Eddie Reynolds

Union Square Consulting

Union Square Consulting is a GTM Strategy & Operations consulting firm. 

I spend the majority of my time:
1. Managing our Sales and Marketing Team
2. Managing our VPs of GTM Strategy & Operations Consultants
3. Providing GTM Strategy & Operations Consulting to Customers

We work with high-growth companies, primarily B2B SaaS companies to help them in five areas:
1. GTM Strategy and Planning
2. Go To Market Process
3. GTM Metrics and Insights
4. Systems Implementation and Ongoing Optimization
5. User Training and Enablement

We do this to help companies execute their Go To Market Strategy by:
1. Making sure your systems are working
2. Making sure your revenue team is using the systems properly
3. Making sure they are executing the right process to attract and retain customers
4. Analyzing the metrics to see what's working, what's not and what to do about it
5. Creating a strategy and a roadmap for all of the above to actually get it done

CEO and GTM Strategy & Operations Consultant

RevOps Corner

RevOps Corner is a podcast we produce at Union Square Consulting to share best practices for Strategic Revenue Operations. 

We do this by interviewing amazing guests, ranging from Revenue Operations Professionals to Revenue Leaders to Venture Capitalists and many other experts in the B2B SaaS community. 

We also share what we're seeing in the trenches every day in our work as Revenue Operations Consultants here at Union Square Consulting.

Listen to the Podcast on:
Spotify: https://open.spotify.com/show/1CM3rmelcdtm6gJVL0PtMK?si=00aae750ea7a4937
Apple: https://podcasts.apple.com/us/podcast/revops-corner/id1619571311

Host

Pavilion

Executive Member

Trumid

Trumid is a Unicorn Fintech Startup that has raised over $650 million in funding to date. 

I joined Trumid right when they had achieved Product Market Fit and relaunched their application. 

My role was to manage all our Revenue Operations:

1. Systems Implementation and Management
 - Sales, Marketing, Service and Data Analytics

2. Enablement
 - Provided training and enablement to the customer facing revenue team

3. Insights
 - Worked directly with the Co-CEOs to provide daily insights on revenue metrics

4. Process Mapping
 - Mapped our sales, marketing and service processes prior to architecting systems and data

5. Strategy and Planning
 - Planned, managed and executed our revenue operations roadmap

VP of Revenue Operations

Salesforce

My role at Salesforce was to work with current and prospective customers to explore opportunities to leverage technology to find more prospects, win more customers, keep more customers and enable their business to scale.

We helped customers accomplish this by improving business processes in marketing, sales, customer service and other departments, centralizing their data in one place and building operational efficiencies. This enables them to grow faster and gives leadership more visibility to make better strategic decisions.

I accomplished this by beginning consultations with the objectives of the business and only then discussing technology. My role was to quarterback a number of resources within Salesforce and the client's team to work together to uncover the best business processes to help them overcome obstacles and reach their goals. Then, we would map out how Salesforce and related technologies could be used to execute those business processes.

Account Executive

CrossBay Capital Partners

CrossBay Capital Partners is a boutique placement agent. We raise capital for established alternative investment managers with a primary focus on private equity.

 - Sourced investments by soliciting private equity firms seeking to raise a fund
 - Distributed investments by building relationships with institutional investors
 - Designed and implemented Salesforce.com to support these efforts for the entire team

Vice President - Institutional Sales

Altvia

Altvia Solutions provides a solution, built on the Salesforce platform, for institutional investors and fund managers to manage investing and fundraising processes.

 - Managed sales process from initial prospecting to negotiation and close for new business
 - Acted as my own sales engineer to provide highly customized and tailored presentations
 - Oversaw marketing efforts by working closely with CEO and our advertising agency
 - Worked closely with implementation team to scope project 
 - Helped implementation team customize solution for each new client

Account Executive - Private Equity Solutions

Yen Capital Management LLC

YEN Capital Management assists operating companies raising capital from private equity investors.

 - Built healthcare platform from inception by growing relationships with private equity investors and healthcare companies
- Closed mandates to raise $25 million and $40 million for two pharmaceutical manufacturers

Head of Advisory Services – Healthcare Banking Team

Wells Fargo

Wells Fargo Business Banking provides lending and deposit solutions to small and medium-sized businesses.

- Solicited and built relationships with hundreds of independent businesses across all industries
- Achieved sales production in the top 1% of bankers in the company

Business Banking

Over +20 years in sales, customer success and marketing, I’ve developed a passion for data-driven strategy and process. I’ve always been fascinated by the edge it can give an IC or an entire company. 

Ten years ago, I joined Salesforce as an AE covering high-growth, VC-backed B2B SaaS companies. I met with hundreds of executives and revenue leaders and they all wanted this edge. They wanted to hear how Salesforce and my other customers operated, not how the software worked. 

Our consulting partners, however, were solely focussed on the software, often missing the broader strategy. This inspired me to start a unique consulting firm, merging system implementation with data-driven GTM strategy. 

Since then, I’ve seen some of the deepest ingrained revenue growth problems plaguing B2B SaaS – and we’ve developed a system to solve them.

𝘾𝙍𝙊𝙨, 𝘾𝙈𝙊𝙨, 𝘼𝙉𝘿 𝙑𝙋𝙨:

Does this sound familiar?

💭“I don’t understand what my data is telling me. I’m not even sure it’s accurate.”
💭“We’re getting tons of leads but they’re not converting enough to outpace churn.”
💭“We’ve spent so much money on tech, marketing, training, etc. – but there’s no ROI.”

Or maybe even…

“I don’t want to end up like those guys ☝️ How do I get in front of this?”

𝙔𝙊𝙐’𝙍𝙀 𝙄𝙉 𝙏𝙃𝙀 𝙍𝙄𝙂𝙃𝙏 𝙋𝙇𝘼𝘾𝙀

I founded Union Square Consulting to help B2B recurring revenue brands increase profitability by targeting the source of their revenue engine issues (not just the symptoms).

𝙒𝙃𝘼𝙏 𝙒𝙀 𝘿𝙊

Fractional RevOps that delivers both systems implementation and go-to-market strategy.

𝙒𝙃𝙊 𝙒𝙀’𝙑𝙀 𝙃𝙀𝙇𝙋𝙀𝘿

High-growth brands from Series A to C and beyond like Techstars, Luminate, and Federato.

𝙂𝙀𝙏 𝘼 𝙁𝙍𝙀𝙀 𝘾𝙊𝘼𝘾𝙃𝙄𝙉𝙂 𝙎𝙀𝙎𝙎𝙄𝙊𝙉

Sit down with one of my Senior Revenue Strategists for a personalized Revenue Operations Coaching Session. Walk away with advice you can use immediately.

👉 CLICK HERE: unionsquareconsulting.com/workshop

𝙎𝙐𝘽𝙎𝘾𝙍𝙄𝘽𝙀 𝙏𝙊 𝙊𝙐𝙍 𝙍𝙀𝙑𝙊𝙋𝙎 𝙉𝙀𝙒𝙎𝙇𝙀𝙏𝙏𝙀𝙍

Get actionable and practical tips on optimizing your marketing, sales, and customer success engines.

👉 CLICK HERE: unionsquareconsulting.com/newsletter

Wow! This guy DM'ed me an hour ago and now I have a proposal. 

I got a random connection request this morning.

By pure miracle, this guy is pitching something that is #1 on my priority list this quarter and this morning. 

However, it's still a random guy on LI.

I didn't want a meeting.
He didn't ask. 

I just responded with "how much?"

He responded with 
"Happy to share. Can I ask a couple questions?"

I'm already like....
"Ugh....he's gonna ask for a meeting."

But no, he asked me a few basic questions over DM. 

Then he sent me a full Loom walkthrough of a custom proposal. 

Holy shit!

Okay, this is how I want to buy!

(And no, if you're buying from me, I'm not selling this way. Wish I could.)

But man.....where possible......this is the way!

✌️

CEO | GTM Strategy & Ops for B2B SaaS CROs

"What's the ROI of fixing our GTM Operations?"
I get asked this question constantly.

And every time I hear it, it feels like a slap in the face.

Here's the thing.
- You just told me your GTM is a mess
- Your forecasts are consistently off
- Inbound leads aren't being followed up on
- The pipeline is filled with dead deals
- NRR is slipping because there's no process
- No one has visibility because the systems are broken

But we can’t plug these revenue leaks until we “prove ROI?” 

Warren Buffett said it best: "You don't need to know if a man weighs 300 or 350 pounds to know that he's overweight."

When the problem is obvious, you don't need to overanalyze it.

But here's the real issue.
When your GTM is fundamentally broken, you can't even measure ROI.

Your Close Rate looks like 25%. But it's meaningless.
Some reps create opps after every meeting. Others wait for the verbal.
One group has a 5% Close Rate. The other has 85%.

The blended number tells you nothing.

You can't measure the ROI of fixing your sales process until you've fixed your sales process.

So let's think about this differently.
- What if you improved your Close Rate from 15% to 16%?
- That's $1M in additional ARR on a $25M new business goal.

That single improvement pays for your entire GTM Ops investment.

What if you improved inbound lead conversion from 1.0% to 1.1%?
- That adds $16.7M in pipeline. 
- At a 15% close rate, that's $2.5M in additional revenue.

What if you improved retention from 85% to 86%?
- On a $100M ARR base, that's $1M saved.

These aren't aggressive assumptions.
They're conservative.
And they compound.

Better lead conversion creates more pipeline.
Better close rates turn more pipeline into customers.
Better retention and expansion multiply the impact.

In tomorrow's 📰𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰, I break down the exact math on why any improvement in GTM Ops pays for itself several times over.

But the real question isn't "What's the ROI?"

It's "Can we afford NOT to fix this?"

How much revenue are you leaving on the table with broken GTM processes?

🤔

Get the full breakdown (including the image below) in tomorrow's 📰𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰
Subscribe to get it here: https://bit.ly/49RCm0h

✌️

How do you actually calculate the most important GTM Metrics?

Following the 𝗚𝗧𝗠 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 & 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 we published yesterday, we released a 𝗚𝗧𝗠 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗮𝗻𝗱 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗜𝗻𝗱𝗲𝘅 outlining how to calculate each of these metrics. 

We're coving the following types of metrics:

𝗚𝗧𝗠 𝗘𝗙𝗙𝗜𝗖𝗜𝗘𝗡𝗖𝗬 𝗠𝗘𝗧𝗥𝗜𝗖𝗦

We ask questions like:
 - How efficient is our overall GTM Engine?
 - What does it cost to acquire customers?
 - What does it cost to grow revenue by $1?
 - What's the lifetime value of our customers?

We answer them with metrics like:
 - CAC
 - CAC Ratio
 - CAC Payback
 - LTV:CAC
 - Magic Number
 - GTM Efficiency Ratio
 - GTM Efficiency Margin

𝗙𝗜𝗡𝗔𝗡𝗖𝗜𝗔𝗟 𝗠𝗘𝗧𝗥𝗜𝗖𝗦

We ask questions like:
 - Are we growing fast enough?
 - Are we growing profitably enough?
 - Do we have strong unit economics?
 - Are we producing enough cash flow?
 - Are we spending too much in sales/mktg?

We answer them with metrics like:
 - Rule of 40
 - Growth Rate
 - Gross Margin
 - Net Income
 - Etc.

𝗣𝗜𝗣𝗘𝗟𝗜𝗡𝗘 𝗚𝗘𝗡𝗘𝗥𝗔𝗧𝗜𝗢𝗡 𝗠𝗘𝗧𝗥𝗜𝗖𝗦

We ask questions like:
 - Are we generating enough pipeline?
 - Are we generating enough inbound leads?
 - Are we logging enough outbound activities?
 - How are leads and activities converting to pipe?

We answer them with metrics like:
 - Lead Generation (MQLs)
 - Pipeline Generation (# and $)
 - Sales Activities, Meetings Booked
 - Conversion Rates

𝗣𝗜𝗣𝗘𝗟𝗜𝗡𝗘 𝗠𝗘𝗧𝗥𝗜𝗖𝗦

We ask questions like:
 - Are we closing deals?
 - Are we chasing the right deals?
 - Do we have real pipeline to close?

In other words, do our reps actually know how to identify real qualified sales opportunities and do they know how to take all the right steps to close them?

We answer them with metrics like:
 - Close Rate
 - ASP
 - Sales Cycle
 - Pipeline Velocity

𝗖𝗨𝗦𝗧𝗢𝗠𝗘𝗥 𝗦𝗨𝗖𝗖𝗘𝗦𝗦 𝗠𝗘𝗧𝗥𝗜𝗖𝗦

We ask questions like:
 - Are we retaining customers?
 - Are we expanding customers?
 - Are we onboarding them right?
 - Which customers are healthy?
 - Which can we try to expand?
 - Which are unhealthy?
 - Which are at risk of churn?

We look at metrics like:
 - Gross Retention Rate (GRR)
 - Expansion $ARR
 - Net Revenue Retention (NRR)
 - Customer Health Ratings
 - Onboarding Metrics

More on this in our 𝗚𝗧𝗠 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗮𝗻𝗱 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗜𝗻𝗱𝗲𝘅

Read the Framework and/or get the high-res image in the link in my comment below 👇

Or comment "High Res" below (and send me a connection request if we're not already connected) and I'll DM it to you. 

✌️

𝗚𝗧𝗠 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 & 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 separate Strategic CROs and RevOps Leaders from glorified sales managers and systems admins. 

Getting accurate metrics isn’t easy though. 

Getting real Insights from those metrics is even harder.

We need to:

𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝘁𝗵𝗲 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗧𝗵𝗮𝘁 𝗠𝗮𝘁𝘁𝗲𝗿
Start by identifying the metrics that matter for your unique GTM motion. 

To help, our 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗮𝗻𝗱 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 will have a 𝗚𝗧𝗠 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗜𝗻𝗱𝗲𝘅 outlining the most common metrics in B2B SaaS and how to calculate them. 

𝗗𝗲𝗳𝗶𝗻𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝘁𝗵𝗮𝘁 𝗙𝗲𝗲𝗱 𝗠𝗲𝘁𝗿𝗶𝗰𝘀
Metrics are only as accurate as the process being executed. 

If our salespeople don’t know how to qualify deals, for example, our Close Rate will tell us nothing. 

We have to clearly define processes, train the team, and drive them to adopt and execute in order to be a data-driven organization. 

𝗨𝗻𝗯𝗹𝗲𝗻𝗱 𝘁𝗵𝗲 𝗙𝘂𝗻𝗻𝗲𝗹
It’s not enough to see our Lead Conversion Rate, or Close Rate, across our entire business. 

These numbers are blended together across different types of leads and lead sources, different segments (SMB, MM, ENT), geos, products, etc. 

To see what’s really happening, we have to unblend the funnel. 

More on this in our 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗮𝗻𝗱 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 

𝗜𝗻𝘀𝗽𝗲𝗰𝘁 𝗗𝗮𝘁𝗮 𝗥𝗲𝗴𝘂𝗹𝗮𝗿𝗹𝘆
People only execute processes when held accountable. 

To get accurate data, we need to inspect the data regularly to be sure it’s accurate. 

To get real insights into our business, we need to analyze that data regularly to spot trends and take action.

This requires the right person/people with the right skills and uninterrupted time to do “deep work.” 

CROs usually don’t have time to do this well and RevOps can’t if they’re constantly harassed with system admin requests. 

𝗗𝗿𝗶𝘃𝗲 𝗔𝗻𝗻𝘂𝗮𝗹 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴
As we get to this part of the year, finalizing our annual plan, it’s a bit too late. We have dirty data and have to make some BIG assumptions. 

If we’re in this boat, we need fix this for next year.

Additionally, Annual Plans aren’t set in stone. We need to track them and iterate as we hit or miss goals and milestones. 

More on this in our 𝗚𝗧𝗠 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗮𝗻𝗱 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸.

See the Framework and get the high-res version in the link in the comment below. 👇

If you want more breakdowns like this, subscribe to our newsletter at the link to get weekly insights directly in your inbox. 

✌️

The current GTM AI frenzy reminds me of the same shiny object syndrome that drove Predictable Revenue and Outreach and Salesloft. 

It's not that any of it's wrong. 
It's that GTM leaders overlook fundamentals. 

Here's what we all saw last time.
 - Predictable Revenue came out
 - Outreach and Salesloft came out
 - And it felt like a magic easy button
 - Just hire a bunch of outbound SDRs
 - Buy and implement Outreach or Salesloft
 - Slap together some cadences and templates
 - Reps press "Send All" and watch the money roll in

And this worked for some
And this worked for some time
But response rates ended near zero

Why?

Think about the fundamentals:

 - Do we have the right ICP?
 - And the right Buyer Personas?
 - Do we know our outbound capacity?
 - As in the number of prospects we can work?
 - Have we identified the best prospects to target?
 - And have we segmented similar types of buyers?
 - And created sequences for each of those segments?
 - And trained our reps to do actual research before send?
 - And built a reporting and review engine for management?
 - To identify what's working, what's not, and what to iterate?

If yes, this approach and these tools worked very well. 

If not, they didn't, at least not for long. 
 - Not after we burned through the first batch
 - Got a <1% response rate from our best prospects
 - And had to dig for scraps waaaaaaay outside the ICP

AI is not different. 

There's no magic prompt to write the perfect message to be all things to all prospects. 

If we want AI to work, we need to master the fundamentals. 

✌️

I've had 3 back to back calls with major PE firms facing massive pressure to implement AI in GTM. 

One told me "Even if these AI tools don't add value to GTM, they add value to the company."

I had to digest that one. 

What he was telling me is this:
 - If a company implements AI in GTM
 - And it produces zero impact or improvement
 - Just saying "we have AI" increases company value

I was shocked by this!
But I really shouldn't be. 

I've spent the last +20 years working with PE/VC investors and they're just as susceptible to shiny object syndrome as any other humans.

So I get it.

Everyone is facing this pressure. 

But, as we address it, we might as well create some real value too.  

To do this, we need to master the fundamentals:
 - Pipe Gen
 - Closing and Forecasting
 - Renewals and Expansion

Within each of these is a series of basic steps. 
Unique to each market, each product, each GTM team. 

Many have not defined these steps. 
Many don't know what "good looks like"
Making it extremely hard to replicate "good" with AI. 

For those that have mastered these fundamentals. 
It's FAR easier to look through each step for use cases. 

If you need some help, check out our GTM Efficiency Pyramid. 

This will outline the fundamentals for you. 

So you can quickly get to the shiny objects AND see real value. 

Link below in the comments 👇

✌️

Outbound is not dead!
 - It's working for us
 - It's working for our clients
 - What's dead is Spray and Pray
 - It's pressing "Send All" that's dead
 - Sending generic templates to everyone

Relevant/Personalized outbound works
 - Highly targeted messaging
 - To a very narrow niche of prospects

We see this w/ our clients
 - We see the reports
 - We see what's working
 - We see what's not working

Outbound works when reps reach:
 - The right people
 - In the right companies
 - With the right messaging

Here's how to do this "at scale"

𝗜𝗖𝗣/𝗕𝘂𝘆𝗲𝗿 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝘀

Most ICP/Persona definitions miss the "ideal" and cast far too wide a net, targeting broad industries and revenue ranges without getting granular enough to define the "ideal" customers. 

𝗖𝗮𝗽𝗮𝗰𝗶𝘁𝘆 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴

Reps have 2,000 accounts and can only cover 200. 

They're missing 90% of the best accounts and/or doing their own analytics to identify them. This is NOT an efficient use of seller's time. 

Instead, we should carefully analyze capacity and give reps the absolute best accounts they can work. 

𝗧𝗲𝗿𝗿𝗶𝘁𝗼𝗿𝘆 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴

Territories need to match capacity with the best accounts and contacts in our ICP/Personas, within that capacity. 

𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝗧𝗮𝗿𝗴𝗲𝘁 𝗟𝗶𝘀𝘁𝘀

Break territories into segments so reps can focus on one person in one type of company at a time. 

Reps can share far better messaging in far less time if they're focussed on one avatar with one set of challenges. 

𝗖𝗮𝗱𝗲𝗻𝗰𝗲𝘀/𝗣𝗿𝗼𝗰𝗲𝘀𝘀

Define the process reps need to execute to maximize conversion rates on this extremely targeted outbound. 

Define where messaging needs to be personalized/tailored and where it can be targeted with highly relevant templates for each segment. 

𝗘𝗻𝗮𝗯𝗹𝗲𝗺𝗲𝗻𝘁, 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴, 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴

Train the team and use reports to ensure they're targeting the right people with the right messaging and executing the process. 

This requires active effort and ongoing coaching from management. 

𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻

With this foundation in place, we can get accurate data and look at what's working, what's not, and where we can optimize the targets, messaging and process. 

Pipeline Council is just one way to do this in a more formal way. 

𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻

Once things are working, we can scale that foundation with automation, AI, and other advanced motions. 

--------------------------

We broke this down in our 𝗢𝘂𝘁𝗯𝗼𝘂𝗻𝗱 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸

👉  See the link in comments to get it. 👇

𝗪𝗮𝗻𝘁 𝘁𝗵𝗲 𝗵𝗶𝗴𝗵-𝗿𝗲𝘀 𝗶𝗺𝗮𝗴𝗲? 

Grab it in that same link. 

Or comment "High Res" below 
 - Send a connection request if we're not connected
 - We'll DM it to you

✌️

Improving your CRM won't fix your bad data.
Improving your data won't fix your poor reporting.
Improving your reporting won't fix your poor process.
Improving your process won't fix your poor GTM strategy.
And improving your GTM strategy won't fix your lack of focus.

Your focus is everything.

One buyer
One product
One GTM motion

Just get that right.
Ignore absolutely everything else.

If you're a $1M startup, there shouldn't be anything else.
If you're a $1B public company, you can't fix it all at once.

Your focus will lead to great GTM Strategy
Your focussed strategy will lead to great process
Your focussed process will lead to great reporting
Your focussed reporting will lead to great execution
Your focussed execution will lead to great GTM data
Data will then circle back up to further improve GTM strategy

✌️

I see a lot of CROs set up to fail.
It happens for a lot of reasons, but here's one. 

I met a CRO and CMO a little while back. 

Core Issues:
 - Pipeline mismanaged
 - Inbound leads being ignored
 - Outbound prospecting neglected

Potential customers in their ICP were raising their hands, asking for demos, getting zero response from sales. 

My 1st Reaction:
 - What is the issue?
 - You're the CRO and CMO
 - Just fix the process tomorrow
 - We can help you fix this, and fast

Unfortunately, they had other blockers. 

Second Layer:
 - The CRM is a mess
 - We have 500 custom fields
 - It's a nightmare for our reps

My 2nd Reaction:
 - We can fix this too. What's the issue?

This looked like a tech issue, but it wasn't. 

Third Layer:
 - The CTO built this
 - CRO and CMO are new
 - And CTO says he's got this
 - Except that he's slammed now

My 3rd Reaction:
 - Okay.....
 - The CTO built the CRM
 - And made an enormous mess
 - So much so that sales can't use it
 - Can't follow up with hot inbound leads
 - So you're loosing easy revenue every day
 - We need to get aligned with your CEO on this

What happened next?
 - We couldn't get the CEO into a conversation
 - We spoke with the CTO and ended as you'd expect
 - Leaving the CRO and CMO fighting to swim upstream 

The REAL Core Issue:
 - CEO is not committed to GTM

The CEO is committed to spending money
 - On a competent CRO
 - On a competent CMO
 - On a robust GTM tech stack
 - On marketing spend to drive leads
 - On salespeople to convert those leads

But the CEO isn't committed to understanding it
 - Or making sure it works

As a CEO myself, I get it. 
 - We don't have time to fix every problem

But revenue generation is never something to ignore. 

✌️

There's a good reason salespeople get paid more.
And it's not just that they're closer to revenue. 
It's also not just that it's (in theory) more measurable. 

It's about accountability. 

Think about every other job in a company. 

1. Finance
 - Customers paid late
 - "We followed up. What else can we do?"
 - They still get paid all/most of their comp

2. Product
 - Customers didn't like new features
 - They still get paid all/most of their comp

3. Marketing
 - Leads didn't convert to pipeline
 - We can blame sales for not closing
 - They still get paid all/most of their comp

Etc.

Now, contrast this with sales. 

1. Leads Not Converting
 - Even if they followed up
 - Even if everyone knows leads are bad
 - They lose half their income and/or their job

2. Customers Don't Pay Bills
 - They get clawbacks
 - Sometimes they have to chase them
 - They lose half their income and/or their job

3. Product Features Can't Compete
 - "You need to sell better."
 - "Sell value not features."
 - They lose half their income and/or their job

Sales is one of the few jobs where even when you're right, you can be wrong. 

The one job where no matter what obstacles are thrown in your way you just have to overcome them or deal with the consequences. 

The only job I know of that has more accountability than this....

Bootstrapped Founder/CEO

And sales is one of the best training grounds for it. 

Agree/disagree?

🤔

Most companies define ICP too broadly. 

They look at who they've already sold to.
Pull a report from the CRM.
Filter by company size, industry, revenue.
Call it done.

That's a smart place to start.
But a dangerous place to stop.

Because our easiest wins aren't always our true ideal customers.

We recently had Brady Jensen, CEO of Clear Go-To-Market, on our podcast to talk about how to actually validate ICP.

Not just define it. Validate it.

Here's what he told us:

ICP isn't something we engineer in a conference room.

It's something we discover through direct conversations with the people we're trying to sell to.

Not just our best customers.
Not just the people already in our pipeline.
But the prospects who match our criteria and haven't yet bought.

Brady's process is straightforward:
- Start with a hypothesis based on who buys fastest, expands most, stays longest
- Talk to people who fit that profile
- Test whether they experience the problem
- Test whether they value the solution
- Test whether they would actually buy

You're not just looking for fit.
You're testing for signal.

And here's where most companies fail:

They define ICP once and freeze it.
They don't pressure-test it in the real world.
They don't learn from the "no's."

"You have the ability to learn a ton from people saying 'no'," Brady explains. "Oftentimes, the 'no' is not 'I don't like your product.' It's 'I don't believe I have the problem you say I have.'"

That feedback loop between our ICP hypothesis and the market's response is where high-leverage refinement happens.

But it only works if we're disciplined enough to say no to the wrong customers.

Even when we need the revenue.
Even when the deal is right there.
Even when leadership is pushing for more logos.

"The problem we often see is organizations will just sell to everybody," Brady says. 

"And then they have a bunch of unhappy customers, and they're like, 'I don't know why they're unhappy.' Well, because they were never a good fit."

That lack of discipline trickles down through the entire organization:
- Product builds for the wrong use cases
- CS struggles with misaligned expectations
- Onboarding becomes custom every time
- Renewals suffer
- Team morale tanks

And the biggest thing I've seen from making this mistake myself:

You're less valuable to the right buyers
 - You've underinvested in your real ICP
 - The product isn't as good for them as it could be
 - Nor the marketing materials and sales messaging

Real GTM clarity comes from pairing data with direct customer conversations.

When we understand our buyers really well, we can build a business that serves them really well.

How often are you validating your ICP assumptions with real buyer conversations?

🤔

Read more in tomorrow's 📰 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛  📰

Or listen to the full episode on the🎙𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝙋𝙤𝙙𝙘𝙖𝙨𝙩🎙

See comments below for links 👇

✌

What's the first thing I'd do as a new CRO?
I'd hire VAs for every person in GTM

Yep, my first thing would be hiring VAs
 - It wouldn't be AI
 - It wouldn't be fixing the CRM
 - It wouldn't even be the annual plan

All of those things are important. 

But I'd hire a VA for every single person in GTM
 - VAs for every AE
 - VAs for every BDR
 - VAs for every AM/CSM
 - VAs for every marketer
 - VAs for everyone in RevOps

Let's say this costs $10/hr.
That's net, not gross.
No office space.
No benefits or taxes.
Just a straight $10/hr.

Now, imagine the immediate impact.
 - AE has a $1M quota
 - How much time do we need to save?
 - To justify $10/hr for a VA? 
 - AE costs $500/hr in sales quota
 - So a VA needs to save them 1 hour
 - For every 50 hours that VA works for them
 - That's some pretty obvious ROI right there

How about the BDR? 
 - Half that? 25 hours?

How about the AM/CSM?
Or the marketing manager?

Just imagine if the VAs were:
 - Trained in using ZoomInfo/Clay
 - Trained to do basic things in SFDC
 - Trained to do basic things in Hubspot
 - Helping to do manual account research
 - Helping to manually create prospect lists
 - Helping to schedule and confirm meetings

Well I don't have to imagine. 

I've been doing this for ~9 years. 

I've had multiple VAs
I also have a NYC based EA

I cannot even describe the ROI we get. 

And after doing this, I can do the bigger things. 

Knowing what good looks like, we can look at each task and leverage AI. 

But there are always gaps with the AI. We need a "human in the loop."

Do I want that human carrying a $1M quota?

Or do I want someone at $10/hr doing the first pass?

🤔

There's a reason CROs aren't getting what they want from RevOps.

I was on a call like this the other day... 

CRO:
 - RevOps is purely reactive
 - They're not bringing me insights
 - They're not driving revenue growth
 - RevOps doesn't have any North Star

Me:
 - Who do you have on your team

CRO:
 - We have a Salesforce Admin
 - We have a Marketo Admin
 - And we have another admin

Me:
 - Who does RevOps report to?

CRO:
 - They report to this person
 (This person has zero GTM experience)

Me:
 - Asks detailed questions about GTM

CRO:
 - We have poor pipeline hygiene
 - No one trusts it and we can't forecast
 - We're very inconsistent with outbound
 - We don't follow up with inbound leads well
 - We are using over 40 different GTM tools now

Me:
 - I see the issue
 - Unfortunately we're at time
 - I'd like to schedule another call
 - To narrow in on the key priorities here

CRO:
 - Yep!
 - Work with {name} on that.
 - I'm really slammed at the moment. 

Me:
 - The person with zero experience in GTM?

Huh?

🤔

Let me share the real issue here:

1. RevOps has no North Star
 - Because the CRO has no North Star

2. RevOps is purely reactive for a few reasons
 - The CRO isn't investing time with them
 - They also don't have the right experience
 - And reporting to someone with GTM experience

3. There's no prioritization
 - Admins spend all day in tools
 - Because that's what admins do
 - And even if they wanted to stop
 - There's no prioritization to guide them
 - They're flooded w/ requests to update tools
 - With no clear priorities to decide when to say no

4. The GTM Process is broken
 - And none of these folks can fix it
 - Pipeline is a mess bc of the sales process
 - No amount of SFDC config will fix this issue
 - You have to change the process and train people
 - Then you have to drive them to change their actions
 - And I've never once seen an SFDC Admin do this alone

✌️

This guy DM'ed me and I had a full proposal an hour later. 
And I just signed a contract with him.

This was the smoothest buying experience.
 - I get a LI Connection Request with a DM
 - I'm actively searching for this solution
 - I accept it and respond to his DM
 - But I don't know this guy at all
 - I don't want to "jump on a call"

I ask if I can ask questions over DM
 - He says yes
 - So I hit him with questions
 - He asks me some questions too
 - We're essentially into a disco session
 - But then I have to jump into a meeting

When I get back
 - I have another DM
 - With a link to a full proposal
 - With a personalized video walk through

I'm basically sold at this point
 - He understood all my needs
 - The proposal reflected those needs
 - The pricing was very fair and attractive
 - And he shared more details in his video
 - He shared past successes, testimonials, etc
 - He built a lot of credibility in this ~5 min video

So I was sold
 - But I was vetting 3 vendors in total
 - So I took a couple of weeks to evaluate
 - And circled back and signed with him last week

This is how we all want to buy
 - Meet me where I'm at
 - Ask thoughtful questions
 - Answer my questions asap
 - Share details as soon as possible
 - Make it very easy for me to buy from you

✌️

How do you flip a GTM motion from 95% outbound to 95% inbound?

And close deals 4x faster than your competitors while doing it?

We recently had Aviv Canaani, CMO/CRO of Datarails, on our Podcast, to break down how his team built a revenue engine that grew new sales 90% YoY.

Here's what they did:

They engineered speed into every part of the motion.
- Five-minute SLA on demo requests
- Next-day AE availability
- Sales cycles a third of the industry average

They built predictable forecasting systems.
- Every dollar mapped to meetings, opps, revenue
- Conversion rates tied to historical data
- Quarterly targets they could actually hit

They treated GTM like a factory, not separate departments.
- Marketing, sales, RevOps as one machine
- Each team doing their part
- No silos, just coordination

The result?

AEs stopped prospecting. They didn't need to.

The inbound engine was feeding them qualified pipeline.

And their biggest deal in company history?

The lead source was ChatGPT.

This isn't about copying someone else's playbook.

It's about thinking like a systems builder instead of a department head.

When you connect every lever, 
- From inbound to outbound
- From content to conversion
- From SDR to AE...
…you don't just grow faster.

Your revenue becomes more predictable.

How repeatable are your systems today?

🤔

More on this in tomorrow’s 📰𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰
Subscribe to get it here: https://bit.ly/49RCm0h

Listen to the full podcast episode on 📰𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 📰 here: https://bit.ly/4agM6Bo

✌️

How do you get an ROI from GTM Ops?
A 0.6% improvement in Close Rate could be enough. 

That's it!

We’re often held back in GTM. 
 - We have broken processes
 - Our team isn’t executing consistently
 - And we don’t have visibility into our GTM

But we can’t get budget to fix it. 
 - Because hiring a sales rep has a “clear ROI” (in theory).
 - And GTM Ops feels harder to measure. 

Let me share a simple way to look at this.

Say we expect to close $25M in new biz w/ a 15% Close Rate.
 - If we improve Close Rate to just 15.6%...
 - We would close an additional $1M in ARR

Here’s the math:

$166.67M of Pipeline
x 15% Close Rate
= $25M Closed Won ARR

$166.67M of Pipeline
x 15.6% Close Rate
= $26M Closed Won ARR

ROI => +$1 million of additional ARR

Now, let’s look at our current situation:
 - Pipeline is very messy
 - Reps chasing unqualified deals
 - Reps are way too busy as a result
 - Reps missing critical steps in sales process
 - We’re not getting access to the right stakeholders
 - We’re not asking the right questions in the journey
 - Mgmt has zero visibility into this in pipeline reports
 - So it’s harder for them to spot these issues in real time 

Could fixing this improve Close Rate by 0.6%?

The answer is pretty obvious.

Now, what about the rest of GTM?
 - Our inbound lead conversion?
 - Our outbound prospecting conversion?
 - Our onboarding, health, and renewal rates?
 - Our generation and closing of expansion opptys?

This is an EXPONENTIAL RETURN
 - More qualified leads
 - More qualified outbound mtgs
 - Higher conversion rates for both of them
 - Means more qualified pipeline for us to close
 - With higher Close Rates, ASPs, and shorter cycles
 - Means more new business this year and the next
 - With higher renewal rates and more expansion opptys
 - Meaning more revenue from each new customer
 - On top of more new customers

It’s all pretty obvious.

And yet, I see GTM teams NOT fix these issues.

Because they’re worried about the ROI…..?

🤔

But I get it.

We get asked this question, because CROs, CEOs, CFOs, get asked this question. So we broke this down in fine detail, with math and visuals, based on EXTREMELY conservative assumptions, to help everyone map out the ROI in GTM Ops. 

Check it out in yesterday’s 📰𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰

Get it here: https://bit.ly/3M6IbQu

✌️

Most CROs are stuck playing Whac-A-Mole.

Pipeline dips. They panic. They spin up new campaigns.

Deals stall. They blame the team. They change the comp plan.

Forecast misses. They scramble. They push harder on the same broken levers.

This is what happens when you lead departments instead of building systems.

We recently had Aviv Canaani, CMO/CRO of Datarails, on our podcast. 

His team grew new sales 90% YoY.

Not because they worked harder.

Because they stopped thinking like department heads.

Here's what that actually means:

They connected the entire revenue chain:
- Marketing didn't just generate leads
- They mapped spend to meetings to pipeline to revenue
- Sales didn't just work opportunities
- They fed insights back to optimize the top of funnel
- RevOps didn't just run reports
- They turned data into capacity planning decisions

When meeting volume spiked, they didn't let it become a bottleneck.
They pushed HR to hire faster.

When demo requests came in, they didn't let them sit.
They built a five-minute SLA and next-day availability.

When forecasting felt like guesswork, they didn't accept it.
They built conversion benchmarks tied to historical data.

Every part worked together.

Like a factory line, not separate departments.

Most revenue leaders are optimizing individual functions:
- Better marketing campaigns
- Better sales training
- Better CS processes

But they're not connecting them into one engine.

So when one part improves, another breaks.

When demand spikes, capacity can't handle it.
When data is needed, it's not trustworthy.

That's the difference between tactics and architecture.

Tactics fix today's problem.
Architecture prevents tomorrow's fire.

Are you building systems or managing departments?

🤔

More on this in our last issue of 📰𝙏𝙝𝙚 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰
Get it here: https://bit.ly/4inXUXG

Listen to the full podcast episode on 📰𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 📰 here: https://bit.ly/4rgmRYO

✌️

Nothing feels more meta than consulting in RevOps while operating as CEO and CRO in my own company. 

RevOps
 - We work with CROs and CEOs
 - We try to help them build processes
 - We try to help them get insights from data
 - We try to help them use data to plan better
 - We try to help them build a repeatable machine

CRO
 - I try to practice what I preach
 - We've built all these processes here
 - We have all the data our customers want
 - We review that data in our weekly team mtg
 - We plan carefully based on this data 

CRO (Small Business)
 - I don't have a big team
 - So I'm also selling and marketing
 - And also doing some CS work as well
 - Working on the front lines every single day
 - I'm creating marketing content all by myself
 - And also working with our team to create more
 - And tracking all marketing through to won revenue
 - And taking inbound leads, selling, closing deals myself
 - And outbound prospecting and pipeline mgmt every day
 - And hiring, training and managing our salespeople as well
 - And tracking our NRR and working with my SVP of Delivery

CEO
 - And then I step out of GTM
 - And it's the same types of things
 - How is the rest of the business working?
 - When do I work ON the business, not just IN it?
 - Do we have defined processes and metrics in place?
 - What are we spending and what revenue is it generating?

And ALL of this comes down to just a few things.

In somewhat reverse order of importance:

1. Process
 - Do we have clear process?

2. Execution
 - Are we executing that process?

3. Efficiency
 - Is this profitable?

4. Focus
 - Are we focused on the right things?
 - Or trying to do too many things at once?

Notice I didn't mention strategy. I still don't know what that word means. I think, whatever it is, it comes from focus, from thinking about the same thing day after day after day until you figure it out, or decide to walk away. 

✌️

Your outbound motion isn't working.
Is it a message problem or an audience problem?

Most teams assume it's the message.

So they rewrite the sequences.
Test new subject lines.
A/B test the CTAs.

But the real issue is simpler.

They're targeting the wrong people.

Brady Jensen, CEO of Clear Go-To-Market, puts it this way: "If your outbound motion doesn't work… you either have a message problem or an audience problem."

Here's how to tell the difference.

If you're reaching out to people who:
- Don't believe they have the problem you're solving
- Don't think the problem is worth solving
- Aren't actively looking for a solution

No message will fix that.
You're talking to the wrong audience.

This is why ICP validation matters.

It's not about building the perfect persona deck.
It's about testing your hypothesis against real market resistance.

Brady's approach is straightforward:
- Talk to prospects who match your ICP criteria but haven't bought yet
- Don't pitch. Listen.
- Look for patterns in the "no's"

"You have the ability to learn a ton from people saying 'no'," he explains.

The friction you hear tells you:
- Whether they recognize the problem
- Whether they've tried to solve it before
- What triggers them to evaluate new solutions
- Who inside their org feels the pain most

That feedback loop between your ICP hypothesis and the market's response is where the real refinement happens.

It's how you avoid building strategy around people who look right on paper but aren't ideal customers in practice.

And it's why your outbound motion is actually a discovery tool.

When prospects consistently say no, they're telling you something.
The question is: are you listening?

What's your outbound response rate telling you about your ICP?

🤔

More on this in the latest 📰𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰
Listen to the full podcast episode on 🎙𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚🎙

Links below in the comments 👇

✌️

There’s a BIG hidden cost to complex comp plans. 
Reps lose motivation because they don’t understand them. 

Any more than 3 variables loses reps. 

Let me walk through a personal example.

Variable 1:  You earn 10% of all contracts.
 - Simple enough
 - If I close a $100K deal
 - I get paid $10K in commission
 - That hits my bank on February 1
 - And I can book that ski trip if it closes!

This is motivating for a rep.
They can visualize the outcome.

Variable 2: 5% for one-time deals
 - So now it’s….
 - 10% for recurring
 - 5% for one-time deals
 - My deal was $80K SaaS
 - And 20K for implementation
 - So now it’s…
 - Harder to do the math
 - 10% x $80K = $8K
 - 5% x $20K = $1K
 - Total = $9K

Okay, I got there.
The ski trip could still be on!
Let’s close this deal as soon as I can!

Variable 3: 2X boost for multi-year
 - So now it’s….
 - 10% for recurring
 - 5% for one-time deals
 - And another 10% for 3yr deals
 - Okay, so I’ve got that in my deal here
 - 10% x $80K = $8K
 - 5% x $20K = $1K
 - 10% x 80K = $8K
 - Total = $17K

Alright, that was harder to calculate but I’m still here. 

Variable 4: 1.5X boost if Product X is included
 - Okay, I give up.
 - I’m working 15 deals
 - Some have Product X
 - Some have multi-year
 - Some have implementations
 - But I’d need an excel sheet to do this math

I personally experienced this as an AE at Salesforce.
 - We got comped on….
 - Percent of Closed Won $
 - Accelerators at different levels of quota
 - And more accelerators for multi-year deals 
 - And some other stuff that I never remembered

I vividly remember some spiff where I was like….
“I have no idea if focusing on this will make me money or cost me money so I’m just going to ignore it and keep my head down and work the plan I understand.”

And FWIW, I am a math nerd.
But I couldn't justify spending all day in Excel
When I had an extremely difficult quota to hit

This is a common comp failure we see.
 - Companies over-engineer comp plans.

The other common failures?
- No deal reporting standards (every rep records deals differently)
- No commission cutoff process (deals close after payroll runs)
- No formal approval chain (nobody knows who approved what)
- No process documentation (comp rules exist in someone's head)

And all of these stem from that complexity. 
Reps are confused.
Managers are confused.
RevOps is also confused.
Finance is confused as well.

So, instead of motivating reps.
We’re frustrating them and burning valuable time. 

What’s the worst comp plan you’ve seen?

🤔

More on this in yesterday’s 📰 𝙂𝙏𝙈 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝘽𝙧𝙞𝙚𝙛 📰

We broke down the common mistakes companies make building commissions plans and how to fix them.

Get it in the link below in the comments 👇
Or click “View my blog” at the top of this post 👆

✌️

Jonathan M K.

VP of GTM Strategy & Marketing - Momentum | Founder GTM AI Academy & Cofounder AI Business Network | Business impact ​> Learning Tools | Proud Dad of Twins

I’m Jonathan, an AI and GTM strategist passionate about transforming how businesses harness AI for real impact. With over 15 years in Revenue Excellence, Enablement, and GTM Acceleration, I’ve successfully developed and implemented transformative enablement programs for global organizations, Fortune 500 companies, and startups. Recognized in SEC’s 2023 & 2024 Enablement Ones to Watch and honored as an Enablement Legend by Seismic and the Enablement Squad, I strive to stay ahead of industry trends.

4 Years ago I deep dove into AI after enabling an AI tech for an internal team and it's customers and in 2022, I founded the GTM AI Academy to bridge the gap between learning AI tools and creating tangible business outcomes. My mission is to provide AI-driven strategies that cover all functions of a Go-To-Market (GTM) team, helping professionals implement actionable use cases for their own companies. I also consult on AI integration and strategy for high-growth businesses, offering GTM insights that drive revenue growth and efficiency.

If you’re looking to leverage AI either for Yourself, Your team, or C-Suite and Board level advising, refine your GTM strategies, or accelerate business outcomes, feel free to connect. I’m always open to discussing the future of AI in business and how to make true impact.

Head of GTM Revenue Enablement & Product Marketing

- Develop and execute revenue enablement strategies to drive sales growth and enhance customer experience.
- Collaborate with cross-functional teams to align revenue goals, optimize processes, and identify market opportunities.
- Conduct market research and competitive analysis to stay ahead in the payment media industry.
- Implement and oversee enablement programs, including training, tools, and resources for our presales, CSM, BDR, partner, and sales team.
- Analyze sales performance data and provide insights to improve revenue generation and forecasting accuracy.
- Cultivate strong customer relationships and support our clients in adopting Simetrik's solutions effectively.
- Drive continuous improvement initiatives to enhance revenue processes and strategies.
-Manage the Product Marketing team creating internal and external facing assets such as videos, blogs, one pagers, white papers, case studies, success stories.

Google just quietly built the most comprehensive AI stack on the planet—and 90% of GTM teams are ignoring it.

Here’s what most people miss:

While everyone debates ChatGPT vs Claude, Google shipped 40+ AI products that already live inside the tools your team uses daily.

Gmail. Docs. Sheets. Meet. Drive. Search. Maps. YouTube.

All connected. All powered by Gemini. All learning from each other.

The math:

$19.99/month gets you:
→ Gemini 3.0 Pro (outperformed GPT-5 Pro on 19/20 benchmarks)
→ AI in every Workspace app
→ NotebookLM Plus for research
→ Image and video generation
→ 2TB storage

That’s less than most teams spend on a single AI tool.

Real GTM use cases delivering results right now:

Pipeline Research
NotebookLM + company 10-Ks + earnings calls + news articles = comprehensive account intelligence in 15 minutes vs 3 hours of manual research.

Meeting Leverage
“Take notes for me” in Meet auto-generates summaries with action items. “Send Gemini to meetings” attends calls you can’t make and reports back.

Content Velocity
Deep Research compiles multi-page reports from Gmail, Drive, and web sources. One prompt. One output. Ready for editing.

Outbound Personalization
Gemini processes prospect LinkedIn profiles, company news, and your CRM notes simultaneously. Personalized sequences at scale without the robotic feel.

Competitive Intel
NotebookLM Audio Overviews turn competitor documentation into 10-minute podcast briefings your team actually consumes during commutes.

Proposal Generation
Workspace Studio agents (just launched) automate the grunt work—pulling CRM data, generating first drafts, routing for approval. 20 million tasks executed in month one of alpha.

The strategic advantage nobody’s talking about:

Google’s AI isn’t just in your browser. It’s on your phone (Pixel), in your home (Nest), on your wrist (Watch), and in your car.

One ecosystem. One subscription. Context that follows you everywhere.

Your competitor is still copying and pasting between 6 different AI tools.

You can have one system that already knows your emails, calendar, documents, and workflow patterns.

The bottom line:

The best AI stack isn’t the one with the highest benchmarks.

It’s the one your team actually uses because it’s already embedded in their workflow.

Google understood the assignment.

Jonathan M Kvarfordt, MBA

Last call to get people into my  TEST course teaching AI using only... AI. Would love testers, anyone else want in?

This month it will be 3 years since I launched the GTM AI Academy and have had thousands of people go through it with lots of amazing feedback.

It is time to do my refresh and updating of content and part of which I want to experiment and launch a new course while only using AI to teach every module, do the testing, quizzes etc.

This is just a thought experiment and honestly want to test it out to see if it actually can help someone in the learning process vs the old school way of watching videos, giving assignments and then putting in a quiz.

So I am genuinely curious, who would be down to test something like this?

My goal is to get content as good as I can, but all with AI.

If you wanna be part of the group, I would ask you to do the following:
1-Like this post
2-Comment AI me
3-I will send you a link when its ready later this month
4-Be willing to give it an honest try and give me feedback if you are learning the required outcome.

I believe the topic will be on prompting and AI agent strategy, although I may do a few different topics.

Let me know if you are open or ready or down for that?

Most people prompt every AI the same way. That’s why their outputs are mediocre.

I’ve tested hundreds of prompts across every major AI platform. The difference between average and exceptional outputs isn’t prompt length. It’s prompt style matched to the tool.

This framework breaks it down:

ChatGPT → Prompt like an instructor.

Start with a role assignment: “Act as a productivity coach.” Define the specific task. Ask for step-by-step action plans with timelines. Specify your desired format—table, outline, bullet list. Request tool recommendations. ChatGPT excels at structured guidance and task planning. Give it constraints and it delivers.

Perplexity → Prompt like a research analyst.

Lead with specific information requests. Include relevant keywords, timeframes, and geographies. Ask for cited sources and reference links for verification. Request trend summaries with citations. Follow up with comparison questions that require data-backed reasoning. Perplexity is built for evidence-based analysis. Treat it like a junior analyst who needs clear research parameters.

Grok → Prompt like a candid friend.

Use conversational tone: “Hey Grok, what do you think about…” Add emotional context. Ask for honest, unfiltered feedback and alternative perspectives. Request comparisons or opposing viewpoints to challenge your assumptions. Ask for common pitfalls and mistakes to avoid. Grok thrives on casual brainstorming and identifying blind spots others miss.

Gemini → Prompt like a project planner.

Explain the overall project goal upfront. Define expected outputs—tasks, subtasks, timelines. Ask about Google Workspace integrations. Request detailed weekly or daily action plans. Ask for dependency breakdowns and milestones. Request formatted outputs like tables and charts. Gemini is optimized for project management and collaborative workflows.

Why this matters:

Each model has a personality bias baked into its training data and architecture. ChatGPT leans toward structured helpfulness. Perplexity toward verification and sourcing. Grok toward irreverence and contrarianism. Gemini toward organizational workflows.

When you fight these tendencies, you get generic outputs.
When you lean into them, you unlock capabilities most users never see.

The tactical shift:

Stop copying prompts between platforms. Start adapting your communication style to each tool’s strengths.

Same question, different framing = dramatically different quality.

One prompt style for all tools is lazy.
Adapted prompting is leverage.

Every VC I've talked to in the last 4 months (more than 10 VCs of big names) and 100+ CRO and Revenue leaders says the same thing: "Cut your enablement headcount. AI replaces them."

Here is the problem: They're dead wrong about what enablement actually does.

Last week, another investor told me to eliminate enablement roles. I asked what they thought enablement did. Their answer? "Training, onboarding, updating battle cards."

That's not enablement. That's busywork we got stuck with.

Real enablement is what happens when your sales rep wastes 3 hours finding the right pricing doc. When marketing builds a "game-changing" tool nobody uses. When your $50k AI investment sits at 12% adoption because nobody thought about workflow integration.

We're the ones who spot that your top performer spends 70% of their time on admin work. Who notice your RevOps team built 155 fields but only 8 get used. Who realize your new AI tool contradicts your existing process.

But here's the spicy part: Enablement is dying because we let ourselves get packaged wrong.

We became the LMS managers. The training coordinators. The PowerPoint updaters. And now VCs and Revenue leaders galore think that's all we do.

Meanwhile, companies are failing at AI adoption at an 85% rate (Gartner's number, not mine). Why? No change management. No workflow design. No friction removal.

Exactly what enablement should be doing.

The solution isn't defending a dying brand. It's repackaging what we actually do. Call it AI Ops, GTM Strategy, Revenue Acceleration - I don't care.

Stop fighting for a title that's been poisoned. Start owning the work that actually matters: orchestrating tools, removing friction, driving adoption.

Because while everyone's debating whether enablement has value, someone needs to fix the fact that your sellers spend 33% of their time actually selling.

That someone used to be called enablement. Tomorrow, we'll be called something else.

The work remains critical, I believe in Enablement more now than ever, the problem is how revenue leaders and VCs view the title.

What if your entire GTM team could be 10x more effective, without hiring a single new person?

Sounds like vendor BS, right?

But here’s what’s actually happening:

We literally wrote a book about it with Ignite. 

Winning by Design calls this the “Revolution Pivot”and the gap between companies who get it and those who don’t is about to become insurmountable.

For years, we scaled through labor: more reps, more touches, more burn.

Then we evolved: grow smarter through better systems and process.

Now we’re entering the Durable Growth Era: AI becomes the infrastructure itself, not a feature you bolt on.

The difference?

→ One approach adds cost with every new customer
→ The other makes each customer cheaper to acquire than the last

→ One requires constant manual intervention
→ The other learns and improves from every intervention

→ One scales linearly
→ The other compounds exponentially

This requires first principle thinking. You can’t optimize your way here. You have to architect for it.

Tomorrow, we’re breaking down exactly how to build it: Nov 19, 9am PST
Growth Architecture Primer: Designing Systems for Compounding Growth

Comment “growth” and I’ll send you the details
or get it here: https://lnkd.in/gc3dgrKN

No alternative text description for this image

Amazon: 14,000 layoffs. Verizon: 13,000 layoffs. Both citing AI as a primary driver.

But Yale’s 2025 labor market analysis shows minimal AI-induced job disruption across the broader economy.

What’s actually happening:

Amazon’s cuts follow pandemic overexpansion and bureaucracy reduction. Their AI investments are going into AWS infrastructure and research—reallocation, not elimination.

Verizon’s restructuring stems from T-Mobile competition, declining subscribers, and retail franchising. The “AI-era reskilling fund” is a $20M footnote to a 13% workforce reduction.

Nearly 50,000 U.S. tech job cuts in 2025 referenced AI. But analysts note these decisions are driven by cost structures, competitive pressure, and organizational complexity more than actual automation displacement.

The disconnect: Companies use AI as justification. Labor economists see gradual transformation, not mass replacement.

For GTM leaders: Don’t confuse corporate restructuring narratives with market reality. AI is reshaping how work gets done, but the “employment reset” hasn’t materialized. The opportunity is in strategic deployment, not defensive positioning against phantom displacement.

The companies winning aren’t the ones cutting fastest, they’re the ones investing in AI infrastructure while their competitors rationalize headcount.

98% of executives would rather be safe than first.

That was March 2024. MIT Tech Review surveyed 205 C-suite leaders predicting their AI deployment timelines. Now that we’re closing 2025, the prediction accuracy is fascinating.

What they predicted:

- 50% expected full AI deployment across all functions by now
- 90% planned to increase AI readiness spending significantly
- Data quality was the #1 deployment blocker (50% cited)
- Governance and security concerns outweighed speed (45%)

What actually happened:
Most companies are still stuck in pilot purgatory. The ones that broke through didn’t solve for data quality first—they solved for workflow orchestration. The insight engines didn’t win. The execution engines did.

The “safe over first” mentality backfired for most. While companies spent 18 months building perfect data foundations, their competitors shipped imperfect AI that automated real revenue workflows. Turns out buyers don’t care if your data is pristine. They care if your AI books the meeting, writes the follow-up, and moves deals forward.

What I’m seeing now:

- Companies that picked 1-2 high-impact workflows and went deep are seeing 10x ROI
- The data quality problem solved itself through use, not preparation
- Agent swarms handling end-to-end processes beat point solutions by miles
- ROI measurement is still broken—most still measure time saved vs revenue accelerated

Where we got it wrong:
The report said “data liquidity matters more than data volume.” True, but incomplete. Execution velocity matters more than both. The companies winning now didn’t wait for perfect data. They built feedback loops that improved data quality through automated workflows.

If you’re still waiting for AI readiness, you’re already behind. Ship the workflow. Fix the data in production.

MIT AI strategy 

Happy Thanksgiving everyone. Truly and genuinely grateful for you. Now get off LinkedIn and bond with your peeps.

Boston Consulting Group (BCG) recenter released research on fully autonomous companies, with zero employees, only coordinated AI agents. $116B invested in H1 2025. The timeline is debatable. The implications aren’t.

The AI-Only Advantage

AI model costs drop 10x annually. A sales agent handles prospect research, outreach, and scheduling in seconds, operating 24/7/365, learning from every interaction across all agents simultaneously. No coordination friction. Strategy deploys instantly.

For revenue teams: 70% of a rep’s time goes to activities AI handles today. The cost structure alone creates advantage incumbents can’t match with traditional models.

Where Humans Win

AI creates new constraints faster than it solves old ones:

Curation: When AI floods markets with content, taste becomes the bottleneck. Cultural context and brand identity require human judgment.

Evaluation: AI generates infinite hypotheses but can’t distinguish creative from feasible. Research shows it fails consistently at prioritization. Humans determine which problems merit investment.

Empathy: Trust-sensitive domains—healthcare, education, high-stakes B2B—require genuine human presence. 89% of executives say in-person meetings seal deals. An AI-only insurer struggles when customers need assurance a real company honors promises years later.

Relationship Capital: Decades of accumulated trust can’t be replicated by an entity that can’t shake hands. Incumbents become relationship brokers and guarantors in AI ecosystems.

Messiness: AI does not do well with messiness. Humans are messy, things change all the time in ways that are difficult for the best of machines to predict. Beyond the prediction it’s handling the messiness in a way that is constructive. AI current state still needs help here. 

The Strategic Question

The firms that win aren’t pure AI-only or traditional. They’re AI-first companies that redesign workflows around agents while leveraging human judgment where it compounds advantage.

The question isn’t whether AI-only firms will exist. It’s which new constraints emerge as AI commoditizes current advantages—and whether you’re positioned to solve those constraints or get bypassed.

Revenue leaders: track AI development, pilot agentic tech now, and identify where human capabilities solve emerging constraints in your domain.

Thanks for Michael for the doc.

BCG Why CEOs should prepare against AI competitors

Everyone knows someone, who gets sh$t done in creative ways. Do you? Let’s celebrate them!

Introducing the 2025 Momentum GTM AI Awards: Celebrating the Innovative Doers

You know who they are.

The RevOps leader who stays late to clean the pipeline so the team can hit their number.

The CS manager who spots the churn signal at 11 PM and saves the account by morning.

The sales leader who doesn't wait for the "perfect process" instead they ship, iterate, and win while others are still planning.

Every company has them. The people who don't just talk about getting things done, they actually do it.

In 2025, we're celebrating these Innovative Doers with the GTM AI Awards where we will be recognizing the revenue professionals who refuse to let manual processes slow them down, who embrace new tools to move faster, and who understand that execution beats analysis every single time.

We're looking for the people who turn "someone should do this" into "I did this." The ones who see a broken process and fix it instead of complaining about it. The teams that ship while others strategize.

Because the world needs more people who execute without excuses.

Nominations open NOW. Winners announced in 2 weeks! 

If you have someone or even nominate yourself, then di the following:

1-Like this post
2-Comment “I got someone!”
3-repost so we can get this out there to the community. 

Can’t wait to see who gets celebrated.

It is TIME for the GTM AI Podcast and newsletter, this week we got a lot of goodies including the amazing interview with Ken Roden around his research paper he is doing which is FASCINATING.

That and tons of research, news, trends, and more in the free GTM AI Newsletter with some AI goodies, let me know if you want it!

View newsletter: GTM AI Podcast & Newsletter

Once again it is TIME for the GTM AI Podcast and newsletter sponsored by the GTM AI Academy and AI Business Network. This week we have a lot to get in

Open article: 12/4/2025: Why 88% AI Adoption Actually Means You’re Already Behind by Jonathan M K. • 6 min read

12/4/2025: Why 88% AI Adoption Actually Means You’re Already Behind

Want a deep dive into AI agents and how to use AI in companies? Today's podcast guest Elliot Garreffa goes into how he does it with sharing screen and all the goodness.

Most AI projects fail because companies are asking the wrong question.

They ask: "How can AI make this process faster?"

They should ask: "If I had this capability from day one, what process would I design?"

Here's what stood out:
The Real Problem Isn't the Technology

Companies say "we tried ChatGPT for content and it wasn't good"—but that's like judging a car by only using first gear.

The breakthrough happens when you stop bolting AI onto broken processes and start reimagining workflows entirely.

-Why Most POCs Never Scale
Elliot's team spends zero time touching technology in phase one. They talk to the actual teams, map workflows, identify root causes (not symptoms), and build business cases with real projected ROI.
Result? Systems that teams actually use instead of another forgotten pilot program.

-The Autonomy Trap
Fully autonomous AI isn't there yet. The companies winning are building rigid workflows with strategic human checkpoints—not because it slows them down, but because it's the difference between content that converts and content that screams "AI-generated."

His live demo compressed months of SEO agency work into a chat window conversation. Same research depth. Same strategic recommendations. Minutes instead of months.

The episode drops insights on:
-Why your CRO's diagnosis is probably wrong
--The "proof of value" framework that gets executive buy-in
---When to use no-code tools vs. going technical
----How MCPs are changing the game for workflow automation
-----If you're tired of AI projects that look impressive in demos but die in production, this one's worth your time.

Once again it is TIME for the GTM AI Podcast and newsletter sponsored by the GTM AI Academy and AI Business Network. We have a lot to go through with 

Open article: 12/10/25: AI Adoption Splits: Enterprise Dollars Rise While Competition Implodes Everything by Jonathan M Kvarfordt, MBA • 4 min read

12/10/25: AI Adoption Splits: Enterprise Dollars Rise While Competition Implodes Everything

I told ya.... Forward Deployed Engineers but for the GTM team...

GTM Engineer | VC Scout | GTM Engineering Newsletter: claymation.io

I recently caught up with Andreessen Horowitz on GTM in the AI era.

As GTM Engineer at Clay, I'm witnessing how buyers and selling motions are changing & adapting.

Partners Seema Amble and James da Costa summed up these changes really well in their recent post:

"𝘕𝘦𝘦𝘥 𝘧𝘰𝘳 𝘚𝘱𝘦𝘦𝘥 𝘪𝘯 𝘈𝘐 𝘚𝘢𝘭𝘦𝘴: 𝘈𝘐 𝘋𝘰𝘦𝘴𝘯’𝘵 𝘑𝘶𝘴𝘵 𝘊𝘩𝘢𝘯𝘨𝘦 𝘞𝘩𝘢𝘵 𝘠𝘰𝘶 𝘚𝘦𝘭𝘭. 𝘐𝘵 𝘈𝘭𝘴𝘰 𝘊𝘩𝘢𝘯𝘨𝘦𝘴 𝘏𝘰𝘸 𝘠𝘰𝘶 𝘚𝘦𝘭𝘭 𝘐𝘵.”

Some of my favorite, most useful takeaways to think about in GTM: 

💰 𝗧𝗵𝗲𝗿𝗲'𝘀 𝗺𝗼𝗿𝗲 𝗯𝘂𝘆𝗲𝗿𝘀 𝗶𝗻 𝗺𝗮𝗿𝗸𝗲𝘁, 𝗺𝗼𝗿𝗲 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝗹𝗲𝘀𝘀 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝘁𝗶𝗼𝗻.

It's no longer just about "what you do" and its becoming way more important to show "how quickly and reliably you do it it."

⏳  𝗕𝘂𝘆𝗲𝗿𝘀 𝘄𝗮𝗻𝘁 𝗔𝗜 𝗻𝗼𝘄, 𝘁𝗵𝗲𝗿𝗲'𝘀 𝘁𝗼𝗻𝘀 𝗳𝗼𝗿 𝗙𝗢𝗠𝗢 𝗳𝗿𝗼𝗺 𝗽𝗲𝗲𝗿 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗺𝗲𝗻𝘁𝘀.

This means that speed of deployment and value creation needs to be faster than ever.

According to another one a16z's surveys: 𝟳𝟬 𝗽𝗲𝗿𝗰𝗲𝗻𝘁 𝗼𝗳 𝗯𝘂𝘆𝗲𝗿𝘀 𝗿𝗲𝗽𝗼𝗿𝘁𝗲𝗱 𝘁𝗵𝗮𝘁 𝘀𝗽𝗲𝗲𝗱 𝗼𝗳 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝘄𝗮𝘀 𝗮 𝘁𝗼𝗽 𝗳𝗮𝗰𝘁𝗼𝗿 𝘄𝗵𝗲𝗻 𝗲𝗻𝗴𝗮𝗴𝗶𝗻𝗴 𝗔𝗜 𝘃𝗲𝗻𝗱𝗼𝗿𝘀.

🔒  𝗧𝗿𝘂𝘀𝘁 𝗵𝗮𝘀 𝗻𝗲𝘄 𝗻𝗲𝗲𝗱𝘀.

Software used to be just a conduit to something else (Airbnb helps you find houses to book), but now tech/AI is the product.

This means that trust needs go from "𝘄𝗲 𝗹𝗼𝗴 𝘄𝗵𝗮𝘁 𝗵𝘂𝗺𝗮𝗻𝘀 𝗱𝗼 𝗼𝗻 𝗼𝘂𝗿 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲" to "𝘄𝗲 𝗱𝗼 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸 𝗰𝗼𝗿𝗿𝗲𝗰𝘁𝗹𝘆 𝗮𝗻𝗱 𝗰𝗮𝗻 𝘀𝗵𝗼𝘄 𝗵𝗼𝘄."

📖  𝗕𝘂𝘆𝗲𝗿𝘀 𝗮𝗿𝗲 𝘀𝗲𝗹𝗳 𝗲𝗱𝘂𝗰𝗮𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗴𝗼𝗶𝗻𝗴 𝗱𝗲𝗲𝗽𝗲𝗿.

You need to come to the table with:

• A stronger, more thought out point of view
• A personalized demo that gets to a 'light bulb' moment faster
• Need to show tangible value earlier (before the traditional POC)

⚙️  𝗦𝗮𝗹𝗲𝘀 𝗿𝗼𝗹𝗲𝘀 𝗮𝗿𝗲 𝗯𝗲𝗰𝗼𝗺𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹

"Instead of understanding the people using your software, AEs need to understand the technical details of how agents will actually do the work of humans."

At Clay, we collapsed the AE & Solution Engineering roles to provide a better customer experience and to help with points 1-4. We're called GTM Engineers.

👷‍♀️  𝗙𝗼𝗿𝘄𝗮𝗿𝗱 𝗱𝗲𝗽𝗹𝗼𝘆𝗲𝗱 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗵𝗲𝗹𝗽 𝗴𝗲𝘁 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝘁𝗼 𝘃𝗮𝗹𝘂𝗲 & 𝗳𝗮𝘀𝘁𝗲𝗿 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀. 

AI-native success teams work directly with customers to design prompt logic and data integrations while passing feedback to GTM and product teams. 

Decagon calls this an Agent PM; 
Harvey calls it a Solutions Architect.
Clay calls them Growth Strategist

Check out the post for more insights in the comments.

As a musician and AI nerd, this is crazy. 

In the strongest sign yet that the world’s biggest record labels are embracing AI, leading AI-music platform Suno announced Tuesday that it has settled Warner Music Group‘s lawsuit over the use of its songs in Suno’s training data, and Suno and WMG are partnering on "next-generation licensed AI music."

"This landmark pact with Suno is a victory for the creative community that benefits everyone," Robert Kyncl, CEO of Warner Music Group, said in a statement. 

Read more here: https://lnkd.in/gAAgvaVj

62% of your pipeline is complete bullsh*t and you are wasting time on the wrong people. This is 

This is what came out of my conversation with Hussain Al-Shorafa CEO of Revic who just dropped one of the most uncomfortable truths about modern sales I've heard:

Your tech stack is lying to you. And everyone knows it except the people signing the checks.

Here's what actually happened when Hussain walked into a company using SixSense, ZoomInfo, and every intent data provider you can name:

"We told them 62% of the accounts you're pursuing are outside your ICP."

Their response? "Go pound sand. You're a nobody startup."

Four months later, the CRO is at dinner when he gets an email: they just lost a major deal. Hussain pulls up his phone and shows him: "You never had a chance with this account. Also, you have $40 MILLION in pipeline exactly like this."

The Pattern Nobody Wants to Admit
Listen to this episode if you wanna learn about:
• Why that deal you're counting on for Q4 was dead 6 months ago (and how to spot it)
• The job posting signals that predict buying behavior better than any intent data
• How one dinner conversation exposed $40M in fake pipeline
• Why your 15-year sales vet might be your biggest ICP problem
• The real reason playbooks don't transfer between companies (hint: it's not skill)

One of my favorite conversations and more in the full Newsletter on Substack, if you want to hear it, let me know in the comments!

HAPPY THANKSGIVING WEEK! I am truly, humbly grateful for all your support, insights, and how good you have been to me this last year of 2025. So many 

Open article: 11/26/25: Why AI Engineers Are Betting Against Unicorns (And What GTM Leaders Should Actually Build Instead) by Jonathan M K. • 6 min read

11/26/25: Why AI Engineers Are Betting Against Unicorns (And What GTM Leaders Should Actually Build Instead)

Your AI pilots aren't failing because of the technology.. take a wild guess why they fail? Wanna know? Let me send it to you...

It is time for the GTM AI Podcast and newsletter and I was fortunate to interview Ken Roden diving into his doctoral research at Temple University, and what he uncovered should fundamentally change how every GTM leader thinks about AI implementation in 2026.

Ken surveyed 200 professionals with statistically significant findings and the pattern he discovered explains why every headline is screaming about AI pilot failures. But it's not what MIT is telling you. It's not what the consultants are writing case studies about. And it's definitely not what you think.

The real blocker isn't employee resistance. It isn't inadequate technology. It isn't even change management.

I'm not going to spoil the actual finding here because you need to hear Ken walk through the data himself. But I will tell you this: If you're a GTM leader who thinks you understand how your team is using AI right now, you're almost certainly wrong. And that misunderstanding is costing you deals, talent, and competitive positioning every single quarter.

We also unpacked:
→ Why the people who think they're AI experts are often the least competent (and how to fix that) 
→ The "boring" use cases that are saving 20+ hours per week per rep (hint: it's not what's getting VC funding) 
→ Why your most confident AI users might be your biggest liability 
→ The AI Sandwich Model that's actually getting pilots to production 
→ What "AI fatigue" really means and why it's about to hit your team hard 
→ Why GPT-5's "Gronk problem" means you need to diversify your AI stack immediately

This conversation was one of those rare ones where I kept saying "wait, go back to that" because the implications kept cascading. The trust architecture piece alone will change how you think about rolling out AI across your org.

Not only that but I always deep dive into each weeks major AI releases that impact GTM leaders and professionals that you can read for free.. and I may give some other AI goodies in there too ;)

Want it? You know what to do... like
-Like this post
--Comment Your favorite Christmas song
---Repost cuz who doesn't wanna see lists of Christmas songs?

#GTM #ArtificialIntelligence #SalesStrategy #Leadership #GoToMarket

AI Engineers are betting against Unicorns, AI model updates and more, I break it down for you, want it?

HAPPY THANKSGIVING WEEK! 🦃

I'm genuinely grateful for all of you who've been part of this wild 2025 journey. Your insights, challenges, and late-night "hey, is this AI thing actually real?" messages have shaped everything I do.

This week's newsletter is... spicy. 

We're talking about why the smartest engineers in the room are betting against unicorns, how one CEO exposed $40M in fake pipeline at dinner (with receipts), and the uncomfortable truth about why your tech stack might be lying to you.

The research papers alone took me down a rabbit hole about inverse unit economics that will change how you think about AI pricing forever. I've already loaded everything into a NotebookLM for you to explore deeper.

Three things that shocked me this week:
• That $20B valuation on 0.2% market share (the math is brutal)
• Why Equifax and TransUnion have nothing in common (wait, what?)
• The real reason playbooks don't transfer between companies

Whether you're cooking turkey or closing deals this week, this one's worth your time.

Because sometimes the best insights come when everyone else is distracted.

If you want the goods, then do the following:
1-Like this post
2-Comment TURKEY
3-I will send Post haste!

Or get it here: https://lnkd.in/g9_8Bv7M

And have an amazing holiday!

taplio

The Battle

Eddie Reynolds

Jonathan M K.

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Performance ScoreEddie Reynolds's LinkedIn Performance

Performance ScoreJonathan M K.'s LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Eddie Reynolds

Jonathan M K.

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);}Eddie Reynolds's LinkedIn Performance

Performance ScoreJonathan M K.'s LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreEddie Reynolds's LinkedIn Performance