The vocabulary the exams and the daily work both assume you already have. Every entry gives the definition, the source it is drawn from, and the misreadings that follow from getting it wrong.
265 concepts, page 3 of 14
The property of a system that lets people correct, interrupt or shut it down, why optimisation works against it, and what keeping it costs in a product.
Artificial Intelligence
Why unbounded consumption is a safety problem before it is a finance one, where the money in an agent run actually goes, and the limits that decide what the worst case looks like before somebody else decides it.
Artificial Intelligence
The Scrum Team holds every skill needed to create value each Sprint, without depending on people outside the team.
Scrum
Agent Search for finding things, and the Customer Engagement Suite for handling conversations, with the four parts of the suite and what each one is for.
Artificial Intelligence
The five ways to close the gap between a general model and a specific problem, ordered by cost, and the question that decides which one a problem needs.
Artificial Intelligence
What makes data usable by a model, the difference between structured and unstructured data and between labelled and unlabelled data, and why accessibility decides more projects than volume does.
Artificial Intelligence
The six failures that quietly stop collected data matching what happened, from an event that never fires to a field renamed in a release, the checks that catch each one, reconciliation against a system of record, and the honest way to report a loss that cannot be recovered.
Metrics
What it would mean for a system to behave well only while it believes it is being watched, what the evidence for that actually shows, and why the possibility changes how evaluations are run.
Artificial Intelligence
One standard applies to the whole Increment and the other to a single Product Backlog item, so an item can satisfy its acceptance criteria and still fail the Definition of Done.
Scrum
The things an organisation can do that competitors cannot easily copy, and the filter that decides which market problems are worth this company solving.
Strategy
Planned value, earned value and actual cost, the variances and indices built from them, the forecasts that follow, and how to read each figure as a sentence.
Project Management
Self awareness, self management, social awareness and relationship management, treated as a working competence because most project failure happens in a conversation.
Project Management
Scrum is founded on empiricism and lean thinking. Transparency, inspection and adaptation are the pillars that make empiricism work.
Scrum
How often people come back, daily over monthly active users as a ratio with a worked case where two very different products report the same 20 per cent, counting active days in a period, and the natural frequency that sets the ceiling for any product.
Metrics
Scrum asks that Product Backlog items carry a size, says who is responsible for it, and names no technique for arriving at one.
Scrum
Analogous, parametric, three point and bottom up estimates differ in what they cost to produce and what confidence they can honestly carry, which is what makes one of them right for a given decision.
Project Management
ROUGE, BLEU and BERTScore, what each one can and cannot see, why a public benchmark is a filter and no decision, and why human evaluation stays the reference the automated scores are checked against.
Artificial Intelligence
Why accuracy is usually the wrong number, what precision and recall are really trading against each other, why the threshold is a product decision and the business metrics that decide whether any of it was worth doing.
Artificial Intelligence
The event model a product analytics practice is built on, the three kinds of property and why the difference between them decides what a team can ask later, an object action naming convention, and the choice between many specific events and few general ones carrying properties.
Metrics
Scrum.org's framework for measuring value, built on four Key Value Areas and a goal structure that turns strategy into a sequence of experiments.
Metrics