The Growth Operating System turns AI into revenue.
Not output. Producing got cheap and nothing ships faster, because AI never decided what a company is allowed to say. We build the system that does, with the team that will run it.
Trusted by teams and leaders at
"Grace did a great job providing an overall framework for how to set goals for AI projects, define workflows, and establish governance. She combined this with live demos on building agents for surfacing prospects that match your ICP."
Craig PremoDirector of Marketing, RosmanSearch"Grace is probably one of the best presenters I've learned from. I attend a lot of sessions just as background, and Grace's sessions always draw me in."
Logan Mathew JungAnalytics Manager, Meta Business Services, Meta"Grace is an inspiring leader with a real gift for making complex ideas feel clear and approachable. Whether you are just starting out or looking to take things to the next level, her guidance and insights are incredibly valuable."
Toey ChitmanasakRegional CRM and Data Manager, Michelin"Hands-on and interactive. Good at showing that it is possible to build a stable context structure and then interesting content from small everyday snippets like transcripts."
Maibritt Harritz GrosenChief Operations Officer, Clearwater"This course put structure around things I'd been doing by feel. Grace's frameworks build on each other; every module sharpened the last, and she makes strategy and AI in marketing converge in a way that's practical."
Tania MillanSr. Manager, Digital Experience and Strategy, Forum Health"Really useful course, whether you are new to AI agents or already have some experience. It meets beginners where they are and still gives intermediate users real depth. You walk out with working agents you can refine and start using right away."
Geraldina Scarascia OlsonFractional Marketing LeaderProducing got cheap. Shipping did not.
Four sentences we hear on almost every call. Every one of them describes the same thing: the bottleneck moved, and nobody moved with it.
Ask three people what we do and you get three answers.
Every one of them is defensible and no two are the same. Buyers compare notes, and what reads internally as nuance reads externally as a company that has not decided.
I rewrite almost everything the AI produces before it goes out.
It saves the writer time and costs the reviewer theirs. Net, the team is busier and nothing reaches a buyer any sooner.
Pipeline goes quiet in the middle and we find out at quarter end.
Nobody watches the long middle. By the time it gets attention it is too late to act on, and the forecast was wrong for weeks.
Everyone uses AI, and none of it compounds.
Individual drafting from a blank context, every time. Nothing written this quarter makes next quarter cheaper, and two people describe the same product two different ways.
None of that is a discipline problem. It is no longer making the work, it is the queue in front of the work: the approvals, the claim with three versions and no owner, the reviewer whose head holds the only copy of what is true. AI made the first draft free. It did not decide what a company is allowed to say.
Find the gap first. Build only what closes it.
Nothing gets built before we know what is actually slowing you down. Four steps, in this order, every time. Open any of them to see what it produces.
Understand the business, the gaps, and the priorities
What you are measured on this quarter, what is in the way, and which of it actually matters. Priorities before process, because a faster version of the wrong work is still the wrong work.
One page your leadership already agrees with: the number that matters this quarter, and the two or three things standing in front of it.
Audit the growth system, end to end
An operational audit of how growth and marketing actually run: how work enters, who touches it, where it waits, and what it costs in hours before anything reaches a buyer.
Your workflow drawn out with the waiting time on it, which is usually the first time anyone has seen the whole thing on one page.
Find the bottleneck
One constraint usually sets the pace of everything else. Naming it is what stops a year being spent optimizing the parts that were never the problem.
The one constraint, named, with the evidence next to it. Often it is not the step anyone expected, and that is the point of measuring rather than guessing.
Decide what actually closes it
An agentic AI workflow, straightforward automation, or something that is not AI at all: a process change, a decision nobody has made, or a person. We will say which, including when the answer is that you do not need us.
A recommendation with an owner and one number against it, in writing. If the honest answer is that AI is not the fix, that is what the recommendation says.
Four things AI has to know before it can produce anything worth shipping.
Most of the pieces already exist somewhere in the stack. Nothing joins them, and the one that needs a human decision has never been written down. That is the work.
What the company sells
The claim set, with a source, an owner and a review date on every line.
Who it sells to
The segments, the buyers inside them, and the story each one needs.
What it is allowed to say
Approved, unapproved, and the difference, written down rather than held in a reviewer’s head.
How it reaches market
The workflows that carry all three out the door without a queue in the middle.
Every capability is the same four boxes.
This is the teaching claim the whole system rests on. Learn the shape once and the fifth layer is an afternoon rather than a project. Hover any step to see what it looks like on the day.
- Input
Approved truth
The knowledge layer, plus your own systems. Never a blank context.
On the dayOne priority account, its history, and the proof your team has already approved.
- Agent
The volume work
Inside boundaries you set. It drafts and scores, it does not decide.
On the dayFive roles mapped, a narrative and a first touch drafted for each, in minutes.
- Gate
A named human
Reviews before it acts. Operator, Reviewer, Approver, named people.
On the dayRed pen on the pack. What is right, what is wrong, what is missing.
- Output
Work, and one number
Something that ships, and the single measure it reports.
On the dayThreads out per seat, and stakeholders engaged per account on the scorecard.
Nine layers, one shape.
In build order. Open any of them, and the workflow underneath is the same four boxes every time, which is the point of teaching it once.
The context layer
The floor everything else stands on. Positioning, ICP, segments, proof, objections, and the claims the company is allowed to make, structured so a machine can read them rather than written as prose for a human.
The two at the bottom are built first and they are not optional. Everything above them writes from what they hold, which is why a team that starts at content is rewriting output six weeks later and a team that starts at the floor is not.
Where it sits in the week.
A capability nobody has time for is a capability that stops. The loop goes in the team’s own calendar before anyone leaves the room.
What the numbers say to work on this week. The scorecard decides, not the loudest request.
The system produces, a human judges. This is where most of the volume work lands, and where the gate does its job.
What shipped, what landed, and what returns to the knowledge layer as evidence rather than opinion.
Definitions reviewed, account tiers reviewed, and anything that stopped earning its place gets retired.
Three questions, three hats, on every capability.
Before anything runs: what does this produce and what does it not touch, who reviews the output before it acts, and what happens when it is wrong.
The Operator
Runs the capability day to day. Knows what it produces and what it deliberately does not touch.
The Reviewer
Checks the output before it acts. Not a rubber stamp: the person whose judgment the work actually needs.
The Approver
Releases it. Answers for it when it is wrong, which is the question that makes the other two roles real.
On a small team one person often wears all three. Name that explicitly rather than leaving it implied. Skip it and the result is not automation, it is expensive shadow work.
Three things, and most teams already have two of them.
No stack is sold here and none is mandated. Every team arrives on something different, and the architecture is the same either way.
The CRM and the databases
Pipeline state, account history, the lead list, whatever already holds the record. Capabilities read from the systems a company already runs and write back to them. Nothing gets migrated.
An agentic workflow builder
Whatever puts a model behind a schedule or a trigger, pulls from those systems, and holds the result at a gate. Several do this well and they change every quarter, so we teach the shape rather than the buttons.
A named human on the team
The part nobody can buy. Three hats on every capability, held by people with names rather than roles in a policy document.
One system, built with the team that will run it.
The growth operating system that turns AI into revenue. There are two ways to pay for it, and both leave it running inside the company, in its own stack, whether or not anything is still being paid.
Boardroom
Rolling monthly, pause anytime. Team Training includedOne growth system built, launched, iterated and refined every month, together with the team that will run it. Month one is the training. Every month after runs the same four weeks: build, launch, iterate, refine.
- Team Training included, in the first month
- Unlimited requests queued, one active build at a time
- A working session every week, with the people who own it
- It speeds up: build five costs a fraction of build one
Team Training
One off, private to one team, scoped to the groupThe team architects the growth system on its own accounts and builds the first working piece live, on a real account somebody in the room already knows. Nothing is practised on sample data, so what gets built is running on Monday.
- The system architected on the company’s own pipeline
- One working piece running before the day ends
- A scorecard and a 90 day build order, in writing
Team Training costs $4,500 on its own, and it is included in the first month of Boardroom at $4,950.
Three doors, and all three get paid before anything ships.
Tool vendors are paid on seats. Trainers are paid on attendance. Consultancies are paid on delivery. None of them is measured on whether the work reaches market, which is why all three can succeed on their own terms while nothing ships any faster.
Buy another tool
Every vendor with a brand voice setting sells storage for a decision somebody still has to make.
Send the team on a course
They come back informed, motivated, and returning to a system that has not changed.
Hire a consultancy
They build it, it works, and then they leave with the part that made it work.
Not every gap is reachable by a growth system.
A real share of any revenue gap sits behind pricing, product, market timing and territory decisions that no system touches. Those get named, with owners, and the system is held accountable for everything else. Saying it in August is what makes the scorecard credible in December.
One system, read by every function.
The same objection turns up in a landing page, a sales follow-up and an onboarding email. Today that is three answers, written by three people, in three tools. One source is the only structure where it is the same answer in all three places without anyone coordinating.
Marketing
What changes on Monday?
Campaign briefs become asset sets that ship instead of getting rewritten. Asset five is as good as asset one, because neither one is guessing what the company is allowed to claim.
Sales
Why does this reach us at all?
Every rep answers the top objections the way the best rep does, from week one. The approved answer, the cleared proof, and the pricing rules are the same ones marketing writes against.
Product marketing
Does this replace what I already wrote?
It enforces it. The messaging that exists stops living in a document nobody opens and starts being the thing every tool reads before it writes.
You own the system, from day one.
Yours on handover
Every prompt, context file, and workflow sits in your own workspace. There is no platform of ours to stay subscribed to in order to keep using what you built.
Hiring it is fragile
A senior GTM hire is roughly $180,000 loaded, three months to find, six to ramp, and the capability leaves when they do. Most companies in this position have already run that experiment.
Outsourcing it does not compound
An agency builds the campaign, keeps the method, and re-charges for the next one. The knowledge layer that makes the second segment cheap never forms.
A human governs every send
A named Operator, Reviewer, and Approver on every capability. Nothing publishes itself, in the room or afterward.
The asset that makes account two cheaper than account one is approved, structured, reusable truth, and it only accumulates if it lives inside your company.
What leaders are saying
Growth, marketing, and operations leaders who built the system themselves. The longer stories sit behind these: what each team was stuck on, what they built, and what actually moved.
"Grace did a great job providing an overall framework for how to set goals for AI projects, define workflows, and establish governance. She combined this with live demos on building agents for surfacing prospects that match your ICP."
Craig PremoDirector of Marketing, RosmanSearch"This course put structure around things I'd been doing by feel. Grace's frameworks build on each other; every module sharpened the last, and she makes strategy and AI in marketing converge in a way that's practical."
Tania MillanSr. Manager, Digital Experience & Strategy, Forum Health"Hands-on and interactive. Good at showing that it is possible to build a stable context structure and then interesting content from small everyday snippets like transcripts."
Maibritt Harritz GrosenChief Operations Officer, Clearwater"Grace is an inspiring leader with a real gift for making complex ideas feel clear and approachable. Whether you are just starting out or looking to take things to the next level, her guidance and insights are incredibly valuable."
Toey ChitmanasakRegional CRM & Data Manager, Michelin"Really useful course, whether you are new to AI agents or already have some experience. It meets beginners where they are and still gives intermediate users real depth. You walk out with working agents you can refine and start using right away."
Geraldina Scarascia OlsonFractional Marketing Leader"Grace is probably one of the best presenters I've learned from. I attend a lot of sessions just as background, and Grace's sessions always draw me in."
Logan Mathew JungAnalytics Manager, Meta Business Services, Meta"For the past few months, Grace has been helping me launch my data science consulting business. She has shown me practical ways to get in front of customers and clearly communicate the value I provide. What stands out is how structured she is. She doesn't hand you a pile of ideas and wish you luck. A few months ago I had no clear path for turning technical credibility into a client-facing business. Today I have a marketing plan, a public presence, and a pipeline of opportunities."
James MottFounder and CEO, James Mott Consulting"Grace is over-the-top knowledgeable. I highly recommend her training. This one specifically would be beneficial for any team to start building out their automation, workflows and agents. I will be introducing this to our internal social media team to help their overwhelm on time."
Sue RandallPrincipal and Creative Director, Only Eye Design"Grace is an amazing mentor with a deep understanding of AI and its applications. Her insights into using automation for marketing workflows and integrations have been invaluable to me."
Martha CruzMarketing Manager, SPI BorescopesWhat you are actually thinking
A license is a tool. This is the operating model that decides what to build for your pipeline, which approved truth it reads first, who reviews it before it acts, and which number it reports. It runs on whatever models and tools you already pay for. Tools change every quarter. The model does not.
The honest question back is: what is still running from it? A generic session teaches the tool on someone else’s examples. This builds one capability live on a real account of yours, hands it to a named owner, and attaches one number to it before anyone leaves the room.
Yes, and we would rather say so than pretend. The difference is whose truth it starts from and who decides. Every capability reads your approved knowledge layer, and a named human approves before anything moves.
Then the capability is in the system and the library, not in the person. That is the whole reason a team of leaders builds it rather than one, and why everything sits in your own workspace.
Ten more on the Team Training page.
The tools are not the hard part.
Deciding what is true about a company, writing it down, and building the thing that carries it to market is the hard part. That is the work, and the team does it with us.