Full Pipeline without 3+ BDRs or a Lead Gen Agency ✨ Top 5 Clay Creator | Founder @ Enablement.ch

You're doing cold outreach already. So your sales pipeline should be full. 

But where are the leads & deals? 

Creating a full sales pipeline is easy. 

You just have to:
→ Create an apollo account and build a list
→ Use an email template from a "LinkedIn Influencer"
→ Send emails & LinkedIn DMs with Lemlist

and on top of that - share content on LinkedIn every day 

You probably tried this already. 
Or hired a Lead Gen Agency to do it for you. 

Why does it not work? 
Here's the truth

#1 - Time
You don't have the time to manually build lists 
AND personalise every message. 

So either reach out to just a few people
or you just spray and pray

#2 - Trust
Everyone can send 1000 emails. 

Just look at your inbox:

→ You are spending 5-10 minutes every DAY to delete emails
→ You look like another Joe Shmoe wanting to ""jump on a call?""

= You & your message don't stand out. 

BUT 

You also know that this can work. 

You see people raving about tools like Clay, RB2B and AI generated messages. 

And you heard about that through people on LinkedIn. 

Ergo personal branding & outreach DO work. 
they can generate qualified meetings,
a full pipeline
and $$$

ONLY 

If you do it right
and create an actual engine
where everything is connected & automated

This system is not just cold outbound
and not just praying that your LinkedIn content creates inbound
This is ALLBOUND

And how do I know this? Two reasons:

#1 - I've done it twice already
 
I generated over $2.4m in revenue in my last role as sales leader at a HubSpot Agency
↳hyper personalised messages at scale in 2022 - BEFORE ai was even possible. 

And now at enablement we generated $200k pipeline in 20 days from a single campaign. 

We practice what we preach. 
Here's how we make our money: 
→ 49.4% Outbound
→ 29.3% LinkedIn
→21.3% Referrals

#2 - We worked with over 70 B2B Tech Companies in the last 18 months

Bound (fintech) 
→ 2x Pipeline in Q1 24
→ 70% Revenue from Cold Outreach

Scrypt (fintech) 
- 10 meetings with C-level per month

Skribble (B2B SaaS)
→ Reduced BDR Team by 80%
→ Still hit revenue targets

XPLN (B2B SaaS)
→ 20+ meetings with CEOs per month

Fruitcore Robotics (Robotics) 
→ Consistently book 85+ meetings per month
→ $543k in Pipeline

If you're thinking now:

"That makes sense, I want know how you REALLY use AI & Automation to create a full pipeline - without a Lead-Gen-Agency or a big BDR team" 

here's the next step. 

DM me and we have a chat. 

PS: This only makes sense if you ACTUALLY want to make a fundamental change in your business and not just looking for a quick fix

Lanny M. Heiz

I started 2025 with $75.9K in monthly revenue, 10,377 followers on LinkedIn, and just 2 people (Gilbert Kralinger and me).

But we had no upsell motion, no renewal system. 

Just a high-margin consulting business. Held together by stress and hustle. 

The goal was clear: hit $100K+ per month and bring on a third person to help with fulfilment or sales.

By Q1, we crossed that $100K mark.

But it didn’t feel like growth. It felt like burnout in disguise, and we were overwhelmed.

Gilbert was pulling 14-hour days to keep delivery afloat.

I stopped doing the thing I was supposed to do (sales, marketing, top of funnel) and got dragged into fulfilment.

We had to pause new client onboardings.
And the momentum stopped.

It was one of the first times I thought, “Maybe we built the wrong thing.”

I kept telling myself we just needed help. And that’s when we hired Pablo Ferrer, total A-player.

But even then, I couldn’t get the energy back.

Deals I was sure we’d win slipped through.
Engagement tanked.

I didn’t want to post. 
I didn’t want to sell.
I didn’t want to scale a system that felt like a treadmill.

Emotionally, I was at rock bottom. 

but then I saw it clearly.

In consulting, if you do your job well, you make yourself unnecessary.

Every project ends. Every month starts from zero.

No compound motion. 
No retention. 
No leverage.

The business was profitable, but fragile.

So we made the call. 

Gave up 90% profit margins, and we went all-in on Fractional GTM Engineering.

We now build, manage and optimise GTM agents for our clients. 

Deliver value every month, get paid every month.

Predictable.
Recurring.
Scalable.

6 months later, I’m entering 2026 with:

$142K MRR,
A 5-person team (still hiring),
18,711 LinkedIn followers.

Most of the revenue now comes from renewals + expansions.

And clients staying 12+ months instead of 3.

A model that actually gets easier, not harder, as we grow.

2025 looked good on paper.
But it felt like survival.

2026 feels like a business.
Built on a foundation. 

LFG

Lanny M. Heiz ✨

GTM Agents that build inbound + outbound pipeline | Clay Enterprise Partner | Founder @Enablement.ch

Personalization stopped working when everyone learned how to do it.
 
Because there’s a big difference between “I saw you went to Harvard”
 
and
 
“I know exactly why you’re googling alternatives to [tool name] at 1PM.”
 
Everyone’s been obsessed with identity-based personalization:
 
Job title, company name, school, funding news, even what podcast you were on.
 
Cute. But not useful.
 
What actually moves the needle in 2026?
 
It’s called Timing-based Context (aka: Why this buyer, why now.)
 
 → What internal trigger was fired?
 → What pain surfaced?
 → What behaviour signaled a need?
 
For example:
 
You don’t sell to a CFO because they raised $50M.
 
You sell because their CAC payback just crossed 24 months and their CEO is pissed.
 
That’s not “personalization”.
That’s precision timing.
 
Allbound teams (inbound + outbound = one system) crush this daily:
 
 📥 Inbound tracks intent signals
 📤 Outbound maps contextual plays
 💡 GTM feeds feedback loops from both
 
It’s not just about guessing who’s a fit.
It’s about catching people when the timing is stupidly perfect.
 
And 99.9% of teams still don’t know how to build this engine.

In 2026, the average B2B scaleup spends over $535,000 a year on GTM tools (Outreach, Zoominfo, Clay, etc.) - but nobody shows how you connect them into a true GTM system. 
 
The Old Predictable Revenue Model:

→ SDR gets Zoominfo seat, builds list manually
→ Prospects each lead 1:1 (or spray and pray)
→ Load it into Apollo / Outreach
→ Hope someone replies
 
This model stopped working 2,3 years ago. Now AI totally killed it.

Why?
 
Because everyone can create a list and send AI personalised emails in seconds.
 
But few build an actual system. Here's the flow we see working in 2026 (based on 100+ clients)  
 
IDENTIFY → ENRICH → ENGAGE → CAPTURE → LOOP
 
This is not a sequence.
 
It’s a cycle, and every part feeds the next.
 
01. IDENTIFY (track signals)
Buyers leave clues long before they submit a form or reply.
 
If you're reaching out without intent signals, you're guessing - and guessing kills reply rates.
 
WHAT TO TRACK
(1) Who visits your website
(2) Social signals (LinkedIn, Reddit, podcasts)
(3) People who viewed your ads
(4) Changes in leadership 
 
🛠️ Tools: Syft Data,Fibbler,Trigify.io, @teamfluence
 
02. ENRICH (Orchestration / Data)
 
When signals fire → triggers activate automations.
 
Not every signal is intent. Sometimes it’s just noise. Enrichments create context -right person, right time, right message
 
WHAT TO DO 
(1) Enrich the account (size, tech stack, persona)
(2) Use AI to score leads based on ICP fit 
(3) Get contact data (email, phone)
(4) Find relevant pain points 
(5) Add leads to CRM 
 
🛠️ Tools: Clay, OpenAI, Anthropic , Gemini

03 ENGAGE (with relevance)
  
If enrichment doesn't shape your message, you've wasted the step. 
 
WHAT TO DO 
(1) AI writes a personal message (based on enrichments)
(2) Create a personalised offer (lovable) 
(3) Add to multi-channel sequence
(4) Sync all activity to your CRM
 
🛠️Tools: Lovable, lemlist, Smartlead , n8n
 
04. CAPTURE (the demand)  
 
A reply isn't the finish line. It's the start of the human in the loop. Call straight away - If it takes more than 5minutes to call a lead, your connect rates drop to <5% (instead of 20-25%) 
 
WHAT TO DO 
 
(1) AI to classify replies (negative, neutral, positive)  
(2) n8n workflow to get the phone number 
(3) Slack notification to SDR to call lead  
(4) Send personalised Loom video     
(5) Book discovery call
 
🛠️ Tools: OpenAI, n8n, BetterContact , Slack , Loom, HubSpot 

05. LOOP (integrate learnings) 
 
Most teams stop here - but this separates a workflow from a system that compounds.

Every outcome feeds the system.

Feedback flows into:
 
Channel: What combo closed the fastest? 
Timing: Time from signal to outreach? 
Content: What triggered replies?
Persona: Who's converting? 

Your GTM starts to learn.
 
Every signal sharpens targeting. 
Every reply sharpens messaging. 
Every close sharpens the whole loop.
 
Stop buying more disconnected tools
Start building a system that compounds
 
This is GTM in 2026.

We just hired a former prospect, who went from cold lead → $500K/month pipeline at Warmly → our GTM teammate in 2 years.
 
I met Ivan Nieuwoudt in 2023.
 
He was part of a sales process for ORCA (yep, they later became a client).
 
We trained him from scratch as a GTME.
 
3 months later, he was booking 30+ meetings a month.
Asking smart questions no one else was asking.
Building stuff most SDRs wouldn’t even think of.
 
But then…
 
He gets a wild offer from Warmly, -one of the most THE GTM tools out there.
 
He called me. “Should I take it?”
 
I told him the truth:
“It’s a killer opportunity. Go learn. But one day, I want to hire you.”
 
He said: “One day, I want to work for you too.”
 
So we stayed in touch.
 
He’d send me updates from Warmly.
I’d send him unsolicited life advice 😅
 
Fast forward to November.
We got to run a small project together.
 
He crushed it. Again.
 
And this time…
 
We had the right window.
The right budget.
The right timing.
 
We matched his salary.
We gave him autonomy.
We gave him the opportunity to learn & work with the best
 
He said yes.
 
And just like that, the loop closed.
 
🧨 From a cold lead in 2023…
 → to half a million dollars/month in pipeline at Warmly…
 → to now building with us, from the inside.
 
If that’s not a full-circle LinkedIn moment, I don’t know what is.
 
PS: Ivan didn’t just accept an offer. He made a bet on the non-VC path.
The profitable, build-slow, build-elite path.
The one that prioritizes craft over hype.
 
I respect the hell out of that.
 
🔥 Let’s f-go, Ivan

The CEO of HubSpot just declared signal-based prospecting as the new standard. Love that. (but let’s not pretend like this is a 2026 invention.)
 
The best GTM teams have been living on signals for years.
What’s new is that the big enterprises are finally catching up.
 
While this is all nice, Yamini Rangan did not answer the real question
 
What does “signal-based prospecting” mean in practice?
 
And no, it’s not just “they liked our post, let’s call them.”
 
The whole go-to-market architecture shifts.
 
Because when signals matter, 3 things change:
 
01) Marketing becomes a signal engine, not a content machine.
 
It’s not just “create awareness” anymore.
It’s “create intent signals” that sales can act on.
 
This means tracking micro-signals → not just form fills.
Time-on-page, repeat visits, linkedin engagement, ad views (but no conversion)
 
02) Sales doesn’t prospect cold. It prioritises hot.
 
The best reps don’t start with 10,000 leads.
They start with 50 intent-qualified accounts this week. (Powered by tools like Trigify, Teamfluence, syft, Fibbler) 
 
No “maybe they’ll reply.” Just timing + context.
 
03) AI handles the 95% that’s not human-worthy.
 
The signal tracking, the enrichment, the qualification, the copywriting, the routing. All automated.
 
Because if your rep is still googling company news, you’re not doing signal-based. You’re doing spreadsheet-based.
 
So yes.
 
Signal-based prospecting isn’t just a tactic.
It’s a system-level unlock.
 
One that requires:
 
 → GTM alignment
 → Signal tracking → scoring → routing
 → Tooling + GTM motion + messaging connection
 → And way fewer SDRs building lists
 
The new GTM isn’t “outbound vs inbound.”
It’s signal-in, value-out.
 
GTM is Allbound

Had a call with a team sending ~150,000 emails a month. 3 years ago, they were getting ~6,000 replies per quarter. Last quarter? 80% drop. Here's what happened (and how we fix it) 
 
Reply rates did not slowly decline. They jumped out of the window. From 6k down to 1,000 replies per quarter. 
 
Same effort.
Same volume.
Way less oxygen.
 
And the funniest part is that everyone’s first instinct is always the same: 
 
"AI personalisation"
"We need Clay"
“Let's test different copy"
"We should signal-based outreach"
 
Is that the solution? 
Nope.
 
This was way more painful + boring than that.
 
It was the unsexy stuff that quietly ruins everything while your team keeps “testing the messaging” and "buying new tools"
 
Here’s what was actually happening:
 
they tried to trick spam-filters with a DIY SMTP Server
 
which sounds smart until you realize it’s like “I’ll fix my car by building an engine myself”
 
Reputation got messy
 
Sending patterns got weird
 
and inbox providers basically went “respectfully, no”
 
Then:
 
They pulled leads straight out of ZoomInfo
 
bounced ~35% (yeah… thirty five)
 
and every bounce was basically them telling Gmail/Outlook:
“hey we spam. Please treat us accordingly.”
 
And then the cherry on top:
 
Their emails weren’t personalised
 
like not even “okay-ish” personalised
 
just… same message, 150k times a month
 
which in 2026 is basically speedrunning the spam folder
 
So yeah, reply rate didn’t “decline.”
It got cooked.

3 years of this. ~$120M in revenue they never saw.
 
Not because buyers changed. Because infrastructure quietly rotted while they kept "optimizing copy."
 
What we’re doing to fix it (simple map):
 
Step 1: rebuild the email foundation
 
Zapmail.ai + Maildoso 
 
proper inbox setup, warming, constant monitoring/replacing and a sending logic that doesn’t look like a bot having a panic attack (this alone should pull them back toward the old baseline)
 
Step 2: stop mailing ghosts
 
Clay + waterfall validation
 
Leadmagic enrichment/verification so bad addresses don’t even touch the domain.
 
Step 3: add actual relevance
 
not "Hey {{first_name}} BS."
 
real context, real triggers, real reasons to reply
and this is where reply rate doesn’t just recover, it jumps.
 
Most outbound teams aren’t losing because “buyers changed.”
They’re losing because their infra + data quietly decayed, and they kept scaling the decay.
 
Garbage in - garbage out
 
Go compare your reply rate to 6,12, and 18months ago? 
 
Did it go down/fall off a cliff? 
 
Might be your infra setup

Last year, I did 2,150,517 impressions on LinkedIn. That’s a 178.4% over 2024 (wild).

Spent 4 hours this weekend trying to figure out why.
And tbh I was wrong about what works.

Here’s the breakdown:

Listicles & Rankings: 673,397 impressions (31%)
AI GTM workflows: 485,545 impressions (23%)
Memes about AI: 425,607 impressions (20%)
Lead magnets: 266,329 impressions (12%)
Industry news: 165,549 impressions (8%)

You know those “comment X to get Y” posts?

Everyone tells you to do them.
You see 1,000+ comments and think: "I should try this too."

I did. A lot.

They got comments.
They got reach.
They barely got me pipeline.

Only 12% of total reach.
And even less in actual sales.

So what worked for me?

(1) Rankings + Lists.

Everyone asks me “what tools should I use?”

I’ve spent $100K+ testing them.
I just post what’s working right now. Not 6 months ago.

Why it works:

 → People save it
 → People trust takes
 → People love to argue (engagement = reach)

Templates you can steal:

"7 best questions to ask in your discovery call"
"The best and worst GTM tools of 2025"
"The 5 WORST cold calling openers"

(2) GTM Workflows.

No one wants another AI tool.
They want to know how to actually use it.

We’ve built systems that generated $50M+ pipeline.
I just break them down.

 → One workflow
 → One problem
 → One outcome (with numbers)

That’s it.

(3) Memes.

One of the memes generated us $20K MRR in December.

Memes don’t just get likes.

They surface pain.
They make buyers say: “f*ck, that’s us.”

Just don’t make it cringe.

The takeaway?

Stop farming comments.
And start solving real problems.

Because if it doesn’t help your buyer make a better decision, it’s noise.

Now go build something worth reposting.

This morning, I read a post stating "Google just killed cold email with the AI inbox" - From someone who hasn't sent a cold email in the last 12 months.

Cold email has been pronounced dead so many times that I start to think it has biblical resurrection capabilities. Basically the Jesus of GTM channels.  

But what ACTUALLY  happened? 

Google just announced the AI Inbox. It summarises your emails and picks the most important ones. 

That's it. 

Nothing crazy new. 

The old inbox still exists; now you just have an additional tab "AI Inbox"

So nothing changes? 

Not really. 

Fundamentals are the same: 

→ Send from a solid infrastructure (low volume, warm domains)
→ Short and clear value proposition
→ Strong offer (you can't refuse)

It just highlights that SDRs are WAY too expensive to try to break past AI filters. 

So make 2026 the year you invest in an AI-led GTM motion.

Last year, my posts generated 2,150,517 total impressions - 178.4% more than 2024. I spent 4 hours analyzing what changed. Big surprise: Lead magnets stopped working (down 35%). Here's what works now.
 
The results surprised me - it's not what everybody tells you to do. 

𝗧𝗛𝗘 𝗗𝗔𝗧𝗔
 
→ Listicles & Rankings: 673,397 impressions (31%) 
→ AI GTM workflows: 485,545 impressions (23%)
→ Memes about AI: 425,607 impressions (20%) 
→ Lead magnets: 266,329 impressions (12%) 
→ Industry news: 165,549 impressions (8%)
 
Lead magnet posts get all the hype. You see these posts everywhere
 
"Comment X to get Y" 
 
You see the 1,431 comments and think "I should do this too"
 
Truth is they are FAR less important than you think 
 
They only account for 12% of my reach - and even less of my sales pipeline. 
 
𝗧𝗵𝗲 𝟯 𝗯𝗲𝘀𝘁 𝗽𝗼𝘀𝘁 𝘁𝘆𝗽𝗲𝘀

1/ Listicles & rankings

They crush it because I just answer the # 1 question I get asked every week: 

"What tools should I use?"

I've spent $100k+ testing tools - so I share what works in the real world. 

Why rankings work: 

People save them because they are practical
People trust you because you're a stance
People LOVE to tell you how wrong your list is. 

To create one, just ask yourself: "What FAQ can I turn into a ranking?"

Templates you can steal 
- "7 best questions to ask in your discovery call"
- "The best and worst GTM tools of 2025"
- "the 5 WORST cold calling openers"

2/ GTM Workflows 

People start to realise that buying a clay, n8n and instantly won't fix the problem.

You also need to have the right workflows to connect them. 

In the last 2 years, we generated over $50M+ in pipeline for our clients. 

I just show the exact workflows that made it happen. 

→ One workflow
→ One specific problem/use case
→ One measurable outcome (before/after)

Important: if your post does not include a measurable outcome, it's just theory - people can't tell if it actually works. 

Templates you can steal 

"Customer X reduced churn from 20% → 1%. Here are the 2 changes they made in their onboarding"

"We spent $300k on BDRs and closed 1 customer. We changed 1 tool and won 2 new logos in the first 4 weeks. Here's how:"

3/ Memes

Memes are risky. You either sound like a cringe boomer - or you go viral and close deals. 

In December for example,  1 meme closed 2 deals worth $20k MRR

The key? Use the meme to illustrate the problem you solve.


𝗧𝗔𝗞𝗘𝗔𝗪𝗔𝗬
Stop chasing viral lead magnet posts.

Start answering the questions your prospects actually ask.

Your content should solve real problems — not just collect comments.

These 5 post types created 2,100,000 impressions (2)

Claude analysed 1 million chats and 1 trillion API calls and put the findings into a report. I read the whole 54 pages, so you don't have to. Here are the 12 most interesting stats 

𝗨𝘀𝗮𝗴𝗲 𝗖𝗼𝗻𝗰𝗲𝗻𝘁𝗿𝗮𝘁𝗶𝗼𝗻
1.) The top 10 tasks account for 24% of all Claude conversations

2.) 6% of ALL Claude usage is concentrated on ONE single task: Modifying software to correct errors.

3.) Computer and mathematical tasks represent 34% of Claude.ai conversations and nearly half (46%) of API traffic. Coding isn't just popular—it's the dominant use case by a wide margin.

4.) Claude usage breaks down as: 46% work-related, 35% personal use, and 19% coursework. Work dominates, but personal use is surprisingly substantial.

𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝘃𝘀. 𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻
5.) 52% of claude conversations are focused on “augmentation” (users iterate/chat with claude to get the job done). 

6.) API usage is totally different. 75% of interactions are for automation (task execution) and only 14% are augmentation. 

7.) There's a near-perfect correlation (0.92) between how sophisticated your prompt is and how sophisticated Claude's answer is. In other words, you get what you put in (Claude mirrors you)

𝗚𝗲𝗼 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻
8.) The top 5 US states account for 50% of Claude usage - despite representing only 38% of the population. 

9.) Claude usage will equalise across the US in the next 2-5 years. That’s 10x faster than previous groundbreaking technologies (like the internet), which usually take 50 years. 

10.) 1% increase in GDP per capita correlates with 0.7% increase in Claude usage per capita. Wealth is THE predicator for AI adoption globally. 

𝗪𝗼𝗿𝗸 𝗶𝗺𝗽𝗮𝗰𝘁
11.) 49% of jobs now have AI usage for at least a quarter of their tasks—up from 36% in earlier reports. 
AI is penetrating the workforce faster than many expected.

12.) AI adoption could increase US labor productivity growth by 1.8 percentage points annually over the next decade. That’s productivity gains last seen in the late 90s/early 00s


Which fact surprised you the most?

Economic-Index_v4_2026.01.14_g

Boss to Alex (SDR): You can either prospect all your accounts manually in Zoominfo and keep Salesforce up to date...or free-solo climb a 500m tall skyscraper (and potentially di* while livestreaming)

Alex:

Chili Piper hit $30M+ pipeline with just 2 marketers in 2025 — while cutting costs by 50%. Now they leaked their 2026 budget (it's the opposite of what most tech companies do)

Back in November 2023, Founder Alina Vandenberghe 🌶️ was staring at spreadsheets with bloodshot eyes.
 
Every tab told a different story.
 
Sales leads in one silo. Marketing campaigns in another.
 
Deals were stalling. The quiet blame game had started.
 
The obvious fix? Hire more SDRs.
 
She did the opposite.

After looking at the data, she found one pattern:

- Deals from Marketing close in 243 days
- Deals from SDRs close in 300 days
- Combined they close in 192 days

That's 36% faster. 

And they were also bigger. 50% higher ACV

The problem was not headcount or marketing spend. 

The problem was the mindset

There is no inbound. No outbound

Only Allbound.

That's when she decided to shift the budget

Most B2B companies spend 6-10% of ARR on GTM. The budget looks like this: 

- 40-50% on programs (demand gen, content etc) 
- 10% on tools & tech
- 40% on people

Companies overspend on people because they still follow the "predictable revenue model" - and this requires a lot of people to run. 

That does not scale in an AI world. 

Chili Piper flipped it:
 
→ 60% on programs (demand gen & content)
→ 25% on tools (AI agents + orchestration)
→ 15% on people (GTME not SDRs)

Before: 10 inbound SDRs manually qualifying leads. 
Now: 1 GTM operator running AI agents.

Same pipeline output. Fraction of the cost.

Here's what the AI Agents do: 
 
→ Inbound qualification and routing
→ Meeting prep summaries 
→ Filter our spam leads
→ No-show follow-ups 

The result: 

→ Costs down 50% 
→ 30,000,000 in pipeline
→ 100% increase in ACV
→ Deals close 36% faster
 
The takeaway
 
2026 isn't about buying more AI tools or hiring more reps.
 
It's about two shifts:
 
1. Move budget from people to programs + tech
2. No inbound. No outbound - just Allbound
 
The teams that win won't have the biggest budgets.
 
They'll have the tightest alignment.

PS: Alina'sfull article in the comments

Anis Bennaceur

Co-founder and CEO at Attention.com

Advisor

Listed on Coinbase on Oct 11, reaching a $1.6bn valuation (FDMC).

World’s largest exchange for blockchain-enabled social currencies for creators.

Jason M. Lemkin thank you for the shoutout on Lenny Rachitsky's podcast this week!

Crazy to hear that orgs deploying agents like Attention for their reps are now carrying 10x quota 

Worth a listen if you’re thinking about what AI changes in revenue teams.

Open article: We replaced our sales team with 20 AI agents—here’s what happened next | Jason Lemkin (SaaStr) by lennysnewsletter.com

We replaced our sales team with 20 AI agents—here’s what happened next | Jason Lemkin (SaaStr)

Selling to startups as a startup is incredibly valuable, but it comes with some important nuance.

Early-stage companies are true early adopters. They move fast, they're willing to try new things, they give direct feedback because they actually need the product to work, and they expect you to ship very fast.

But "startups" isn't one market. There's a big difference between selling to companies with real PMF versus ones that won't exist in 18 months. Fundraising velocity and hiring pace aren't perfect signals, but they definitely help.

The other piece: you need a plan to expand beyond just startups. Sometimes that's your early customers graduating into enterprise accounts. Sometimes it's pushing upmarket directly. That transition is hard.

But if you're thoughtful about who you sell to early on, and you have clarity on where you're headed, selling to startups can be a route to learning what actually works.

It's pretty amazing to see how the length of coding tasks AIs can handle has increased over the last 5 or so years. This makes sense considering the deterministic nature of writing code.

I’d be curious to see this graph for selling tasks, which can be far less deterministic – not just in outcomes, but in how long you need to hold context across messy, multi-week deal cycles. Similar inputs like product, buyer profile, incentives, etc. can yield different tactics and outcomes for different sellers.

It’ll be even more interesting to see how this changes for GTM as context capture improves over the next few months.

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Lanny M. Heiz's LinkedIn Performance

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