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Recognize why detailed upfront plans become fragile when needs, constraints, and knowledge change during the work. Sort examples into predictable work, uncertain work, and work where the real requirement is discovered by building.
Translate a request like “build this feature” into the value it is meant to create for a customer, user, or business. Practice separating outputs from outcomes so the team can decide what is worth doing first.
Trace how feedback turns guesses into evidence through demos, user behavior, tests, metrics, and stakeholder review. Decide what kind of feedback is useful when a team needs to learn whether the work is valuable, usable, or technically sound.
Apply the previous explanations in a guided problem.
Identify product, technical, delivery, and business risks before they become expensive surprises. Choose early learning moves such as prototypes, spikes, experiments, or thin slices when the riskiest assumption needs proof.
Follow a work item from request to done and notice queues, bottlenecks, work in progress, lead time, cycle time, and throughput. Use a simple board or flow diagram to reason about why starting more work can make finishing slower.
Check your understanding with a short quiz.
Spot common forms of waste in changing work: waiting, handoffs, rework, context switching, partially done work, extra features, and unused output. Connect each waste to the delay, confusion, or hidden cost it creates.
Break large efforts into small batches that can be finished, checked, and adjusted sooner. Compare horizontal task slices with user-visible vertical slices, and reason through how smaller batches reduce risk, delay, and wasted effort.
Review this chapter with practice based on your mistakes.
