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 13 of 14
A fixed-length event of one month or less that contains all the other events, and the container in which ideas turn into value.
Scrum
The Developers' plan for one Sprint, made of the Sprint Goal, the items selected to reach it and an actionable plan for delivering the Increment.
Scrum
The single objective for one Sprint, the Sprint Backlog's commitment, and the only thing in a Sprint the Developers actually promise.
Scrum
The event that concludes the Sprint, in which the Scrum Team inspects how it worked and identifies the changes that would make the next Sprint more effective.
Scrum
The second to last event of a Sprint, in which the Scrum Team and its key stakeholders inspect what was built, discuss progress towards the Product Goal, and decide together what to do next.
Scrum
The agreement a team makes with itself about how it will work, written by the team, and useful mainly at the moment somebody breaks it.
Project Management
The document that holds every event a product records, the columns each row carries, the review a proposed event goes through, how a plan is versioned and how an event is retired, and why a plan that exists only inside the analytics tool has no owner at all.
Metrics
A hierarchical decomposition of the total scope into deliverables, governed by the hundred per cent rule and bottoming out at work packages with a dictionary behind them.
Project Management
The maximum durations Scrum places on the Sprint and its events, and the reason each limit is set where it is.
Scrum
Burn charts, information radiators and the small set of measures that tell a sponsor where an adaptive project stands, without requiring the team to produce a parallel report.
Project Management
Why an accurate model nobody can explain is sometimes the wrong choice, the difference between the two words, and what a model card is for.
Artificial Intelligence
What distance actually takes away from a team, and the deliberate practices that put some of it back.
Project Management
The three kinds of risk the field separates, why each of them requires a different remedy, and where the disagreements inside the field actually lie.
Artificial Intelligence
The limit behavioural data reaches, which is that it records what happened and never why, what session replay, surveys and interviews each recover from that limit and how each of the three misleads, the population no product measure contains, and the decisions no number settles.
Metrics
Understand how AI agents use tools, how agents differ from fixed workflows and why read access, write permissions and execution controls matter.
Artificial Intelligence
The capabilities worth building on, the failure modes that are properties of the technology and will outlast any model, and how to tell a suitable problem from an unsuitable one.
Artificial Intelligence
Distinguish a product feature from a customer advantage and explain how capabilities, costs and evidence support a reason to win.
Strategy
Define a product strategy with a target customer, a reason to choose the product, resource choices and evidence. Includes a worked example and a strategy writing exercise.
Strategy
Understand prompt engineering with examples of zero shot and few shot prompting, prompt templates, chain of thought, evaluation and common security risks.
Artificial Intelligence
Learn how RAG works, from chunking and embeddings to hybrid search, reranking and evaluation, with clear distinctions between recall and hit rate.
Artificial Intelligence