AI systems & workflows | Running distribution via AI UGC

Pinned Tweet
Got my first repost from Elon Musk Honestly, it's inspiring when the world's first trillionaire reposts your content It feels like social proof that I should keep improving my content and myself as an expert X is the best platform for getting quality content noticed and selling services at a high ticket The repost feels great. Creating useful content feels better. Back to work
grokbot it's an agent with its own identity, its own computer, and it stays on when you're not here's what "active AI employee" actually looks like in the demo: - chief of staff agent - checks in on your other agents, reads your calendar, dispatches tasks to the right one automatically - shopping agent - logged into your accounts, books tickets, buys groceries, reports back - marketing agent - signed into your actual linkedin, browses your past posts for tone, then writes and publishes a new one on its own - engineering agents - self-triage bug reports, kick off cloud coding agents, come back with a pull request, a screenshot, and a video of the fix the interface isn't a dashboard, it's a chat - same shape as texting a coworker, no tool calls to babysit the number that matters more than any of the demos: grok 4.6 scored 70.8% on cursor bench at $2.81 a task, fable 5 max scored 70.5% at $17.32 same capability, 6x the cost difference - that's the unlock that makes running a fleet of these actually affordable instead of a novelty
26
5
114
9,592
rewind retweeted
X will now pay you when your AI bot gets used... it's called Grok Bot Template Rewards: - build a bot, share it as a template on X - paid every 2 weeks through X Money - based on how many people use it and how often they come back - your own usage doesn't count - likes and impressions don't decide payouts invite-only pilot, U.S. only, about 2 months, amounts fully at X's discretion but the shift is bigger than the program: creators used to get paid for attention now there's a payout for being useful
20
3
35
1,472
rewind retweeted
Opus 5.5 + GPT Image 2.5 + Seedance 2.5 is the AI UGC stack right now... 2 releases in 2 weeks, plugged into the video model everyone already runs, and none of them overlap Opus 5.5 thinks: - reads yesterday's numbers, writes the brief - mines real buyer phrasing from reviews - writes 30 scripts with the image + video prompts embedded - reviews every output and names the exact problem GPT Image 2.5 builds the creator: - one base portrait -> multi-angle reference set - up to 16 references per edit, so face, scene and template load together - Flare for volume, Sunburst for the hero shots - a failed slide gets one element edited, not regenerated Seedance 2.5 moves her: - 30s single pass with native audio - same references as the slides, so the face in the carousel is the face in the video one creator across slides, carousels and video that's what builds recognition... and recognition is what makes an account compound
Opus 5.5 + Blender + Seedance 2.5... the camera finally does exactly what i planned Claude built the whole scene as a 3D blocking in Blender first, then i generated it with Seedance 2.5 on Higgsfield camera moves and character movement match the blocking almost 1:1 what Opus 5.5 improved over my previous runs: - the blocking itself: textures added, camera moves way smoother - the Higgsfield prompt: much more precise to what's actually in the scene the pipeline: - Claude builds the rooftop, the skyline and the explosion in Blender with basic shapes - colored boxes stand in for the character, camera paths get animated - Opus 5.5 writes the Seedance prompt from the blocked scene - Seedance 2.5 turns boxes into a guy jumping rooftops at night still some errors, and the visual quality can go further next step is realism and facial expression, which i didn't touch at all for this one
13
2
36
1,000
rewind retweeted
Jev-Omni just played Chrome Dino, fully local on a MacBook... 12B decision model, fine-tuned from Gemma 4, released a day earlier you give it an image + a question + options, it returns a probability for each one that's exactly what a game loop needs: - every ~100ms, crop the slice of road where the obstacle *will be* when the key press lands - latency × game speed decides where to crop, so the delay is baked into what the model sees - one question: "what is in this slice?" - 3 options: bird in the air / empty road / cactus or low bird -> duck / nothing / jump - runs on an M4 Max via MLX at 8-bit (4-bit hurt accuracy) - the prompt is KV-cached, so each frame only adds 29 new tokens ~10 decisions per second, $0 in API costs, best run 2412 the interesting part isn't the dino... it's that "look at this and pick one" now runs in a loop on a laptop
14
1
47
1,352
rewind retweeted
Opus 5.5 + Blender + Seedance 2.5... the camera finally does exactly what i planned Claude built the whole scene as a 3D blocking in Blender first, then i generated it with Seedance 2.5 on Higgsfield camera moves and character movement match the blocking almost 1:1 what Opus 5.5 improved over my previous runs: - the blocking itself: textures added, camera moves way smoother - the Higgsfield prompt: much more precise to what's actually in the scene the pipeline: - Claude builds the rooftop, the skyline and the explosion in Blender with basic shapes - colored boxes stand in for the character, camera paths get animated - Opus 5.5 writes the Seedance prompt from the blocked scene - Seedance 2.5 turns boxes into a guy jumping rooftops at night still some errors, and the visual quality can go further next step is realism and facial expression, which i didn't touch at all for this one
this account just did 30M views in 2 days using AI UGC... 32.6K followers, 168 posts, here's the funnel behind it: - one repeatable skit format... - instagram bio drops straight into the shopify product page - landing page runs the standard urgency stack... "100+ orders in the last 24h," a hot product/low stock badge, tiered bundle discounts defaulted to buy 2 AI UGC will help you reach the market faster, but it can't make the market bigger the format didn't create the audience, it just found the fastest way to show them something they already wanted
12
3
39
2,080
rewind retweeted
Jev is the first AI model that actually fits content research... numerous individuals are sharing poor-quality demos of it; thus, here is the marketing use case that truly resonates. Jev does not engage in writing; instead, it makes decisions You present it with a question and options, and it provides a selection, a score, or a yes/no likelihood, accompanied by a confidence metric that's literally what content research is: thousands of tiny calls a human makes while doomscrolling here's how Virlo wired it in: - a research agent pulls videos from 12.8M+ TikToks, Reels and Shorts in your niche - Jev checks every video first: is it actually on-niche, or just hashtag-stuffing - judged on caption + hashtags + transcript, not tags alone - 25 videos = ~7k input tokens, around 0.03 cents at Jev's pricing - only what passes gets tagged by hook, format and angle - the top outlier becomes a beat-by-beat script the rule: high confidence -> act, shaky -> escalate to a bigger model or a human you don't need a reasoning model to check if a video is on-topic... that's hiring a lawyer to sort your mail
12
2
44
1,454
rewind retweeted
this account just did 30M views in 2 days using AI UGC... 32.6K followers, 168 posts, here's the funnel behind it: - one repeatable skit format... - instagram bio drops straight into the shopify product page - landing page runs the standard urgency stack... "100+ orders in the last 24h," a hot product/low stock badge, tiered bundle discounts defaulted to buy 2 AI UGC will help you reach the market faster, but it can't make the market bigger the format didn't create the audience, it just found the fastest way to show them something they already wanted
GPT-Image 2.5 is incredible using for AI UGC makes a lot of sense here's the prompt: { "prompt_type": "photorealistic_reference_variation", "objective": "Use the supplied reference photograph as a guide for the same close vertical smartphone selfie composition, lighting, upscale interior, crop, and polished social-media aesthetic. Create a visually similar image, but make the woman a distinct person with subtly different facial features, hairstyle details, jewelry, expression, and wardrobe color. Completely remove all text, icons, hearts, buttons, interface graphics, timestamps, watermarks, logos, or other on-screen elements.", "reference_fidelity": { "target": "high similarity in overall composition, camera perspective, lighting, setting, and fashion beauty aesthetic, while preserving a clearly distinct subject identity", "priority_order": [ "overall vertical crop and composition", "bright frontal daylight against a darker luxury living-room background", "close upper-body smartphone selfie framing", "warm luminous skin and polished soft-glam beauty styling", "sleek dark updo with face-framing strands", "elegant strapless satin bustier", "large gold statement earrings", "natural high-resolution smartphone-camera rendering" ], "variation_instruction": "Do not replicate the exact face from the reference. Create a new adult woman with a slightly more heart-shaped face, softer jawline, hazel-brown eyes, a subtle closed-lip smile, a deep side-part hairstyle, and different sculptural gold earrings." }, "canvas": { "orientation": "portrait", "aspect_ratio": "approximately 918:1588", "framing": "tight vertical smartphone selfie", "crop": "from just above the top of the hair to below the bust and upper torso", "subject_scale": "large, occupying most of the frame", "subject_alignment": "slightly right of center", "camera_distance": "close arm's-length selfie distance", "headroom": "very small", "bottom_crop": "cuts through the lower torso and structured satin top", "left_background": "fireplace and framed artwork softly visible", "right_background": "soft sofa and doorway or window edge visible", "instruction": "do not include any white heart icon or social-media interface graphics" }, "scene": { "location": "upscale dimly lit modern living room or lounge", "time_of_day": "daytime with strong natural window light", "mood": "polished, elegant, intimate, warm", "visual_style": "authentic high-resolution smartphone beauty selfie", "background_complexity": "moderate but visually subdued", "environment": { "walls": "dark warm taupe textured walls", "fireplace": "minimal stone or plaster fireplace at left", "sofa": "large soft light-gray sectional sofa in the rear-right", "art": "large framed muted abstract artwork above or near the fireplace", "lighting": "bright frontal daylight on the subject with a darker ambient interior behind" } }, "subject": { "description": "a distinct adult woman taking a close front-facing selfie indoors", "identity_instruction": "Create a naturally beautiful woman who is not an exact facial copy of any reference person.", "position": "center foreground", "body_visibility": "head, neck, shoulders, upper chest, and upper torso", "pose": { "head": "upright with a very slight turn toward viewer-right", "torso": "mostly frontal", "shoulders": "relaxed and bare", "camera_arm": "extended toward camera outside the visible frame", "posture": "upright, elegant, and composed" }, "expression": { "overall": "calm, confident, softly warm", "mouth": "closed with a faint natural smile", "lips": "softly relaxed", "gaze": "directly into camera", "brows": "relaxed but defined" }, "skin": { "tone": "warm medium olive-tan with a golden undertone", "finish": "luminous satin glow", "texture": "realistic fine skin texture with subtle pores", "freckles_and_marks": "a few faint freckles and small natural beauty marks retained", "highlights": "bright natural highlights on forehead, cheekbones, nose bridge, collarbones, shoulders, and chest", "retouching": "light-to-moderate social-media processing, never plastic" }, "face": { "shape": "soft heart-oval shape with slightly higher cheekbones and a gently tapered jaw", "forehead": "medium height", "cheekbones": "defined but natural", "jaw": "slender and softly sculpted", "chin": "small and rounded", "eyes": { "shape": "almond-shaped", "color": "warm hazel-brown", "size": "medium", "lashes": "long, curled, dark, cleanly separated", "eyeliner": "very subtle brown-black lash-line enhancement", "eyeshadow": "soft bronze-peach neutral tone", "catchlights": "bright natural window reflections" }, "eyebrows": { "shape": "full with a soft natural arch", "color": "deep brown", "density": "medium-full", "finish": "cleanly groomed and softly filled" }, "nose": { "shape": "straight and refined", "bridge": "narrow-medium", "tip": "softly rounded", "highlight": "subtle centered highlight" }, "lips": { "shape": "full but natural", "upper_lip": "defined cupid's bow", "lower_lip": "slightly fuller", "color": "muted dusty-rose nude", "liner": "slightly deeper nude-pink", "finish": "soft satin gloss" }, "makeup": { "style": "natural soft glam", "foundation": "smooth radiant skin-like finish", "bronzer": "warm subtle sculpting", "blush": "soft peach-rose blush across cheeks", "highlight": "controlled luminous sheen on cheekbones", "eyes": "neutral bronze shadow with defined lashes", "lips": "dusty nude rose" } } }, "hair": { "color": "dark chestnut brown, almost espresso", "style": "sleek low bun or low tucked ponytail", "part": "deep side part", "texture": "smooth and glossy", "crown": "softly controlled with a little natural volume", "front_sections": "two long, slim face-framing strands left loose on both sides", "left_face_strand": "a thin dark strand falls from the temple past the jaw toward the shoulder", "right_face_strand": "a matching strand curves softly alongside the cheek toward the chest", "back": "hair gathered into a neat low bun or tucked ponytail", "flyaways": "minimal but realistic", "shine": "soft warm highlights along dark strands" }, "jewelry": { "earrings": { "type": "large sculptural twisted oval gold drop earrings", "shape": "rounded organic vertical form, distinct from rectangular earrings", "material": "polished warm gold metal", "surface": "smooth reflective metal with subtle ridged detailing", "size": "medium-large statement earrings", "visibility": "viewer-left earring highly visible, opposite earring partially visible", "finish": "bright reflective warm gold" }, "necklace": "none visible" }, "wardrobe": { "top": { "type": "strapless structured satin corset or bustier top", "color": "pale champagne ivory with a soft rose-beige undertone", "neckline": "straight to gently curved strapless neckline", "construction": "boned corset-style structure with refined cup seams", "cups": "shaped underwire-style satin cups", "center": "subtle central vertical seam and structured paneling", "fit": "close-fitting and supportive", "material": "smooth satin", "finish": "soft pearl-like sheen", "wrinkles": "small realistic tension creases in satin", "instruction": "preserve the elegant structured fashion silhouette without making the garment exaggerated or costume-like" } }, "body_and_pose": { "shoulders": "bare and evenly lit", "collarbones": "visible with soft natural highlights", "upper_chest": "warm natural skin tone with subtle tonal variation", "torso": "slightly angled but mostly frontal", "left_arm": "partially visible near the lower-left edge, extended toward camera", "right_side": "cropped close to shoulder and torso edge" }, "background": { "left": { "fireplace": { "type": "minimal traditional stone or plaster fireplace", "color": "warm gray-beige", "mantel": "thick simple mantel shelf", "opening": "dark black fireplace opening", "interior": "very dark" }, "artwork": { "type": "large framed monochrome or muted abstract artwork", "position": "above the fireplace", "frame": "light gray or off-white", "content": "abstract forms only, no readable text" } }, "center_rear": { "lighting": "small soft warm accent light near the wall", "furniture": "dark low-profile furnishings partly obscured" }, "right": { "sofa": { "type": "large plush sectional", "color": "light gray", "cushions": "soft oversized cushions", "focus": "slightly out of focus" }, "vertical_edge": { "type": "bright door frame or window frame", "color": "white", "position": "far right edge" } } }, "lighting": { "type": "strong natural daylight from directly in front of the subject", "primary_source": "large window or open doorway near the camera", "direction": "front and slightly above", "quality": "bright but diffused", "contrast": "high subject-to-background contrast", "subject": "face and upper body brightly illuminated", "background": "intentionally darker and moodier", "skin_effect": "warm luminous highlights without clipped whites", "hair_effect": "subtle glossy reflections", "satin_effect": "soft pearl sheen with gentle highlights", "color_temperature": "neutral-warm daylight", "shadow_style": "very soft facial shadows and deeper background shadows" }, "camera": { "device": "modern smartphone front-facing camera", "orientation": "vertical portrait", "lens": "standard wide selfie lens", "focal_length_equivalent": "approximately 24-28mm", "camera_height": "slightly above chest and near face level", "camera_distance": "approximately 45-70 cm from face", "perspective": "mild wide-angle smartphone perspective", "focus": "sharpest on eyes and face", "depth_of_field": "moderately deep but background naturally softer", "image_quality": "high-resolution smartphone image", "dynamic_range": "strong HDR preserving bright skin and dark room", "processing": "subtle sharpening and noise reduction", "grain": "very light realistic phone-sensor grain", "motion_blur": "none" }, "composition_geometry": { "face_center": "approximately x=55%, y=31%", "eye_line": "approximately y=28%", "head_top": "approximately y=2%", "mouth": "approximately y=43%", "shoulder_line": "approximately y=60%", "neckline": "approximately y=82%", "corset_center": "approximately x=55%, y=91%", "viewer_left_earring": "approximately x=27%, y=37%", "fireplace": "left-rear background", "sofa": "right-rear background", "visual_balance": "bright subject contrasted against a dark elegant room" }, "color_palette": { "dominant_colors": [ "warm olive-gold", "dark chestnut brown", "champagne ivory", "warm gold", "charcoal", "light gray", "taupe" ], "skin": "golden olive tan", "hair": "deep chestnut espresso brown", "top": "champagne ivory with a rose-beige undertone", "earrings": "warm gold", "background": "dark taupe and charcoal", "sofa": "light gray", "overall_saturation": "moderate", "contrast": "moderately high", "white_balance": "warm-neutral" }, "image_texture": { "skin": "fine pores, faint freckles, and small natural beauty marks", "hair": "individual sleek strands and minimal soft flyaways", "satin": "smooth woven sheen with fine tension folds", "earrings": "polished gold-metal reflections", "walls": "matte textured plaster", "sofa": "soft woven upholstery", "fireplace": "subtle stone or plaster texture" }, "photographic_style": { "genre": "beauty and fashion smartphone selfie", "aesthetic": "luxury social-media portrait", "realism": "extreme photorealism", "retouching": "polished but believable", "production_value": "personal phone photo with high-quality natural light", "desired_result": "looks like a genuine high-resolution selfie captured near a window in an upscale living room" }, "negative_prompt": [ "text", "caption", "white heart icon", "social media UI", "buttons", "watermark", "logo", "screen overlay", "extra people", "different camera angle", "full-body shot", "side profile", "heavy head tilt", "long loose hair", "curly hair", "blonde hair", "red hair", "high ponytail", "messy bun", "missing face-framing strands", "silver earrings", "small stud earrings", "hoop earrings", "missing earrings", "heavy contour", "red lipstick", "smoky black eye makeup", "large smile", "open mouth", "looking away", "black top", "white t-shirt", "sports bra", "dress with sleeves", "visible straps", "bedroom", "bathroom", "kitchen", "outdoor setting", "bright background", "studio backdrop", "hard flash", "cold blue lighting", "dramatic cinematic shadows", "extreme bokeh", "fisheye distortion", "plastic skin", "over-smoothed face", "over-sharpened pores", "CGI", "3D render", "illustration", "anime", "cartoon", "distorted anatomy", "warped shoulders", "asymmetrical eyes", "deformed corset", "exact facial copy of the reference person" ], "final_generation_instruction": "Generate one extremely photorealistic vertical smartphone selfie using the supplied image only as a guide for composition, lighting, fashion mood, and upscale interior. Show a distinct adult woman centered close to the camera with warm olive-golden skin, hazel-brown almond eyes, full dark brows, soft peach-rose blush, long lashes, and muted dusty-rose nude lips. Her dark chestnut-brown hair has a deep side part and is pulled into a sleek low bun or tucked ponytail, with two long narrow face-framing strands beside her cheeks. Add large sculptural twisted oval gold earrings. Dress her in a pale champagne-ivory strapless satin corset bustier with subtle structured cups and visible seam construction. Frame the image from the top of the head to the lower upper torso, with the subject filling most of the image. Keep the dim upscale living room behind her: dark warm-gray walls, stone fireplace and framed artwork on the left, plush light-gray sectional sofa on the right, and a bright white door or window edge at the far right. Illuminate the subject with bright diffused frontal daylight so her face, shoulders, jewelry, and satin top glow while the room remains darker. Preserve realistic skin pores, faint freckles, natural smartphone HDR, mild phone-lens perspective, and crisp facial detail. Completely omit all text, buttons, hearts, watermarks, logos, interface graphics, and screen overlays." }
9
2
34
2,004
rewind retweeted
ran Opus 5.5 and GPT-6 Sol side by side, here's what actually separates them Opus 5.5: - Anthropic's frontier model, beats Fable 5.1 across nearly every benchmark, agentic coding 66.4% vs 55.8% - 40% cheaper than Opus 5, $4/$20 per million tokens - noticeably less verbose, leads with the actual answer instead of burying it - takes longer on complex tasks, 35 min and ~200K output tokens on a Blender scene, but the extra thinking shows in the output, full walkable game environments, near-exact SVG logo recreation GPT-6 Sol: - sits below GPT-6 Astra, a cheaper, faster tier, not OpenAI's top model - $2/$10 per million tokens, a fraction of Astra's $10/$50 - deception rate dropped from 10% to 1.3% gen over gen - hits a real chunk of Astra's performance at a much lower cost, ~30% on automation bench for about 25 cents where Astra-level performance runs closer to a dollar the real fork isn't which model is smarter, it's what tier you're actually comparing Opus 5.5 vs Sol 6: different weight classes, one's a flagship, one's a budget tier Opus 5.5 vs Astra is the fairer fight, Opus 5.5 leads on coding depth and design quality, Astra stays cheaper and faster per task for high-volume, low-complexity work: Sol or Luna. for tasks complex enough that longer thinking time pays off in output quality: Opus 5.5
9
2
44
1,248
rewind retweeted
built a full production app with opus 5.5 and jev... fed it a url, it screenshots the site, scores it against a list of known patterns, and ships a shareable report here's the actual pipeline: - gemini flash takes the screenshot, that's the only vision step needed - jev scores it against a fixed list of criteria in a fraction of a second, no text generation, just structured ratings - opus 5.5 writes the entire app, front to back, off a single planning prompt - product os turns the plan into a spec, then a roadmap, then working code, task by task - code review, security audits, and testing happen automatically as it builds, not after - a deploy checklist gets generated too, walks you through auth setup, hosting, env variables, step by step - cost to run per scan lands in fractions of a cent, both models chosen specifically because they're cheap at their job what actually makes this work: opus 5.5 handles everything generative, jev handles every decision that doesn't need generation, and neither model gets used for a job it's not built for that split is why the whole thing runs on pennies instead of frontier-model pricing pair that with a structured build system instead of one long freeform prompt, and a non-coder ships a live, secured, production app in an afternoon, not a sprint
15
1
42
1,275
rewind retweeted
Jev doesn't write text... and the pricing model only makes sense once you get why $0.042 per million input tokens, output is free: - jev never generates a sentence, it answers one of three question types: choice, score, or yes/no probability - every model since chatgpt got optimized to be helpful in conversation, jev is optimized for the opposite... fast decisions under uncertainty - parallel sampling instead of token-by-token generation, that's the actual reason output costs nothing - 70-500ms end to end, 40 to 200x faster than a frontier model on the same task - structured in, structured out... choice, score, null, the same primitives every automation pipeline already runs on - built for the stuff current LLMs technically can do but were never optimized for... routing, sorting, filtering at scale frontier models keep getting smarter at conversation, jev is betting the bigger opportunity was never in the chat window at all
12
2
43
1,349
rewind retweeted
Jev now decides which model actually renders your AI UGC ad... higgsfield wired it in as the router, here's the actual pipeline: - generate 100 AI avatars as candidates - jev + deepseek filter that down to the 20 worth rendering - render product UGC videos for those 20, in parallel - for existing assets, jev filters and selects the best candidates first - deepseek + higgsfield turn the selected assets into finished ad creatives - for a single prompt, jev reads it and picks the right model for cost, speed, and quality before higgsfield's api generates anything the actual shift: model choice stops being your decision and becomes its own step before render even starts
9
3
32
828