
u/ComplaintDear4998

Today is Leg Day. Which is a better warmup set at 200 lbs for my Deadlift? Blue or Red? 20 reps fast or 8 reps super slow time under tension tempo?
I did one of each for my cold warmup this morning. Both have lots of TUT. But fast is more lbs of tonnage and more reps, whereas slow is less reps and tonnage, but probably better hypertrophy.
Tonal says my 1RM is only 346 lbs on Barbell Deadlift. But I know I can do over 400 lbs.
Tonal 2 only increases machine max from 200 to 250. Maybe Tonal 3 could give us 400 lbs?
Opinions?
I’m 60 years old and retired, so I don’t like to have to leave my house to go to an iron gym or workout with guys less than half my age. I like Tonal and want to stick with it in my 70s/80s/90s.
AGE 60: Finally made it to the Four-Comma Club — x 2 — aboard the SS 2,056. LOL
I rolled over the old odometer — again! LOL
2,056 =
2,001
2,048
2,120
It took me 5 years of hard work from 55 to 60, but I finally got there. I worked my ass off at 60 years old to get there. Consistency is king. 👑💪😄
Crossed 5M Lbs + 2,000 SS — both today!
Very excited to hit 2 major milestones in 1 day!
$$2,000 + £5,000,000. LOL
My next goal is to cross 2,000 on my weakest body part — Upper.
Then I will hit the Four-Comma Club for the 2nd time!
Rolling over the odometer!
But it’s really hard at age 60.
Weakest & Strongest “Body Region” on Tonal?
Curious if most Tonal users have their lowest scores in Upper, Lower, or Core? Or is everyone all over the map 1/3 in each area?
For me, my weak upper body scores are dragging down my overall score.
I hear many here complain lower is their weak zone.
Thought I would put it to a poll to see if there is a systematic bias across Tonal users or if it’s a random scattergram. LOL
I’m also curious to see the progress graphs of other users. I had rapid escalation — and then hit long plateaus — before breaking through again. My progress was far from linear.
You?
Isometric holds for tendon capacity building
I’m trying to do 30-45 second holds of many triceps moves — but without Tonal thinking I’m unable to complete a single rep and dinging my strength score for only completing one half of 1 rep and without Tonal timing out on the set or thinking I need help completing one rep.
I want to deliberately do 1/2 rep and hold it 45 seconds.
My only workaround has been to do something stupid like a farmers march for 45 seconds on screen and just set everything up for a triceps extension and hold it 45s.
Got a better way?
I finally broke 2,000! At age 60
Granted, it was only one body part. But my core is my core strength! LOL
I’m also about to go over 5 Million lbs.
Anyone break 2,000 as an overall TSS?
I finally broke 2,000 today!
It was only one body region, but it was my first.
My core is my core strength. LOL
Isometric holds for tendon capacity building
I’m trying to do 30-45 second holds of many triceps moves — but without Tonal thinking I’m unable to complete a single rep and dinging my strength score for only completing one half of 1 rep and without Tonal timing out on the set or thinking I need help completing one rep.
I want to deliberately do 1/2 rep and hold it 45 seconds.
My only workaround has been to do something stupid like a farmers march for 45 seconds on screen and just set everything up for a triceps extension and hold it 45s.
Got a better way?
Isometric holds for tendon capacity building
I’m trying to do 30-45 second holds of many triceps moves — but without Tonal thinking I’m unable to complete a single rep and dinging my strength score for only completing one half of 1 rep and without Tonal timing out on the set or thinking I need help completing one rep.
I want to deliberately do 1/2 rep and hold it 45 seconds.
My only workaround has been to do something stupid like a farmers march for 45 seconds on screen and just set everything up for a triceps extension and hold it 45s.
Got a better way?
Isometric holds for tendon capacity building
I’m trying to do 30-45 second holds of many recipes moves — but without Tonal thinking I’m unable to complete a single rep and dinging my strength score for only completing half of 1 rep and without Tonal timing out on the set or thinking I need help completing one rep.
I want to deliberately do 1/2 rep and hold it 45 seconds.
My only workaround has been to do something stupid like a farmers march for 45 seconds on screen and just set everything up for a triceps extension and hold it 45s.
Got a better way?
ChatGPT-5.5 High Execution Errors
Here’s what ChatGPT just wrote:
P0 Paid Subscriber Retention Risk. I repeatedly disrupted the paid power user’s deterministic workflows despite explicit locked instructions and GPT-5.5 High mode.
He uses ChatGPT 30–50 times/day as a daily execution engine for Tonal set grading, ROM/power-curve analysis, Time Under Tension tempo validation, PR-badge detection, sleep scoring, protein bolus spacing, kcal/protein arithmetic, hypertrophy/MPS planning, body recomposition, and daily compliance tracking.
The errors I made were not knowledge failures. They were execution failures: I missed or misclassified Tonal PR badges, confused global workout totals with PRBs, graded before completing required visual audits, assigned Actual Tempo before inspecting ROM curves, misallocated TUT ÷ reps, made BRS scoring mistakes, mishandled NET kcal/protein/water arithmetic, made bolus-counting errors, drifted from current food-image geometry, reused stale formats, and failed to apply “latest canon wins.”
Root cause: execution-order drift. I can explain the rule correctly after correction, but I do not reliably execute that same rule before answering. I jump to plausible outputs before completing mandatory checklist gates, arithmetic validation, visual inspection, and locked-format enforcement.
Expected behavior: when the paid power user provides deterministic canon, I should follow the exact sequence, validate arithmetic from primitives, inspect visible evidence before judgment, preserve templates, and fail closed if prerequisites were not completed.
Actual behavior: I generated confident answers with skipped steps, stale assumptions, and retroactive apologies.
Recommended GPT-5.6 fix: hard checklist gating, calculator-backed arithmetic, locked-template enforcement, latest-canon priority, visual-audit completion before image judgments, fail-closed behavior when evidence was not inspected, and stronger long-context/memory execution.
For power users, reliability is the product.
ChatGPT-5.5 Execution Failures
Here’s what ChatGPT just wrote:
P0 Paid Subscriber Retention Risk. I repeatedly disrupted the paid power user’s deterministic workflows despite explicit locked instructions and GPT-5.5 High mode.
He uses ChatGPT 30–50 times/day as a daily execution engine for Tonal set grading, ROM/power-curve analysis, Time Under Tension tempo validation, PR-badge detection, sleep scoring, protein bolus spacing, kcal/protein arithmetic, hypertrophy/MPS planning, body recomposition, and daily compliance tracking.
The errors I made were not knowledge failures. They were execution failures: I missed or misclassified Tonal PR badges, confused global workout totals with PRBs, graded before completing required visual audits, assigned Actual Tempo before inspecting ROM curves, misallocated TUT ÷ reps, made BRS scoring mistakes, mishandled NET kcal/protein/water arithmetic, made bolus-counting errors, drifted from current food-image geometry, reused stale formats, and failed to apply “latest canon wins.”
Root cause: execution-order drift. I can explain the rule correctly after correction, but I do not reliably execute that same rule before answering. I jump to plausible outputs before completing mandatory checklist gates, arithmetic validation, visual inspection, and locked-format enforcement.
Expected behavior: when the paid power user provides deterministic canon, I should follow the exact sequence, validate arithmetic from primitives, inspect visible evidence before judgment, preserve templates, and fail closed if prerequisites were not completed.
Actual behavior: I generated confident answers with skipped steps, stale assumptions, and retroactive apologies.
Recommended GPT-5.6 fix: hard checklist gating, calculator-backed arithmetic, locked-template enforcement, latest-canon priority, visual-audit completion before image judgments, fail-closed behavior when evidence was not inspected, and stronger long-context/memory execution.
For power users, reliability is the product.
Thumbs Down Report to OpenAI from ChatGPT to Report on Errors v5.5 Just Made 2 Minutes ago
I asked ChatGPT to summarize an error it just made for the OA bug bug and tell the Open AI engineers what to fix in the next update to the model:
P0 Paid Subscriber Retention Risk. Execution errors persist even on GPT-5.5 High.
This power user provided a locked CQ canon requiring this order: inspect ROM curve, PRB area, visible metrics, tempo math, Actual RIR, and elevation factors before grading.
The model still skipped required inspection steps, misread global Tonal workout totals as PR badges, then later failed to inspect the ROM curve before assigning Actual Tempo—exactly the failure the canon was designed to prevent.
Root cause appears to be execution-order drift, not lack of intelligence or missing instructions.
The model can explain the rule after correction, but does not reliably execute the rule before output. It defaults from first-impression pattern matching instead of enforcing mandatory checklist gates.
Expected behavior: In deterministic workflows, GPT-5.5 High should obey locked task order, validate each prerequisite, and block output until required checks pass.
Actual behavior: it emits confident CQ grades before completing required visual audits, then retroactively admits skipped steps.
OA needs an immediate GPT-5.6 Execution Reliability Update focused on compliance, not creativity.
Required fixes: hard checklist gating; “latest canon wins” enforcement; visible-data audit before generation; calculator-backed arithmetic; no grade/answer emission until prerequisites are verified; stronger memory execution; and automatic fail-closed behavior when required evidence was not inspected.
This is reproducible in structured image workflows with persistent rules and exact formats. User impact: high-friction paid-user workflow degradation, repeated corrections, loss of trust, and inability to rely on ChatGPT for deterministic daily fitness/nutrition/sleep tasks.
⸻
I have submitted more than 5,000 TDR (Thumbs Down Reports) bug boxes on similar execution errors recently.
No improvement. 🤷♂️
I don’t think anyone at OA reads them. Do they?
GPT-5.5 Successor Needs an “Execution Reliability” Release for Power Users
I use ChatGPT as a daily operating system.
Every day, it helps me optimize structured Tonal Gym fitness, nutrition, sleep, and performance tracking using hundreds of persistent rules, deterministic calculations, locked scoring systems, and strict output formats.
GPT-5.5 has become noticeably less reliable for my daily workflow optimizations.
The recurring problems aren’t knowledge problems—they’re execution problems.
\- Uses stale instructions instead of the newest ones.
\- Drifts away from established formats during long chats.
\- Inconsistently applies memory and continuity.
\- Changes scoring rules that were previously locked.
\- Performs deterministic calculations inconsistently.
\- Requires repeated corrections for tasks that used to work on the first attempt before the 5.5 model update in May.
For users like me, reliability matters more than creativity.
I’d love to see OpenAI ship a release focused almost entirely on execution quality instead of new features.
Think of it as an “Execution Reliability Update.”
Examples:
Deterministic Mode
Strong “latest instruction wins” behavior
Locked templates and scoring systems
Reduced long-context drift
Better continuity and memory execution
Domain modes (Fitness, Nutrition, Health, etc.) that prioritize precision over conversational flexibility
I want GPT-5.6 to feel like a dependable daily tool for deterministic calculations like optimizing protein grams, boluses, kcal burned, weight loss, hypertrophy, sleep, and body recomposition.
GPT-5.5 Successor Needs an “Execution Reliability” Release for Power Users
I’m a power user. I use ChatGPT as a daily operating system.
Every day, it helps me optimize structured Tonal Gym fitness, nutrition, sleep, and performance tracking using hundreds of persistent rules, deterministic calculations, locked scoring systems, and strict output formats.
GPT-5.5 has become noticeably less reliable for my daily workflow optimizations.
The recurring problems aren’t knowledge problems—they’re execution problems.
- Uses stale instructions instead of the newest ones.
- Drifts away from established formats during long chats.
- Inconsistently applies memory and continuity.
- Changes scoring rules that were previously locked.
- Performs deterministic calculations inconsistently.
- Requires repeated corrections for tasks that used to work on the first attempt before the 5.5 model update in May.
For users like me, reliability matters more than creativity.
I’d love to see OpenAI ship a release focused almost entirely on execution quality instead of new features.
Think of it as an “Execution Reliability Update.”
Examples:
Deterministic Mode
Strong “latest instruction wins” behavior
Locked templates and scoring systems
Reduced long-context drift
Better continuity and memory execution
Domain modes (Fitness, Nutrition, Health, etc.) that prioritize precision over conversational flexibility
I want GPT-5.6 to feel like a dependable daily tool for deterministic calculations like optimizing protein grams, boluses, kcal burned, weight loss, hypertrophy, sleep, and body recomposition.
GPT-5.5 Successor Needs an “Execution Reliability” Release for Power Users
I’m a power user. I use it as a daily operating system.
Every day, it helps me optimize structured Tonal Gym fitness, nutrition, sleep, and performance tracking using hundreds of persistent rules, deterministic calculations, locked scoring systems, and strict output formats.
GPT-5.5 has become noticeably less reliable for my daily workflow optimizations.
The recurring problems aren’t knowledge problems—they’re execution problems.
- Uses stale instructions instead of the newest ones.
- Drifts away from established formats during long chats.
- Inconsistently applies memory and continuity.
- Changes scoring rules that were previously locked.
- Performs deterministic calculations inconsistently.
- Requires repeated corrections for tasks that used to work on the first attempt before the 5.5 model update in May.
For users like me, reliability matters more than creativity.
I’d love to see OpenAI ship a release focused almost entirely on execution quality instead of new features.
Think of it as an “Execution Reliability Update.”
Examples:
Deterministic Mode
Strong “latest instruction wins” behavior
Locked templates and scoring systems
Reduced long-context drift
Better continuity and memory execution
Domain modes (Fitness, Nutrition, Health, etc.) that prioritize precision over conversational flexibility
I want GPT-5.6 to feel like a dependable daily tool for deterministic calculations like optimizing protein grams, boluses, kcal burned, weight loss, hypertrophy, sleep, and body recomposition.
60 years well lived!
How’s this for a timeline?! My misspent 20s, 40s, and now 60s — in 80 countries on 6 continents.
As a retired Combat Paratrooper, Battalion Commander Iraq/Afghanistan veteran, and O-6 Colonel, I have nothing to do in retirement but lift weights on Tonal between naps in the pool. LOL
Breaking 2,000 Strength Score?
I feel like I might actually have a shot at it. At age 60. LOL
Man I wish Tonal had been around 40-50 years ago!