Build-With-Me
The workflow ran on the course data and broke on yours. Your screen, your data, 1 on 1, until it holds.
Why it stalls
That is not one problem. It is 4, and they arrive looking like one.
Getting the AI to actually produce the thing, and getting the dashboard to sit somewhere people will look at it.
Pulling from systems that disagree, and cleaning them so the join is honest rather than just tidy.
Which number belongs there, how it is built, and what it is supposed to tell whoever reads it.
Which steps the AI takes, in what order, what gets checked, and who signs off. One good prompt is not a workflow.
Your IT team owns the first. Your analyst owns the second. Your accountant owns the third. Nobody owns the fourth, or the seams between them, and that is where it breaks.
Why a course does not finish the job
A good course gives you the concepts and shows a dashboard being built. Then it meets your own data and breaks. Nobody checks whether each step was done right on your numbers. That is the check you are buying here.
Five moments when the format is the problem, not the teaching.
A board meeting, a month-end, a project due. It gets compressed into one session on the actual work.
The training made sense. Assembling it on real data is where it stalls. That is the usual reason people quit, and one session clears it.
Courses teach on textbook data. Here the live forecast the boss is waiting for comes to the session, or the close that will not reconcile.
General AI finance training goes shallow here. This is the part I have done for twenty years, at Fortune 500 scale.
One to one, and the screen stays yours. The recording goes to you and to nobody else, and your figures are never used as an example anywhere.
Two ways in
Both are coached: you hold the pen, I guide it live. Open the one that fits for price, scope and how it runs.
Coached: one session
The forecast that will not reconcile, the output nobody can defend, the workflow that ran on the course data and broke on yours. You share your screen and build, I ask the questions that stop it breaking later, and you leave with it working and the reason it broke.
What to bring
How it runs
I do not read files beforehand, write a review, or build it for you. A written look at the numbers is a Focused Diagnostic. If the output is wrong because the data underneath it is wrong, it shows early and the session turns to the data.
Booked and paid in one step. Reschedule free up to 24 hours before.
Coached: the full build, 4 sessions
One workflow, built on your data, tested against numbers you already trust, and handed over with the summary your board or your CFO can read. You keep it running afterwards, because your hands built it.
The four weeks, in this order
Where it ends
How it is bought
Between sessions you build. There is no support channel between sessions, which is what keeps the price where it is.
Which one fits? The free 30-minute review settles it.
Who is on the other side
I have sat in the CFO chair, and at 3M I ran inventory operations that cut non-moving inventory from 8.5% to 5% while holding a 100% fill rate through the semiconductor shortage. I build production AI workflows for closing, variance and inventory analysis.
So a session is not a prompting lesson. It is a working review of what you are building, by someone who knows what a controller, an auditor and a board will each do to it.
For a team, or a room
The same method taught to several people at once: a finance team building its first AI workflow, a leadership group, a conference. Hands on, on real-shaped data, with something working at the end.
What gets built in these sessions
21 drivers and the logic between them, no dataset behind it. Capacity authorised in spring for a summer nobody can predict, with every case already run.
Open itOne closing workflow run 3 ways, side by side. The workflow file and 2 datasets are included.
Open itA file can pass every technical check and still be worthless. How to notice it, prove it, and know who fixes it. 8 pages.
Read itIn this AI era, where many people are talking about what AI tools can do, Sharon is actively building with them ... diagnostic frameworks that turn raw inventory data into answers a CFO can actually defend. Her systems reflect real financial judgment, not just technical skill.
She doesn't critique outputs, she diagnoses the system behind them: backtesting, train/test splits, auditability. That's the rigor senior finance professionals actually need.
Albert LeeFounder, FP&A advisory practice. FCPAI've seen how she breaks down technical AI and data concepts into something finance professionals can actually apply. Her blend of operational finance background and AI fluency is rare, and it makes her advice both credible and immediately useful.
Charles T.CEO, intellectual property technologyShe has great ability in distilling complex subject into practical workflow and application.
Emily MooreSenior finance and FP&A leader. CPA, PMPShe brings positive energy, strong subject matter expertise, and practical AI insights to every interaction. Her feedback was always constructive and actionable, helping participants elevate their thinking.
Sharon is knowledgeable and approaches a situation from a real-world perspective.
Sharon has deep expertise in AI and she teaches it with ease, giving students tips without giving a complete solution from the start. This approach motivated me extremely to come up with my own solution.
Her coaching style encourages critical thinking, problem-solving, and genuine understanding rather than reliance on prescribed answers. She creates an engaging learning environment that consistently challenges and inspires students to reach a higher level.
Sharon's guidance was exceptional. She provided thoughtful, detailed reviews of my project submissions. By expertly identifying both my strengths and specific areas for improvement, she helped me take my AI skills to the next level.
She provided thorough, insightful feedback on our projects and demonstrated deep expertise in the subject matter. Highly valuable, helping me improve both my work and my understanding of the concepts.
I received very thorough feedback that was an appropriate mix of positive and constructive: direct and actionable as well as completely fair and on point.
Sharon is an excellent hands-on instructor. Her coaching is amazing and her AI skills are incredible.
Sharon was a great coach, providing comprehensive feedback on my assignments.
She offered insightful and timely responses to student queries during live sessions, and offered 1:1 support to all students within the cohort. She is knowledgeable, supportive and humble: a rare combination.
Sharon helps businesses maximize their cash flow through scenario planning and forecasting, using POs, inventory, cash and cash flow assumptions. She has made this turnkey with AI powered tools: custom agents, dashboards, and monthly workflows. You upload your data each month, it is cleansed and normalized, and it feeds interactive dashboards for full visibility and control.
She's a forerunner building a new category in AI in inventory optimization, where she shares regularly on use cases, tips and best practices. A strong finance perspective, a collaborative spirit, and a genuine interest in helping others grow in this evolving AI finance landscape.
Finance leaders coached on AI workflows. Names as they gave them, roles from their own profiles.
Built on your data, checked against figures you already trust, and yours to run.
One email when a new tool or workflow is ready. No schedule, no filler.
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