Practice before theory
Theory is introduced exactly when you need it — that's when it sticks.
a profession simulator
AI Ops Analyst
Make the numbers honest. Interrogate metrics, audit triage agents, write reconciliation tests, brief AI that surfaces bad news instead of burying it.
$799· from $33/moFree · Ch 17 chapters · ~8.7h
~60 min · works with any model runnerChapter 1 is free. You only pay when you decide to continue.
Task 2 of 6
You revoked the agent's auto-close. Now you open the board deck the CEO is presenting Thursday. The headline metric, in 48-point font: 'Weekly Active Businesses: 31,402 ↑ 4% — engagement at an all-time high.' The CEO loves this number. Before you let it ship, you ask one question.
Which question most reliably tells you whether 'Weekly Active Businesses' is a healthy signal or a vanity metric?
AIs the number going up? Up-and-to-the-right means it's working.
BWhat exactly counts as 'active', and does that definition predict revenue or retention?
CIs it higher than our top competitor's number?
DDoes the chart look smooth, or is it noisy week to week?
Auto-check: correct
WhyA metric is only as honest as its definition.
This isn't an online course with lectures — it's a simulator of real work.
80% practice · 20% theory×2 your hourly rate
- Chapter 1 free forever
- No card required
- Cancel any time
- Progress is saved
Approach
Why it works
Verifiable certificate
Proves your skills with a publicly checkable link — add it straight to your résumé.
Real market data
Salaries: remote-market medians and hh.ru / Habr Career — both markets shown.
Progress & streaks
Persist between sessions to keep you on track.
Flexible payment
Bank card · cryptocurrency.
The super-profession
The AI Ops Analyst is a super-profession: one person now does the work of a data analyst, a metrics auditor, an on-call ops reviewer and a decision writer — with AI agents doing the legwork. You become the person who can say whether a number is honest, and prove it.
What you'll be able to close on your own
- Catch a vanity metric by interrogating its definition, not its direction
- Write reconciliation tests that walk a headline number back to raw
- Audit an automated triage agent and spot when it silences real incidents
- Prepare a board-ready decision: claim, number, action — auditable end to end
- Brief an agent to surface bad news plainly instead of burying it
- Isolate a silent redefinition hiding behind a flat line that should be moving
- Tell an anomaly that's noise from the canary that's a real incident
- Define activation, retention and NRR so they tie to money, not vibes
The AI-mastery scale
Where are you on the AI-mastery scale?
Most people never get past asking ChatGPT a question now and then. The top levels — automating your work and building AI systems — are rare, and that's exactly what makes them valuable. This is the band the school lifts you into.
Click a level to see the skills it unlocks
Percentages are an illustrative estimate of the market distribution, not hard data.
The problem this solves
Companies make million-dollar calls off dashboards nobody has interrogated. A vanity metric trends up while real customers churn; a triage agent auto-closes the one incident that mattered; a flat line hides a silent redefinition. Decisions get made on numbers that look right and aren't — and the cost shows up a quarter later as missed churn, a wrong board narrative, and a team that trusted the green light.
What changes for you
You become the person in the room who can tell whether a number is honest — and prove it. You interrogate definitions, reconcile every headline back to raw, and brief AI agents that surface bad news instead of burying it. It's the judgment a strong analytics team is built on, learned by working a real crisis instead of reading about one.
Who it's for
Data and product analysts who own the numbers
Stop shipping metrics you can't defend. You'll catch a vanity metric by its definition and walk any headline number back to raw with reconciliation tests.
Ops and on-call folks running triage automation
Read an automated triage agent and spot when it's silencing real incidents — then re-brief it to suggest-and-confirm instead of auto-close.
Founders and operators who present to a board
Turn a noisy dashboard into a one-page memo — claim, number, action — that you can defend line by line when the board pushes back.
Career-switchers aiming at the AI Ops Analyst role
Build the exact reflex the job interviews for: inherit a lying dashboard under deadline and produce an honest review you can stand behind.
Who it's not for
- People looking for a BI / dashboard-building course — this is about making metrics honest, not making charts pretty.
- Anyone who wants a tour of every analytics tool; the discipline ports across stacks and outlives any one of them.
- Those who'd rather trust a green number than interrogate its definition — that instinct is exactly what this unlearns.
How the learning works
It's a simulator, not a course
Day one at Ledgerline: the trusted dashboard is green, three enterprise customers just churned, and the board deck is due Thursday. You investigate, not spectate.
Real cases, real stakes
A vanity metric, a triage agent that auto-closed the real incident, a flat line hiding a redefinition. The scenarios are reconstructed from how analytics actually misleads teams.
Answer first, theory after
You call whether the dashboard is right or lying before any explanation appears. Committing first is what makes the lesson land — and stay.
Theory arrives exactly when you need it
No statistics textbook up front. The ~150 words of theory show up the moment a task needs them, then send you back to the investigation.
Your pace, with a mentor track if you want it
Progress saves per step. Run it solo, or join the mentor cohort where a reviewer reads the board review you defend line by line.
What you'll learn
Interrogate the number
- Catch a vanity metric by questioning its definition, not its direction
- Isolate a silent redefinition behind a flat line that should be moving
- Tell an anomaly that's noise from the canary that's an incident
Make it reconcile
- Write reconciliation tests that walk a headline number back to raw
- Define activation, retention, and NRR so they tie to money, not vibes
- Catch silent drift with tests instead of eyeballing a chart
Guardrail the agents
- Read a triage agent and spot when it's silencing real incidents
- Set severity by blast radius, not row count
- Brief an agent to report bad news plainly instead of spinning it
Brief the decision
- Turn a dashboard into a one-page memo: claim, number, action
- Present a board review you can defend line by line
The career this opens
Roles you can work as
- AI Ops Analyst
- Data / Product Analyst (AI)
- Analytics Engineer
- Decision Analyst
Where the profession is in demand
Examples of companies hiring AI engineers. Not affiliated with the school; employment is not guaranteed.
What the market pays
Median market salaries for this profession on the international remote market, 2026 ($/mo).
Junior+
$1 800 – 3 200 / мес
First roles: metric definitions, reconciliation, reading triage automation.
Middle
$3 800 – 6 500 / мес
6–12 months in: you own the honest-metrics layer and guardrail the agents.
Senior
$7 000 – 12 000 / мес
Analytics architecture, board-level decision memos, the number everyone trusts.
These are market salary ranges for the profession on the international remote market, 2026 — not what our graduates earn (we are a new school with no track record) and not a guarantee. Your income depends on you.
7 chapters · ~8.7h
- Free
The dashboard is lying
60 minDay one at Ledgerline. Learn to catch a metric that lies before the board does.
- Locked
Define the metric that pays the bills
70 minActivation, retention, NRR — definitions that tie to money, not vibes.
- Locked
Reconcile or it didn't happen
70 minWalk every headline number back to raw. Tests that catch silent drift.
- Locked
Guardrails for triage agents
75 minSuggest-and-confirm over auto-close. Severity by blast radius, not row count.
- Locked
The decision memo the board trusts
75 minFrom dashboard to one-page memo: claim, number, action — auditable end to end.
- Locked
Anomalies vs. incidents
80 minWhen a spike is noise, when it's the canary. Cohorts, seasonality, root cause.
- Locked
Capstone — the honest review
90 minThursday is here. Present a board review you can defend line by line.
Who teaches this
Alexander Mihalkevich
Founder, mihalkevich.com
I build and ship products solo with AI agents every day. This course is the exact discipline I run on — no theory I don't use myself.
mihalkevich.com →Why now
As companies wire AI agents into ops and analytics, someone has to keep the numbers honest and the agents from auto-closing the incident that mattered. That role — analyst who can audit both metrics and agents — is new and short-staffed. The demand window is open now.
Pick how you learn
Start with Chapter 1 free. Pay only when you decide to continue.
Самостоятельно
from $33/mo
$799 one-time · or 24 payments
- Все главы курса
- Авто-проверка заданий
- Сертификат о прохождении
С ментором
Best valuefrom $54/mo
$1 299 one-time · or 24 payments
- Всё из «Самостоятельно»
- Проверка заданий ментором
- Личная обратная связь
- Чат когорты
С трудоустройством
from $83/mo
$1 999 one-time · or 24 payments
- Всё из «С ментором»
- Резюме и портфолио под конкретные вакансии
- Тренировка собеседований с разбором
- Не нашёл работу за 6 месяцев — вернём деньги
Payback: At a market Middle salary the band sits comfortably above the price of the course over a generic junior-analyst rate — so the course can pay back inside the first month or two on the role. A framing, not a promise: it assumes you land the seat and grow into it.
- 14-day refund if it's not a fit
- Employment tier — on written terms
- 1-on-1 mentor review
- Lifetime access
Launch pricing · seats in this cohort are limitedPrice rises after the cohort fills
Join the community on Telegram
New chapters and simulators, breakdowns of course tasks and discussion with other learners. Free.
What stays in your portfolio
- A board-ready honest review you can defend line by line
- A reconciliation test suite that walks a headline number back to raw
- An audit of a triage agent with the guardrails you added
- A verifiable certificate and a one-page decision memo: claim, number, action
The certificate you'll earn
A real, shareable credential — issued the moment you complete the chapter. Add it to LinkedIn or send the link.
Still on the fence?
Chapter 1 is free and self-paced — no card, no commitment. If the first hour doesn't feel like the real job, you've lost nothing. If it does, you'll know exactly why the rest is worth it. The only way to find out is to do the first chapter.
Start Chapter 1 free →FAQ
AI Ops Analyst
Day one at Ledgerline, a Series-B fintech. The dashboard the whole company trusts is green — but three enterprise customers churned last week and nobody flagged it. The board deck is due Thursday. The on-call agent auto-closed the real incident as noise. You're the new AI Ops Analyst. Find out whether the dashboard is right or lying.
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