:
[paste]

Rewrite it. Then explain in one line what you changed and why.

the explanation part is for me to learn from. i steal the patterns it uses and update our writer guidelines.

example - here's a "before" my newer copywriter wrote:

>

after Claude pass:

>

the second one isn't "good copy" by 2019 standards. it's choppy. that's the point.

3. Reply classification at scale

this is the boring one but it saves us probably 6 hours/week per SDR. when you're sending 8-15k emails a month per client, you get a LOT of replies. most are not interested in some form. but you have to read them all to find the gold.

we run replies through Claude in batches:

You will classify cold email replies into ONE of these categories:

INTERESTED - they want to talk, book a call, learn more, or are asking real qualification questions
REFERRAL - they're saying "talk to [other person]" or "this is more of a [other team] thing"  
NOT_NOW - interested in concept but bad timing (busy season, just bought competitor, contract renewal in X months)
HARD_NO - not interested, not a fit, will never buy
UNSUBSCRIBE - asking to be removed, GDPR request, "stop emailing"
OOO - out of office autoresponder
QUESTION - asking a question we need to answer before they commit either way

For each reply, give me: category, confidence (high/med/low), and if NOT_NOW, the specific timing they mentioned.

Output as a table. Don't editorialize.

Replies:
[paste batch of 30-50 replies separated by ---]

NOT_NOW is the one that prints money. those are people you should sequence again in X months. most agencies just lose them.

we feed the NOT_NOW replies + their stated timing into our CRM and queue automatic re-engagement. closed a 24k/yr deal last month from a "circle back in Q1" reply from february.

4. Account research before manual outreach (for the high-value accounts)

we do tiered campaigns. tier 1 accounts (the dream logos for the client) get manual research. that research used to take 30-45 min per account. now it takes 10.

the ask is basically - im prospecting [company] for a client who sells [offer]. based on publicly available info (website, recent news, hiring patterns, leadership backgrounds), give me three signals suggesting they might need what we sell OR three signals suggesting they dont. recent strategic moves in the last 6 months that someone INSIDE the company would be talking about. the specific person or role most likely to feel the pain we solve. a non-obvious angle for outreach - not "congrats on the funding round" because everyone says that, something a competitor or vendor wouldnt have noticed. and a reason NOT to pursue them if you spot one.

then the line that matters most: be honest. if you dont have enough info on something, say "insufficient info" - dont make it up.

that last bit is critical. itll still hallucinate occasionally so we never use specific facts (revenue, headcount, recent funding rounds) without verifying. but the patterns and angles it spots are usually solid.

the "reason NOT to pursue" question has saved us from wasting cycles on accounts that had obvious red flags (recent layoffs, just bought a competing solution, exec team that just turned over). probably the most valuable single line in any prompt i use.

5. Variant generation for testing (the right way)

this is where most people screw up. they ask Claude for "20 subject lines" and get 20 versions of the same thing.

instead we ask for variants across DIFFERENT psychological angles:

I have one cold email. I want to test 5 subject line variants, but each variant should be testing a DIFFERENT hypothesis about what makes prospects open emails in this category.

Hypotheses to test:
1. Curiosity gap (a question or incomplete thought)
2. Pattern interrupt (something that doesn't look like a sales email)  
3. Specificity (very specific number or name that signals research)
4. Mutual connection / social proof
5. Direct value claim

Email body for context:
[paste]

For each: give me the subject line, then in one line explain what behavior it's optimized to trigger.

now you're actually testing something. when one wins by a meaningful margin you've learned something about your audience, not just "this 7-word version beat that 8-word version."

6. The "is this campaign actually any good" pre-flight check

ok pretend youre a skeptical b2b buyer who gets like 40 cold emails a day. persona = VP Marketing at a 100-500 person SaaS company.

im gonna paste a 5 step cold email sequence below. for each email tell me:

1. what would you ACTUALLY do if this hit your inbox - delete, ignore, reply, read it fully
2. the single weakest sentence and why its weak
3. what about it screams "automated outbound" vs a real human reaching out  
4. if youre skeptical of any claim being made, what specifically is making you skeptical

be harsh pls. id rather you tear it apart now then have my prospects ignore it next week.

sequence:
[paste]

we kill campaigns at this stage. probably 1 in 4 sequences gets sent back to the writer. clients don't see the bad ones.

the meta-stuff

what doesn't work

• letting Claude decide WHO to email. lead list quality is still 80% of cold email success. AI can't fix a bad ICP, it just sends bad emails faster
• "personalization at scale" via mass first-line generation. prospects can smell it. the algos can sometimes detect it. don't.
• using Claude output verbatim for high-stakes accounts. always have a human pass on tier 1 stuff
• treating it as a copywriter. it's a thinking tool, not a writer. the best prompts are the ones where you do the thinking and use it to compress time, not generate ideas you don't understand

the workflow shift that mattered

we restructured our SDR role around this. used to be: SDR researches account → SDR writes email → SDR sends → SDR handles replies. now it's: SDR + Claude does research in 1/3 the time → SDR writes email (no Claude) → Claude does deliverability/quality pass → SDR sends → Claude pre-classifies replies → SDR handles the ones that matter.

per-SDR account capacity went from ~80/day to ~220/day on tier 2/3 work. tier 1 still gets the slow human treatment.

revenue per SDR roughly doubled. churn didn't change. that's the whole story.

one weird thing i'll mention

we tried having Claude write emails based on prospect LinkedIn profiles. classic personalization play. didn't work as well as you'd think. the emails were "personalized" but in the same WAY every time - mention their job title, congratulate something, then pitch. prospects pattern-match on the structure, not just the words.

what worked better: have Claude SUMMARIZE three random prospects in a campaign and look for what they have in COMMON. then write ONE email that addresses that common thread, sent to the whole segment. counter-intuitive but reply rates were higher.

happy to answer questions. not selling anything, not gonna DM you a "free audit". just figured this stuff was worth writing down because the discourse around AI in outbound is mostly people selling shovels.