Why double progression beats every other rep scheme

Linear, 5/3/1, RPE, autoregulation — every model tries to answer the same question. Here's why double progression answers it most honestly, and what we changed when we built it into the app.

Linear, 5/3/1, RPE, autoregulation — every model tries to answer the same question. Here's why double progression answers it most honestly, and what we changed when we built it into the app.

The problem with linear progression

Most beginners are taught to add five pounds to the bar every session. It works for about three months and then it doesn't — and the only people who don't notice are the ones who stop training before they hit the wall. The wall is real. It is also predictable, which means it is programmable.

Double progression is the simplest way around it. Pick a rep range. Work inside the range until every set hits the top of the range. Then — and only then — add weight. The rule is boring. The results are not.

Earn the bump. Don't schedule it.

How Progressor implements it

The graduation rule is enforced at the data layer. Every working set is compared against your last completed session for the same exercise instance. If — and only if — every working set hits rep_range_max, the app flags graduation and increments the suggested weight by your configured default (2.5 kg, or 5 lbs).

Miss a rep? Nothing happens. Same weight, same range, next session. Three sessions stuck at the same wall? The app offers a 10% mini-deload and resets the counter. The point is that the rule is the same whether you're benching 60 kg or 160 kg — only the numbers change.