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Deep dive·April 24, 2026·8 min read

How OLM's training journal works: 8 axes, voice notes, and the AI coach

An inside look at OLM's training journal — the 8-axis radar chart, voice-note transcription, and the AI coach that suggests what to drill next based on weak axes.

Why a journal at all

Most members don't journal because the friction is high — opening Notes, writing complete sentences, deciding what to capture. The result is that two years of training disappears into 'I did some stuff'. When they want to compare their guard from this year to last year, the data is gone.

OLM's design philosophy: log in 30 seconds or less, structured enough to be useful later. The post-class screen offers two paths — tap a cluster of pre-defined tags, or hold down a record button and dictate.

The 8 axes

BJJ training breaks down naturally into eight functional buckets: Guard, Passing, Submissions, Sweeps, Takedowns, Escapes, Pressure, and Conditioning. Every tag (and every transcribed voice note) maps to one or more of these axes.

Over time, the radar chart shows where someone has been spending their reps. A guard player who never drills passing has a polygon that's heavily lopsided to the Guard axis — visible at a glance to them and to their coach.

The axes are configurable per organization. Judo dojos use a different breakdown (Tachi-waza, Ne-waza, Kuzushi, Tsukuri, Kake, Conditioning, Tactical, Mental). Muay Thai gyms use yet another. The 8-axis structure is the design pattern; the specific axes are per-discipline.

Voice notes and transcription

After class, members can hold a record button and talk for 60-90 seconds about what they worked on. The audio is transcribed automatically and run through a tagging step that maps phrases to axes. 'Drilled deep half from bottom, hit two sweeps' tags Guard and Sweeps.

The voice note + transcription is stored together. Members can scrub their journal entries by date, axis, or instructor and listen to the original audio — useful for long-form review of how their thinking has evolved.

The AI coach

When the radar chart shows a clearly weak axis (e.g., Passing is consistently the smallest segment), the AI coach surfaces a specific drill suggestion the next time the member opens the app. 'You've spent 40 reps on guard this month and 6 reps on passing — try Coach Alex's Tuesday positional class, or drill these three sequences off-mat.'

Suggestions are advisory and skippable. The point isn't to replace coaches; it's to help members notice patterns in their own training that are obvious from the data but invisible from the inside.

What instructors see

Aggregate journal data at the academy level surfaces what the room is collectively strong and weak at. If half the active members have a stunted Passing axis, that's actionable curriculum information. Instructors can prioritize Tuesday's class around passing for a month and watch the collective polygon fill in.

Individual member journals stay private to the member by default. Instructors only see academy-aggregate data; only the member chooses whether to share their own journal with their coach.

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