Team Management

Capacity Planning

Plan the next sprint with what your team will actually have. iftrue subtracts PTO, on-call, meetings, and review load from raw capacity, then forecasts realistic commitments using historical velocity and AI tool impact.

Sprint 24 capacity preview · Backend
starts Mon Apr 14

Effective capacity

160h

of 200h raw

Forecast velocity

42 pts

+ AI lift 18%

Allocated so far

140h

87% of capacity

Per engineer · hours available vs allocated

Maya
28h / 36h
Jordan
32h / 38h
Priya PTO Mon-Wed + on-call
38h / 14h
Sam
12h / 40h
Alex on-call rotation
30h / 32h

Reallocation suggested

Priya is over-allocated (38h vs 14h available). Sam has 28h spare. Move 2 frontend tickets before sprint starts.

Effective capacity per engineer, not headcount

PTO, on-call, and meeting deductions automatic

Velocity forecast adjusted for AI adoption

Spot over and under-allocation before sprint starts

Effective capacity

Headcount is not capacity

5 engineers x 40 hours x 2 weeks = 400h on paper. iftrue subtracts everything that's actually consumed: PTO, public holidays, on-call rotations, recurring meetings, and review obligations. What's left is the capacity you can actually plan against.

PTO and holidays
Synced from your HR system. Public holidays per region applied automatically.
On-call rotations
Pulled from PagerDuty or Opsgenie. Primary on-call gets a configurable capacity haircut.
Meeting and review load
Calendar-aware. The senior engineer reviewing 40% of team PRs gets credited capacity for it.

Sprint capacity breakdown · 5 engineers · 2 weeks

Raw capacity 400h
PTO (Priya 3d, Maya 1d) −32h
On-call (Alex) −16h
Meetings (avg 6h/engineer) −30h
Review load (Maya, Alex) −12h
Public holiday (Mon) −40h
Effective capacity 270h

67% of raw. Plan against this number, not 400.

Velocity forecast · Sprint 24

+ AI lift
Last 6 sprint avg 36 pts
AI-adjusted forecast 42 pts

+18% from sustained Cursor/Copilot adoption since Sprint 21

Currently committed 38 pts (90% of forecast)

Room for ~4 more points before you're at the realistic ceiling.

Forecast velocity

Velocity that accounts for AI

Historical velocity says one number. AI tools have changed it. iftrue blends your last 6 sprint averages with measured AI lift per team, so the forecast you commit to reflects how the team actually works today, not 6 months ago before Cursor adoption.

Trailing average
Six-sprint moving average. Outlier sprints (vacation weeks, incidents) are weighted down.
AI lift adjustment
Measured from your AI Impact data. Velocity gain since adoption applied to the baseline.
Confidence range
P50 and P80 estimates so you commit to the safe number and stretch toward the optimistic one.

Quarterly planning

Roll capacity up to the org

Engineering managers see per-team capacity. VPs see the whole org. Plan a quarter against the engineering hours you actually have, not the headcount on the org chart.

Backend

89%

240h allocated / 270h capacity

Frontend

Over

111%

245h allocated / 220h capacity

Platform

Under

58%

180h allocated / 310h capacity

Frontend is over-committed. Platform has spare capacity. Reroute scope before the quarter starts.

Who it's for

Built for engineering leaders

Engineering Managers

Walk into sprint planning knowing what each engineer can realistically commit to. Stop overcommitting and rolling work over.

Tech Leads

See who has bandwidth this sprint after PTO and on-call. Assign with confidence instead of asking around.

VPs of Engineering

Forecast quarterly delivery based on real available capacity across teams. Plan roadmaps with numbers, not optimism.

Ready to transform your engineering organization?

Start your journey to data-driven engineering management. Book a demo to see how iftrue can help your team.