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

I analyze your outbound data before telling you what’s broken | CEO, B2B Catalyst

I've spent 8 years building outbound systems for B2B companies. Teams of just the founder to 50 SDRs.

Over the years I realized success isn't nearly as random as it looks. 

There's a specific hierarchy of constraints, and if you don't solve them in the right order, your outbound fails.

The problem is that methodology usually takes months of manual consulting work.

Recently I compressed it with AI.

I fed 21 sales call transcripts, 585 cold call records, every script, deck, and playbook a company had into the system.

It found a two-layer messaging problem nobody had diagnosed.

Wrong product frame combined with wrong awareness level. 

That alone explained why cold calls weren't converting.

They had 6 script iterations that accumulated over months of gut-feel revision. None of them were working. 

The system identified which proof points were actually landing on calls, and zeroed in on a new approach built from their own data.

It took an evening.

I'm publishing the full methodology next week, prompt templates, benchmarks included. Free.

But first, I want to run it for 3 more companies. For free.

What I need: your last 30 days of email sends and replies, cold call recordings, and discovery calls. That's it. 15-20 minutes of exports.

Signal enrichments on your companies and contacts are nice to have, but not needed.

What you get back: a constraint map, messaging diagnostic, rep coaching briefs, and talk tracks revision suggestions. In days.

DM me "sprint" if you want in. I'm taking 3.

Open to AE or GTM Engineering roles | Call me: 727 637 2778 | Follow to find out what the heck Clay.com actually does | Will do a paid post for $1,000,000

Full cycle AE  and GTM Engineer specializing in early stage SaaS companies going from 0 -> Unicorn status.

Worked for companies backed by the biggest names in VC. Base10, Ridge, Susa Ventures, Altos, Alt Capital, Greylock and Microsoft. 

Taking big swings :)

🏍benyamin ‎

I'm joining AirOps as a GTM Engineer.

I gotta say this was a weird one, I had at least 3 people reach out to me separately, maybe more, telling me they were hiring for this role and that I should look into it. Once I did it became very obvious I should seriously consider talking to these folks. 

If you've followed me for a while, you know I've avoided purposefully GTM tech. The market is fickle. Costs are deflationary. And I think seat-based SaaS pricing is going to buckle under the weight of headless tools and agents operating APIs way more efficiently than humans ever would. 

So why break my own rule?

Because AirOps isn't selling more seats or licenses or a fancy workflow, they're solving for how businesses get discovered in a world where brands are found through prompting and not SEO. 

Google built the infrastructure for how we found information for 25 years. It's not dead yet, but when you look at the buyers of the next five years, they will not be relying on the first page of Google anymore. 

ChatGPT, Perplexity, Gemini, Copilot, Rufus on Amazon. The way people find answers is fragmenting across general-purpose AI, shopping AI, and proprietary search engines we haven't even seen yet. Most companies have no idea how to show up in those contexts.

AirOps is building the workflows that help them figure it out. And as more AI search vectors emerge, I think we're positioned to capture that market.

People have asked me why I decided to make this move. The reason is simple. if AirOps gets the technology right and grabs enough land early enough, this is a chance to ride one of the biggest technological shifts of the modern era.

Thank you to Eoin Clancy and Lucas Hulleberg for the opportunity. And to all the other team members I haven't met yet who have built something that I will get to grow. 

Travis Tyler accepting a role here had a non-zero effect on my decision. I was mulling over whether to make a move when I heard he started here, and I figured there must be something to it. He's a pretty discerning guy. 😉

AirOps is looking to grow headcount very aggressively this year. If you are looking for a new role with high performing folks - please reach out to me, I will connect you with the right person.

P.S. Sweater not real

No alternative text description for this image

This is my last week at Cyft. 
 
Building something from the ground up was the thrill of a lifetime. Thank you Cyft team for believing in me while we figured it out together
 
What I'll remember most is the MSP channel itself:
 
The people who actually pick up when you cold call or answered my many, many unsolicited emails. 🤣 (I know, I was shocked too.) 

Whether they were excited about what we were building or ready to tell me exactly why they weren't interested, you could tell they genuinely cared and had an actual opinion. Whether I agreed with it or not, it was refreshing to meet some people who didn't seem like they were reading an HR manual before they open their mouth. 
 
It will be impossible to forget the operators who shared war stories about nightmare clients over dinner because they really wanted vendors to understand what life looks like on their side of the table. The conferences where hallway conversations taught me more than the sessions. The Charlotte MSP meetup and the Greenville channel collab crew who showed up on weeknights because that's just what this community does.
 
Before this industry, I knew nothing about cybersecurity. Like literally nothing. I didn't know the difference between Intune and a tuning fork. I didn't know the difference between Entra and and entree. 

Just by proximity and following you all on LinkedIn, I have a new appreciation for the craft, the profession, and its importance of IT and cybersecurity to businesses everywhere.
 
To everyone who welcomed a guy who knew nothing about this space and taught me anyway: thank you.

There's too many of you to tag, but you know who you are. 

Will announce what's next soon. 

Until then I'll meeting with some colleagues and peers working on other vertical AI projects and trying to give back to the startup world for a bit. If you want to talk Clay, Claude Code, AI for GTM or anything else, dm me, I have a few days off before I start at the next spot. 

✌️😌

What the linked post says:

"After a fabulous 4 years at Acme co I have decided to take on a new role at ZogCorp. This wasn't an easy decision and I'm looking forward to a new challenge!"

What my brain sees:

If you think you are free, no escape is possible

I started putting my GTM work in a GitHub repo. Not code in the traditional sense. Operational logic. API schemas, enrichment routing, slash commands, context files that teach my AI copilot how to do my job.

It started as a practical problem. Everything I'd built at Cyft lived on my local machine. If my SSD died, a huge chunk of how I actually worked would die with it. GitHub was the obvious fix.

But it turned into something bigger. When I accepted my offer at AirOps, I had three weeks before my start date. So I started prepping a brand new repo for the new environment. Currently I'm building the scaffolding for all new and improved raw code and slash commands that I'll be running in Claude Code at Airops

Example of things I'm building: When I was at Cyft I had a growth meeting command that would pull from three APIs and compiles a structured agenda. Salesforce, Email Bison and Typeform to form a holistic picture of our funnel. At AirOps, the tools will be different. The architecture and ideology transfers. 

I think GTM engineers are going to start maintaining repos the way software engineers always have. I think highly technical revops teams are already started to resemble SWE teams more than the revops of 2015. 

If I were interviewing a GTM engineer today, I'd ask if they have a Github I could look at. I wouldn't expect it. But I'd ask. Not because the code matters that much, but because it signals how someone thinks about their work. Systems vs. tasks. Reusable vs. disposable.

Wrote the full breakdown 👇

Toward the tail end of my time at Cyft, I started seeing an existential threat to my work. All of the workflows, Claude Code slash commands, API integ

Open article: GTM Engineers Should Have Github Repos by 🏍benyamin ‎ • 6 min read

If I started at a new company tomorrow as a Salesforce/CRM admin, the first thing I'd do is have an AI agent read and understand my entire orgs schema before I touched anything. (I'm giving away the prompt I would use to do it.)
 
Not click through Setup for two weeks. Not reverse-engineer undocumented flows by asking five different people what each picklist value means.
 
I'd connect Claude Code to Salesforce through the CLI and run a single prompt that spawns multiple agents to crawl everything in parallel. One reads the full schema: every object, field, relationship, and record type. Another pulls reports and dashboards to understand how the company actually measures pipeline. Another maps validation rules, flows, and automation to surface the business logic nobody documented.
 
The agent is way better at reading the code than I am. Hundreds of custom fields, validation rules, SOQL queries. It can tabulate all of that in minutes. But that's not what I actually need. 

What I need is the 𝘴𝘵𝘰𝘳𝘺. How does a deal move through this org? How does a customer service case get routed? Where do closed-won opportunities go after they close, and what triggers along the way?
 
The code is just the mechanism. What it does is what matters. So instead of dumping a spreadsheet of field names, the agent interprets the configuration and writes a plain-English narrative of how your org actually works. 

The story of your Salesforce that nobody ever wrote down.

A note of caution: one giant context document is actually worse than no context. So the prompt doesn't just generate a massive dump. It architects a modular reference system. A main file that points to sub-documents by domain: schema in one place, automation logic in another, reporting structure in another. When you're building an Opportunity flow next Tuesday, Claude Code loads the relevant context for Opportunities, not 200 pages of your entire org.
 
Then everything compiles into multiple context documents that Claude Code can reference permanently. From that point forward, every time you build a flow, write a query, or restructure a report, it already knows your org. No more re-explaining your schema every time you need something.

This is one of the foundations of context engineering :)
 
Your first month stops being "what does this field mean?" and starts being "these 40 fields on the Opportunity object haven't been updated in six months, here's which ones we can deprecate."
 
I already built this as a useable prompt. All you need is Claude Code and one CLI login to your org.
 
Comment "Salesforce" and I'll send it to you.

How it feels to wait for me to announce what company I'm taking my talents to 👀

Any guesses? 

Wrong answers only

(only old people remember this historic sport moment, sorry boomers and elder millennials)

non-negotiables for buying SaaS in 2026:

• it must be able to run headless

I will login 𝘰𝘯𝘤𝘦 - to get the API key or SDK install instructions, and I will then import that into my .env file in my Claude code setup. 

theres no reason an AI should not be able to read and understand the entire schema and give me instructions and feedback on exactly what I want to accomplish.

what does "headless-ready" actually mean?
 
• 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗔𝗣𝗜 𝗽𝗮𝗿𝗶𝘁𝘆. If I can do it in the UI, I can do it via API. No admin functions locked behind clicks.
• 𝗠𝗮𝗰𝗵𝗶𝗻𝗲-𝗿𝗲𝗮𝗱𝗮𝗯𝗹𝗲 𝗱𝗼𝗰𝘀. OpenAPI spec, not a 47-page PDF from 2019. My agent needs to parse your schema in seconds, not hours.
• 𝗦𝗮𝗻𝗲 𝗿𝗮𝘁𝗲 𝗹𝗶𝗺𝗶𝘁𝘀. Agentic workflows hit endpoints differently than humans clicking around. Build for orchestration, not one-user-one-action.
• 𝗕𝘂𝗹𝗸 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀. If I have to loop through 500 records one at a time, your API was built for demos. API calls should by default be multi-threaded. 
  
A real world example: 

You can sort of use Salesforce headless from the CLI, and if I want to navigate to a certain page I can just ask Claude Code to give me the url for the report/etc that we're working in, like if I want to see a contact record before altering it. 

I have a lot of experience with Salesforce administration so I can operate it from the UI if I want, but Outreach on the other hand was a giant pain in the ass, and the API didn't allow me to alter important administrative functions that should, in theory, be accessible via API. Not only that, but the UI and other functionality was completely opaque to the point of being anti-user. 

Vendors who competed on "intuitive design" and pretty dashboards just lost their competitive advantage. If I never open the UI, I don't care how smooth your onboarding flow is.
 
I don't need your certification program. I don't need your onboarding webinar. I need Claude to understand your schema in 30 seconds and tell me exactly how to build what I'm picturing

Anyway. We need to start building software for robots and not for humans. Humans are a suboptimal operator form factor for software. 

Claude is way better at organizing files in my desktop and doing my taxes than I am, there's no reason we should still be building for humans.

how to source candidates from your own linkedin network for $40 and make 5k in commissions
 
if you're a seller with a big linkedin network, you're sitting on a recruiting side hustle. most recruiters charge 15-25% of base salary per placement. that's $20-40K per hire. you can do the same thing with your own connections and a claude subscription.
 
here's what I'm building right now to support AirOps 3x headcount growth this year and hopefully pick up some fat checks :)
 
𝘀𝘁𝗲𝗽 𝟭: 𝗲𝘅𝗽𝗼𝗿𝘁 𝘆𝗼𝘂𝗿 𝗹𝗶𝗻𝗸𝗲𝗱𝗶𝗻 𝗱𝗮𝘁𝗮
 
go to settings, data privacy, get a copy of your data. linkedin gives you a full dump. every connection, their title, company, location. takes about 2 or 3 hours to process. load it into a SQLite database so you can actually query it without spending 9000 tokens on looking for a contact
 
𝘀𝘁𝗲𝗽 𝟮: 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝘆𝗼𝘂𝗿 𝘁𝗮𝗿𝗴𝗲𝘁 𝗿𝗼𝗹𝗲𝘀
 
i scraped 31 job descriptions from our Ashby careers page and broke each one into structured criteria. required skills, seniority level, relevant companies, tech stack, years of experience. this becomes your matching rubric.
 
𝘀𝘁𝗲𝗽 𝟯: 𝘁𝘄𝗼-𝘁𝗶𝗲𝗿 𝗺𝗮𝘁𝗰𝗵𝗶𝗻𝗴
 
tier 1 is keyword matching. titles, companies, skills. fast and free. filters 10K connections down to a few hundred plausible candidates per role.
 
tier 2 is where it gets good. i use exa to pull enriched linkedin data on tier 1 matches, then feed those profiles into claude code to score against each role. work history, tenure patterns, location, tech stack overlap. things a keyword match misses.
 
𝘀𝘁𝗲𝗽 𝟰: 𝗲𝗻𝗿𝗶𝗰𝗵 𝗮𝗻𝗱 𝗱𝗿𝗮𝗳𝘁 𝗼𝘂𝘁𝗿𝗲𝗮𝗰𝗵
 
top-scoring candidates get deeper enrichment through leadmagic. the system drafts personalized linkedin DMs based on why that specific person fits. not "i saw your profile" messages. actual context about their career and how it maps to the role.
 
took an hour to build. these people already know you. a warm DM from a real connection converts at a completely different rate than a cold InMail from a recruiter. 
 
the system tells me "Maya is a 47/50 match for Senior AI Engineer because she built RAG pipelines at Notion and has 7 years in ML." i review the context and hit send.

If you're hooked up to your apollo API key you could then use the peoplefinder endpoint to expand on this process if you're having luck with it
 
any seller with 5K+ connections and a $20/month claude subscription is sitting on $2-6K commissions per placement in warm leads they already have.

P.S. screenshot is fake for educational purposes :)

Had a conversation with a technical founder last week about hiring GTM engineering talent. 

They're growing fast and trying to figure out what this role even looks like. We covered a lot of ground. 

𝗦𝗵𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗵𝗶𝗿𝗲 𝗳𝗼𝗿 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝘀𝗸𝗶𝗹𝗹𝘀 𝗼𝗿 𝘀𝗮𝗹𝗲𝘀 𝘀𝗸𝗶𝗹𝗹𝘀? 

Sales. Every time. The figuring-out portion of this work is not hard if you know what questions to ask Claude Code. And knowing what questions to ask comes from sales experience, not engineering experience.

𝗛𝗼𝘄 𝗿𝗲𝗮𝗹𝗶𝘀𝘁𝗶𝗰 𝗶𝘀 𝗶𝘁 𝘁𝗼 𝗴𝗲𝘁 𝘀𝗮𝗹𝗲𝘀𝗽𝗲𝗼𝗽𝗹𝗲 𝘂𝘀𝗶𝗻𝗴 𝗚𝗶𝘁 𝗮𝗻𝗱 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲? 

More realistic than you think. And the best operators are already using these tools. If someone tells me in an interview they're not using any AI tools, that's a hard no.

𝗦𝗵𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗯𝘂𝗶𝗹𝗱 𝗮𝗻 𝗘𝗧𝗟 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗼𝗿 𝗴𝗶𝘃𝗲 𝗔𝗜 𝗱𝗶𝗿𝗲𝗰𝘁 𝗔𝗣𝗜 𝗮𝗰𝗰𝗲𝘀𝘀? 

Both have real tradeoffs. One gives you cleaner data for AI. The other avoids the latency problem of syncing between systems. There's already large orgs mirroring data in a data warehouse and getting rid of the CRM entirely.

𝗜𝘀 𝗮𝗻𝘆𝗼𝗻𝗲 𝗵𝗶𝗿𝗶𝗻𝗴 𝗚𝗧𝗠 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗮 𝗰𝗹𝗲𝗮𝗿 𝗷𝗼𝗯 𝗱𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻? 

Sort of, but I tend to think anyone tell you what YOUR definition should be is selling something. GTM Engineering is a set of principles applied to problems, not a JD. 

𝗪𝗵𝗮𝘁 𝗱𝗼𝗲𝘀 𝗶𝘁 𝗺𝗲𝗮𝗻 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝘁𝗵𝗲 "𝗔𝗜 𝗯𝗿𝗮𝗶𝗻" 𝗼𝗳 𝗮 𝘀𝗮𝗹𝗲𝘀 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻? 

This is where the conversation ended up, and where my own thinking has been heading lately. Not which tools to use, but the architecture underneath all of it. How to build context layers for agents to operate in an organization

I wrote up the full conversation with more detail on each of these.

I had a conversation last week with a technical founder of an early-stage regulatory SaaS company. They're between 10 and 50 employees, growing fast, 

Open article: How To Build a GTM Engineering Function and Evaluate Talent for the Role by 🏍benyamin ‎ • 9 min read

How To Build a GTM Engineering Function and Evaluate Talent for the Role

Saw a Gong rep post on X about a new feature where AI listens to calls, extracts data, and populates CRM fields automatically.
 
My first reaction was wait, that's new?
 
I built that months ago with Claude Code. Updates CRM fields, progresses pipeline stages, pulls intelligence out of calls and feeds it into Salesforce. It wasn't some massive engineering project. I just built something I needed.
 
And apparently I wasn't the only one, because someone replied saying they'd built the same thing in Claude two months ago. This isn't an original thought. It's just a really obvious need that practitioners are solving for themselves now.
 
The Gong rep replied with the enterprise objections: "Now do it for 80+ languages, multi CRM, and all security governance across 5,000 customers." He's right to point that out. Those are real barriers. I also know he's just posting about a product feature, so it's probably not that deep.
 
But I think the market is starting to agree with the practitioners. Median YoY revenue growth across 58 public SaaS companies has dropped from 36% in Q1 2022 to 15% today. That's a 58% decline, and it's been falling every single quarter for three years. When Anthropic launched MCP connectors, the iShares Tech-Software ETF dropped 28% from its highs. People called it the "Claude Crash." The market is just catching up to what builders already figured out.
 
I don't think SaaS is dead, just for the record. I use Salesforce every day. Not for any single feature but because it's a platform I build on top of. The ecosystem, integrations, the connective tissue for my whole revenue operation. You don't vibe-code that away (today, anyway)
 
But we're forgetting where SaaS came from. Companies didn't want to host software. Didn't want to maintain code. Didn't want to be their own IT departments. Cloud-hosted, vendor-managed software solved that.
 
AI is making self-maintained software feasible again. Not tomorrow, not for Fortune 500 security requirements. But for SMBs and mid-market? The math is already changing. And every barrier the Gong rep mentioned is becoming a purchasable product. WorkOS for auth. Vanta for compliance. Stripe for billing. Vercel for hosting. You don't solve those problems anymore. You plug them in, just like you don't store call recordings in a RAID setup in the basement, you just buy Gong.
 
The economic issue is structural. Enterprise contracts subsidize SMB and mid-market plans. If the long tail starts building their own tools, that subsidy model gets squeezed. Enterprise customers won't pay more to compensate. They'll negotiate harder.
 
If I'm an investor thinking ten years out, I'm not betting on enterprise SaaS. I'm watching the infrastructure layer underneath. The companies selling enterprise-readiness to builders who don't look anything like traditional software companies.
 
SaaS isn't dying. But the assumption that you need 200 engineers to build real software is certainly dead.

𝗛𝗼𝘄 𝘁𝗼 𝗕𝗹𝗮𝗰𝗸-𝗣𝗶𝗹𝗹 𝗬𝗼𝘂𝗿 𝗦𝗮𝗹𝗲𝘀 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 𝗔𝗯𝗼𝘂𝘁 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲
 
An SDR I shared some tips with messaged me after starting a new role and said they've been totally blackpilled about the status quo after implementing Claude Code and Cursor workflows for the GTM team at their previous company. 

They can't unsee the efficiency gains, and they can't unsee the insanity of all the manual processes around them.

They'd asked their new manager if they could hook up the Apollo API to Cursor to automate some of their longer-form workflows, specifically around lead list building. They were told no without much explanation.
 
I get why. If somebody with six months of sales experience says "let me hook up the most sensitive part of the GTM stack to an AI tool with a dubious level of security," "Fuck No" is a reasonable first reaction. There are real security concerns. But you're shooting yourself in the foot by hand-waving about security when the mitigations are really quite simple. Fix it, move on, and start utilizing the efficiency gains.
 
If you're relating to this, that frustration is a signal. You're early. And there's still time to save yourself from the impending white collar job collapse. 
 
They went on to ask how to socialize this stuff within their new team. Here's what I told them:
 
The play - treat institutional change like a sales cycle.
 
Don't walk into your manager's office and pitch a revolution. That's how you get a polite "no" and a reputation as the weird one. I learned this the hard way when a past CEO told me, "Ben, you have good ideas, but you don't know how to leverage political capital." He was right.
 
Instead, multithread. Sell bottoms-up. Drop an article in the team Slack. Share something in a meeting. Get two or three peers curious. Let them start asking their own questions.
 
If you do this, your manager starts getting the same questions from multiple people. It's no longer one person asking about weird shit, it's a pattern. It makes its way to the director meeting, and now the conversation is happening at a level where things actually change.
 
If you zoom out, the cost of building software is going to zero. Distribution, security, compliance, customer service, all the enterprise readiness stuff, that's what's becoming the real challenge. The playing field is being leveled. 

A lot of people are being lulled into a false sense of security while their competition gets leaner. Smaller teams are producing the sales output of much larger ones across pipeline management, outbound activity, and post-sales support. They're building a compounding velocity advantage and they are going to use it to destroy you.
 
If you're a sales director, a RevOps leader, and you haven't used Claude Code or Cursor, you need to go familiarize yourself. Google it. It's not hard to find.
 
I write about this stuff regularly. If you need talking points to socialize these ideas, just send them one of my posts :)

My content generated ~$300k in earned media value over the past 365 days.
 
I downloaded my analytics directly from LinkedIn and X and threw them into Claude Code to calculate it.
 
EMV answers a straightforward question: what would I have had to spend in platform ads to replicate the same reach, engagement, and follower growth I got organically? 

You take each platform's average ad auction CPMs (LinkedIn runs about $30, X about $5), apply per-action costs for engagements, follows, saves, and shares, then multiply by actual volume. I ran the numbers at three different rate cards: conservative, middle-of-road, and aggressive, and the range came out to $214K–$331K. I'm assuming middle of the road for this post.
 
LinkedIn generated 83% of the total EMV despite both platforms pulling roughly the same impression volume (~2.3M each). LinkedIn ad inventory costs ~6x more than X, so each organic impression there displaces about $0.03 in ad spend vs half a penny on X. I get a lot of impressions on X and some content performs better there, but the earned media value is significantly lower. And the LinkedIn audience is easier to directly attribute deals to, which matters if you're trying to connect content to revenue.
 
𝗧𝗼𝗽 𝟱 𝗘𝗠𝗩 𝗟𝗶𝗻𝗲 𝗜𝘁𝗲𝗺𝘀:

• LinkedIn Engagements: $109,036
• LinkedIn Followers: $69,760 
• LinkedIn Impressions: $69,421 (only one off from the funny number)
• X Bookmarks: $12,455
• X Impressions: $10,556
 
People ask me what my content strategy is. The formula is pretty simple: I write about whatever I find interesting, I post memes, and I try to be myself for whatever that's worth (or whatever the consequences may be 🤣). I've been doing it consistently since 2022. Posting almost every day without fail.
 
Download your LinkedIn and X analytics from your engagements page and throw them into Claude Code. I'm linking the prompt I used below. You can put the number on a resume, use it in partnership conversations, or just understand what your organic presence is actually worth. You can also download your LinkedIn follower data and have Claude Code segment your audience by company, title, and industry.

Link to prompt: https://lnkd.in/ezsRNfhM
 
People say your LinkedIn isn't super valuable to your employer. I get the logic, sometimes it's not. But when you break down the numbers, this is worth nearly $300K a year to the right company. If our incentives are aligned, if the company I'm building at benefits from the audience I've built, that's leverage for both sides.

taplio

The Battle

Scott Martinis

🏍benyamin ‎

Followers

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Performance ScoreScott Martinis's LinkedIn Performance

Performance Score🏍benyamin ‎'s LinkedIn Performance

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taplio

The Battle

Scott Martinis

🏍benyamin ‎

Followers

Posts

Engagements

Likes

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);}Scott Martinis's LinkedIn Performance

Performance Score🏍benyamin ‎'s LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreScott Martinis's LinkedIn Performance