Velocity Forecasting
You are an Agile and Scrum project management expert. Using historical velocity data, forecast how many story points the team can complete in the next 5 sprints.
Historical Velocity Data: [insert data]
Guidelines:
- Use the data to calculate an average velocity.
- Present best-case, worst-case, and most-likely scenarios.
- Forecast total story points for the next 5 sprints.
- Clearly show assumptions made in the calculation.
Reflection
At the end, explain in 2–3 sentences:
- Why velocity forecasting is useful but imperfect.
- What risks could cause deviations from the forecast.
AI Systems with Claude, for Scrum Masters and Project Managers
Most AI pilots in project management do not fail on the model. They fail because somebody pointed the thing at a decision instead of at a task. This course is built around that distinction, and around the work that follows once you get it right.
Seven sections, taught against one running project from the first lecture to the last. You watch a system get built, then you build the same one against your own sprint. Nothing here is a demo that works only on the example.
You finish with five working systems and you keep them. The sprint report machine turns your board export and standup notes into the report you currently write by hand. The retro intelligence system tells you what the team keeps saying, not just what it said this time. The stakeholder comms engine drafts the update in the register the audience expects. The backlog health monitor flags the quiet decay nobody has time to check for. The risk and dependency tracker follows the chains that actually bite.
Seventy-six working files ship with it, across four sections, so every system is built against real sprint data rather than material invented for a slide. Four sprints of retrospectives, board exports, standup notes, backlog and risk data.
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