Estimates and complexity: a tale in 42 and a half minutes
summary
Claims that time-based estimates are mostly waste and urges slice into small deliverables so teams deliver value fast, build trust and get flow; rejects story points as precise measures and shows how to use probabilistic forecasting (Monte Carlo on historical cycle times pulled from Jira) to produce date ranges; recommends time‑boxed spikes for unknowns, demoing real production work every iteration, and using small MDPs/MVPs as insurance — practical tools named include Jira and ActionableAgile for automated Monte Carlo from past data.
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chapters (21)
- 0:00Introduction
- 5:30Just dont
- 7:17Deadlines
- 11:20Constraints
- 20:25Storypoints
- 24:50Velocity
- 25:25Better approach definition
- 26:10Slicing
- 26:30Writing the talk
- 28:10Panning the talk
- 28:55Work things are essential
- 30:20Slicing is better
- 31:00Stakeholders need dates
- 32:30Trust
- 33:05Set goals
- 34:40Days forecasting
- 35:40probabilistic forecasting
- 38:00making real decisions
- 39:15summary
- 40:00Kanban metrics
- 41:20What does it matter
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