Co-Founder & CEO at LeadHaste - a world-class B2B lead-gen agency that sends you ready-to-buy prospects so your team can spend time on what matters most: closing deals.

️Dimitar Petkov

My Christmas gift from Clay  arrived on January 20.

Because I forgot to add my country code to my phone number.

So my gift went on a world tour without me.

The package is packed with little GTM-engineer joy.

A “GTM Engineer Dept.” cap.

A blue “Data Kit” toolbox.

Stickers and a notepad.

And a book called “Consolations,” which feels oddly on-theme for my data mistake.

It’s a good reminder that most “big” ops problems start as small input problems.

One missing prefix.

One wrong field.

One assumption that nobody checks.

Here’s the mini checklist we use now before anything ships, syncs, or launches.

Step 1: Normalize phone numbers to E.164 (+country code, no guessing).

Step 2: Add validation at the form level, not after it hits the CRM.

Step 3: If the number looks local, force a country selection.

Step 4: Store raw input and cleaned output, so debugging is easy.

Step 5: Spot check a handful before the first batch send.

My takeaway.

Data hygiene is not admin work.

It is pipeline protection.

What is the smallest data detail that causes the biggest downstream mess in your GTM process?

⚡️Dimitar Petkov

Clay World Record Holder | Co-founder @ LeadHaste | Clay & Smartlead Certified Partner

Two small Clay updates just fixed two daily annoyances for me.

I have been waiting for both for a long time.

Update 1 is in Waterfall Email Finder.

The old flow could validate the same email over and over if multiple providers returned the same address.

That meant paying to re-validate an email we already had.

Now we can set a “Threshold for duplicate results” in the waterfall.

If the same email shows up 2 or 3 times, Clay stops running more providers instead of burning credits.

The setup I use now is simple.

Pick your providers like before.

Set the duplicate threshold to 2 or 3.

Let the waterfall stop itself when it is clearly repeating.

Update 2 is a built-in wait time before a node runs.

I used to do this manually with an n8n setup and I even made a YouTube video on it.

Now you can just set “Run after delay” right inside the node run settings.

This is huge for async HTTP API calls where the first request starts a job and the data shows up later.

We use BetterContact for some “find people” workflows, and that async timing is exactly where this helps.

If Gmail doesn’t trust you, nothing else matters.

You can have perfect copy, clean lists, the right tool stack, and still land in spam because your sending pattern screams “new sender + risky behavior.”

One advanced deliverability habit that moves the needle fast: traffic shaping.

Most teams “ramp volume.”

Very few shape where that volume goes and how it behaves per mailbox provider.

Here’s the framework:

1. Keep a stable baseline. 
- Gmail hates volatility. 
- Ramp up, but do it with small, consistent steps. Spikes look risky.

2. Shape by engagement, not by inbox provider
Instead of trying to “split Gmail vs Outlook,” split by behavior:
- Start sends to your best-fit, most responsive segment
- Expand only after you see replies/opens stay healthy
- Pause the dead segment before it drags your whole domain down

3. Protect the first touch

First email should be plain and easy to trust:
- one idea
- no heavy link stuffing
- no weird formatting
- one clear question

4. Warm up the right way

Warm up isn’t “seed replies.” It’s proving you’re a normal sender:
- age domains before volume
- authenticate properly (SPF, DKIM, DMARC aligned)
- ramp slowly with real outbound patterns, not artificial inbox activity

5. Don’t rely on reseller lists if you care about deliverability

- If the data is stale, you’ll pay for it in bounces and complaints.
- At scale, list quality is the deliverability lever: validate, suppress risky addresses, and cut anything that spikes hard bounces.

Connect with me & Reply “DELIVER” and I’ll send my full checklist of 46 items.

Dimitar Petkov📨

Clay World Record Holder | LeadHaste | Clay & Smartlead Certified Partner

Sales calls are fun when you stop treating them like a trial.

And start treating them like a conversation with another human.

I was reviewing a call transcript and the thumbnail made me laugh.

Two founders smiling like we are on a podcast.

A notetaker bot waiting patiently in the corner.

And a prospect on the other side of the screen (blurred).

This is the part people forget about sales.

Most calls are just two adults trying to solve a real problem with limited time.

When you show up curious, the call gets lighter.

Not fluffy.

Just human.

Here is what makes the process genuinely enjoyable for us.

We do not try to win the call.

We try to understand their Tuesday.

We ask, “Walk me through the last time this went wrong.”

We ask, “What did you try already.”

We ask, “What would make this a clear yes for you.”

Then we say the quiet part out loud.

“If we are not a fit, I will tell you fast.”

That one line drops the guard almost every time.

And the call turns into a real exchange.

Less performance.

More problem solving.

We also do one small thing that keeps it fun.

We look for the moment we both laugh.

Because that is usually the moment trust starts.

Not because we are friends.

Because the pressure is off and the truth comes out.

Our rule now is simple.

If we cannot build rapport while staying direct, we are making sales harder than it needs to be.

What do you do on calls to keep it human without losing the edge?

The first 500 outbound messages should never be delegated.

Not to an SDR.
Not to an agency.
Not to automation.

Founders see things nobody else does.

You hear the real objections.
You notice which words trigger replies.
You learn what people actually care about, not what your deck says they should care about.

Most teams skip this part.
They hand outbound to someone else too early.
Then they spend months fixing the wrong problems.

Those first 500 messages are not about scale.
They are about signal.

After that?
Yes, systemize it.
Yes, automate it.
Yes, hire.

But only after you’ve earned the right to delegate.

Curious how many founders here actually sent their first outbound themselves?

Most cold emails fail because they feel risky to answer.

Not because the offer is bad.
Not because the timing is wrong.

Because replying feels like work.

Every question you ask adds friction.

Every calendar link raises commitment.

Every long explanation creates pressure.

From the prospect’s point of view, replying is a decision with consequences.

“Will this start a sales process?”
“Will I get pitched?”
“Will this eat my time?”

The best cold emails do the opposite.

They lower emotional commitment.

They make replying feel safe.

Examples that reduce friction:
- Binary replies instead of open questions
- “Worth exploring?” instead of “Can we schedule a call?”
- Permission language instead of urgency
- Short emails that can be answered in 5 seconds

Reply rate is not about persuasion.

It’s about how easy it feels to say something back.

Curious how others here design for low-friction replies. What’s worked for you?

The real power of Clay isn’t enrichment.

It’s constraint.

Most outbound systems fail because they surface too many options.

Too many signals.
Too many scores.
Too many “maybes.”

You end up debating leads instead of acting on them.

Clay becomes dangerous when it’s used to add information.

It becomes effective when it’s used to remove ambiguity.

One table.
One rule.
One output.

Good Clay setups don’t ask,
“Is this a good lead?”

They ask,
“Should this be sent or not?”

If a human has to think after the table runs,
the system is unfinished.

Decision compression is the goal.

Less interpretation.
Fewer edge cases.
Clear yes or no paths.

Clay isn’t there to make you smarter.

It’s there to make decisions boring and obvious.

How are you using Clay today: exploration or execution?

Cold email is about to be judged by something that is not human.

Google is rolling AI summaries into Gmail.
Which means your email might get read, compressed, and ranked before a person ever sees it.

That changes how I think about writing outbound.

Not the format.
Not the tools.
The intent.

Up until now, we wrote emails for skimming eyes.
Subject line.
First line.
Maybe a second glance.

Now you are also writing for an AI that asks one question:
“What is this actually about and should it matter?”

If your message is vague, clever, or hides the point, the summary will expose that.
If your value is clear, it might actually help you.

Here is the real shift I see coming:

Cold email stops being about intrigue.
It becomes about clarity under compression.

When an AI turns your email into two sentences, do those sentences help you or hurt you?

A few things I expect to matter more:

- Plain language over clever copy
- One obvious outcome, not three soft benefits
- Offers that sound useful even when stripped of tone
- First touches that give value instead of asking for a meeting

And fewer emails that start with “quick question.”

This will probably hurt spray-and-pray outbound.
It might actually reward people who already write clearly and honestly.

No one knows exactly how Gmail will rank or surface these summaries yet.
But one thing feels safe to say:

If your email can’t survive being summarized, it probably wasn’t strong to begin with.

Curious how others are thinking about writing for an AI-first inbox.

Deliverability problems should not be discovered in a dashboard.

They should show up in Slack in under a minute.

We built a small Smartlead to Slack anomaly alert runbook for that.

It watches a few webhook events that tend to show trouble first.

It posts a clean alert into a dedicated #deliverability-alerts channel.

It includes the exact campaign, domain, and the rates that triggered it.

For severe cases, it pauses the campaign and blocks the bad domain or lead in our database.

It then opens a triage thread or task so someone owns the follow up.

These are the Smartlead events we monitor 24/7 for:
- campaign.bounce_threshold.breached 
- email.account.disconnected
- campaign.status.changed

Slack gets the same message format every time.

- Campaign
- Domain
- Bounce rate
- Seed summary
- Recommended next step

The last step is ownership.

We create a ClickUp task and start a threaded Slack message tagging the owner.

The rule we follow now is simple.

Alerts without an owner are just noise.

What is your “red line” metric where you auto pause instead of waiting for a human?

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Good cold emails feel unfinished on purpose.

That sounds wrong, but it works.

When an email explains everything, there’s nothing left to respond to.
No tension.
No curiosity.
No reason to type back.

The best cold emails leave a gap.

They hint at a problem without diagnosing it fully.
They suggest an outcome without showing the whole playbook.
They sound human, not polished.

Over-edited emails get skimmed.
Slightly awkward ones get replies.

This is why decks don’t belong in cold email.
This is why long explanations kill response rates.
This is why “just enough” beats “perfect.”

Your job is not to convince in one email.
Your job is to start a conversation.

What’s the smallest amount you can say and still make someone curious enough to reply?

Scaling outbound isn’t hiring more SDRs.

It’s fixing the system they work inside.

Most teams try to grow volume
before they fix flow.

Leads come in messy.
Routing is unclear.
Replies sit untouched.
Follow-ups depend on memory.

Adding headcount just multiplies the chaos.

Real scale looks boring.

Clean enrichment before a lead ever hits a sequence.
Clear rules for who follows up and when.
Automatic routing based on intent, not titles.
One source of truth for replies.

When the system is right,
one rep does the work of three.

When it’s not,
ten reps still miss deals.

Before you ask “who should we hire?”
ask “what should happen automatically?”

Want a subject line that NEVER gets opened?

Use these.

If you use any of these, your open rate is fighting for its life.

1. RE: when there was no previous email
2. FWD: because lying is apparently a strategy
3. Free!!! (triple exclamation marks never convinced anyone)
4. 100% guarantee (of being ignored)
5. Act now like it’s a 1999 infomercial
6. Risk-free said by someone you don’t trust yet
7. $$$ because spam filters love money symbols
8. ALL CAPS ANYTHING
9. Exclamation marks everywhere!!!!!
10. Emojis in cold outreach 😱🔥🚀
11. Obvious clickbait (“You won’t believe this…”)
12. Fake urgency (“Last chance” sent 3 weeks in a row)
13. “Quick question” followed by 7 paragraphs
14. “Just circling back” on the first follow-up
15. Overpromising math (“Save 1,52,453 hours per second”)
16. Buzzword soup (“Synergizing AI-driven growth levers”)
17. Long ass headlines that sound like a landing page hero
18. Subject lines longer than the actual email
19. Trying to be clever instead of clear
20. “How Can My Amazing SaaS Help You Save Everything Forever With Zero Effort”

Good subject lines do one thing.

They make someone curious enough to open.

Not impressed.
Not sold.
Not tricked.

Just curious.

If you want replies, write like a human.

What would you add to that list?

Personalization is killing your cold email replies.

Yes. Even when it looks “smart.”

Here’s the trap I see all the time in cold email.

People personalize the wrong thing.

They open with
“Loved your recent post about X”
or
“Congrats on the Series A”

And then… nothing relevant follows.

The reader thinks:
“Cool. You stalked me. Why are you emailing me?”

Personalization without relevance is just noise.

It actually hurts you because:
	•	It delays getting to the point
	•	It signals automation in disguise
	•	It steals attention from the real problem you solve

The goal of the first line is not to prove effort.

It’s to prove relevance.

A better test:
Would this email still make sense if I removed the personalized line?

If the answer is no, you’re hiding behind personalization.

Relevance beats personalization every time.

Curious where you draw the line between useful context and wasted words in cold email.

Most outbound tests are statistically useless.

Especially in cold email.

Teams spin up Smartlead campaigns, run 5 subject lines, and declare a winner after 2 days.

Nothing meaningful was tested.

Why?

Because the variable wasn’t the copy.
It was the list.

Different ICP slices.
Different company sizes.
Different intent levels.

So when one subject line “wins,” you didn’t learn anything.

You just emailed a better audience.

Good outbound testing is boring:
	•	Same ICP
	•	Same filters
	•	Same volume
	•	One variable changed

If you can’t explain why something won, it didn’t win.

Subject lines don’t fail in isolation.
They fail in messy systems.

Fix the system first.
Then test the copy.

Curious what you standardize before running outbound tests.

More data does not make outbound better.

It usually makes it worse.

Most teams treat Clay like a slot machine.

Pull every enrichment possible.
Add 15 fields.
Hope something magically converts.

What actually happens:
	•	Lists get noisier
	•	Personalization gets forced
	•	Reps don’t know which signal to trust

The best outbound teams don’t use data to add context.

They use data to remove bad fits.

Examples:
	•	Excluding companies that already use a competitor
	•	Filtering out roles that can’t buy
	•	Killing accounts with obvious disqualifiers

That’s data hygiene.

If enrichment doesn’t change a decision, it doesn’t belong in your workflow.

Outbound isn’t a data collection problem.

It’s a decision-making problem.

Curious what signals you’ve found most useful to exclude prospects, not personalize them.

Early lead gen is discovery.

Late lead gen is execution.

In the beginning, everything is noisy.

You are testing ICPs.
You are guessing messaging.
You are learning what actually triggers replies.

Your system should be flexible.

Messy data is fine.
Manual reviews are normal.
Iteration speed matters more than efficiency.

Most teams rush past this phase.

Then, once patterns are clear, the job changes.

Late-stage lead gen is about consistency.

Fewer experiments.
Tighter rules.
Stricter filters.
Less creativity.

At this stage, creativity hurts performance.

Systems win because they remove variance.

The mistake I see most often is running an “early-stage” outbound system forever.

Same chaos.
Same guesses.
Same excuses.

Lead gen maturity isn’t about volume.

It’s about knowing when to stop exploring and start executing.

Where do you think most teams get stuck?

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Peter Kersting

Peter Kersting

Couldn't agree more with this! It's a little like when rewriting something is faster than fixing an old first draft. 

You could keep tweaking the original text, changing paragraphs, shifting the meaning and direction... or you could just write a new draft with your fresh thoughts in the forefront of your mind. 

And similar to writing tools like Grammarly and text-prediction...the danger is in outsourcing your critical judgement, "Yeah, I guess I'll use that word instead" rather than hone in on your craft.

In my experience, AI is: 

-Great for getting unstuck or started (out of your own head). 
-Terrible at deep, accurate research.
-Phenomenal when the use-case and LLM is hyper-specific (ala removing grain from images or cutting between multi-cams).

When people ask me if I use AI my answer is yes, but with this very heavy caveat in mind.

Voice Actor and Content Creator elevating brands with authenticity, energy, and enthusiasm. Elearning | Corporate | Explainer | YouTube | More

Success requires all of you. I’ll make the introductions. Reformed introvert, Professional Weir-Do on a mission to help you Unbland yourself. Get help with your personal brand → Content Lab.

My friend watched me work for 10 minutes and said:
“I think I’ve been using AI wrong this entire time.”

He’s an AI phenom. Years deep in platforms, prompts, and processes. A wizard with AI. There’s very little he can’t do with it.

Me? I’m an old-school Photoshop and Illustrator guy.

We spent the last week jamming on new projects. While making YouTube thumbnails, he hit a wall. The AI kept producing images that were almost right. Close, but not quite.

Weird facial expressions. Odd skin detail. Missed references. Strange lighting. No extra fingers anymore (progress), but mystery hands holding things up.

We laughed every time it output something absurd. Prompt. Re-prompt. Prompt again. Tokens burning.

After his 47th iteration, I said, “Let’s do this like it’s 1999.”
I jumped into Photoshop. Fixed faces. Adjusted lighting. Painted over the weird bits. Combined three outputs into one image.

Fifteen minutes later: done.

He stared at the screen. Then at me.
“I forgot I could do that.”

That’s when it hit us both. He’d become obsessed with one-shotting it. Slowly, conveniently, he outsourced judgment to the machine.

“Lost in the gloss” of shiny AI output.

There’s a "reported" Apple finding that AI isn’t intelligence. It’s sophisticated mimicry. Like a knock-off luxury bag. Good from afar. Far from good.

The irony of AI?
It reminds us to be human.

Back to craft.
Back to taste.
Back to judgment.

Not for nostalgia. But to get it right.
He thanked me—not for fixing the image—but for reminding him why he fell in love with design.

AI didn’t replace his creativity.
It just made him forget he had it.
AI is great for ideation. Terrible for precise, nuanced execution.

The ideal workflow:
Intent and ideas (you).
Repetitive labor (AI).
Judgment, refinement, editing (you).

The best work still happens when you don’t export thinking to the machine.

Are you trying to one-shot your work?
What skills have you let atrophy?
What happens if you pick them back up?

This post reflects how I use Stanley (AI):
Human input. AI output. Human refinement.

I’ll drop a link if you’re curious.
#sponsored #designthinking #creativity

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