Founder | B2B GTM | Scale without headcount by mapping your playbooks into an AI revenue engine

Be honest - how many Linkedin posts have you seen this year saying that XYZ tech/playbook/widget is absolutely essential to your GTM this year?

Probably a lot

We now have thousands of sales and marketing technologies on the market

And all of them are pitching their solution as best in class

With playbooks, agencies, influencers to sell them

And yes, we have preferred tech vendors

Here's the difference

We don't throw you in canned playbook, we actually look at your Go to Market model before making recommendations

Let me tell you a funny story

I talked with an SDR team that was booking 80 meetings a month with parallel dialers and 10k emails per SDR per month

But 60% of their meetings got disqualified

Why?

They didn't qualify target accounts before doing outreach

Tech and playbooks don't save you deploy the wrong one at the wrong time

So what do we do different?

When you work with us, we start with an assessment

We look at your funnel metrics, your best customers, your messaging/copy, and get input from your team on detailed attributes that make up a great customer

That you CAN'T find in an off the shelf tool

After that we use our knowledge of best practices and tooling to identify the biggest opportunities to unlock more revenue per headcount in your team

This could look like

> Customer analysis
> Serviceable Addressable Market Mapping (because TAM is where you lose deals not win them)
> Target Account Lists
> Automated Contact Prospecting & Enrichment
> Pipeline Validation (we build out a script, test it to book meetings for you, help you take the meetings through completed discovery with next steps, then give you a completed call framework, email sequence, and discovery framework)
> Outbound Sales Team Coaching (Phone first)
> Sales Process Optimization
> Managed Cold Emails & Cold Calling
> Inbound Lead Flow Optimization
> AI Business Case Building (which we used to open a $300k+ opp at UPS)
> Implementation of Nooks, Clay, Evergrowth, and other sales tooling

Yes, we do that under one roof

Yes, it was very hard to find a team good enough to do all of this in one place

If you want to learn more, book a time here: https://calendly.com/b2bcatalyst/your-gtm-system-audit-linkedin
> Cold Email Infrastructure

Scott Martinis

GTM engineers & AI platforms are trying to figure out GTM context engineering by reinventing product marketing from first principles. Most will fail.

Context - I am seeing a ton of really smart people like Nico Druelle, Charlie Saunders, Alex Fine🌲, 🏍benyamin ‎ and others start to work on the problem of how to create centralized context libraries to iterate on messaging and targeting.

I am also seeing many platforms try to do the same thing.

The operators I included above will probably succeed. 

The platforms and GTM engineers that follow in their footsteps will largely fail.

Why?

Simply put - GTM context engineering is effectively reinventing a complete and fleshed out disciple (product marketing) from scratch.

Given INSANE amount of training volume, ML modeling (Karpathy released a new library to help automate this) CAN effectively invent the necessary cognitive architecture to help generalize those patterns.

Outreach could probably do this if they really wanted to. Gong as well.

But that's a waste of time, and anyone with less training data will probably fail horribly.

Think about what ACTUALLY happened to optimize messaging in high performing GTM orgs years back:

Product marketers would run meeting analysis, win/loss interviews, customer interviews, and talk with analysts.

They would then consolidate this into strategic narratives, positioning frameworks, competitive battlecards, ICP/segment/persona definitions, and value frameworks for major audiences.

If you want to do context engineering, you could try to reinvent this discipline from first principles.

But you're going to demonstrably slower than people who just... 

Interview good product marketers 

And figure out how to automate the product marketing analysis pipeline.

The marketers I've been most recently impressed with on this front are Emily Pick, Julia Hugg, Trinity Nguyen 💎

Octave, of course, is way, way ahead of the pack here.

Instead of trying to figure this out all by themselves, GTM engineers and revops leaders should take the shortcut and take the time to learn product marketing from elite practitioners instead

This was why all the AI SDRs failed by the way. 

It's not the lack of data foundations that broke them as many revops people supposed (though that doesn't help)

It was actually the lack of understanding the GTM strategy is quite complex, and guessing and checking without proper PMM foundations is not fast enough to get ROI on automated outbound.

What does this mean?

Well, the actual foundation of your GTM strategy is not revops OR GTM engineering, it's REALLY good product marketing

Both of those functions rely on good PMM to build good data models and automated workflows... though they both relying to some degree on well thought out enablement playbooks to know what to include in the data model and what to automate as well.

TLDR: model your context engineering on PMM. Will save 6-12 months.

I make AI work for complex B2B GTM through pipeline impact, not data projects | CEO, B2B Catalyst

So it turns out you can CSV dump from every GTM tool into your GitHub repo then Claude Code can write you data lake scripts in like... 20 minutes?

And if you dump in cold call transcripts from Gong or Chorus then you can basically rewrite any messaging playbook your org has in a few hours

Working next on ways to extract use cases from sales calls at scale, map in depth what messaging wins and loses

Then take the use cases and scrape online presence of won deals to extract custom signals

Tag won and lost deals with them

And build custom signal models predicting win rate and ACV

Future is pretty wild

Next up:

- Automated coaching briefs across the org
- Down funnel marketing campaign attribution
- Automated and targeting iterations for marketing campaigns and sequences
- Weekly or monthly auto playbook updates broke. down by segment
- Weekly or monthly value framework updates, battle cards, competitor battle cards (possibly automated)

Of course the more normal use cases like 

TAM scraping, signal sourcing, account prioritization, contact sourcing, qualification, classification 

TitanX phone intent

AI outbound personalization on emails calls LinkedIn

AI content generation and amplification 

AEO

AI inbound and outbound SDRs

Personalized ABM content

Personalized meeting prep

ETC

Candidly those feel a bit more pedestrian and table stakes to me though in 2026

Still... very exciting possibilities for GTM orgs

The key I think is knowing where to start

Which is usually your biggest bottleneck 

(DM me "context lake" if you want this in your org)

Every GTM intelligence tool is racing to answer the same question: who should we target?

Intent data. Buying signals. De-anonymization. Account scoring.

The targeting layer is getting genuinely good. 

And it's about to be commoditized. 

The same way signal aggregation became table stakes after Clay and 6sense turned it into infrastructure.

There's a deeper problem.

These tools are optimized for finding people who want to buy tools like them. They surface intent signals and firmographic matches.

They don't find the prospects where YOU have a differentiated advantage at closing.

That's a different ICP layer. Not "who looks like our customers" but "who has a problem we solve better than anyone else."

Most teams build messaging off the same shallow foundation. Company value props plus signals. "They just raised a Series B, mention growth." "They posted a sales role, mention scaling."

Relevant first line. Generic pitch.

The signal tells you WHEN to reach out. Your value prop tells the buyer what YOU think matters. 

Neither one tells you what the BUYER thinks matters.

The thing that converts is explaining why your solution beats the buyer's current state in a way they actually agree with.

That's differentiation. And it's missing from almost every discussion on signals & ABM I've seen. 

A VP of Ops at a 200-person logistics company. What's her job-to-be-done? What objection does she raise first?

That's not in your intent data. It's in your call recordings. It's in the patterns your best reps know but nobody's formalized.

Pull your last 30 closed-won deals. Listen to the first calls. What did the buyer say they cared about? Group them.

You'll find 3 to 4 patterns. Those are your real use cases.

Each one should shape both WHO you target and WHAT you say. Not a template with a different first line. A different reason to meet, built on why your solution changes their current state.

The targeting will keep getting smarter. The message won't get better until someone studies the buyer.

If you want help building this layer, DM me.

I rebuilt my company's website through an MCP inside Claude Code. Told my AI co-worker what to change. It read the Webflow data directly, made the edits, and published.

Mostly. I still had to open Webflow for some formatting changes the MCP couldn't handle. But 80% of the work happened without touching the UI.

That alone changed how I think about platforms.

MCP is Model Context Protocol. It lets AI talk directly to a platform's data and take actions.

Every legacy platform is walking the same path right now.

Step 1: Platform. You log in, click buttons, build reports, configure sequences. Standard SaaS.

Step 2: The AI can READ the platform's data. Pull reports, see pipeline, check analytics. You still log in to do anything.

Step 3: The AI can ACT. Create records, update fields, trigger workflows. You log in less.

Step 4: The AI owns the domain. It decides what to do, does it, reports back. You make decisions. You rarely touch the platform.

I'm somewhere between step 3 and 4 with Webflow. It's not perfect. But the direction is clear.

Now think about Salesforce, HubSpot, Outreach, Salesloft.

Once an AI can read your CRM, update records, pull analytics, manage sequences, and trigger workflows.. what's the UI for?

Salesforce has Einstein. HubSpot has Breeze. Outreach has "AI everywhere."

Bolting a chat window onto a legacy platform is step 2.5 at best. And the companies building step 4 aren't starting from step 1. They're starting fresh.

Pick the GTM platform you use most. Map it against the 4 steps. Where the AI feature actually sits vs. what the marketing claims will tell you everything you need to know about that vendor's roadmap.

Dhruv Patel

Co-founder @ Saleshandy

Hey there,  

I'm a guy who wears many hats, and I like it that way! 

My marketing journey kicked off at a company where I managed a team of over 25 folks as the Marketing Lead and Operations Manager. 

But my itch for something more took me down the road of content and niche marketing. That's how I ended up co-creating Saleshandy, a place where I'm still enjoying the ride and helping the company grow.

I'm a marketing junkie and a business starter, and I get my kicks from companies that encourage teamwork and don't put up roadblocks to success. I live to meet and exceed what customers want. I keep a close eye on the results and always tinkering with my game plan based on what's needed. When things go south, I don't get bent out of shape; I see it as a chance to learn. I take a good, hard look at what went wrong, figure out why, and then cook up solutions based on the facts.

As a growth hacker and digital marketing buff, I thrive on the hustle and meet life with a never-say-die attitude. My constant grin shows my love for creating strong teams and my readiness to lend a hand at the drop of a hat.

So here I am, a Co-founder at Saleshandy, extending an invitation for you to join me on this wild ride as we take over the marketing world, one success story at a time. 

Let's get together and see how we can help each other grow. What do you say?

Co-Founder

Saleshandy is a cold outreach platform that helps B2B businesses automate and scale their outbound sales efforts. 

» I am the person responsible for
- majority of marketing stuff
- people management
- developing and implementing systems & procedures throughout the organization
- operations

No outbound tool on earth can solve this debate (including Saleshandy).

I saw this exact question pop up on Reddit:

"I tried cold emails and LinkedIn DMs, but neither worked. What tool should I try?"

Here’s the thing: It’s not the tool — it’s your expectations.

Cold email is designed for reach.

LinkedIn is built for visibility.

Cold email requires you to:
> Send in volume
> Use data
> Test fast
> Have new conversations

LinkedIn requires you to:

> Have social proof
> Take a warmer entry
> Use lower volume, but with higher intent
> Provide context before outreach

But here’s the mismatch:

People expect cold email to book meetings in less than an hour.

People expect LinkedIn to scale like ads.

That’s where things break.

Both channels have their risks:

Cold email: Deliverability issues, spam complaints, bad targeting hurts fast.

LinkedIn: Slower scale, inactive users, platform restrictions.

Neither channel is magic.

If you understand the differences, your strategy is simple.

If you don’t, you’ll be stuck blaming tools FOREVER.

Co-founder @ Saleshandy | Automating cold emails to drive lead generation & sales

Most founders don't have a productivity problem.

They have a body problem they've renamed as a productivity problem.

The truth is:

We build systems for everything:

Pipeline. Hiring. Product. Revenue.

But very few real systems for our body.

And here's the dangerous part 

You don’t notice it breaking down in one dramatic moment.

You slowly become:
> Less sharp
>  Slower to decide
> Quicker to snap
>  Less focused after 3pm

You’ll blame it on workload, but it’s not just that.

It’s years of quiet neglect compounding.

Here’s what I now know, and wish I knew at 25:

Your body doesn’t give you one loud warning.

 It gives you a decade of small signals you ignore.

And then one day, you're 30+, dealing with back pain, lower energy, and a 
shorter focus window.

Fitness doesn’t get easier as you age.

Compounding works both ways.

If you’ve been consistent, your baseline stays high.

Recovery is faster. Focus lasts longer. Stress tolerance is higher.

If you haven’t, each year it gets harder to bounce back.

In your 20s, you can neglect your body and recover quickly.

In your 30s, the same neglect starts sending a bill.

I’ve seen founders spend their 30s trying to rebuild what could’ve been maintained in their 20s.

Don’t wait for the wake-up call.

Build systems for your body the same way you build them for your business.

Every cold email expert you follow was once a beginner figuring out who to email and who not to.

They didn’t become experts because they started early. 

They became experts because they moved to the next stage.

The groundwork for all success: Knowing your stage.

There are 3 stages:

Stage 1: 0 Certainty

You don’t know anything. You’re guessing. Your message changes every week.
 
What do most people do?

They rush out of it.

They see 2 replies, assume they’ve found product-market fit, and hire SDRs.

That’s ego, not evidence.

Stage 2: Some Certainty

Now, you see traction. But confirmation bias kicks in.

You only listen to buyers who agree, ignoring those who don’t.

You shape the story to fit your beliefs.

That’s how weak positioning is born.

And most get stuck here, not knowing how to get out.

Stage 3: Scaling 

Scaling isn’t about “doing more.” 

It’s about protecting what works and testing what might work next.

Most teams either experiment forever and never scale, or scale forever and never improve.

The best teams know when to switch gears.

ICP research isn’t a marketing task—it’s decision control.

If you don’t control the stage you’re in, the stage controls you.

And that’s dangerous.

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