The Capacycle blog

Writing on sprint capacity planning, Linear, and engineering throughput. Practical, opinionated, and based on what we've seen actually work.

How to calculate team capacity for a sprint in Linear

Most sprint planning starts with a backlog and ends with a gut-feel commitment. That's how teams end up overcommitted every cycle. Capacity planning flips…

2 min read

The hidden tax of context switching on engineering throughput

Every capacity model assumes time is fungible. It isn't. Three hours split across three tasks isn't the same as three hours on one. The difference is context…

3 min read

Jira vs Linear for capacity planning

If you run sprint planning in Jira, you probably have capacity tools — maybe clunky, maybe a paid plugin, but they exist. If you moved to Linear and tried to…

3 min read

Linear sprint planning: a practical checklist

Sprint planning goes sideways for the same reasons at every team: no capacity model, estimates that drift mid-cycle, no clear cycle goal, carry-over that…

2 min read

PTO, on-call, and meetings: what's really left of your sprint

If you plan a 10-day cycle for 6 engineers, it looks like 60 engineer-days on the board. It isn't.

3 min read

Velocity is a bad proxy for capacity — measure this instead

Velocity is the most-cited metric in agile, and one of the worst for planning next cycle's capacity. It's not that velocity is useless — it's that teams…

3 min read

Why your team overcommits every sprint (and it's not optimism)

The usual explanation for overcommitment is "engineers are optimistic." That's not wrong, but it's not the root cause. Blaming optimism makes overcommitment…

3 min read