Developer Relations, PrismML
Expertise into products people pay for


If you do knowledge work for a living, a large share of your week is one judgment call made over and over with slightly different inputs: triage the inbox, categorize the request, decide how the company should answer, write it in the house voice, log it, report on it. Nicole used to bill that kind of work at $85 an hour for about twenty-five hours a week, roughly eight thousand dollars a month of labor that a general-purpose model can already do most of, and that a small specialized model might do better and cheaper. This cohort exists to find out whether that's true for your job, on hardware you control, and what it would be worth if it is.
I'll be straight about what this is: an experiment with a method, not a guaranteed outcome. I own an NVIDIA GB10 and I've spent about $4,000 of my own money renting frontier models, so I know what each rung costs, but I don't yet know how far a small model trained on your domain gets on Apple Silicon or the GB10. We find out together over three Fridays, with a benchmark that's allowed to tell us no. If the answer is no, you leave knowing it with the numbers attached, which is a result I'd pay for.
By the end you'll have a benchmark for your job, a small model measured against a big one, and a cost sheet that says what it's worth.
Write down the hardest cases in your domain, the ones where a wrong answer actually costs something, and turn them into a test set.
Run a general-purpose model against it first, so you have a baseline that isn't a vendor's benchmark.
Know, with evidence rather than a feeling, when a model gets your job wrong.
Tune a small model on your domain, on your laptop or on the GB10, and compare it with the general model on your own benchmark.
Read the gap in both directions, including the cases where the small model is worse and what that means for your decision.
Understand what the hardware actually buys you before you spend money on it.
Decide in week one whether you're cutting the cost of this work or protecting the data in it, because those are different buyers.
Put a monthly number on the model next to what a person costs to do the same work, at each rung from rented to owned.
Write the budget cap and the guardrails that keep the bill from surprising you.
Finish with a one-page cost sheet and a plan: sell the model, use it in your own practice, or keep it in-house.
Make the case to the room the way you'd make it to a client or a board, with Nicole running the pitch round.
Know which of the three paths fits you and what the first step on it costs.

Owns a GB10, has spent $4,000 renting models, and prices AI work live.

Went from billing hours to owning what she produces; runs the pitch week.
Knowledge workers whose week is mostly one repeatable judgment, and who would rather sell the model than keep selling the hours.
Founders and domain experts who know a corner of healthcare, education, or public infrastructure better than any model does.
Builders who can already run and fine-tune a model but have never had to defend its unit economics or name who would pay for it.
Bring one job you know well and a laptop; most recent ones can run a small model, and I run the heavier jobs on my GB10.
Live sessions
Learn directly from Jai Bhagat & Nicole Mercede in a real-time, interactive format.
Three live Friday sessions
Seventy-five minutes each with Jai and Nicole, run as I do, we do, you do: we price and build one job together, then you work on yours with the room watching.
A benchmark and a cost sheet you keep
Templates for both, filled in with your own job during the sessions, so the artifacts leave with you and keep working after the course ends.
Pair feedback every week
You swap benchmarks and cost sheets with a partner in a different field and take each other's assumptions apart, because that is where most of the learning happens.
Honest results
If your small model loses to the big one on your benchmark, we say so and work out what the gap means for your decision.
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
3 live sessions • 13 lessons • 3 projects
Nov
20
Nov
27
Live sessions
1-2 hrs / week
Fridays at noon Eastern on Nov 20, Nov 27, and Dec 4, run as I do, we do, you do: we price and build one job together, then you work on yours.
Fri, Nov 20
5:00 PM—6:00 PM (UTC)
Fri, Nov 27
5:00 PM—6:00 PM (UTC)
Fri, Dec 4
5:00 PM—6:00 PM (UTC)
Build work on your own job
1-2 hrs / week
Writing benchmark cases, running the models, and filling in the cost sheet, all on the job you brought with you.
Async materials
1-2 hrs / week
Short readings and recordings before each session, so the live time goes to building and pair feedback instead of lecture.
Maven for Teams
Reimbursement
Get your company to pay
Everything L&D needs: email template, receipts, and certificate of completion.
Get reimbursedTeam discount
Learn with your teammates
Save 20%+ when 2 or more teammates enroll in the same cohort.
Save 20%+ with a teamPrivate cohort
Run a cohort for your org
A dedicated cohort with a custom schedule and curriculum, tailored to your team.
Book a private cohort$801
USD