Episode 17
The GTM Cheat Code: Partner-Led Growth &
AI That Actually Work With Justin Gray
Justin Gray
He is a serial entrepreneur and operator who founded and successfully exited Lead MD, a leading marketing and revenue operations consulting firm with 64 employees. He is now co-founder of In Revenue Capital, which invests in seed to early-stage companies and takes an “operator immersive” approach, providing hands-on go-to-market guidance alongside founders. He is also the author of “Go to Market Cheat Code: The Secret to Unlock B2B Growth.
Justin Gray on AI in GTM, Phantom Equity, and Why Partnerships Beat Cold Outreach
Introduction
Justin Gray built LeadMD from a $7,500-a-month retainer business into a 64-person consultancy, then sold it to private equity. Half the exit value went to his employees through phantom equity, a program he started years before the sale closed.
On this episode of Ops in Motion, Shiv and Kawal sat down with Justin to talk through three things RevOps and marketing ops teams are dealing with right now: what AI is actually doing inside GTM teams versus what people claim it’s doing, how he built a people-first culture that produced a 20-30% success rate for phantom equity payouts across his career, and why his new book argues partnerships beat outbound in a market where trust is harder to earn.
Justin now runs InRevenue Capital, where he and his partners write $1M-$3M checks into seed and early-A startups and then operate alongside the founders. This isn’t passive investing. It’s the same operator-led approach he used at LeadMD, applied to a portfolio instead of one company.
Who should read this: RevOps leaders, marketing ops managers, and founders trying to figure out where AI actually creates value in go-to-market versus where it’s still just noise.
Key Takeaways
- AI delivers clear value on operational friction: reporting, pipeline visibility, and data access. It struggles with the parts of GTM that are judgment calls, not workflows.
- Most companies don’t have an org-wide AI strategy. They have scattered departmental experiments, which is why the value isn’t compounding.
- Data has been treated as an administrative afterthought for 20 years. That’s the real bottleneck for AI, not the models themselves.
- Phantom equity gave LeadMD’s team a stake in the outcome without triggering a tax event at grant, and it kept the entire company focused on one goal: the exit.
- Partnerships work because they borrow trust that already exists between a buyer and a vendor, instead of trying to build that trust from zero.
Building LeadMD: People, Not Product
Justin started LeadMD in 2011, right as Marketo and Eloqua were fighting for the marketing automation market. Companies wanted the technology but had no idea how to run it. Lead scoring, lifecycle automation, nurture sequences: all new concepts at the time. That gap is what built the business.
He’s direct about what makes a services business different from selling software: the product walks out the door every night. LeadMD’s edge wasn’t a platform. It was retaining senior people long enough for them to become genuinely good at the work.
The mechanism he used was phantom equity, granted to employees as they took on more responsibility, with no tax liability at the time of the grant and no vesting cliff outside the eventual exit. By the time LeadMD sold, the company had 64 employees, some with a decade of tenure, and 50% of the exit value went to them.
Key insight: Justin also built structured career paths he called “tours of duty,” two-year commitments where employees defined what they wanted to learn and where they wanted to go next. One employee used the program to prepare for a career change into nursing while still on staff.
“The greatest reward for being great at your job is more work. Your best people carry the most, so you owe them a real stake in the outcome.”
— Justin Gray
Where AI Actually Helps in GTM (and Where It Doesn’t)
InRevenue Capital ran a study across its portfolio and the broader market, published as “Cheat Codes” on their site. The finding: AI is delivering the most value where the work is binary, like code. Engineering teams can multiply output because code is a discipline you can quantify and QA.
Go-to-market doesn’t work that way. Crafting a message, reading a buyer, deciding when to push and when to wait: none of that is a solved discipline. That’s why AI adoption in GTM looks scattered. Most companies Justin’s team spoke with had no company-wide AI strategy. They had a marketing team on one tool, a sales team ignoring it, and individuals running their own personal subscriptions with no shared plan.
Where AI is working cleanly right now is operational friction: reporting, pipeline evaluation, and getting to unstructured data without waiting on a new platform purchase or a database rebuild. That’s a real, immediate win. Stringing together the full buyer journey across marketing, sales, and customer success into one coherent AI-assisted strategy is a much harder problem, and most organizations haven’t cracked it.
Key insight: Justin’s core warning is that AI is confidently wrong when the underlying data is bad. It won’t tell you it’s guessing. It will just answer.
“Just because there’s an output, don’t automatically trust it. AI is incredibly optimistic, and it will always give you an answer.”
— Justin Gray
Kawal made a related point during the conversation: the quality of any AI output depends entirely on what’s feeding it, both the prompt and the state of the CRM behind it. Garbage in still means garbage out, no matter how good the model is.
Partnerships Over Cold Outreach
Justin’s book, “The Go-To-Market Cheat Code: The Secret to Unlock B2B Growth,” argues that as automation gets commoditized, trust becomes the scarce resource. His answer is partnerships: not logo-level agreements, but relationships built at the individual level with people who already have your buyer’s attention.
He used Marketo as the example. LeadMD didn’t just sign a partner agreement with Marketo. They put former CMOs and VPs of marketing on staff so they could speak directly to the buyers Marketo’s sales reps were struggling to close, buyers who cared about total cost of ownership and organizational change, not product features. That relationship produced over 6,000 Marketo implementations across LeadMD’s lifetime, including white-label work done under the Marketo and later Adobe name.
Key insight: The mechanism is simple. Give value before asking for anything in return, and do it at a level specific enough that it solves an actual problem for the person you’re partnering with.
“I don’t just need to serve the business. I need to serve the person, and I’ll give something before I ever expect to get something back.”
— Justin Gray
Action Items
Audit where AI is actually being used across your marketing, sales, and customer success teams before assuming there’s a shared strategy. There probably isn’t one.
Fix your data capture before investing further in AI tooling. If your CRM is an administrative afterthought, your AI output will reflect that.
Treat every AI output as a draft, not an answer. Check it against the underlying data before you act on it.
If you’re building or evaluating a partner program, look past the logo-level agreement and ask whether the relationship exists at the individual, day-to-day level.
If retention is a problem on your team, look at equity or profit-sharing structures tied to a clear outcome, not just annual raises.
FAQs
What is phantom equity?
A compensation structure that grants employees a stake in a future exit or change-of-control event without creating a tax liability at the time of the grant. There’s no vesting cliff outside the liquidity event itself.
Why does Justin Gray say AI struggles with go-to-market?
Because GTM decisions, like how to message a buyer or when to advance a deal, are judgment calls shaped by context that changes daily. AI handles binary, rules-based work like code and reporting far more reliably.
What is InRevenue Capital?
A venture firm founded by Justin Gray that invests $1M-$3M in seed and early-A startups, then works alongside founders operationally rather than just advising from the board.
Talk to Digital DI Consultants
If your team is dealing with the same problem Justin describes, scattered AI experiments with no shared data foundation, that’s a RevOps and marketing operations problem before it’s an AI problem. Talk to our team about building the data and process foundation your GTM strategy actually needs.
