# 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.

## See what your engineering org is missing.
30-minute walkthrough, tailored to your stack. No slides. Your team's data.