Weekly Check-In Triage: 3 Signals Justin Harris Uses Before Changing the Plan

Weekly Check-In Triage: 3 Signals Justin Harris Uses Before Changing the Plan

When the scale is noisy, the decision quality problem is usually the triage problem.

The strongest pattern in the KB is blunt: during recovery, the scale is the wrong primary tracking tool because it moves from glycogen, water, digestive content, and hormonal fluid shifts, not just fat. The mechanism is fluid redistribution, and the practical result is that bad check-in triage can trigger bad diet decisions. Justin Harris’s coaching logs make the same point from the other side: he repeatedly adjusts plans from appearance, performance, fullness, and recovery rather than from a single number. The falsifiable thesis is simple: better weekly check-ins are not more data-rich; they are better triaged, and the first job is to decide whether the new information is real signal or just scale noise.

The trap: one number, too much authority

In the Drive recovery notes, the argument is explicit. A 3–7 lb jump in the first few weeks of reverse dieting is framed as restoration, not regression. Glycogen comes back, water follows it, food volume rises, and hormones alter fluid distribution. That means the weight change is real, but the meaning people attach to it is often wrong.

That distinction matters because weekly check-ins are usually where coaches get pressured into action. If the athlete reports a heavier scale and the coach responds with a reflexive reduction, the coach may be “solving” a fluid shift by creating a performance problem. The KB’s warning is not that the scale is useless; it is that scale weight is a poor primary decision rule when recovery is underway.

Justin’s message to Michael Main lands in the same place, but from a bodybuilding lens. He says that if the scale is moving up, it is water or fat over any short period shorter than several months. He also says that water can facilitate new myofibrillar growth, which is why the rebound is effective, but it is still water until that point. That is a mechanism statement, not a motivational slogan. Weight can support progress without being the thing you should chase.

What to triage first: signal quality

Weekly check-in triage should start with a basic question: is the change likely to be signal or measurement noise?

The KB gives four categories that are more decision-relevant than raw weight alone:

• training performance
• energy quality
• sleep
• mood stability
• recovery rate between sessions

Those markers are useful because they move in causal order. If the athlete is recovering better, lifting better, sleeping better, and staying stable mentally, that is the kind of cluster that supports holding course or making small, deliberate changes. If the scale is up but those markers are good, the scale is not the highest-priority problem.

That is also why “better check-in” does not mean “more screenshots.” It means using the right filter before making a change. A coach who sees an uptick in bodyweight but also sees improved pump, stable training, and better recovery is looking at a different situation than a coach who sees a flat scale, worse sessions, low energy, and disrupted sleep. The number is identical in importance only to people who skip triage.

How Justin’s logs show the sequence

The Joe Webb thread is a clean example of decision order. Justin does not respond to the check-in by making the biggest possible change or by obsessing over one macro line. He says the newer diet revision has 65g carbs per meal on low day versus 60g, and that medium day has 145g carbs pre- and post-workout where it was 135g previously. He explains the goal: bring the diet back to two high days while accounting for the fact that the athlete had been doing three high days, so the two-high-day plan needed small increases on the other days. Then he says he wants to use the newest diet revision that week.

That is triage in practice. He does not treat the check-in as a referendum on the athlete. He treats it as a small data update that informs the next revision. He also ties the change to a specific visual and physical read: “I think I look leaner and tighter, but not super full,” followed by the adjustment to add carbs on medium and low days to offset that. In other words, the decision is made from appearance plus fullness plus plan context, not from scale drama.

The Michael Main thread shows the same logic in a more explicit way. Justin says the scale can be hit fast if desired, but doing so would mean added water on the system and, over time, would be a net negative to progress. That is the core coaching insight for weekly triage: not every achievable target is a useful target. If a number can be manipulated quickly, it may be a poor signal of whether the plan is working.

The decision tree that actually helps coaches

Here is the practical version.

1) Classify the check-in before changing anything

Ask whether the athlete is in a state of:

• recovery / rebound / offseason progression
• stable maintenance
• contest prep / tightening phase

The scale has different meaning in each context. In recovery, the KB explicitly says the scale is the wrong primary tracking tool. In offseason, Justin warns that chasing a particular bodyweight is almost always a net negative. In other words, context is not a detail; it is the first branch in the tree.

2) Compare scale change against the biological markers

If the scale is up and the athlete looks leaner and tighter, the default assumption should not be “too much food.” If the athlete is fuller, training is better, recovery is improving, and mood is stable, the change is probably usable information. If the scale is up and the athlete looks worse, feels flatter, and recovery is worse, then the weight gain may be hiding a real problem.

The point is not to worship appearance either. It is to cross-check the scale against the rest of the system before deciding.

3) Make the smallest change that matches the evidence

Justin’s Joe Webb adjustment is small on purpose: 60g to 65g on low days, 135g to 145g on medium-day pre- and post-workout carbs, with the high-day structure revised from three highs to two highs. That is a coach behaving as if uncertainty is normal. He does not swing the plan wildly because the signal is incomplete.

That is a useful standard for coaches. If the data are messy, the change should be modest and testable. Larger interventions should require cleaner evidence.

What bad triage looks like

Bad check-in triage usually has three failure modes.

First, it overweights single-day scale readings. That produces panic cuts or unnecessary food additions.

Second, it ignores context. A reverse diet, rebound, or offseason growth phase will naturally bring water and glycogen changes that can look like “rapid gain” if you forget the mechanism.

Third, it chases round numbers. Justin’s Michael Main note is the clearest warning here: wanting a particular weight can become a motivational trap that worsens the year, not a sign that the year is on track.

What good triage looks like

Good weekly check-in triage is boring in the best way. It starts with context, checks the real markers, and then makes the smallest change that fits the evidence. That is not flashy, but it is how you avoid turning short-term noise into long-term damage.

For coaches using AI tools, this is where the technology should help rather than replace judgment. AI can summarize trends, flag outliers, and surface patterns across check-ins. But the decision quality still depends on the coach’s first principle: is this signal, or is it fluid?

That is the thesis the KB supports. The best weekly check-ins are not the ones with the most data. They are the ones that correctly triage the data, because better triage beats faster reaction.

Sources Used

• raw/_consumed/2026-05-26/troponiniq_kb.md
• raw/_consumed/2026-05-26/troponin_nutrition_products.md
• raw/kahunas-export/2026-05-28/clients/michael_main___members-a2m88q4kyryqrsbdgta-x0mipybv-fzeobfolztzovk.json
• raw/kahunas-export/2026-05-28/transcripts/joe_webb___members-rksigkykimaxwmo_t4_e8nwvbtc2j0etleutkyysads.md
• wiki/drive-nutrition-recovery-tracking-and-biofeedback.md