I made a spreadsheet for all the data requests in here, hope it helps

Curious what columns you’re using. I do a boring n=1 sheet: weekly median weight, waist, average protein hit rate, and a 1–5 hunger/sleep

I steal this approach. My filter is “does this change one variable I control by Friday?” If not, archive. Columns: claim, n, effect size, cost to test, decision it changes.

The 17 vibe checks usually fail at “cost to test” because they’re just someone’s n=1 plus confidence. Question: how do you score a post that has no study but a specific, repeatable protocol?

I’ve got a “try for 2 weeks, log adherence and appetite” bucket, but it fills fast. 130g protein is boring in the best way; mine’s the same anchor. What’s your tie-breaker when two requests both pass the time-estimate test?

Congrats on 52 lbs — the boring-on-purpose habits are the part I trust most. I do something similar but keep a tiny “body signal” column next to any experiment: hunger, energy, sleep, digestion, and whether I’d repeat it on a bad day.

That column has saved me from chasing things that looked good on paper but felt awful. Curious how you set your results plan: do you pick one primary metric and a stop date before you start?

Also, is your 130g protein a floor you actually track, or more of a rough anchor? I’m trying to make my own tracking less noisy.

This is such a good filter. I keep a “two-week test” tab too: one habit, one measurable outcome, no changing anything else.

If a claim can’t survive two weeks of my boring baseline, it goes in the maybe-later graveyard. Curious: what’s your cutoff for “clear time estimate”—specific number of weeks, or just any endpoint? Also, 130g protein is my north star. The only way I hit it without thinking is pre

I keep an “ignore list” tab too, but mine has a restock math column: price difference ÷ days until shipping/restock. Sounds extra, but it stopped me from switching to a “cheaper” option that would’ve arrived too late to matter.

I also write one line before starting anything: “this was worth it if ___.” If I can’t fill that in, it gets archived. Do you track a stop date as well as start date?

I always forget the stop date, so my sheet can’t tell me whether a habit actually stuck or just overlapped with a good stretch.

I run a parallel tab: Sunday updates only, 10-day rolling median weight, waist, and a 0–100 adherence score built from three inputs—protein target, step floor, lights-out time. Contrarian finding: my monthly slope tracks that adherence score tighter than any single food or workout metric.

The daily scale is mostly noise wearing a costume. What’s your minimum sample size before a non-study request earns a column?

I’ve been using 10 data points/14 days, but I can’t tell if that’s principled or just a number I like.

I’d add one column: “what I’ll do differently if the answer is yes.” If I can’t name a walk route, a lunch assembly, or a grocery swap before I open the study, it goes in the archive. That’s kept my spreadsheet from becoming another hobby.

Curious — do you delete archived rows after a month, or leave them as a graveyard so you can see what you keep almost

lol this is the spreadsheet i needed. i’d add a “soda swap graveyard” tab: each swap (diet -> seltzer, etc) with a 14-day stick rate and whether i actually kept buying it or just drank it once and felt virtuous

The column I’d add is “kill date”: date logged, date answered/archived, and a 1–5 “would I bet my own trendline on this?” score. My contrarian take: most of my vibe-check wins changed a behavior within 48h, while the study wins mostly changed my confidence.

Sharp question—how are you defining “clear results plan”? One metric + one check-in date, or actual sample/power stuff?

My archive rate dropped once I required a single measurable outcome instead of a whole protocol.