Become the finance partner product teams can’t ship without.
Coaching and hands-on training for Product Finance, Cloud & AI Finance, and FP&A roles — from unit economics and capacity planning to the final-round case interview.
Free consult · No obligation · Reply within 48 hours
AI assistant: unit economics per 1M tokens
- AWS
- Google Cloud
- Microsoft Azure
- Snowflake
- Databricks
Who the programs are for.
Wherever you’re starting from, you’ll leave able to model a product, explain its economics and hold your own with engineering and product leads.
Breaking into Product Finance
From accounting, banking, consulting or corporate FP&A into a role that sits beside product teams.
Typical targets: Product Finance Analyst, Sr. Financial Analyst
Moving into Cloud & AI Finance
Learn the economics most training skips: usage-based revenue, capacity, GPU and inference cost, security and AI go-to-market.
Typical targets: Cloud Finance, AI Infrastructure Finance, FinOps
Leveling up in FP&A
For analysts and managers ready for senior scope: driver-based planning, strategic partnering and leading reviews.
Typical targets: Finance Manager, Sr. Manager, Director
What hiring managers actually test for.
Six modules, each ending in a case you model, present and defend — the same way you will on the job.
Cloud usage & revenue modeling
Consumption revenue, usage drivers, commitment burn-down and cohort-based forecasts.
You build: Build a 12-month consumption revenue forecast from customer usage and committed-spend data.
Forecasting, variance & scenarios
Annual plans, quarterly forecasts, month-end close, variance bridges and bull/base/bear scenarios.
You build: Bridge a quarterly forecast miss back to plan and present bull, base and bear cases.
Capacity & CapEx planning
Region and data center builds, server and GPU supply vs. demand, utilization and CapEx returns.
You build: Size GPU and storage capacity for a new region and calculate the CapEx payback.
Deal & discount economics
Private pricing agreements, commit-based discounts, deal P&Ls and margin guardrails.
You build: Model a three-year private pricing deal and recommend whether to approve it.
Unit economics & launches
Cost to serve, gross margin by service, and business cases for new features, regions and products.
You build: Build cost to serve and gross margin by tier for a new AI feature launch.
Partnering & interview readiness
Business reviews, written narratives, SQL-backed analysis, case studies and modeling tests.
You build: Write a one-page business review and complete a timed case interview.
Go deep on the business you want to support.
Pick one alongside the core modules. Each comes with its own case exercise.
GenAI & AI infrastructure
AI go-to-market solutions
Cybersecurity
Core cloud infrastructure
Programs and pricing.
Not sure which fits? Book a free consult and we’ll recommend one — or tell you honestly if you don’t need us.
Interview Sprint
For candidates with interviews already on the calendar.
- Mock case interview with written feedback
- Timed modeling test & walkthrough
- Behavioral story review
- Resume & LinkedIn teardown
Product Finance Cohort
The complete curriculum, taught live with a small group.
- All six modules, taught in weekly live sessions
- Real case exercises & model templates
- Graded capstone presentation
- Interview prep & alumni community
1:1 Coaching
Personal guidance for career moves and ramping in a new role.
- A plan built around your target role
- Career transition strategy
- First-90-days support in a new job
- Async feedback on your models & decks
What happens after you reach out.
Free consult
A short call on where you are and the role you want.
Your plan
We map the skill gaps and the program that closes them.
Train on real cases
Build models, present them and get direct feedback.
Land & ramp
Interview with confidence, then hit the ground running.
Augustine Archibong
Founder & Lead CoachI’m a Finance Manager for AWS Object Storage, where I forecast new features, regions and products, plan capacity, and support cloud deals and private pricing. Nearly a decade across accounting, audit, FP&A, strategic planning and analytics has taken me from engineering school in Nigeria to banking and audit in Lagos, an MBA in St. Louis, and now Seattle. Each stop taught me to see a business a little differently.
“The habit I teach: check whether the numbers actually back up the story.”
Views shared here are my own and not those of my employer.
What clients say.
My coach gave me a clearer framework for evaluating growth and investment trade-offs. The examples made the concepts easy to grasp going into my final interview loop.
The course helped me connect the operating drivers in our cybersecurity business to the financial story. I’m far more confident explaining the assumptions behind our forecasts, and when we miss, I can explain the variance clearly.
The course gave me a practical framework for valuing different cloud workload types and explaining the key drivers behind them. What stood out most was how it tied the numbers back to business strategy.
Surnames are abbreviated for privacy.
See what you’ll build.
Every module ends in a deliverable you could put in front of a hiring manager. These samples use fictional companies and numbers.
12-month cloud revenue forecast
Built from customer usage and committed-spend data, with a variance bridge that explains the gap to plan.
AI unit-economics model
Cost per 1M tokens, gross margin by plan tier, and what happens to margin when inference costs fall 30%.
Investment recommendation deck
A six-slide case for launching a new region: demand, CapEx, payback and a clear go or no-go call.
What’s the difference between Product Finance and FP&A?
FP&A typically owns company-wide planning, budgeting and reporting. Product Finance sits closer to specific products — pricing, unit economics, investment cases and roadmap trade-offs — and partners daily with product and engineering leaders.
Why focus on Cloud & AI finance?
They’re fast-growing areas with economics most finance training skips: usage-based revenue, capacity and CapEx, GPU and inference costs, private pricing deals, and new AI and security products.
Do I need a finance background?
Not necessarily. The programs are built for people already working in finance, accounting, banking or consulting, and for strong analysts moving over from product, engineering or data roles. If you’re newer to finance, we’ll use the free consult to check your fundamentals and recommend the right starting point, which may be a few 1:1 sessions before you join a cohort.
Is it live or self-paced?
Both. Lessons and model templates are self-paced, so you can fit them around work. Live sessions are where you present cases and get feedback. Coaching comes two ways: in small groups as part of the cohort, or 1:1 when you want a plan built around your own goals.
What if it’s not the right fit?
That’s what the free consult is for: we’ll only recommend a program if we think it fits your goals. If something isn’t working once you’ve started, tell us early and we’ll find a fair solution, such as switching formats or moving you to a later cohort.
Your next role starts with one conversation.
Tell us where you are and where you want to be. We’ll give you an honest read on the gap — and the fastest way to close it.