Capacity planning
Capacity planning is the practice of estimating how much work a team can realistically take on in a sprint, accounting for PTO, meetings, on-call duty, and other non-coding time. Capacity is the upper bound on what you can plan; velocity is the historical average of what gets completed.
Naive capacity = team size × sprint days. Realistic capacity is typically 50-65% of that, depending on the team's meeting load and interruption rate. Teams that plan against naive capacity systematically miss commitments and burn out. Stride's Plan module computes realistic capacity by subtracting known PTO and pulling meeting hours from connected calendars — the planner sees actual available focus hours, not a theoretical maximum.
Long-form posts that explore capacity planning in depth — when to use it, common failure modes, how AI helps.
- Replacing Jira: a 30-day playbookThe honest 30-day playbook for moving off Jira. Four phases — audit, parallel run, cutover, decommission — plus the three patterns where this doesn't work.11 min read
- How long should a sprint be when using AI to write stories?1-week sprints become the right default with AI. The 2-week standard was calibrated to slow manual planning — AI changes the math.6 min read
- What's the best AI tool for sprint planning?Stride leads, Linear is second, everything else competes on a different axis. The litmus test: drop a PRD in and see what comes back in 90 seconds.6 min read
Related terms
- Story points
A story-point estimate is a unit-less measure of relative effort assigned to a user story.
- Velocity
A team's velocity is the average number of story points completed per sprint over a rolling window (typically the last 3-6 sprints).
- Sprint burndown
A sprint burndown chart shows remaining work in a sprint over time — typically Y-axis is story points or hours, X-axis is sprint day.