Here's what caught my eye this week. A lot of conversation about signals, AI-powered outbound, and the mechanics of follow-up. Some of it is genuinely useful. Some of it is people discovering things practitioners figured out years ago. Let's go through it.
The Email That Made 49,000 People Stop Scrolling
Nearly 50,000 likes and over 10,000 saves. That's not engagement - that's people bookmarking a reference. When a cold email example gets that kind of traction, it tells you something important: most people sending cold email have never seen what a great one actually looks like. They're guessing. That gap between what practitioners know and what the market produces is exactly why cold email still works so well when you do it right. The bar is low because almost nobody clears it.
"I've Never Opened a Cold Email Until Today"
This is the real proof of concept. Not a case study. Not a screenshot of a reply rate dashboard. Someone who actively ignored cold email their entire life got moved enough to open one and post about it publicly. That's the standard worth aiming for. And notice it wasn't "I replied" - it was "I opened." The subject line did the job first. If you want to see what subject lines actually get opens, we have a full breakdown at /subject - this kind of real-world reaction is exactly what the best ones produce.
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Access Now →What a Growth Engineer Actually Does
>writes cold email sequences AND builds the automation that sends them
>sets up enrichment pipelines so ur list isnt 40% dead emails
>figures out why ur product doesnt show up in chatgpt and fixes it
>scrapes intent signals from reddit twitter and linkedin to find warm leads
>builds landing pages AND runs the A/B tests on conversion
>sets up attribution so u actually know which channel ur customers came from
>automates follow-up sequences (where 50%+ of replies actually come from)
>optimizes ur site so AI search engines cite u not ur competitor
>writes content that ranks AND builds the infra that distributes it
>monitors competitor mentions and turns them into displacement campaigns
>builds lead scoring models so sales talks to the right ppl first
>sets up separate outbound domains so ur main domain doesnt get torched
>waterfalls multiple data providers because no single one has clean data
>tracks headcount changes by department to spot buying signals
>reads job posts to find companies actively looking for what u sell
>pulls competitor customer pages and enriches every logo into a target list
>builds dashboards that connect content performance to actual signups
>creates drip campaigns that adapt based on how the lead interacts
>turns churned power users into warm leads at their new companies
>filters lists by mx record before writing a single line of copy
>finds the 3 attributes every closed-won account shares that ur ICP doc never mentions
1,653 saves. That's the number that matters here. People are saving this as a job description, a checklist, and a service menu all at once.
A few lines stand out. "50%+ of replies actually come from follow-ups" - that matches what I've seen across millions of emails. The first touch is a bet. The follow-up is where you collect. "Filters lists by mx record before writing a single line of copy" - this is the kind of thing that separates people who understand deliverability from people who keep wondering why their open rates collapsed. You validate the list first. Every time.
The one I'd push back on slightly: this list describes a unicorn. In practice, the best outbound operators I've worked with are excellent at two or three of these, not all twenty. If you're hiring, pick the three that are actually your bottleneck and find someone who is elite at those. Don't hire a generalist who is mediocre at everything on this list.
How a Cold Email Started a 2M Company
It all started with a cold email to @fejes713 and @tornjanski_ asking if they wanted to brainstorm about starting a company. We spent the next four months ideating before finding the gap in enterprise-grade video AI. Today, Fortune 500 brands, global agencies, and Hollywood studios create on Preview.
There are 3,000 studios on Preview's waitlist. Sign up today.
$12M raised. Sequoia involved. It started with a cold email asking if someone wanted to brainstorm. Not a polished pitch deck. Not a warm introduction through a VC network. A cold email. This is what I mean when I tell people cold email is not just a sales tool - it's a relationship-building tool, a co-founder-finding tool, a career-launching tool. The people who think cold email is only for flogging SaaS subscriptions are leaving enormous value on the table.
Timing Is the New Personalization
when every competitor can generate personalized outreach at scale, personalization alone stops being an advantage.
timing becomes the edge.
you can build a Hermes agent that watches your target accounts for new hires, funding, product launches, expansion, leadership changes, and other signals tied directly to your offer.
qualified accounts stay in monitoring until the agent finds a credible reason to start the conversation.
when a signal appears, Hermes verifies the source, refreshes the account research, identifies the right buyer, and prepares outreach around what actually changed.
the article below shows how to build this signal-driven outbound system with Hermes:
This is the most practically important idea in cold email right now, and it deserves more than 116 likes.
The argument is correct: when AI lets every competitor spin up "personalized" outreach at scale, personalization stops being a differentiator and becomes table stakes. What nobody can fake is timing. If you reach a prospect the week they hired a VP of Sales, or three days after a funding announcement, or right as they're expanding into a new market - that's not personalization, that's relevance. And relevance is worth more than any first-line compliment about their LinkedIn post.
I've been running signal-based targeting at ScraperCity for a while now. Job postings alone are one of the cleanest buying signals available - a company posting for a role adjacent to what you sell is practically waving a flag. The growth engineer list above mentions this too: "reads job posts to find companies actively looking for what u sell." That's not a new idea but most outbound teams are still not doing it systematically. If you want to set up a proper tech stack around this, check out what we put together at /coldemailtechstack2025.
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Try the Lead Database →The Outbound Channel Tier List That Needs a Correction
S TIER
- linkedin inmails
A TIER
- cold email
- linkedin connection requests
B TIER
- cold calling
- paid ads
C TIER
- conferences and trade shows
- organic content
D TIER
- direct mail
- ai sdr platforms
F TIER
- cold dms on twitter or instagram for b2b
- buying leads from a broker
LinkedIn InMail in S tier above cold email. I can't let that one go.
InMail has a volume ceiling that cold email doesn't. You can send 500,000 cold emails in 90 days - I have clients doing exactly that right now. You cannot do that with InMail. Cold email is also cheaper, more controllable, and more measurable. InMail works well, I'm not denying that, but S tier implies it's categorically better than cold email and the data doesn't support that at scale.
AI SDR platforms in D tier is also interesting. I think the placement is right directionally - most of them are middleware that adds cost without adding strategy - but the reason is nuanced. It's not that the technology is bad. It's that people plug AI SDRs into broken offers and weak lists and expect the automation to fix the fundamentals. It won't.
Organic content in C tier feels about right for pure outbound impact, but the compounding effect over time makes it more valuable than the tier suggests. Content warms your entire list, which makes every cold email you send easier to land. It doesn't show up in your reply rate spreadsheet but it's doing real work.
The 90-Day Multichannel Sequence That Booked 42 Calls
we changed exactly ONE thing (and i'm giving it to you for free):
we stopped running cold email as the entire funnel... and made it just the top.
before that fix, the SAME breakdown was repeating itself, and i see it at almost every company i audit:
→ a warm reply lands and nobody follows up fast enough, so it goes cold
→ the same interested account gets one touch and then nothing after it
→ the pile of "not right now" leads just sits there and never gets called
you NEED to watch out for this.
it sneaks up on a lot of you who are busy, but still have an outbound engine running.
outbound is only the top of the funnel, and one weak point downstream kills the whole motion.
and with trust collapsing across every channel right now, a single disconnected touch will almost NEVER close.
what will ACTUALLY book you calls is a connected 90-day sequence, and it's the exact one we run internally.
so i documented it in one resource… and inside I go over:
1. the 90-day sequencing map: cold email in the first 30 days, LinkedIn from day 30 to 60, phone calls from 60 to 90, paid ads once you pass 90
2. the machine-gun-then-sniper testing method that proves the offer works before you build a single workflow
3. the LinkedIn credibility layer that flips a cold reply into a booked call
4. the warm-call reactivation play that pulls a booked meeting out of your stuck pool in a 30-second dial
5. the 5-question offer screen that kills pointless workflow-building at the very start of the engagement
6. the channel decision grid that tells you when to bolt on a new channel and when to cut one
The core diagnosis here is exactly right: cold email as the entire funnel is a setup for failure. The email gets the conversation started. What happens after the first reply determines whether it closes.
The specific breakdown he describes - warm reply comes in, nobody follows up fast enough, it goes cold - is the single most common and most preventable pipeline leak I see when I audit outbound operations. You built the machine to get the reply, then you let the reply die in someone's inbox. That's not a cold email problem. That's a follow-up problem. The fix isn't better emails - it's a faster process from reply to booked call.
The 90-day sequencing structure (email first 30 days, LinkedIn 30-60, phone 60-90) is a reasonable framework. The channel layering matters because trust accumulates across touchpoints. Someone who has seen your name in their inbox and on LinkedIn is a fundamentally warmer prospect than someone who has only seen one channel. For a detailed look at how to build that follow-up sequence properly, see /followup.
$4.3M ARR and 500,000 Cold Emails: The Real Numbers
A few months ago we were at €0.
This is the second SaaS I've built. The first one I sold at €500K ARR.
This time, we moved faster.
Here's exactly how we did it, so you can do it too.
The core principle that changed everything:
We used our own tool to grow our own tool.
1) Outreach (the engine)
- LinkedIn: 10 accounts, 30 connection requests + 30 DMs per account per day.
Only targeting warm leads showing real intent.
- Cold email: currently sending 15,000 emails per day.
500,000 sent in 90 days.
120 domains, 300 inboxes, plain text only, no links, no images, 2-3 email sequences max.
Total infra cost: ~$5000/month.
The offer is always the same: a valuable blueprint. No pitch. Just value first.
2) Inbound (the compound effect)
- LinkedIn: 6 posts per day across 6 accounts.
- Reddit: 14.8M+ views in 12 months.
- YouTube: Long-tail SEO content targeting competitor keywords.
- SEO: 100K visitors/month and growing fast.
3) Paid (we're just starting)
- Facebook retargeting + acquisition ($2000/day)
What actually worked:
→ Using our own tool on ourselves (this alone is a cheat code)
→ High-intent outreach > cold outreach. Every single time.
→ Lead magnet posts on LinkedIn that generate thousands of comments.
One post added $5K MRR in under 24 hours. Cost: $0.
→ Speed. Every delay kills momentum.
→ AI helping us do 10x more than we ever could alone.
The path from €0 to $4M ARR is not glamorous.
It's 18-hour days, boring repetitive work, testing things that fail, and doing it all again tomorrow.
This is one of the most honest growth breakdowns I've seen posted publicly in a while, and the infrastructure numbers are worth studying closely.
120 domains. 300 inboxes. 15,000 emails per day. $5,000 per month in infra costs. That's what serious volume looks like. Not 5 domains and a shared IP. The people complaining that cold email doesn't work are usually running it on 2 domains with 1 inbox each and wondering why their deliverability collapsed after week three.
"Plain text only, no links, no images, 2-3 email sequences max" - this matches everything I've tested. Every time someone adds a logo, a calendar link, or HTML formatting to a cold email, they're adding spam triggers and reducing the chance the email reaches a human. Strip it down. If you want templates that follow these principles, /killercoldemails has the frameworks.
The part I want to highlight most: "The offer is always the same: a valuable blueprint. No pitch. Just value first." This is the Hormozi approach applied to cold email, and it works. You're not asking for time - you're giving something useful first. The law of reciprocity does the rest. One of the tweets this week (from @MitchellKeller_) made exactly this point about Hormozi's early strategy: give so much upfront that the prospect feels almost obligated to engage. It's a legitimate psychological lever, not a trick.
Using their own tool on themselves is also worth flagging. I do the same thing at ScraperCity - we use ScraperCity to build our own prospecting lists. If you won't use your own product to grow your business, that's a signal worth paying attention to.
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Access Now →The AI Voice Agent That Handles the Whole Top of Funnel
A business wanted one thing that could handle the whole top of funnel: call the lead, reach the right person, qualify them, and book the meeting, then fall back to email for anyone who didn't pick up.
The hard part was never the calling. It was judgment. The agent has to know it's talking to the actual decision-maker before it says a word about the offer, because the second you pitch the receptionist, the lead is dead. That one rule, confirm the right person or don't pitch at all, took more prompt engineering than the rest of the build combined.
What I shipped:
→ An AI voice agent that calls, sounds human, and presses through automated phone menus to reach a real person
→ Gets past the gatekeeper, confirms the decision-maker, then qualifies with real questions
→ Books straight into the calendar or warm-transfers to a live rep on the spot
→ When no one picks up, a multi-step email sequence takes over on its own
→ Every call and reply syncs back to the CRM automatically
The stack: Retell AI, n8n, GoHighLevel, SmartLead for cold email, Twilio
The technique I'd use again: a hard decision-maker gate before any pitch. The agent stays in "get me to the right person" mode until someone confirms they own the decision. Only then does the offer come out.
The decision-maker gate insight is the best piece of tactical thinking in this thread, and it applies directly to cold email too.
Most cold emails fail not because the copy is weak but because they're going to the wrong person. Sending a pitch to someone who can't approve budget is worse than not sending at all - they become a blocker. The principle here (don't pitch until you've confirmed you're talking to a buyer) translates directly to how you build your list before you write a single word.
The fallback to email for anyone who doesn't pick up is smart system design. Smartlead as the email engine in this stack is a solid choice for that use case - it handles the sequencing and inbox warmup without you having to babysit it. The broader lesson: AI voice and cold email are not competing channels. They're complements. Phone call attempts the high-intent conversation; email catches everyone else and keeps the sequence alive.
Cold Email Teaches an Important Business Lesson
Point is you always need some sort of CTA attached to it. Buy, reserve, pre order, sign up, whatever. Where it's impossible for you to receive an answer that isn't a clear yes or no. They either take the action you tell them to take or they don't
Again sole goal is to find out asap whether any of this is actually real or not. Getting repeatedly rejected is a W equally as much as getting money thrown at you. Ditch idea, tweak idea, or continue with idea. Gives you data that will immediately inform your next move. Remember that the only L is not putting yourself in a vulnerable enough position to receive that data
"The only L is not putting yourself in a vulnerable enough position to receive that data." That's one of the cleaner articulations of why cold email matters beyond just booking meetings.
Cold email, when you strip everything else away, is a fast feedback loop. You send 100 emails with a specific offer and a specific CTA. The replies (or the silence) tell you whether the offer resonates, whether you're talking to the right people, and whether the problem you're solving is real. You can learn in 72 hours what would take months through building in isolation.
This is why I tell founders who haven't validated their offer yet to send cold emails before they build anything else. The market will tell you the truth faster than any advisor, investor, or focus group. Every no is a data point. Enough no's in a row means you adjust the offer, the ICP, or the message - not that you quit.
Cold Email Wins a PhD and Starts a Company
I will always to say a word of prayer for both of them 🙏🤲
This one is worth including precisely because it has nothing to do with selling SaaS. A cold email secured PhD funding. Before that, one started a $12M company (see the Preview raise above). Earlier in the week's conversation, a Waterloo intern mentioned using a cold email to land a Tesla internship in California.
Cold email is a universal mechanism for getting in front of people who can change your trajectory. Most of the people who dismiss it have never sent a well-crafted one to someone who actually mattered to them. The templates that work for B2B sales work for graduate school applications, partnership pitches, job offers, and co-founder conversations. The structure is the same: relevance, specificity, clear ask, easy to say yes to.
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Try the Lead Database →The Three-Paragraph Formula That Still Works
>subject line shows value to the reader
>three very short paragraphs (who you are + vision + homework)
>clear CTA
thats really all there is to it
576 saves. This formula gets saved every time it surfaces because it's correct and it's simple enough to act on immediately.
The "homework" paragraph is what most people skip. You, who you are, what you want - that's what most cold emails contain. The homework paragraph is the one that proves you actually looked at their business, understood a specific problem, and came with something relevant. It's not flattery. It's evidence that you did the work before asking for their time. That's the difference between a cold email and a spam blast.
Subject line shows value to the reader, not value to you. This is the mistake I see constantly. "Quick question" shows no value. "Idea for [Company]'s Q4 pipeline" gives the reader a reason to open. The value has to be on their side of the transaction from the first word. For a full breakdown of what's working in subject lines right now, check /subject.
The Claude AI Watermarking Claim - Slow Down
the watermark is baked into how Claude picks its words
so deleting the little AI tag does nothing, cropping does nothing, rewording a sentence does nothing
the pattern lives in the word choices themselves, spread across the whole text
that means every essay, caption or cold email you pass off as your own can be traced back to a model
here is what this changes for you
if you are selling AI writing as human work, that gap is about to close
start building that habit now while everyone else is still pasting raw output and hoping nobody checks
Treat this with skepticism until there's something concrete to verify. The claim that Claude is embedding undetectable watermarks in word-choice patterns is not confirmed by Anthropic publicly, and the framing here is designed to create urgency around a problem that may not exist yet.
That said, the underlying point is sound regardless of whether this specific claim is true: if you're passing raw AI output as human-written outreach, you're building on shaky ground. Not because of watermarks - because AI-generated cold emails that haven't been edited, personalized with real signal, or connected to a genuine offer read exactly like what they are. Recipients can feel the pattern even if they can't articulate it. The fix isn't to panic about detection tools. The fix is to use AI as a starting point and put real thinking on top of it.
The Takeaway Worth Acting On This Week
If I had to pull one thing out of this entire week's conversation and hand it to someone building an outbound system from scratch, it would be this: the teams producing results right now are not winning on copy quality. They are winning because they reach the right person at the right moment with a relevant reason to respond.
Personalization at scale is now a commodity. Every competitor has access to the same AI tools. What they can't replicate easily is your system for identifying and acting on real buying signals - job changes, funding rounds, product launches, headcount expansion, competitor mentions. Build that signal layer before you spend another hour rewriting your opening line.
And when the reply comes in, have a follow-up sequence ready to run before you need it. The $4.3M ARR case and the 42 calls in one month case both point to the same thing: the email gets the conversation started, and the system keeps it alive. If you want the scripts to build that system out, start with /top5scripts and layer from there.
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