ERIC KIM BLOG

Here are 3 viable architectures (from most realistic to most “barbell-like”), plus the core engineering rules that make them survivable.

Option A: The “Forklift Rack Pull” (Most realistic, safest)

Concept: You don’t put 1000 kg on a bar. You put it on two steel forks (or a solid lifting yoke) that connect to handles or a short bar section.

Why it works

• Load stays close to the uprights → minimal bending.
• You can add mechanical safeties (pins + catches) that actually work at this load.
• Uses solid steel members designed for compressive load, not a long bar in bending.

Key elements

• 4-post frame (like a power rack, but industrial)
• Fork carriage that rides on rails or fixed in set positions
• Multiple catch levels (primary + backup)

Option B: The “Center-Stack Stack” (Plates stacked 

under

 you, not on a bar)

Concept: Plates (or steel slabs) are stacked on a center tower. You lift via a short chain/bracket to handles or a small “bar” at rack-pull height.

Why it works

• Plates don’t have to fit on sleeves.
• Centered mass reduces tipping moments.
• You can build a boxed tower that cradles the stack if anything shifts.

Key elements

• Guided stack column (keeps plates from walking)
• Load-spreader base (so you don’t punch through concrete)
• Enclosure / “blast shield” around the stack (seriously)

Option C: “Side-Loaded Barbell Illusion” (Closest to a barbell, hardest to engineer)

Concept: A barbell-looking handle connects to two side carriages that hold plates near the uprights (so the “bar” isn’t really carrying the bending load).

Why it’s hard

• A real bar at 1000 kg becomes a bending/whip problem.
• Sleeves, collars, and shaft are the weak link.
• Even if the steel survives, the dynamics (sway, bounce, twist) get ugly.

If you insist on “barbell vibes”

• Treat the “bar” as a handle, not a beam.
• The load should be borne by side frames/carriages, not the bar shaft.

The Non-Negotiable Engineering Rules (for 1000 kg)

These are the constraints you build around, no matter the design:

1) Stop thinking “plates on a bar.” Start thinking “load path.”

You want load to go:

handles → short connector → rigid carriage → uprights → base → floor

…and not:

handles → long flexible bar → sleeves → plates hanging in space

2) Safety factor must be huge

For human-rated lifting rigs, “it held once” is meaningless.

• You want redundant safeties and no single-point failures.

3) Floor + base is the silent killer

1000 kg isn’t just weight — it’s contact pressure and shock load.

• You need a load spreader (thick steel + laminated wood + big footprint).
• You also need to assume drops/settling and design for it.

4) Control the failure mode

If something slips, it must land on:

• hard safeties (pins/catches)
• contained zone (no flying plates)
• no guillotine paths (no chains over your feet, no exposed pinch points)

5) “Rack pull” height should be fixed and indexed

Adjustability is great… until it becomes the point of failure.

• Prefer fixed, indexed positions with beefy hardware.

If you want my recommendation

If your real goal is “train the nervous system like a cyber-gladiator” without a death wish:

Build Option A (Forklift rack-pull) and make it feel like a rack pull:

• same hand position
• same start height
• same bracing + hip hinge
• but with industrial load handling

Quick reality check (important)

A true 1000 kg free barbell rack pull is so far beyond normal equipment ratings that the risk profile jumps massively (bar bending, sleeve failure, plate shift, rack instability, floor failure). The safest path is to simulate the movement while shifting the engineering burden to a frame + carriage designed for it.

If you tell me:

1. your space (garage? commercial gym? outdoors?),
2. whether you want conventional or trap/yoke handles,
3. whether you want real plates or steel slabs,

…I’ll sketch a clean concept layout (top/side view), list the modules, and give you a build plan at the “talk to a fabricator/engineer” level with safety features prioritized.

The Product

Name (working): KILLER SELECTS (by Eric Kim)

Promise: Upload a burst. Get a ranked shortlist. Export winners. Done.

Core flow (3 taps)

1. Import 20–30 images (camera roll / Files / AirDrop / desktop drag-drop)
2. Cull → AI ranks + clusters “similar shots”
3. Deliver → “Top 3 / Top 5 / Top 10”, export/share + optional Lightroom flagging

What “Best Photo” Means (scoring model)

Each image gets a composite score from multiple signals:

A) Technical Quality (fast + objective)

• Sharpness / motion blur (edge/FFT metrics + learned blur detector)
• Exposure / highlights clipped / shadows crushed
• Noise level (ISO grain patterns)
• White balance weirdness / color cast
• Compression / artifacts

B) Aesthetic & Composition (learned)

• Subject separation / depth cues
• Composition balance (rule-of-thirds-ish, symmetry, horizon straightness)
• Visual simplicity (background clutter penalty)
• “Impact” model (trained on large aesthetic datasets)

C) Face & People Signals (optional toggle)

• Eyes open / blink / gaze
• Smile / expression strength
• Face sharpness vs background
• Best group shot heuristic (most people looking, least blink)

D) “The Burst Problem” (the real killer feature)

Users don’t just need “good photos,” they need the best frame among near-duplicates.

So we do:

• Perceptual similarity clustering (group “almost the same shot”)
• In each cluster, pick the winner (sharpest, best expression, best moment)
• Show a “stack” UI: Winner on top → swipe to compare losers

UX Screen Blueprint

1) Import Screen

• “Select 20–30 photos”
• Toggle: People mode (faces) / No faces (street / objects)
• Toggle: Fast vs Deep (device-only quick vs deeper analysis)

2) Cull Screen (the money screen)

• Header: Your Keepers
• Sections:
  
  • Top Picks (3–10)
  • Good (maybe keep)
  • Rejects (blur/blink/duplicates)
• Each card shows:
  
  • Score + reason tags (“sharp”, “best expression”, “clean background”, “duplicate loser”)

3) Compare Screen (A/B violence)

• Two-up compare
• Buttons: Keep / Reject / Best of stack
• “Auto-advance” to next cluster

4) Export Screen

• Export options:
  
  • Save to album “Killer Selects”
  • Share sheet
  • Desktop: download ZIP
  • Lightroom workflow: write XMP sidecars (flags/stars) or filename suffixes (_KEEP, _REJECT)

Engineering Architecture (practical + scalable)

Client (iOS first)

• SwiftUI UI
• Photos framework import
• On-device inference using Core ML
• Background processing with progress + pause/resume

ML pipeline (hybrid)

Default: on-device first (privacy + speed), with optional “cloud turbo” if user wants.

• On-device models:
  
  • Blur/sharpness classifier
  • Aesthetic score model (small-ish)
  • Face quality model (optional)
  • Embedding model for similarity clustering (MobileNet/CLIP-lite style)

Optional cloud (for “Deep mode”)

• Higher-quality aesthetic model
• Better semantic understanding (street/story/mood)
• Faster batching for large sets

Backend (if cloud mode exists)

• FastAPI or Node for API
• S3/R2 temporary encrypted storage (short TTL like 1 hour)
• Queue: Redis / SQS
• Worker: GPU inference (if needed)

The “Cull Engine” (algorithm)

1. Preprocess
   
   • Downscale thumbnails for analysis (e.g., 512–768px)
3. Compute features
   
   • Technical metrics
   • Embeddings for similarity
   • Face metrics if enabled
5. Cluster
   
   • Use embeddings + distance threshold to form stacks (burst groups)
7. Score
   
   • Composite score = weighted sum
   • Winner per stack = max score
9. Rank + explain
   
   • Sort winners globally
   • Generate reason tags from top contributing signals

MVP Scope (ship fast)

Week-1 MVP features (minimum lovable):

• Import 20–30 images
• Similarity clustering into stacks
• Sharpness + exposure scoring
• Pick winners per stack
• Export winners to album

Then upgrade (v1.1):

• Face/blink detection toggle
• Two-up compare view
• Explanation tags
• Lightroom/XMP export

Differentiation (make it ERIC KIM)

• “Brutal Mode”: only 1 winner per stack, no mercy
• “Street Mode”: penalize clutter, reward subject separation + gesture
• “Moment > Perfection” slider: user decides if emotion beats sharpness
• Your Taste Model (later): user thumbs-up/down, app learns your style

Monetization (simple, clean)

• Free: 1 album/day or 30 photos/session
• Pro: unlimited sessions + Lightroom export + deep mode
• Optional: “One-time purchase” vibe (photographers love ownership)

If you want, I can generate next:

• A full PRD (screens, user stories, success metrics)
• A data/model plan (which models, sizes, Core ML conversion, benchmarking)
• A clickable UI spec (component list + SwiftUI structure)
• A brand/landing page copy in your voice (“KILLER SELECTS: choose violence against mediocre frames.”)

Say the word: iOS-first or web-first and I’ll lock the tech stack and build plan.

I’m going to design it like a real product + real system: UX flow, AI scoring pipeline, architecture, data model, export, and an MVP build plan.

Product concept

App name (working): KIM CULL

Tagline: “Kill the weak frames. Keep the bangers.”

Promise:

Import a burst/series (20–30 photos). The app groups similar shots, picks the best per group, and lets the photographer confirm with side-by-side comparisons + reasons (“sharpest,” “best gesture,” “eyes open,” “clean exposure,” etc.).

Core user experience

The 30-second workflow

1. Create Project
2. Import 20–30 images (drag/drop, camera roll, or folder)
3. App instantly:
   
   • Groups duplicates / near-duplicates
   • Scores each image
   • Picks winners per group (and optionally top 3 overall)
5. User reviews:
   
   • “Best-of-stack” view (one winner per cluster)
   • Tap to compare side-by-side: winner vs runner-up
7. Export
   
   • Copy/move selected files
   • Export XMP star ratings (Lightroom)
   • Export a “Selects” folder

What makes it feel great

• It doesn’t just rank 1–30. It says:
  
  • “These 5 are basically the same moment—here’s the strongest one.”
• It explains itself:
  
  • “Winner because: sharpness + expression + composition”
• It learns your taste:
  
  • After you override a few picks, it adapts.

Screens and UI components

Screen 1 — Import

• Drag & drop area
• “Street / Portrait / Event / Product” mode selector (sets default weights)
• Toggle: Local-only processing (default ON)

Screen 2 — Results: “Stacks”

A grid of clusters (“stacks”), each showing:

• Best pick large
• 3–6 thumbnails behind it (the rest of the stack)
• Quick labels:
  
  • ✅ Best in stack
  • 🟨 Close second
  • ❌ Soft / blink / motion / bad exposure

Screen 3 — Compare

Two-up or three-up comparison:

• Winner vs runner-up vs third
• Overlay: why score differs
  
  • Sharpness: 8.9 vs 7.1
  • Eyes open: yes vs blink
  • Motion blur: low vs high
  • Aesthetic/composition: 7.8 vs 6.9

Buttons:

• Keep / Reject
• Make this winner
• “Apply preference to this whole project” (optional)

Screen 4 — Export

• “Export winners only”
• “Export winners + runners-up”
• Lightroom stars: ⭐⭐⭐ for winners, ⭐⭐ for runner-up, ⭐ for third
• Output folder chooser

The AI: how it actually chooses “the best”

This is the core: cluster first, then rank within each cluster.

Step A — Preprocessing

For each image:

• Create thumbnail (e.g., 512px)
• Read EXIF:
  
  • timestamp
  • shutter speed, ISO, focal length (useful cues)
• Compute:
  
  • perceptual hash (dupe detection)
  • embedding vector for similarity clustering

Step B — Grouping into “Stacks”

We want to group images that are basically the same moment:

• Use image embeddings (CLIP-like / vision transformer embedding)
• Cluster with something like:
  
  • hierarchical clustering
  • DBSCAN
  • or “burst grouping” using timestamp + embedding similarity

Heuristic that works extremely well:

• If shots are within X seconds AND embedding distance < threshold → same stack.
• If no timestamps (screenshots, exports), rely on embeddings only.

Result: you get stacks like:

• Stack 1: 6 shots (same gesture)
• Stack 2: 4 shots (same scene, slight angle change)
• Stack 3: 1 shot (unique)

Step C — Score each photo (multi-factor)

Each image gets multiple scores:

1) Technical quality score (0–10)

• Sharpness / focus (blur detection)
• Motion blur estimate
• Noise level (esp. high ISO)
• Exposure sanity (blown highlights / crushed shadows)
• White balance “weirdness” (optional; keep lightweight)

2) Subject/face score (mode-dependent)

If faces detected (portrait/event):

• Eyes open / blink detection
• Face clarity
• Expression quality (smile / neutral / grimace)
• Looking at camera (optional)
• Occlusion (hand covering face etc.)

If no faces (street/landscape):

• Main subject detection / saliency
• Subject separation from background
• “Moment” cues (motion energy / gesture probability — optional advanced)

3) Composition score (0–10)

• Horizon level (if horizon exists)
• Subject placement (thirds / central depending on mode)
• Cropping penalties (cut heads/hands)
• Clutter penalty (too busy background)

4) Aesthetic score (0–10)

A learned aesthetic model (trained on general aesthetic datasets) gives a “looks-good” score.

Important product choice:

Make aesthetic scoring one component, not the dictator.

Many legendary photos are “imperfect.” So aesthetic should never override sharpness + moment if the mode is Street/Documentary.

Step D — Combine into final score

A simple, controllable formula:

final = w_tech*tech + w_subject*subject + w_comp*comp + w_aes*aes + w_exif*exif_bonus

• Default weights depend on mode:
  
  • Street mode: tech 0.35, subject(moment) 0.30, comp 0.20, aes 0.15
  • Portrait mode: tech 0.25, face 0.45, comp 0.15, aes 0.15
  • Event mode: face 0.50 (eyes/expression), tech 0.25, comp 0.10, aes 0.15

Then:

• Pick top 1 per stack as winner
• Also mark runner-up if close (within score delta threshold)

Step E — Explanations (critical for trust)

For each winner, generate a “reason card”:

• “Sharpest in stack”
• “Best expression (eyes open, no blur)”
• “Cleaner exposure”
• “Less clutter”
• “More dynamic gesture”

This is just mapping from metric deltas:

• If sharpness winner > others by +1.2 → show “Sharpest”
• If blink detected in others → show “Eyes open”

Personalization: learns YOUR taste

You don’t want generic “Instagram pretty.” You want Eric Kim taste (or any photographer’s taste).

Lightweight personalization that actually works

Store user choices:

• When user overrides the winner, record:
  
  • (chosen_image_id, rejected_image_id) pair
  • feature vectors + scores

Train a tiny ranking model:

• Pairwise logistic regression / small MLP
• Inputs: [tech, comp, aes, face metrics, embedding]
• Output: preference probability

This can run locally and update fast.

Result: after 20–50 decisions, it starts picking in your style.

“Taste sliders” (simple but powerful)

• “Sharpness vs Moment”
• “Clean composition vs Raw energy”
• “Faces priority” (on/off)
• “High contrast preference” (street vibe)

Export + integrations photographers actually want

Must-have exports

• Export selected to folder: /Selects
• Optional: also export rejects to /Rejects (or keep in place)

Lightroom integration (killer feature)

• Write XMP sidecars with:
  
  • star rating
  • pick flag
  • color labels (winner/runner-up)

So a photographer can import into Lightroom and instantly see:

• Winners: ⭐⭐⭐ / Pick
• Runner-ups: ⭐⭐
• Others: unrated

Architecture options

Option 1: Local-first Desktop App (recommended)

Best for photographers: speed + privacy.

Stack

• UI: Electron + React (or Tauri + React for lighter footprint)
• ML inference: ONNX Runtime (fast, cross-platform)
• Image processing: OpenCV + libvips
• Local DB: SQLite to store projects, scores, embeddings

Pros

• No upload time
• Private by default
• Fast on a laptop

Cons

• Need to package ML models

Option 2: Mobile app (iOS/Android)

Great for casual users.

Stack

• React Native / Swift + Kotlin
• On-device inference: CoreML / TFLite

Pros

• Easy import from camera roll
• “Cull on the train”

Cons

• Heavier compute on mobile
• Harder to do full-res operations quickly

Option 3: Cloud web app

Simple onboarding, but upload cost.

Stack

• Web UI + backend
• Queue workers for inference
• Storage (S3/GCS)

Pros

• No installation
• Central model updates

Cons

• Upload latency
• Privacy concerns

If you want “by Eric Kim” and photographers: go local-first.

Data model (simple + solid)

Project

• id
• name
• created_at
• mode (street/portrait/event)
• settings (weights)

Image

• id
• project_id
• filepath
• exif_json
• thumbnail_path
• embedding_vector (stored compressed)
• metrics_json (sharpness, exposure, blink…)
• final_score
• cluster_id
• rank_in_cluster
• user_label (keep/reject/winner override)

Cluster

• id
• project_id
• representative_image_id
• winner_image_id

MVP scope (what to build first)

MVP features

• Import 20–30 images
• Auto clustering into stacks
• Scoring:
  
  • blur/sharpness
  • exposure sanity
  • basic composition (optional)
  • aesthetic score (optional)
• Pick best per stack
• Compare view
• Export winners

V1.1 (fast follow)

• Face/eye open detection for portrait/event mode
• Lightroom XMP export
• Personal taste learning (pairwise ranking)

V2 (beast mode)

• “Moment detection” for street (gesture/action cues)
• Multi-select output presets
• Batch culling for 500+ photos
• Plug-in for Lightroom / Capture One workflow

Practical scoring examples (how the app thinks)

Stack of 5 street shots (same moment)

• Shot A: sharp 9.1, comp 7.2, moment 7.5 → final 8.2 ✅ winner
• Shot B: sharp 8.7, comp 7.6, moment 7.4 → final 8.1 🟨 close second
• Shot C: sharp 7.0 (motion blur), moment 8.3 → final 7.6
• Shot D: sharp 9.0, comp 6.0 (clutter), moment 6.8 → final 7.4
• Shot E: underexposed, noisy → final 6.2 ❌

Reason card:

• “Winner: sharpest + clean exposure + strongest subject separation.”

The “Eric Kim” signature mode (branding + vibe)

You can ship a preset called:

ERIC KIM STREET MODE

• Bias toward:
  
  • gesture / energy / moment
  • high contrast preference
  • “slight imperfection allowed” (don’t auto-reject mild blur if moment is insane)
• Penalize:
  
  • dead frames
  • weak subject separation
  • clutter with no payoff

This is how you make it feel authorial instead of generic.

If you want, I can go one level deeper (engineering package)

Without asking you anything else, I can also generate:

• A full PRD (product requirements doc)
• API contracts (if cloud/hybrid)
• A folder/module layout for the repo
• Model list + ONNX/TFLite packaging plan
• A concrete clustering + scoring pseudocode implementation plan

Just say: “Give me the engineering spec.”

So if you want a setup that can actually handle a 1,000 kg attempt, the smartest move is to stop trying to fit 1,000 kg worth of plates on sleeves… and instead put the plates on short vertical loading pins (like strongman frames / silver dollar setups). That’s exactly what strongman uses when the weights get absurd.

The 3 viable ways to “do 1000 kg” safely-ish

1) Best answer: a 

Strongman Deadlift Frame

 (a.k.a. car deadlift frame / frame deadlift)

This is the cleanest solution to your “plates stacked on the sides” idea.

What it is

• A rigid steel frame with handles (usually neutral grip) where you stand inside.
• Plates load onto multiple vertical pins (often 4 pins), so you can stack a lot of weight without needing mile-long sleeves.
• The frame carries the structural demand — not a thin bar shaft.

Why it wins for 1000 kg

• No sleeve-length limitation.
• No bar bending/whip issues from extreme loads.
• You can scale to ridiculous numbers by adding pins and keeping stacks stable.

This is an established, sold piece of strongman equipment (not a science project). 

How you turn it into a “rack pull”

• Instead of pulling from the floor, you set the frame/handles at a higher start height (strongman does this via frame geometry or by placing it on blocks). The key point is: you’re raising the start position, not relying on rack pins that may not be rated.

2) Modular barbell option: 

Silver Dollar Deadlift Attachments

These are basically “plate towers” that slide onto a barbell sleeve and give you vertical loading pins plus a stable base.

Why they matter

• They let you load plates on pins rather than stacking everything out on the sleeve.
• They’re designed around strongman’s elevated pull standard: commonly 18-inch start height when used as intended.  
• Example listings describe them as thick steel, 50mm-plate compatible, and substantial in mass (e.g., ~21 kg each attachment on one listing).  

The catch

• Your bar still has to survive the load.
• Many bars top out around 2,000 lb ratings; you need a bar that is explicitly rated beyond 2,205 lb plus safety margin. 
  (Bars claiming 2,500 lb capacity exist, but you’d want legit documentation and conservative use.)  

3) “Classic” rack pull in a power rack (least recommended for 1000 kg)

This is the most familiar… and the most likely to go wrong at 1,000 kg.

To even consider it, you need:

• A rack with published rating that’s actually in this range (example: a commercial rack listing showing 1,000 kg maximum rackable weight and 1,500 kg whole rack capacity).  
• Safeties/pins rated beyond your attempt (e.g., some flip-down safeties are listed at 3,000 lb capacity — ≈1,360 kg).  
• A bar that is rated for the load (and realistically, you still want margin beyond 1,000 kg).

Even then: racks are often rated for static loads under ideal conditions. A sloppy rack pull, a missed rep, or any drop can spike forces way above the “number on the plates.”

Why “just stack plates on the sleeves” breaks down fast

Even ignoring strength ratings, you hit pure geometry:

• 1,000 kg is so many plates that sleeve length becomes a joke.
• A deadlift bar spec example shows 16.25 inches of loadable sleeve length. 
  That’s why strongman uses frames/pins/boxes when they want huge numbers.

A practical “1,000 kg capable” concept spec (what you hand an engineer/fabricator)

I can’t responsibly give you a DIY blueprint with exact steel sizes/weld specs for a 1,000 kg device (that’s “failure could kill you” structural engineering). But I can give you a clean requirements spec to get built professionally:

Design intent

• Use-case: rack pulls/partial pulls at adjustable heights (e.g., mid-shin to above-knee).
• Rated working load (minimum): 1,000 kg.
• Design load (recommended): >1,000 kg with a serious safety factor because humans move weights dynamically (and because “oops” happens).

Preferred architecture

• Frame deadlift style with:
  
  • 4 loading pins (2 per side) so no single stack is comically tall.
  • Wide, anti-tip base (footplates or skids) so it cannot rock or walk.
  • Handle height options (either multiple handle sets or an adjustable insert) so you can “rack pull” without needing rack pins.
  • Mechanical hard-stops so if you lose the rep, it lands in a predictable, non-rolling way.

Foundation/platform requirements

• Put this on reinforced concrete or a properly engineered base. A pretty plywood platform is for normal deadlifts; a 1,000 kg miss is a different movie.
• You want load distributed via a rigid frame and wide feet, not point-loading a weak floor.

Plate-stacking strategy that actually works

If your weight is on 4 pins, the loading becomes sane:

• 1,000 kg total on the implement → roughly 250 kg per pin (before accounting for implement weight).
• With 25 kg plates, that’s about 10 plates per pin — doable and stable.

If you try “bar sleeves only,” you can end up needing ~20-ish plates per side depending on plate sizes, and it becomes physically impossible to fit and dangerously unstable.

Safety must-haves (non-negotiable)

At 1,000 kg, you’re not “lifting,” you’re rigging.

• No DIY mystery metal on any load-bearing part.
• Redundant retention: collars + secondary stops so nothing can slide.
• Clear zone: nobody near the stacks, ever.
• Controlled reps only: no dropping, no bailing sideways.
• Inspect every session: cracks, bent pins, loose hardware, floor damage.

My recommendation (if your goal is the real deal)

If you want the most legit “plates stacked on pins, huge number, rack-pull-ish height” setup:

Get/build a frame deadlift with adjustable start height.

That’s the strongman-proven answer for megaton pulls. 

If you tell me just two things:

1. do you want straight bar grip (like a barbell) or are neutral handles fine, and
2. what exact pull height (below knee / at knee / above knee),

…I’ll sketch a tighter “requirements sheet” (dimensions/features/adjustability choices) you can hand to a fabricator without drifting into unsafe DIY structural instructions.

Beef liver doesn’t “magically” build muscle on its own — lifting + enough total protein + enough calories + sleep do the building.

But beef liver does hit a bunch of the “support systems” for growth and training performance all at once, which is why people associate it with noticeable gains.

1) It’s straight-up muscle-building material: complete, high-quality protein

Muscle is literally made of amino acids. Beef liver is a complete protein (it contains all essential amino acids), and a typical serving can give you a solid protein hit (e.g., ~23 g protein in a 4 oz serving, depending on preparation). 

That matters because muscle protein synthesis (MPS) is driven by having enough essential amino acids available after training. 

2) It helps “flip the switch” on MPS via leucine + essential amino acids

Amino acids aren’t just bricks — some are also signals. Leucine is especially known for its role in stimulating MPS (it’s one reason higher-quality animal proteins are so effective post-workout). 

Beef/animal proteins are generally rich in essential amino acids and BCAAs that support repair and rebuilding. 

3) It’s stacked with performance-support micronutrients that indirectly help growth

If training is the “stimulus,” these nutrients help you cash the check:

• Iron → oxygen delivery + muscle metabolism
  Iron is a core component of hemoglobin (moves oxygen in blood) and myoglobin (oxygen in muscle), supporting training capacity and muscle metabolism.  
• Vitamin B12 → red blood cells + nervous system function
  B12 is crucial for normal blood and nerve function, and beef liver is one of the richest food sources — helpful if you’re low and dragging in the gym.  
• Zinc → protein/DNA synthesis + recovery processes
  Zinc plays a role in protein and DNA synthesis and cell signaling/division — all relevant when you’re repairing tissue and adapting to training.  

When someone’s borderline low in one of these (iron, B12, zinc), fixing that can feel like you “leveled up” overnight: better energy, better training output, better recovery — and that supports more muscle over time.

4) It’s ridiculously nutrient-dense… which is also why you can’t spam it daily

Beef liver is famous for being extremely high in preformed vitamin A (retinol). Vitamin A is essential for growth and development, but too much preformed vitamin A can be harmful; the NIH lists a Tolerable Upper Intake Level (UL) for adults and discusses toxicity risk. 

So yes: it’s powerful — but it’s a “dose matters” food.

How to use beef liver for muscle (smart + savage, not reckless)

• Treat it like a high-impact supplement food, not an everyday staple.
• Many lifters do a few ounces once in a while (like weekly-ish) to get the benefits without overdoing vitamin A. (If you’re eating it frequently, it’s worth being more deliberate.)
• Extra caution if pregnant/trying to conceive: high preformed vitamin A intake is a known concern in pregnancy.  
• If you’ve got gout/hyperuricemia: organ meats can be high in purines, which can matter for flare-ups.  

The real truth: liver is a “support” food, not the main driver

If you want the fastest, most reliable muscle gain:

• Keep progressive overload consistent.
• Hit daily protein + calories.
• Sleep like it’s part of the program.

Beef liver just makes the whole machine run smoother — protein + micronutrients + oxygen delivery support — which can translate into better training and recovery, and then more muscle.

If you tell me your goal (lean bulk vs recomp vs strength peak) and how often you lift, I’ll plug beef liver into a simple weekly eating setup that maximizes gains without the vitamin A downside.

x

it helps you hit the two big muscle-growth levers—high‑quality protein + the micronutrients that let you train harder and recover better.

Here’s the full breakdown (science + nutrients + comparisons + bodybuilding use + history).

The real muscle-building equation

Muscle growth = training signal + building materials + enough total food.

• Resistance training flips the “build” switch.
• Protein provides the amino acids to actually construct muscle tissue.
• Leucine (an essential amino acid) is a key signal that helps trigger muscle protein synthesis (MPS), especially when protein doses are smaller.  
• A sports nutrition summary also notes that physical activity + protein ingestion increase MPS, and protein type/amino acid composition matter.  

So liver helps… but only because it supports those fundamentals.

1) Beef liver = complete protein (with a legit leucine hit)

Per 100 g raw beef liver, you get about:

• Protein: ~20.36 g
• Leucine: ~1.91 g  

That’s a high-quality, complete animal protein with all essential amino acids—exactly what muscle needs.

The leucine “trigger” angle

People often talk about needing roughly ~2–3 g leucine in a meal to strongly stimulate MPS (it’s not a magic number, and it varies by person/age, but it’s a useful ballpark). 

With liver:

• 100 g liver ≈ 1.9 g leucine (close, but often not “full trigger” by itself)  
• If you try to force liver alone to hit 3 g leucine, you’d need ~150–160 g… which runs into the vitamin A/copper mega-dose issue (more on that below).

The smart move: use liver as a micronutrient + protein booster, and pair it with another protein source (eggs, yogurt, chicken, whey) so you get the leucine/protein target without megadosing retinol/copper.

2) Liver’s superpower: micronutrient density that supports training + recovery

This is where liver goes full boss mode.

Per 100 g raw beef liver, you’re looking at roughly:

• Vitamin B12: ~59.3 µg
• Vitamin A (RAE): ~4,968 µg
• Copper: ~9.755 mg
• Iron: ~4.9 mg
• Choline: ~333 mg  

Why this matters for training:

• Iron supports oxygen transport (hard sessions = oxygen demand).  
• B12 + folate + B-vitamins support red blood cell production and energy metabolism pathways—stuff you feel as “I can actually push today.”  
• Choline is tied to nervous system function and muscle control—helpful for performance and coordination.  
• Copper is involved in multiple enzyme systems and iron metabolism—again, performance support.  

So liver doesn’t “build muscle” like a steroid.

It helps remove bottlenecks (nutrient deficiencies, low iron/B12 status, etc.) that can quietly cap your training output and recovery.

3) Beef liver vs chicken breast vs whey (who wins what)

Here’s the clean comparison:

Protein + leucine density

• Chicken breast is the lean protein king:
  
  • ~31 g protein per 100 g cooked/roasted  
  • Leucine works out to about ~2.33 g per 100 g (MyFoodData lists 3,259 mg leucine per 140 g; that’s ~2,328 mg per 100 g).  
• Beef liver is lower protein than chicken, but still strong:
  
  • 20.36 g protein / 100 g
  • 1.91 g leucine / 100 g  
• Whey is the concentrated MPS cheat code for convenience:
  
  • A research paper comparing proteins shows whey is very EAA-dense, and lists leucine ~8.6 g per 100 g (whey protein source).  
  • Translation: whey gives you a big leucine hit without huge food volume.

Micronutrients

• Liver wins by a mile for B12, vitamin A, copper, etc.  
• Chicken breast has way less vitamin A/B12 and copper by comparison.  

Punchline:

• Want pure hypertrophy macros? Chicken + whey dominate.
• Want nutrient density + “I feel like a machine” support? Liver is elite.

4) What the research says about “protein for muscle” (the boring truth that actually works)

A huge meta-analysis found that muscle/FFM gains from protein supplementation plateau around ~1.6 g/kg/day (beyond that, gains don’t keep scaling the same way). 

So liver can be part of the plan, but your main driver is:

• progressive overload
• enough total daily protein
• enough total calories
• sleep

Liver is a support unit that makes the whole system run smoother.

5) How bodybuilders actually use liver (practical + effective)

The “don’t overthink it” protocol

Because liver is so high in retinol (vitamin A) and copper, most people do best with small, occasional servings, not daily mega-servings.

A common “performance + safety” approach:

• 2–4 oz (60–120 g) liver
• 1–2x/week
• Pair it with another protein source in the same meal (or later that day).

Make it not taste like sadness

• Quick sear (don’t nuke it into rubber).
• Mix ground liver into ground beef (like 10–20% liver) for “stealth liver.”
• Pâté works if you’re into it.

Food safety note

Organ meats should be sourced well and cooked properly; some guidance recommends thorough cooking (e.g., 160°F for red meats). 

6) The big warning label (this is why liver isn’t an everyday “more is better” food)

Vitamin A: you can overdo it

NIH’s Office of Dietary Supplements lists a Tolerable Upper Intake Level (UL) for preformed vitamin A (retinol) of 3,000 µg RAE/day for adults. 

But 100 g beef liver has ~4,968 µg RAE. 

That’s why liver is usually treated like:

“power dose occasionally” rather than “daily staple.”

Copper: also near the upper limit

The adult UL for copper is 10 mg/day. 

But 100 g liver has ~9.755 mg copper. 

So daily big servings can push you into “too much” territory.

Who should be extra cautious

• Pregnancy / trying to conceive: high retinol intake is a big deal—don’t freestyle liver as a daily food.  
• Hemochromatosis / iron overload issues
• Wilson’s disease / copper handling issues
• Gout (organ meats are high in purines)  

7) Old-school bodybuilding history: liver tablets were a thing

Before modern supplements went crazy, some bodybuilding coaches pushed desiccated liver tablets hard.

• A historical piece notes lifters (including Vince Gironda’s circle) took liver tablets aggressively.  
• A more recent write-up also mentions Gironda prescribing liver tablets and other supplements to his trainees.  

What did it probably do?

• Boosted protein intake a bit
• Boosted B12/iron/etc.
• Maybe helped energy if someone was deficient
  But it wasn’t some magical “new anabolic pathway.”

The brutal takeaway

Beef liver builds muscle because it helps you train harder and recover better—by giving you complete protein + leucine + an absurd micronutrient payload. 

But for pure hypertrophy efficiency:

• hit your daily protein target (~1.6 g/kg/day is a strong evidence-backed anchor)  
• use liver 1–2x/week as a micronutrient turbocharge, not an everyday “main protein.”

If you tell me your bodyweight and whether you’re cutting/maintaining/bulking, I’ll map a simple weekly plan that uses liver intelligently (no vitamin A/copper faceplant).

Your pocket-sized stage coach + gym mirror assassin. You prop your phone up, hit poses, and the app becomes a live, savage, real-time posing judge: it analyzes symmetry, angles, lat flare, lines, transitions, and presence—then barks cues, counts hold-time, auto-captures your best frames, and builds routines you can drill like combos.

Think: “Iron Mirror + AI coach + stage simulator + progress studio” all in one.

⸻

The Core Experience (what it feels like)

1. Set phone down (tripod, bench, water bottle—whatever).

2. Tap “POSE NOW”.

3. Choose:

• Division (Men’s Physique / Classic / Bodybuilding / Bikini / Wellness, etc.)

• Pose (Front Double / Side Chest / Back Lat Spread / Ab & Thigh…)

4. You get a live camera view with:

• A clean overlay guide (lines, angles, symmetry bars)

• A “pose lock” reticle that turns green when you nail it

• A score that climbs in real time

5. The app says stuff like:

• “Chest UP. Left elbow +6°. Flare lats. HOLD.”

6. When you hit the sweet spot:

• Auto-capture the best photo + 2s video clip

• Save it into your Progress Gallery and Best Takes

It’s a video game… but the final boss is your own physique.

⸻

The Killer Features

1) Real-Time Pose Coach (the main weapon)

• Live skeletal tracking + body segmentation

• Pose templates with adjustable tolerance for your proportions

• Angle + symmetry correction

Example: front double biceps:

• elbow height match

• shoulder roll + chest lift

• hip alignment + knee lockout

• lat flare/waist taper emphasis

• Hold Timer + “Stage Ready” timer

• 3s → 10s → 20s holds

• fatigue training: “Keep it clean under burn.”

Modes

• Practice Mode: cues + corrections

• Silent Mode: only visual feedback (for gyms)

• Judge Mode: zero hints—just score + capture (brutal but real)

• Mirror Mode: left-right flipped like an actual mirror

⸻

2) Routine Builder + Transition Trainer

Bodybuilding isn’t just poses—it’s flow. This makes routines drillable like choreography.

• Drag-and-drop routine timeline:

• Pose → transition → pose → transition

• Add:

• Music track (optional)

• Mandatory pose list (auto-checks compliance)

• Stage walk-in / turn / quarter turns

• AI Transition Smoothness Score

• detects wobble, rushed movements, posture collapse

• Dynamic Time Practice

• “Hit pose at beep, hold through second beep.”

⸻

3) Stage Simulator (hardcore realism)

Turn your garage or gym corner into “show day.”

• Lighting presets:

• harsh overhead stage lights

• warm auditorium wash

• side-light drama for classic physique

• Background options:

• black curtain

• stage silhouette

• Audio:

• crowd murmur

• judge callouts (“Number 12—front and center.”)

• Pressure mode:

• random pose callouts

• limited time to hit pose clean

⸻

4) Flex Analyzer: Symmetry, Lines, Ratios

Not “body shaming.” This is objective geometry + consistency tracking.

• Symmetry map: left vs right delts/arms/legs alignment

• Line quality: spine neutral, scap control, posture collapse detection

• Ratios (approximate, trend-based):

• shoulder-to-waist

• chest-to-waist

• quad sweep appearance (pose-dependent)

• “Best Pose” leaderboard for YOU:

• “Your strongest pose is Side Chest.”

• “Back Double is improving fastest.”

⸻

5) Progress Studio: Auto-Captured Best Frames

This app should be a mini photo studio.

• Auto-capture triggers when:

• pose is within threshold AND stable for X ms

• Saves:

• best still

• short clip

• metadata: pose, score, angles, lighting condition

• Comparison tools:

• swipe compare week-to-week

• “same pose, same camera distance” lock mode

• Export:

• coach package (zip/video sheet)

• social-ready crop presets

⸻

6) Pump-Up & Warmup Mode

You’re about to pose? Cool. Let’s get that pop.

• Quick pump timers:

• shoulders/arms pump circuit

• chest activation

• lat “open-up”

• Bands-only presets

• “Don’t gas out” pacing: short bursts + rest control

⸻

7) Coach Mode (remote feedback without pain)

• Share a session link / package

• Coach can:

• draw on frames

• drop time-stamped notes

• set “pose targets” for next session

• Athlete can replay with overlays and coach notes

⸻

The AI Engine (what it actually does)

You can build this with proven computer-vision building blocks.

A) Pose & Joint Tracking

• 2D pose estimation for joints (shoulders, elbows, hips, knees, ankles)

• Optional 3D refinement with depth (newer phones help a lot)

B) Body Segmentation

• Separates you from background → cleaner metrics and overlays

• Helps estimate:

• lat spread silhouette width

• waist line consistency

• stance width

C) Pose Matching + Scoring

• Each pose template is a set of:

• joint angles (e.g., elbow flexion)

• relative positions (e.g., elbow height vs shoulder height)

• symmetry constraints (left vs right)

• “line rules” (spine, hip tilt, knee lock)

Score approach (simple + effective):

• Compute a vector of normalized features:

• angles, ratios, relative distances

• Compare to template:

• weighted deviation penalties

• Add stability:

• penalize shake/wobble over time

• Output:

• Pose Score (0–100)

• “Fix list” ranked by impact

D) Smart Cues (the “coach voice”)

Instead of generic tips, cues are computed from the biggest current error:

• “Raise left elbow” (largest deviation)

• “Rotate torso slightly right”

• “Open chest” (shoulder roll + sternum lift proxy)

• “Shift weight to rear leg” (hip/ankle alignment)

⸻

Interface Design (fast, gym-friendly, one-hand)

Home Screen

• POSE NOW (big button)

• Routine Builder

• Stage Simulator

• Progress Studio

• Analytics

Pose Setup Screen

• Division → Pose selection grid

• Camera setup:

• distance guide (e.g., 2–3m)

• “full body in frame” lock

• tripod mode (bigger UI)

Live Pose Screen

• Camera view full screen

• Minimal overlays:

• symmetry bar

• joint angle hints

• pose lock indicator

• Bottom:

• hold timer

• score

• Side:

• audio cue toggle

• auto-capture toggle

• mirror flip toggle

After-Capture Screen

• Best frame + score

• Top 3 fixes

• Save to:

• Progress

• Portfolio

• Coach pack

⸻

Personality: Make it Hype Without Being Toxic

• The app should feel like a trainer who’s intense but not cruel.

• Celebrate consistency, not just “leanness.”

• Strong defaults:

• hide weight-based judgments

• focus on pose execution and stage presence

• Optional “Hardcore Judge Mode” for people who want the smoke.

⸻

Privacy & Safety (important, but keep it clean)

• Default: on-device analysis for live pose coaching

• Cloud only for:

• syncing your gallery across devices

• sharing coach packages (opt-in)

• Clear controls:

• delete session

• export all

• disable cloud entirely

• Ethical guardrails:

• avoid “body rating” language

• use “pose quality” and “symmetry” and “execution”

• include reminders about rest and injury prevention

⸻

Monetization That Doesn’t Feel Like a Scam

Free

• limited pose library

• basic live feedback

• progress gallery (local)

Pro subscription

• full pose library + division-specific coaching

• routine builder + stage sim

• advanced analytics & comparisons

• coach mode exports

• unlimited saved sessions

One-time purchases

• “Competition Pack” (posing sequences, callouts, stage sim presets)

• “Photo Studio Pack” (lighting + framing presets)

⸻

MVP Build (fastest path to something real)

If you want a version that works and feels insane within a reasonable build scope:

MVP Features

• Live pose tracking

• 8–12 core poses

• Pose scoring + top 3 corrections

• Auto-capture best frames

• Progress gallery + compare tool

V1 Upgrades

• Routine builder

• Stage simulator

• Coach exports

• Voice coach personalities (calm / drill sergeant / silent)

V2 Madness

• Depth-based 3D refinement

• Multi-angle capture (two phones)

• Smartwatch remote trigger

• Competition “callout battles” multiplayer

⸻

Signature Feature Ideas (to make it legendary)

“GREEN LOCK”

When your pose is correct and stable → screen corners glow and the app captures automatically. You’ll chase that lock like a PR.

“POSE PR”

Tracks your best score per pose and makes you beat it like lifting numbers.

“FLEX FATALITY”

At the end of a routine, it generates a highlight reel of your best frames and transitions—instant dopamine.

⸻

Want the next step?

If you want, I can also give you:

• a full pose template sheet (angles + checks for each pose)

• a complete screen-by-screen wireframe spec

• the exact scoring feature vectors for 10 classic poses

• a technical build plan (Core ML / TFLite pipeline + on-device performance strategy)

But even as-is: FLEXFORGE AI is a complete, buildable product concept that would slap unbelievably hard for bodybuilders.

A phone designed around one savage mission: make you look like a carved statue on command—in the mirror, on camera, under stage lights.

1) The core idea

Real-time posing + physique camera intelligence that:

• Guides your pose (angles, elbow height, lat flare, hip tilt)
• Auto-captures the exact millisecond you hit peak contraction
• Picks your best frames (like a ruthless photo editor that only loves winners)
• Builds posing routines (classic bodybuilding poses + your custom flow)
• Tracks progress (symmetry, conditioning, posture, pose consistency)

2) The smartphone: FLEXPHONE (hardware built for physiques)

Not a “general phone that happens to have an app.” This is physique-first.

Front camera system

• Ultra-wide selfie cam (so your whole body fits, even in tiny rooms)
• Depth sensor (clean cutouts, better edge detection, consistent body measurement)
• Low-light gym performance (fast shutter + stabilization so you don’t look blurry and soft)

Bodybuilding-friendly physical design

• Integrated kickstand (portrait + landscape)
• Grippy sweat-proof sides + wipeable back
• One “PEAK” button: press once = starts Pose Mode instantly (no menu diving)
• Magnetic mount system for snap-on accessories

Snap-on accessories

• Mag ring tripod puck (fast setup)
• Pocket ring-light (even lighting = instant “hardness”)
• “Stage Light” clip (high-angle harsh light simulator)

3) The app: FLEX//AI (your coach, cameraman, and judge)

Modes

A) Pose Coach (live)

• Overlay skeleton + pose “targets” (hands here, elbows here, hips here)
• Audio cues like:
  “Elbows up. Chest high. Twist 5°. Hold. BREATHE.”
• “Heatmap” style feedback: what’s popping vs what’s hidden

B) Peak Capture

• Records a short burst (2–6 seconds)
• Detects peak contraction moments and saves only the top frames
• No more 200 near-identical shots. Just the killers.

C) Routine Builder

• Drag-and-drop posing sequence (front double → side chest → back double…)
• Metronome + hold timer
• “Stage walk” practice with prompts and pacing

D) Gym Form + Pump Tracker (optional)

• Exercise recognition + rep counting
• Form cues (depth, knee tracking, bar path) without being annoying
• Links “pump sessions” to “pose performance” (your pump is only real if it photographs real)

4) The AI that makes it feel like magic

Pose understanding

• Full-body keypoints + joint angles
• Pose classification for bodybuilding poses (and variants)
• “Pose Quality Score” based on:
  
  • Symmetry (left/right balance)
  • Alignment (shoulders/hips level)
  • Openness (lat spread, chest expansion)
  • Twist and presentation (how well you’re “showing” the muscle)

Aesthetic camera intelligence

• Detects bad lighting + suggests fixes (“turn 30° toward light”, “raise phone 10cm”)
• Auto-crops for best composition (IG-ready, stage-ready, portfolio-ready)
• Background cleanup options (subtle, not cheesy)

Your personal model

• Learns your best angles over time
• Builds a “Winning Pose Playbook”:
  
  • “Front double biceps: chin down 3°, right elbow 2cm higher = best look”
  • “Side chest: rotate pelvis more, chest up = bigger illusion”

5) The interface (simple, savage)

• Big buttons: COACH / PEAK / ROUTINE / REVIEW
• Review screen:
  
  • Best 5 frames
  • Side-by-side compare
  • “What to fix next time” in 1–2 bullet cues (not a novel)

6) Privacy + sanity features (important)

• On-device by default for pose detection + scoring
• Cloud only if you choose (backup, coach sharing, advanced analysis)
• Anti-body-dysmorphia guardrails:
  
  • Focus on pose execution + consistency, not “you’re not enough”
  • Optional hiding of weight/measurements
  • “Progress = you vs you,” not social ranking

7) Monetization that doesn’t feel cringe

Free: Pose Coach basics + limited Peak Capture

Pro: unlimited Peak Capture, advanced scoring, routine builder, lighting simulator

Coach Marketplace: send a routine + clips to a real posing coach, get feedback inside the app

8) MVP build plan (fast, lethal)

V1 (4–8 weeks):

• Pose Coach (front camera + overlay)
• Peak Capture + best-frame selector
• 5 core poses

V2:

• Routine Builder
• Progress comparisons
• Lighting guidance

V3:

• Personalized angle recommendations
• Coach marketplace
• Form tracking add-on

If you want, I’ll also write:

1. the exact pose library (classic bodybuilding poses + cues for each), and
2. a one-page App Store pitch + pricing tiers, and
3. a UI screen-by-screen blueprint (what every button does).

Beef liver isn’t just food.

It’s biological rocket fuel. Here’s why it turns humans into muscle-forging machines:

🧬 1. NUTRIENT DENSITY = ANABOLIC SIGNAL OVERLOAD

Beef liver is one of the most nutrient-dense foods on Earth.

• Vitamin A (retinol) → gene expression + muscle repair
• B12 → red blood cells + oxygen delivery
• Folate → DNA synthesis
• Iron (heme) → strength + endurance
• Copper → collagen + connective tissue
• Zinc → testosterone signaling

👉 Muscles don’t grow from protein alone.

They grow when the cellular environment is perfect.

🩸 2. HEME IRON = OXYGEN = POWER

Liver’s iron is heme iron—the kind your body actually absorbs.

More iron =

• More hemoglobin
• Better oxygen delivery
• Harder sets
• Faster recovery

This is why lifters who eat liver feel like their lungs and legs upgraded overnight.

🧠 3. B-VITAMINS = ENERGY + CNS FIRE

Beef liver is loaded with:

• B6
• B12
• Riboflavin
• Niacin

These power:

• ATP production
• Nervous system firing
• Muscle contraction

No B-vitamins → weak signals → weak lifts.

🥩 4. REAL PROTEIN + BIOACTIVE PEPTIDES

Liver protein isn’t just “grams.”

It’s bioactive, packed with peptides and amino acids that support:

• Tissue regeneration
• Enzyme production
• Hormonal balance

It’s protein that talks to your body, not just fills macros.

🧠🔥 5. VITAMIN A = TESTOSTERONE & RECOVERY

Vitamin A (real retinol, not beta-carotene):

• Supports testosterone production
• Regulates muscle cell growth
• Enhances immune recovery

Low vitamin A = stalled gains.

Liver fixes that immediately.

🦴 6. CONNECTIVE TISSUE & JOINT ARMOR

Copper + vitamin A + zinc =

• Stronger tendons
• Thicker ligaments
• More resilient joints

This is why old-school strongmen ate organs.

They weren’t stupid—they were durable.

🧠 7. LIVER = SIGNAL, NOT SUPPLEMENT

Supplements try to imitate liver.

Liver is the original stack.

One serving sends a message to your body:

“We have abundance.

Build. Repair. Grow.”

🏆 HOW TO EAT IT (NO EXCUSES)

• 2–4 oz, 1–3× per week
• Pan-seared with salt
• Or frozen, cut, swallowed like capsules
• Grass-fed preferred

You don’t need much.

It’s concentrated power.

⚡ FINAL VERDICT

Beef liver builds muscle because it:

• Fixes deficiencies
• Supercharges recovery
• Enhances oxygen delivery
• Optimizes hormones
• Strengthens joints

This isn’t “bro science.”

This is human biology remembering what it evolved for.

Eat like a predator.

Lift like a god. 💥

So a lot of people fantasize about financial independence retire early, but the truth is, that isn’t or should it be the true goal.

I’m currently watching the new Arnold Schwarzenegger documentary on Netflix, the three part series, mister interesting I’m watching the documentary from the perspective a third person perspective, and I think Arnold might be like in his 70s now… Not sure if early 70s mid 70s or even late 70s, for the most part the good thing is he looks actually in pretty good shape. But certainly not the bodybuilding beast that we knew back in the day.

Even seeing him biking around, his legs look maybe average at best, and apparently my friend Chris told me that he had open heart surgery kind of recently? Probably from all the steroid use.

Anyways, what I find admirable about Arnold is that, in someway he is kind of the epitome of American dream. He essentially came to America when he was well like maybe 20 years old? And his dream was to become the world’s best bodybuilder and win Mr. Olympia which he did, and fast forward in a bit he was successful in movies, politics, but I’m not 100% sure what is up to right now?

Anyways, some flaws:

Honestly at the end of the day, I think everyone just wants a happy family happy family life. Even if you think about Odysseus, all he really wants is to come back home, to his faithful wife Penelope, and his son. He wants to take back the throne and kill all of his suitors.

Even if you have the world‘s greatest mansion, doesn’t matter how big or small or whatever, if you’re in a big ass house by yourself it’s insanely lonely. I think this is why people get dogs to kill the loneliness. 

bitcoin > AI

Radical idea,,, just give me all the money, I could buy all the equipment the trucks whatever, and I could just build it myself? Maybe even go to Home Depot and hire the day laborers myself? 

.

No lifting no life?

LightLifter

AI is like a bicycle for the mind

.

What really matters is the end game?

.

The limits of AI

I guess what’s interesting is when you become an AI insanely superpower user, you start to understand what the true limits are

.

Bodily pleasure and joy vs visual pleasure and joy

.

FIRE is not the goal , power is.

Radical idea,,, just give me all the money, I could buy all the equipment the trucks whatever, and I could just build it myself? Maybe even go to Home Depot and hire the day laborers myself? 

.

No lifting no life?

LightLifter

AI is like a bicycle for the mind

.

What really matters is the end game?

.

The limits of AI

I guess what’s interesting is when you become an AI insanely superpower user, you start to understand what the true limits are

.

Bodily pleasure and joy vs visual pleasure and joy

.

FIRE is not the goal , power is.

Another big thought, now that the sun is intermittent, my insane joy of being in the direct sun… Is unparalleled, even to the greatest of visual pleasures? 

I think what I enjoy so much about biking is how muscular it is. , I love that I could expand more muscular force in order to go faster.  It’s kind of a great idea. 

Also, it’s just like way more fun exciting and thrilling exclamation point you definitely get a bit of a bikers high because when you’re peddling really fast to get somewhere on time, there’s a little bit of the adrenaline rush, as well as the blood rush.

Also another random thing I didn’t really think about is when you’re biking you could actually stand up! Which actually gives you a better advantage point or view than if you simply are stuck in a car? For example, if you’re riding a bike and standing, you’re like a lot taller than even the highest truck. 

I think the difficult thing in today’s world is we are all following these memes from almost like 20 , 30, 40 years ago? And especially the thing is when you’re starting off and you’re kind of yelling and impressionable and you’re not sure how to gain legitimacy… You try to mimic legitimate formulas before? Rather than starting something brand new and carte Blanche?

Cyber gladiators 

Insane cyber as well as insane nature?

Video game warriors 

Fortrrsss

I’m an industrialist 

Humor

Phantom red. 

.

Quiet. Slower

. 

We built a NEW grid

.

Electronic, electric, TRON

the north star?

From: Eric Kim ]

Subject: Proposal — iPhone Pro “ChromaShift Glass”: a Pro-only color‑shifting back that looks impossible (and still feels Apple)

The one‑sentence proposition

Launch a Pro-exclusive back glass finish that shifts color with angle and light—the “3M color‑flip” wow factor, but executed as optical engineering under glass so it’s durable, subtle, and unmistakably premium.

Why this matters now

iPhone Pro’s differentiation is increasingly “camera + titanium + display.” That’s strong—but predictable. We can add a new emotional hook that:

• Creates an instant keynote moment (a single tilt = “how did they do that?”)
• Reads as Pro (not flashy, not gamer) because the effect is controlled
• Signals materials leadership the same way “Ceramic Shield” and “titanium” did
• Adds new demand without new size—a finish people upgrade for

This is a finish that sells in-person (retail table pickup) and on video (social, reviews).

The product concept

“ChromaShift Glass” (working name)

A back glass finish built with a multi-layer interference / dichroic thin-film stack applied to the inside of the glass, paired with an Apple-grade matte texture on the outside.

Result:

• Head-on: clean, restrained, premium
• Tilt + light: a secondary hue appears (deep, glassy, not “paint”)
• Under glass: effect is protected from scratches and wear

This is the “color flip wrap” energy—minus the “wrap” vibe.

What it would look like (Pro, not party)

We pick low-saturation, high-depth shifts—luxury, not loud.

Finish families (pick 2–3 for first year):

• Aurora Graphite: graphite → deep green → violet edge
• Titan Dusk: warm titanium → olive → charcoal
• Glacier Shift: silver → ice blue → soft lavender
• Oil Prism (Ultra vibe): near-black → petrol rainbow edge (most dramatic)

Design detail that makes it feel “designed,” not random:

• A subtle MagSafe halo that blooms only at angle
• Apple logo that reveals at a specific tilt
• Camera island stays matte/titanium for contrast and seriousness

How Apple can ship it without compromising durability

Recommended technical route (best Apple fit)

Under‑glass optical thin-film interference coating

• Coating sits beneath the glass → protected
• Maintains wireless charging + RF transparency
• Effect stays consistent over the device lifetime
• Matte outer glass → fingerprint control, premium tactility

What we avoid

• A “surface film” solution that risks edge lift, bubbles, or that laminated look over time
• Anything that reads like aftermarket accessories

The user experience win

• It rewards motion. Every time you pick it up, it feels alive.
• It photographs differently depending on light and angle—built-in shareability.
• It becomes a signature. People can spot “the new Pro” from across the room.

Risks & mitigation (the real ones)

1. Color consistency at scale (thin-film thickness tolerance)
   
   • Mitigation: spectral QC + binning strategy, limit to 2–3 controlled colorways in year one
3. UV stability / aging
   
   • Mitigation: accelerated aging tests; lock materials stack; conservative pigments (or none—pure interference)
5. Thermal cycling (charging heat)
   
   • Mitigation: laminate + coating stack designed for expansion; prioritize internal coating route
7. Repair/replacement matching
   
   • Mitigation: production controls + “finish matching” process for service inventory

This is hard manufacturing—but it’s our kind of hard.

The launch story (the Apple moment)

Keynote demo:

A single hand tilt under a spotlight and the color shifts like it’s “impossible.”

Then we say the line:

“It’s not a coating on the outside. It’s engineered inside the glass.”

That’s the kind of sentence that lands.

What I’m asking for

A 60–90 day greenlight to build executive-ready prototypes:

• 2 finish families (Graphite/Aurora + Glacier)
• Matte and satin variants
• MagSafe halo concept exploration
• Early manufacturing yield + durability data

Deliverable: a small set of demo units for review—something you can hold, tilt, and instantly decide: Yes, this is the next Pro signature.

Closing

Pro should feel like a precision instrument—and a quiet flex.

ChromaShift Glass is the kind of flex Apple can own: physics, not paint.

If you want, I can also format this into a crisp Apple-style one-page internal brief (headline, customer promise, materials stack diagram, risks, go/no-go metrics) so it reads like it came straight out of a product review deck.