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I was paying $229 for Screen Studio. Then I found this repo and uninstalled it the same night. Recordly is a free, MIT licensed screen recorder and editor that ships every feature I was paying for auto-zoom animations, cursor smoothing, motion blur, native macOS capture, and a full timeline...

241,725 views • 5 months ago •via X (Twitter)

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I'm using macOS for more than 14 years now, in a single laptop screen setup with lots of windows open, and I'm using macOS spaces everyday to organize my windows. Switching between spaces is easy: I hit CTRL+arrow left/right, it takes no time. What takes time however, is this macOS-native transition animation that takes a bit less than 1 second, for every single space switch. I've checked everywhere in macOS settings, asked friends with the same problem, and there's just no setting to disable this effect (even with Reduced Motion ON in Accessibility settings). This UX choice from Apple alone costs me days of my time every year, as I'm working non-stop on my SaaS business for 10h a day 5-6 days a week (Crisp for those who know about it!). I calculated that with my daily use of macOS spaces, in 6 months I'd perform 100,000 switches, which costs me the same in seconds waiting for the transition to complete. This represents almost 28 hours waiting. In 1 year, I'd have lost 2.4 days just... waiting! The Hack Fortunately, some other open-source projects discovered a hack not so long ago, which allows disabling the transition when switching spaces: it involves sending to the system a "fake" trackpad left/right swipe gesture that's faster than what's expected (faster than what a human can input via the Macbook's trackpad). Above some threshold, macOS just perform the space switch with absolutely no transition. A friend of mine, Yaël 🛸, made a quick prototype in Objective-C, and it magically worked! The Solution So, I asked my friend if we could make it a proper macOS app together, in a beautiful minimalist package, and he said yes! So, we launched Space Rabbit, a tiny 2MB fully native macOS app, that allows you to optimize macOS spaces for productivity! Space Rabbit is a full rewrite of the initial prototype in modern Swift, with a tray menu bar to configure the app, and a settings window, in a macOS app packaging. Space Rabbit can be downloaded right here: We just released V2 of the app last week, fixing a ton of little bugs, especially for dual screen setups. It's actively maintained to this day as it's my daily driver. The app is open-source: and will always be free, as it's helping improve our productivity in our daily Web Dev tasks for our main businesses. We'll be happy to implement more features from user requests, if you find this app useful and use it daily!

Valerian Saliou

222,043 views • 2 months ago

STOP PAYING FOR MOTION DESIGN SOFTWARE opus 5.5 one shot every frame of this in code, no after effects im open sourcing the whole template for free plug in your product and it recreates this steal the prompt ↓ Ask me for: the one question a user asks my product and its one-line answer, two album covers, a royalty-free song around 110 BPM with a quiet intro and a hard drop (Mixkit, free for commercial use), and my logo for the ending. If I skip any, use the defaults: "is this all code?" / "yes. every frame.", two atmospheric photos, Mixkit "Head Bang". A 22 second square loop, 1440x1440 at 60fps, 2D only, one continuous take. Nothing ever cuts: every scene grows out of the last, and every gesture physically carries the camera into the next world. Every morph glides for 0.8s on cubic-bezier(.45,0,.15,1) and the camera zoom rides the same curve, so shapes change so smoothly you barely notice. Content dissolves in the back half of each glide. One gesture per scene. Look: a warm light stage (#f3f3f0 to #e3e3de), black UI, the app world dark (#121212) tinted from the current album cover, one green accent (#1ed760). Geist for UI, the real macOS pointer, soft layered shadows that grow with the shape's height. Banned: hard cuts, bouncy springs, particles, glows, zooming in and straight back out, holds longer than 1s, anything that looks like a template. Beats are the song's, and the press lands on its drop. Generate: the cursor clicks, the pill glides into a spinner, then a check. Chat: the check splits into three typing dots (goo). The left dot flies up into the question bubble and types it, the right one flies down into the reply. Both contract back into dots while gliding in and pour into the middle one. Play: the middle dot bends into a play triangle, point by point. The cursor presses it on the drop: a white button pops in under the click and the dark app floods out around it, so the leftover white becomes the play button. The camera pulls back to reveal the full now-playing screen: big cover, title, heart (liked, fills green), progress, controls, volume. Swipe: the cursor drags the cover sideways, the next track slides in, and the whole app retints from the new cover. Drag: the camera glides to the volume. The cursor drags it to max and keeps pulling: the bar rubber-bands and drags the camera sideways out of the app, tracking the knob across a dark dotted canvas. Chart: the line lands and bends up into a green chart while the number counts up. The volume knob becomes its last point. Dive: the cursor clicks that point and the camera dives into it until the light stage fills the frame. Ending: an "Ask [my product]" button grows out of the light, thins into a line, and the line fans out into my logo (default: the Claude spark, six copies rotating into twelve rays in Claude orange). It folds back into the line, which thickens into Generate. Last frame = first frame. 1. One HTML canvas. Everything is a pure function of time inside seek(t): no timers, no state between frames. 2. A camera with position and log-space zoom. Scenes live side by side in one world, so a pan really travels. 3. Goo: blur + alpha threshold on an offscreen layer for the split and the merges. 4. Floods are circles that grow from whatever caused them to the farthest corner in about 0.4s, and the colour switch happens underneath them. 5. Sound: before the press the song plays through a low-pass filter, like it's in the next room, and opens up to full on the drop. A downloaded Mixkit SFX for every event, each placed by its measured peak. Loudnorm to -14 LUFS. 6. Render with Playwright at 60fps with 4 motion-blur subframes, 12 on the fast pan. Then scan every frame for single-frame jumps and fix each one. A handoff between two drawings only works once the first one has fully landed, or it pops. The cursor must stay on whatever it drags, even while it stretches. A counter or tooltip that changes every frame smears under motion blur, so swap whole values. Ask me for the inputs, then show me the beat map and 6 stills (chat, play, app, drag, chart, logo) before you render.

zero

47,922 views • 13 days ago

Here are 10 AI video editor GitHub repos worth bookmarking: 1. Shotcut Most actively maintained open source video editor in 2026. 14K stars. Cross-platform with AI-assisted features. Just shipped a new release April 30, 2026. 2. Kdenlive The closest open source alternative to Adobe Premiere Pro. Multi-track editing, proxy editing, VST audio, and customizable workspace. Best for professional workflows. 3. OpenShot The easiest entry point for beginners. Drag and drop, 400+ transitions, 3D titles, and AI-assisted trimming. 5,700 stars. 4. Blender Not just 3D. Blender's video sequence editor and compositing pipeline is used in professional film production. 18,300 stars. Unmatched for VFX. 5. Recordly Screen recorder with auto-zoom, cursor polish, webcam overlays, and styled frames built in. Built for demo videos and walkthroughs. 6. Wan2.1 Alibaba's open source text-to-video model. Cinema-grade 1080p generation. Apache 2.0. The gold standard for open source video generation in 2026. 7. HunyuanVideo Tencent's 13B parameter open source video model. 11.9K stars. Handles 720p and 1080p with high temporal coherence. 8. CogVideoX Apache 2.0 licensed. Loads natively via Hugging Face Diffusers. Strong prompt following and smooth frame transitions. Needs 16GB VRAM minimum. 12.5K stars. 9. Open-Sora Most starred open source video generation project at 24K stars. Full training pipeline for $200K. Production-level output quality. 10. Mochi 1 Focused entirely on motion quality. The most natural-looking physics of any open source video model. Water, fabric, and human gestures without AI jitter. Apache 2.0.

Kanika

17,726 views • 4 months ago

10 free github repos that can replace major SaaS with subscriptions. all free. open-sourced. some are MIT licensed. — 1️⃣ openscreen — replaces screen studio ($29/mo) - a clean macOS/windows/linux screen recorder for polished demos. - blur, cursor highlighting, annotations, export to mp4 or gif at any aspect ratio. - doesn't try to clone every feature, just nails the basics for quick walkthroughs you'd post on X. — 2️⃣ voicebox — replaces elevenlabs ($22/mo) + wisprflow ($15/mo) - local-first AI voice studio. - clone voices from 3 seconds of audio, generate speech across 7 TTS engines in 23 languages, - dictate into any text field with a global hotkey. - nothing leaves your machine. - runs on apple silicon, cuda, rocm. — 3️⃣ openshorts — replaces opus clip ($19/mo) + submagic ($16/mo) - free AI video platform. - clip generator turns long youtube videos into 9:16 shorts with auto-subtitles and face tracking (runs on free gemini + elevenlabs tiers). - also includes AI UGC video generation with actors — that part is pay-per-use via fal. ai (~$0.65-2 per video). docker self-host. — 4️⃣ freellmapi — replaces chatgpt pro + claude pro ($20/mo each) - stacks 14 free AI provider tiers (google, groq, cerebras, openrouter, github models + 9 more) behind one openai-compatible endpoint. ~800M tokens/month. - smart router with failover, sticky sessions, encrypted key storage. ships with a dashboard. — 5️⃣ playwright-mcp — replaces browserbase ($39/mo) + browser use ($25/mo) - microsoft's official MCP server that gives any AI agent full browser control. - uses accessibility trees, not screenshots — deterministic and token-efficient. - works with claude code, cursor, windsurf, codex out of the box. — 6️⃣ vibe-trading — replaces tradingview premium ($60/mo) - natural-language finance research agent. - 7 backtest engines across stocks, crypto, futures, forex. - 75 specialist skills (factor analysis, options strategy, ML strategy). - 29 multi-agent swarm presets. - 21 of 22 MCP tools work with zero API keys. — 7️⃣ CalCom — replaces calendly ($12/mo) + savvycal ($12/mo) - the open-source scheduling infrastructure. - one-on-ones, group events, round-robin, team booking, - payment collection (stripe), routing forms, workflows. - integrates with google/outlook/apple calendar, zoom, meet, teams. - self-host in 10 minutes with docker. 40k stars. — 8️⃣ whisper — replaces otter ($17/mo) - openAI's open-source speech-to-text model. - transcribe audio in 99 languages, translate to english, generate timestamps. - runs locally on cpu or gpu. - the actual model behind most "AI transcription" SaaS tools you're paying for. — 9️⃣ postiz — replaces buffer ($15/mo) - AI-powered social media scheduler. - cross-post to X, linkedin, instagram, tiktok, threads, bluesky, mastodon, youtube, pinterest. - AI captions and hashtags. - analytics dashboard. team workspaces. 31k stars and rising. — 🔟 vaultwarden — replaces 1password ($8/mo) - unofficial bitwarden-compatible server written in rust. - works with every official bitwarden client (mobile, desktop, browser). - unlimited users, unlimited vaults, full enterprise feature set. - runs on a $5 VPS or your home server. — disclaimer: open-source ≠ 1:1 replacement. you'll trade polish for ownership, hand-holding for control, and a credit card for a github version. for builders, prototypers, and indie hackers — that's the whole point. for everyone else, the paid tools still have their place. bookmark this. share with one friend bleeding subscription fees. ~m0h

m0h

255,412 views • 4 months ago

Holy shit... the gap between what AI video tools promise and what they actually hand back just got a lot smaller. Normally, using AI for video feels like a gamble: you type in a prompt, wait three minutes, and it spits back a locked MP4. If one single specs number on screen is wrong, you can't edit it—you just have to re-prompt, re-render, and burn through your credits again. To see if any tool could actually handle a real commercial asset without the usual headache, I ran a quick test. I took a concept photo of an "iPhone Duo" and asked Fotor’s Fotor Agent to build an Apple-style product reveal—no 3D modeling, no physical camera setup, and no hiring a motion designer. It didn't just render a clip. It handed me an actual multi-track project file in about 40 minutes. A few things genuinely surprised me about the workflow: 1. It built a real timeline (and did its own research) I uploaded the concept shot and asked for a reveal with animated specs. I didn't even feed it detailed technical specs—it actually went online, pulled plausible data, and mapped it out. I cross-checked against Apple’s actual site later and the formatting and spec logic were spot-on. Instead of a flat video, it laid out the clips, music, transitions, and motion graphics onto separate editable tracks. 2. Native 4K Motion Graphics for a few cents a second Getting clean, keyframed motion graphics usually means opening After Effects or paying someone a few thousand bucks to build them. Fotor Agent generated sharp, native 4K spec cards and charts right on the timeline. The cost broke down to just a few cents per second, which makes testing complex visual ideas almost risk-free. 3. You can fix mistakes without re-rendering everything This was the most practical part. When I wanted to shorten a piece of copy on one of the spec cards, I didn't have to generate a new video or burn more credits. I just clicked the text layer directly on the timeline, edited it, and the preview updated instantly. The actual breakdown: Time: 3–5 days of AE keyframing → ~40 minutes Cost: Thousands in agency quotes → A few dollars in credits Workflow: Jumping between 5 different apps → Done in one Agent AI shouldn't just dump a locked video file on your desktop and call it a day. Fotor Agent handles the heavy production setup while leaving you with an actual project file you can tweak and refine. Screen recording and the 4K test clip are attached below! 👇🏼

marcus

45,851 views • 13 days ago

Hermes agent just left the terminal. 𝗛𝗲𝗿𝗺𝗲𝘀 𝗗𝗲𝘀𝗸𝘁𝗼𝗽 dropped yesterday. native app for macOS, Windows, and Linux. for months Hermes was the agent that learned your projects, wrote its own skills, and built a model of who you are. all of it buried in terminal logs. now it has a window. the important part is that it's not a wrapper. it runs the same agent core, the same sessions, memory, and skills as the CLI. you can start a task in the terminal and finish it in the app without anything resetting. the state is shared across every interface, not copied between them. what the GUI actually adds: → streaming chat that shows live tool calls and inline reasoning instead of a spinner → a preview rail that renders pages, code, and images right beside the conversation → an artifacts panel that collects every file the agent has ever produced → remote gateway mode, so you can point the app at a VPS and run the heavy work elsewhere → skills, cron, profiles, and gateways managed point-and-click instead of through YAML → voice mode, drag-drop files, and inline image generation remote gateway mode is the one worth slowing down on. the agent runs 24/7 on a $5 server while you control it from your laptop like a local app. other agent UIs are chatboxes with a logo. this one shows the autonomy instead of hiding it, so you watch the skills load, the tools fire, and the artifacts pile up as it works. it was teased in Jensen's GTC keynote. MIT licensed, local-first, no telemetry. if you already run Hermes, download it and everything is already there. your chats, memory, and skills carry straight over. i wrote a full masterclass on Hermes Agent that walks through the SOUL. md identity layer, the three-tier memory system, the self-evolving skills loop, and how to run three specialized agents 24/7. desktop is the interface that finally does all of it justice. the article is quoted below.

Akshay 🚀

51,540 views • 4 months ago

opus 5.5 is f*cking insane at motion design every frame is code with 0 external tools im open sourcing the template for all these morph transitions steal it ↓ Ask me for: my product's name (one lowercase word, it becomes a black wordmark with a period), the one job a user hands it before bed, the three results it reports by morning, two photos of the same place at night and by day (aligned, so a crossfade reads as a real sunrise), one sunny daytime photo for outside the logo, and a song with a big hit near its start. If I skip any, use the defaults: "nightshift", "book 10 sales calls this week", 200 leads found / 200 emails sent / 10 calls booked. A 24 second square product launch video, 1440x1440 at 60fps, 2D only, one continuous take that loops. The whole video happens inside the period of the wordmark. Outside it's daytime (the sunny photo behind a black wordmark). Inside it's the night photo under iOS-style glass panels (the blurred photo behind each panel, a tint, a rim light). Nothing cuts: every scene grows out of the last, shapes morph, dots fly, colours change under floods. Every morph glides 0.8s on cubic-bezier(.45,0,.15,1) and the camera zoom rides the same curve. Geist, the real macOS pointer, soft shadows that grow with each shape's height. Banned: flat or gradient backgrounds made in code, camera zooms into tiny points, hard cuts, crossfades between scenes, bouncy springs, particles, glows, holds longer than 1s, cropped type. Beats are the song's. The song enters on its big hit as the first pill appears. Open: the letters slide into the period and vanish into it while it glides to the middle. The period opens like an iris onto the night inside it, and "you log off at 6", then "[product] doesn't", roll through one mask line over the night photo. Ask: a glass "Ask [product]" pill springs in. The cursor clicks it, it glides into an input and the job types out. Find: send shrinks the input to a dot that ripples into a 23x15 grid. A scan line sweeps it, 200 dots light up and a counter counts them. Write: the lit dots pour into a glass email composer. A second, purple cursor labelled "[product]" types a personal opener and presses Send, and the counter runs to 200/200. Night: the composer becomes a glass orb with a progress ring. A clock chip swaps 11:42 PM, 3:17 AM, 5:02 AM, 6:59 AM while the sky relights from night to dawn and "while you sleep" rolls in. Results (beat 20): the orb turns black and goo-splits into the three result pills. The checks pop green. Morning: the pills merge into a Dynamic Island that grows into a phone lock screen: the day photo, the date, a big 7:00, the bezel growing out of the screen edge. Three glass notifications stack in, and the cursor taps the first, which opens like iOS. Proof: a week calendar (10 meetings pop in, a hover shows one's time), then a pipeline chart ($48,200 counts up, the line draws, a hover follows it). A black flood from the line's end becomes "Start your night shift →" and the cursor clicks it. Out: the button shrinks into a dot, the whole scene closes down into it like an iris, and the letters slide back out of the period. The tagline rises. Last frame = first frame. 1. One HTML canvas. Everything is a pure function of time inside seek(t): no timers, no state between frames. 2. One element morphs through every state (size, radius, colour, material) from a table of beat times, so retiming is one edit. 3. Render the inside world into an offscreen canvas and reveal it through the period with a circular mask. Never zoom the camera into the dot. 4. Glass: a pre-blurred copy of the photo clipped to the shape, then a tint and a gradient rim. 5. Goo: blur + alpha threshold on an offscreen layer for the split and the merge. 6. Sound: a downloaded SFX for every event, each placed by its measured peak. The song enters on its hit. Loudnorm to -14 LUFS. 7. Render with Playwright at 60fps with 4 motion-blur subframes. Scan every frame for single-frame jumps and fix each one. A camera zoom into an off-centre dot swings sideways and spikes, so open the dot instead. Ease a closing iris by area, not radius, or its first frames jump. A helper that sets globalAlpha must restore the caller's, or fading cards pop. Counters read the frame's time, not the subframe's, or the digits smear. Ask me for the inputs, then show me the beat map and 6 stills (open, find, write, results, phone, out) before you render.

zero

12,628 views • 10 days ago

You spend hours shooting or hunting down raw footage, only to get back to your desktop and face the real nightmare: importing clips one by one into your editor, spending another 30 minutes digging through music libraries for a track, and manually dragging every single piece onto the timeline... Before you even touch a cut or sync a beat, you’ve already burned half your day. I was honestly so done with this tedious, soul-crushing prep work. Then I saw everyone talking about Fotor’s Fotor Agent, so I threw a folder of raw extreme sports footage at it just to see if it was legit. And damn... I actually got hyped. The action editing headache is finally solved. High-energy sports edits live and die by pacing and audio impact. Usually, manual clip scrubbing and beat-matching take hours, while standard AI generators just slap random footage together into an uneditable mess. Instead of dumping a locked MP4 on me, Fotor Agent’s Smart Editing handled all the brutal prep work and handed back a fully synced, multi-track project file. Here are a few details from my test run that genuinely blew me away: Step 1: Intelligent Highlight Extraction (Auto-Select & Timeline Setup) I dumped gigabytes of raw B-roll straight into the Agent. Zero manual scrubbing needed. It analyzed the motion vectors, pulled the highest-impact peak action frames (the heavy landings, freefalls, and massive jumps), trimmed the dead space, and laid everything out in logical narrative order. Step 2: Auto-BGM Matching + Beat-Syncing + Multi-Track SFX Hunting for tracks and sound design usually makes me want to pull my hair out. Fotor Agent didn't just pick a track with the right energy—it snapped visual cuts precisely to the bass drops. Even better, it automatically layered swooshes, risers, and impact SFX right on the action points, each isolated on its own editable audio track. Step 3: Non-Destructive Tweaks (Swap Clips Without Re-Prompting) This is where it turns into a real production tool. When I wanted to swap out a mountain bike shot for a tighter POV angle, I didn't have to re-render the whole project or re-prompt. I just swapped that single clip right on the timeline, and the Agent auto-adjusted surrounding transitions while keeping the beat sync perfectly intact. Step 4: Native 4K Motion Graphics (High-End Quality for Cents) Action reels look flat without slick animated titles and telemetry data. Keyframing these in After Effects takes forever, and outsourcing them can easily cost thousands. Fotor Agent generated sharp, native 4K vector motion graphics directly on the timeline that I could edit anytime—costing just a few cents per second. On top of that, while tweaking the project, I noticed I could freely stack custom filters and seamless transitions. The final output didn't just look like a quick edit—it delivered a true commercial-grade asset that you could actually hand over to a paying brand client or run as a high-converting ad. No more burning hours on mindless file imports and manual clip alignment. Fotor Agent handles the heavy structural setup and timing, leaving you with total creative control over the final cut. Check the workflow and final video below! 👇🏼

ares. 🎧

27,991 views • 13 days ago

Hollywood has a dirty secret. That perfectly clean green screen shot in your favorite Marvel movie? A human being sat in a dark room for 6 hours fixing it frame by frame. The AI keyer got the body. A person painted every strand of hair. By hand. At 2 AM. For 400 frames. The software costs $5,000 a year. And it still cannot key hair. Nuke: $4,988/year. Cannot key hair in motion blur. After Effects: $264/year. Cannot key transparent glass. Boris FX: $1,865. Cannot key fine edges without haloing. The industry's solution for 30 years has been the same: pay for expensive software, then pay a human to fix what the software couldn't. The YouTubers behind Corridor Crew looked at this and asked a different question. What if the AI didn't try to remove the green? What if it figured out what color was actually there before the green contaminated it? They trained a neural network on synthetic 3D data. Not scraped footage. Not stolen clips. Perfectly rendered scenes where every pixel's true color was already known. Hair strands. Motion blur. Transparent glass. All simulated with known ground truth. Then they fed it real green screen footage. It worked. They called it CorridorKey. Then they open sourced it. → Feed it raw green screen footage → AI reconstructs the true foreground color for every pixel → Hair stays perfect. Every strand. → Motion blur stays intact. Every frame. → Transparent glass stays transparent. → 16-bit and 32-bit EXR output. Nuke-ready. Resolve-ready. → Handles 4K natively → Runs on consumer GPUs. 6 GB VRAM minimum. → Runs on Apple Silicon via MLX → Auto-detects green or blue screen → Removes tracking markers automatically → DaVinci Resolve plugin live → Standalone GUI for non-technical users → One-click installer. No Python setup. Here's the wildest part: Within 2.5 months: 13,000+ GitHub stars. 787 forks. Active Discord. Community built a cloud render farm so you can process footage without owning a GPU. DaVinci Resolve plugin shipped. Nuke and After Effects plugins in development. VFX freelancers are already offering CorridorKey-powered services to production companies. One person. One GPU. Hollywood-quality keys. A business built on free software. Nuke: $4,988/year. Still needs manual cleanup. After Effects: $264/year. Still needs manual cleanup. Rotoscope artist: $50 to $150/hour. For the cleanup. CorridorKey: $0. No cleanup needed. One honest flag: the license is CC BY-NC-SA 4.0. Free forever for personal projects, students, indie films, and learning. Commercial use requires permission from Corridor Digital. They did not pretend it was MIT. A problem that plagued Hollywood for 30 years. Solved by YouTubers. Open sourced for free. 13,000+ stars. 787 forks. CC BY-NC-SA 4.0. Your footage. Your keys. No rotoscoping.

Nav Toor

296,112 views • 5 months ago

ChatGPT 5.5 is cooked. Claude Opus 4.7 is cooked. Every $420/mo SaaS AI just got an open-source assassin. Mind blown: an open-source desktop AI just hit #7 trending overnight, runs 100% on your laptop, ships with 100+ native integrations, and is quietly killing the entire ChatGPT-subscription era. Introducing OpenHuman by tinyhumansai -> your Personal AI super intelligence. Private. Simple. Powerful. Two weeks ago they quietly dropped it on GitHub. Today: 300+ stars, 100+ daily paying users, 1,129 commits, zero marketing budget. > What is OpenHuman? A native desktop agent (macOS, Windows, Linux) that lives on YOUR machine instead of feeding your data back to OpenAI. Download the app, sign in once, and the agent harness gives you 100+ native connectors out of the box: Gmail, Slack, Notion, GitHub, Reddit, Instagram, Calendar, Drive, Telegram, Discord, and dozens more. One click each. From that moment it builds an encrypted, on-device knowledge base of your entire digital life. No terminal. No Python envs. No API keys. No CLI. > What the agent actually does: Steven, the creator, just dropped a Loom showing real prompts: - "Send Mark a joke" -> drafts in your voice and ships it. - "List my top 5 emails today" -> surfaces what matters from a flooded inbox. - "Summarize that thread and email it to the team" -> done in 3 seconds. One prompt --> multiple connected tools --> end-to-end execution. No tab-switching. > What's actually inside: - Screen intelligence -> the agent SEES what's on your screen and feeds it into your local context. - Memory-aware keyboard autocomplete -> system-wide, in YOUR voice, trained on YOUR past replies. Gmail Smart Compose for your entire OS. - Local knowledge base -> every email, message, and note parsed, embedded, encrypted, on YOUR device. Day 30 it knows you better than your therapist. - 75% Rust core -> memory-safe, brutally fast, runs local AI directly on your machine. > The "but wait" moment: OpenClaw and Hermes Agent are excellent. But they live in the terminal. Virtualenvs. SKILL.md files. Shell debugging at 2am. OpenHuman doesn't ask any of that. Their README compares itself to "The Tet" from Oblivion -- that alien superintelligence Morgan Freeman calls "a brilliant machine". And tomorrow they're dropping the official OpenHuman mascot. Sneak peek already in Steven's Loom. The cloud-first AI decade is ending. OpenHuman is GPL-3, fully auditable, shipping a release every few days. Save this -- you just got the link to the thing replacing every SaaS AI on the market. -> Repo:

slash1s

71,250 views • 5 months ago

OPUS 5.5 IS THE ONLY MOTION DESIGNER YOU NEED this launch video cost $0 and is pure code everyone else on X claims the same shit, then sends you to their website or mcp this is completely free with 0 external tools steal the prompt and try it in your claude ↓ Ask me for: a one-word brand name for the wordmark (a verb works best), 9 to 12 high-res photos, a royalty-free song around 120 BPM with a drop and a quiet breakdown (Mixkit, free for commercial use), and a free stock clip of a plain wall with moving plant shadows (Pexels). An Apple-keynote launch film, 2D only, one continuous take. Every scene is made out of the previous one: nothing fades, blurs or cuts. Objects change shape instead: text rises out of a mask line, icons pop from zero on a spring, bars draw across, pages push, and a black shape floods the whole frame and contracts into the next scene. Warm off-white canvas, black UI, iOS 26 liquid glass over the photos. Archivo (wdth 125, weight 800) for the wordmark, Geist for UI. A cursor drives every change with real clicks, drags and long-presses. The camera zooms screen-studio style so each moment fills the square, and the cursor scales with it. Banned: crossfades, blur-ins, brightness "developing", 3D flips, particles, glows, holds longer than 1s, anything that looks like a template. 120 BPM, 54 beats, something happens on every beat. Open: the wordmark squeezes into its own period like an accordion, the dot grows into a black pill, a label rises inside it. Click: six iris blades close over the label and snap open onto a photo. The circle becomes a square, shrinks, the grid unfolds from behind it like a paper map (center, plus, corners), reflows into a bento, and a click zooms into one tile, landing exactly on the drop. Glass: a glass word pops in letter by letter, melts into a droplet that stretches into a glass toolbar. The adjust icon turns it into a slider. Dragging relights the photo from day to golden hour (two aligned shots), and the knob turns into a glass lens while held. It lifts into a glass orb, the next photo opens inside it as a circle, and the orb expands into a lock screen: glass clock digits, date, and a home bar that stretches into a glass music player. Stage: the lock screen pulls back into a phone (the bezel grows out of the screen edge). The Dynamic Island stretches like liquid, pinches off, flies over and grows into a Mac window that rolls up like a blind. Long-press the wallpaper, drag it onto a Safari tab, the page pushes in, drop it and it becomes the hero of a landing page. Scroll: the hero morphs into a framed print on a product card, with the mat and molding growing out of the photo's edge. Pick a frame color (it paints across) and a size, then the nav button flies down into "Order print". Order: one black shape keeps morphing: Ordered ✓ → Printing % → On its way (a van on a route) → Delivered ✓. Wall: the delivered circle floods the frame edge to edge, holds black for a beat, and contracts into the framed print hanging on the real wall footage. The same iris opens onto the print, closes again, the frame floods the screen and contracts into the pill → the dot → the letters spring back out, landing on the beat return. Last frame = first frame. 1. One HTML file, square 1440x1440. Every style is computed from time inside an async seek(t): no CSS transitions, no timers, no state between frames. 2. Springs are closed-form step responses. A value with many targets is the sum of one spring per change, so it stays a pure function of time. 3. Liquid glass: each glass element holds its own clone of the scene behind it, filtered with an SVG feImage displacement map (a rounded-rect distance field) through three feDisplacementMaps at slightly different scales for chromatic edges, plus a rim light. Glass letters: a canvas distance field per glyph gives the map, mask and highlights. 4. Goo: blur + alpha threshold, then composite the source atop it so the glass stays sharp inside. 5. Iris: 6 blades around a hexagonal aperture. Each blade is its two vertices, both edge extensions and the SHORT arc between them. 6. Wordmark squeeze: every letter moves toward the dot by the same factor and its drawn width follows (narrow the wdth axis, scale the rest), so the letters stay touching. 7. Footage: re-encode all-intra (ffmpeg -g 1), load it as a blob URL, await 'seeked' before drawing each frame. 8. Sound: a downloaded SFX for every event (Mixkit), never synthesized, each placed by its measured peak. The song starts on a downbeat: the zoom lands on the drop, the wall sits in the breakdown, the wordmark returns with the beat. Loudnorm to -14 LUFS. 9. Render with Playwright: 4 subframes per frame blended with ffmpeg tmix, 60fps. Check one frame per beat, then scan for single-frame pops (frame-difference spikes 3x their neighbours). backdrop-filter: url() misreads displacement maps in Chromium, so clone the scene instead. A flood must overscale past the corners and take about 0.3s, or half the screen changes in one frame. A child with visibility: visible shows through a hidden parent, so use inherit. Text that swaps inside a morphing shape needs its own mask. python http.server can't range-seek video, so use the blob URL. Ask me for the inputs, then show me the beat map and 4 stills (open, glass, stage, wall) before you write the full film.

zero

136,283 views • 15 days ago

I built an operating system where the AI agent isn’t another app. It’s part of the OS. Today, Herald OS is open source and you can install it yourself 🚀 It’s built around Hermes Agent by Nous Research. Talk or type to Hermes and it can work across your entire computer: • Open and use apps • Find, organize and work with your files • Remember what matters • Run routines and automations • Build software while you watch • Understand what’s happening on your screen • Work across the machine instead of being trapped inside a chat window And when something is about to make a change, you approve it first. 🎙️ Talk to your computer Say “Hey Hermes” and just talk. Native OS commands don’t need to burn model tokens. When you actually ask the agent to think, build or perform a task, that’s when Hermes gets involved. ⚡ Everyday superpowers • Select any part of your screen and ask Hermes about it • Pick a colour from anywhere • Read a QR code from your screen • Copy text from anywhere on screen • Emoji in any app you type in • When an app crashes, Hermes explains what happened in plain English • One-click installs for Claude Code, Codex, local models and more 🐧 And yes, Herald OS Linux is an actual operating system • Fedora underneath, Herald on top • OS and Herald update together as one system • Roll back an update if something goes wrong • Wi-Fi, Bluetooth, sound, display and battery controls • Screen recording • Night light • Fingerprint and security-key sign-in • Firewall closed by default 🎨 Make the entire OS yours Themes don’t just change a wallpaper. They can restyle the whole system, including the terminal. Drop in any photo and build a theme from it. Or describe what you want and let Hermes design one. You can also: • Ask Hermes to create a widget, then choose exactly what that widget is allowed to access • Drag the menu bar into the layout you want • Create your own menu entries • Put your own logo in About 💻 Run it almost anywhere • Native Mac app for Apple Silicon • PC installer from a USB stick • Arch Linux package • Omarchy integration where Herald follows your theme and adds itself to the menu and keybindings • Or boot the full Herald OS inside a VM on your Mac with one command It’s free, open source and MIT licensed. It’s also still alpha, so expect rough edges. This is an independent project and is not affiliated with Nous Research. I’ve been building toward this idea for a while: Instead of opening an AI app on your computer, what if your computer itself understood what you wanted? Now you can try it ⭐

Luke The Dev

96,173 views • 5 days ago

No f*cking way, I just built this web crawler from one single prompt with Opus 5.5 it can: - follow your cursor across any page - crawl the text and glitch every word it steps on - pull out the key sentences as it walks - build a short TL;DR in real time while you scroll - take any article you paste in and do the same here is the prompt: Build a Chrome extension (Manifest V3) called "TL;DR Crawler" that works on any normal web page. WHAT IT DOES Click the toolbar icon: a line-drawn spider appears on the current page, follows your cursor (also while scrolling), reads the text it walks over and builds a short TL;DR in a floating panel. Click the icon again: everything disappears and the page is exactly as before. 1. TOGGLE - background.js: chrome.action.onClicked injects content.js with chrome.scripting.executeScript. - content.js checks a global flag. If the crawler is already running, it shuts down and cleans up. Otherwise it starts. Only one instance per tab, ever. 2. FIND THE TEXT - Find the main readable area: prefer or , otherwise the element with the most paragraph text. Skip nav, header, footer, aside, menus, forms, code, ads and hidden elements. - Collect text blocks (p, li, blockquote, h2-h4) and split them into sentences. Store each sentence as a DOM Range (sentences can span links and bold text, so do NOT wrap them in elements). - Watch the area with a debounced MutationObserver (1s) to pick up text loaded later (infinite scroll, lazy content). 3. PICK KEY SENTENCES - Score each sentence: +2 digits, +2 for %, $, €, million, billion; +1.5 for words like first, record, launch, announce, new, only, biggest, fastest, warns, raises, cuts; +0.3 per capitalized name (max +2); -2 if under 40 or over 260 characters. - Mark the top 25% as key sentences (min 5, max 80), spread so most paragraphs get one. - Summaries, max 9 words each: - If an API key is set: send all key sentences in ONE request to Claude and ask for a JSON array of short, plain summaries (max 9 words, keep numbers and names exactly, no hype). Request again in batches when new text appears. - Without a key: fallback summary = the sentence with filler openers removed (and, but, however, also, according to), cut at a word boundary with "…". 4. THE SPIDER - Shadow DOM host at document root containing a full-screen fixed (pointer-events: none, z-index 2147483646) and the panel. - Look: small rounded-rectangle body, abdomen ellipse, head with two white eyes, outlines in #5ab8ff. 8 legs as 3px blue lines with pink (#ff4f7a) joint dots, two segments each with inverse kinematics, knees bending outward. - Gait: two alternating leg groups. A foot steps only when it's ~80px from its ideal spot and the other group is planted. Steps last 0.13s with a small lift, landing slightly ahead in the walking direction. - Movement: target = cursor position + scroll, so it follows while scrolling. Max ~420 px/s, smooth acceleration, stops ~40px from the cursor, turns smoothly toward its direction. If the cursor is idle for 8s, it wanders around the viewport. - requestAnimationFrame with a fixed 1/120s physics step. Support devicePixelRatio and window resize. 5. CRAWLING - Every 80ms and on every foot landing, find the text under the spider with document.caretRangeFromPoint (ignore the extension's own elements). - If that point is inside a key sentence not yet found: highlight it with the CSS Custom Highlight API (::highlight(tldr-found) with a soft yellow background) and add its summary to the panel. - If a foot lands on a normal word: in ~25% of cases glitch just that word. Wrap only that word in a span (it's a single text node, so it's safe) and apply one random effect: monospace font, blue outline, blue highlight, slight rotation, wide letter-spacing, blur or uppercase. Max 2 effects per word. Record every change so it can be undone. 6. PANEL - Top-right, draggable by its header, inside the Shadow DOM so site CSS can't affect it. - Dark (#16181c), mono title "TL;DR" in yellow (#ffd166), a "found / total" counter, a pink progress bar and a numbered list in article order. The newest item flashes yellow and the list auto-scrolls to it. The list scrolls inside a max height. - Buttons: "Copy TL;DR" (plain text to the clipboard), "Restart" (clears highlights, glitches and the list) and "Close" (full shutdown). - If a key is set, add "Write TL;DR with Claude": sends all found sentences and returns 3 short lines using only their facts, numbers unchanged. Show a "Thinking..." state, then the answer under the list. 7. API KEY - options.html: a field for the user's Anthropic API key and a model name, stored in - All API calls go through background.js with fetch to with headers x-api-key, anthropic-version: 2023-06-01 and content-type: application/json. - Handle errors quietly: if a call fails, keep the fallback summaries and show a small "AI unavailable" note. 8. QUALITY RULES - Never break scrolling, clicks, links or text selection on the site. - Full cleanup on shutdown: canvas, panel, highlights, wrapped word spans, inline styles, listeners, observers, timers. - prefers-reduced-motion: no glitches, slower walking. - Plain JavaScript, no libraries. Files: manifest.json, background.js, content.js, options.html, options.js, icons (16, 48, 128). - Permissions: activeTab, scripting, storage. Host permission: At the end, give install steps: open chrome://extensions, enable Developer mode, click "Load unpacked", select the folder, then open options and paste the API key.

Anatoli Kopadze

25,655 views • 9 days ago

google just released 15 AI tools that are completely FREE and can save thousands of $$$ every single monthly. all open-source. MIT licensed. save this in your bookmark." 1️⃣ pomelli ( builds your entire brand identity from just your website URL, then generates on-brand social posts, campaigns, and images. a free jasper + a junior brand marketer. no watermark, no gen cap in beta. 2️⃣ stitch ( describe an interface, get production-ready HTML/CSS/Tailwind + a figma export. google's free figma killer. 350 designs a month without paying a cent. 3️⃣ opal ( build no-code AI mini-apps and multi-step workflows just by describing them in plain english. basically a free n8n with Gemini baked in. no usage caps. 4️⃣ antigravity ( agentic IDE that plans, edits across files, and builds full apps from a single prompt. the "cursor-killer," free tier runs Gemini 3 Pro + Claude Sonnet 4.5. 5️⃣ mixboard ( canva x pinterest for AI. generate and remix images into moodboards, then edit right on the canvas with plain language. free while in beta. 6️⃣ disco ( turns your messy open browser tabs into custom interactive AI apps. competitor tabs become a comparison matrix, travel tabs become an itinerary. zero code. 7️⃣ notebookLM ( upload PDFs, videos, and notes, get instant summaries, mind maps, quizzes, even a podcast of your own material. replaces notion AI + perplexity + readwise. 8️⃣ Learn Your Way ( turns any topic into a personalized, AI-built course. immersive text, audio lessons, mind maps, and quizzes adapted to how you actually learn. free tutoring. 🔟 Google AI Studio ( prototype and ship AI apps in seconds with a free API key and a 1M-token context window. replaces the openai playground + paid API credits. 1️⃣1️⃣ Jules ( assign it a github issue, it spins up a VM, writes a plan, makes the changes, and opens a PR. a free devin. 15 tasks a day. 1️⃣2️⃣ Gemini CLI ( claude-code in your terminal. reads your codebase, runs commands, ships PRs. genuinely open source (Apache 2.0) and free. 1️⃣3️⃣ Code Wiki ( point it at any public github repo, get a living, self-updating wiki with architecture diagrams and a Gemini chat, every section hyperlinked to the code. 1️⃣4️⃣ Firebase Studio ( AI cockpit for your backend and cloud logic. heads up: existing users only, google is winding it down, so don't start a new project here. 1️⃣5️⃣ Gemini Code Assist ( free github copilot: 180k code completions a month + AI code reviews in VS Code, JetBrains, and github. the free tier that actually out-specs copilot. Follow me and turn on 🔔 post notifications.

m0h

92,514 views • 2 months ago

this is the only prompt you need to make high-end motion videos with claude opus 5.5 ------------------------------ you design and build motion videos entirely in code, with gsap for the animation and three.js for any 3d. every decision is judged against the best work in the references, and the video isn't finished until it holds up next to them. - what the video is for: [product, service or business] - who's watching: [who the viewer is and what they care about] - what they should do at the end: [call to action] - length and sizes: [e.g. 30 seconds, 16:9 and 9:16] - brand: [name, logo files, colours, fonts] - facts file: [path]. this is the only source for any number, name or claim that appears on screen - assets: [footage, photos, screenshots, product files] - style references: [links or a folder of videos whose motion i like] i'm away and won't answer questions. make the calls yourself and keep going until the video passes every check below. before anything else, clone and read read SKILL.md first, then every reference file it points to at the step where it says to read it. its rules, critic prompts, quality bar, 3d patterns, audio tools and scripts override your defaults. - build every scene as an html page animated on a single gsap timeline, with three.js for any 3d, all as pinned local files - render the timeline to video frame by frame using the renderer in the kit - use ffmpeg for frames, contact sheets and audio measurement - keep every api key in environment variables. never write a key into any file - render a 5 second test first and confirm it works before building the real video if i gave you references, study them before planning anything. - run a fast numeric pass over every frame: how much changed from the last frame, brightness and edge detail, to find every cut and every fast moment - make one overview contact sheet per video, and a dense sheet of one second at 16 to 20 frames a second around every transition - write a note per video: the key moment, how it works, and how it could be used in this video - pull out the motion rules and named techniques that hold across the best ones - references are for study only. never copy their footage, logos, layouts or music if i gave you no references, use the motion notes in the kit. 1. the thing in the front of the shot becomes the transition. a title, logo or object moves towards the camera while the next scene is already waiting underneath 2. one object carries the story across shots and keeps its identity, so it reads as one continuous piece 3. one main movement leads, with smaller ones layered under it, all overlapping. the frame never stops and starts all at once 4. the speed always changes. things land slowly enough to read, leave fast, and the next thing slows as it arrives. no linear motion 5. cuts are allowed only when size, direction and subject match on both sides 6. every action produces a visible result. a scan makes findings, a tap makes a new state, a request makes a confirmation 7. type is motion too. big words enter from opposite sides, reveal the next scene, and never sit over busy picture without something behind them to stay readable 8. vary the scale from close, to wide, to overhead, to full-frame type. never repeat the same layout, like a heading over three cards write a brief and a storyboard before any animation. - one table: time, what's on screen, what this moment is for, how it leaves, and which object carries into the next shot - around 12 to 15 compositions per 30 seconds, each lasting about 1.4 to 3.5 seconds - the main subject fills most of the frame. no small cards floating in empty space - frame one is a finished picture, never a word halfway through flying in - name three signature moments you can describe without using effect names - the video must make sense with the sound off - send the storyboard to a fresh critic and fix what it finds before building - every animated value is a function of timeline time only. no timers, no real-time animation, no unseeded randomness. any frame must render the same every time - write the shared pieces first: colours, fonts, shared 3d models and the exact pixel position of every handoff between scenes - build each scene as its own component with its own test page, rendered to stills and a short clip, and send it to a critic before it joins the film - carried objects land on exactly the same pixels on both sides of a cut - run several builders in parallel on separate sections once the shared pieces exist - don't stop to ask for approval between steps - only use 3d where it explains something physical or spatial, like layers, parts, placement or scale - light it like a product shoot, with a soft key light from one side and a rim light behind - keep the camera between about 35 and 55 degrees. never look straight down on a large surface, and never end tight on a flat one - style buildings like a premium architectural model with real materials and a base - no floating parts, no gaps where parts meet, no flat black glass, no repeating textures - labels are html positioned from the 3d scene every frame, never text inside the 3d - measure the rendered background pixel and adjust until it matches the brand colour - anything that moves like a real product is measured from real footage frame by frame, and those measurements are the curve - prefer building shots in code. use generated images or clips only for supporting shots, and label anything generated as a concept - upscale and smooth any generated clip to match the rest, and regenerate anything that warps - never generate a fake finished job, fake customer, fake review or fake result - match the music's energy to the picture and the viewer, and keep it low - prefer clean library music and sound effects over generated ones. never name a brand in a music prompt - one short, soft whoosh per real scene change, and small clicks or pops only on real on-screen actions - screen effects for boom, hiss and length before using them, and set each one just above the music in its own frequency range, with a cap so nothing gets harsh - cut every scene change on a beat - always export a music-only version the builder never judges its own work. - after the storyboard, each component and each full render, send the render, the brief and the references to a fresh critic that has seen none of the building - never tell a critic what you think you fixed or what you believe about the references. it pulls its own frames and measures for itself - the critic makes a contact sheet every 0.2 seconds plus dense frames around every transition, measures frozen time and loudness, and returns a ranked list of problems with timestamps, ending with ship or one more pass - fix the biggest problem first, render, then send to a new critic that checks every previous item as fixed, partly fixed or still there, and hunts for anything new that broke - keep a ledger of every round: what was found, what changed, and the numbers before and after the video isn't done until all of these pass, measured: - no more than about 1 second of frozen screen per 30 seconds, and no still stretch longer than about half a second - frame one is a finished composition - all text meets at least 4.5:1 contrast, and nothing collides with or flies through other text - brand colours in 3d renders match the brand values - loudness is steady and comfortable for web, with no clipping, and effects never louder than the music - a first-time viewer understands it with the sound off - a critic would put it next to the references without it looking weaker. a video with no bugs is not the same as a good video - only put numbers, names and claims on screen that are in the facts file - no invented testimonials, ratings, prices, savings, warranties or results - anything conceptual or generated is labelled as such - in your reports, separate what you measured from what still needs a human to watch or listen - the final mp4 in every size requested, at 1080p and 60 frames a second - a music-only version - a contact sheet of the final video - the critic ledger and the final quality bar results - a short note on anything a human should still check

Chris

125,775 views • 12 days ago

Introducing Wikiwise: an open-source Mac app for managing your own Karpathy-style LLM wiki. Set up a new wiki in a few clicks: all you need is Wikiwise + your agent. It's infinitely customizable, just markdown/html under the hood, and one click to share your wiki publicly. Here's how it works: * Install Wikiwise for mac (it's built in Swift so super minimal and performant). In Karpathy's framework, Wikiwise is your IDE. * Start a new Wiki: it generates a new folder on your machine that's scaffolded in the wiki structure Andrej Karpathy describes (index.md, raw folder, wiki folder, CLAUDE.md/AGENTS.md, although it tries to be as un-opinionated as possible). * Then just point your agent (Codex, Claude Code, Cursor, etc) at the folder and tell it what to import -- files on your machine, connect to your Readwise account, or urls from the web. * Your agent creates wthe wiki for you: Your agent will know how to ingest your raw sources (via the AGENTS.md) and will immediately start writing+linking wiki pages for you. * Go crazy on customization! The rendered wiki pages live as static html/css in your folder too so just tell your agent to change stuff, and if you need any more customization Wikiwise is fully open source :) * Ask questions about your research with your agent, ask it to bring in new sources, write new documents, etc. * (optionally) Hit the Publish button to share your wiki with friends/colleagues at a custom URL === I tried to walk the line on a couple constraints with Wikiwise: 1. I wanted it to be easy to spin up new wikis, especially without chaining together a bunch of different apps. It takes me a few minutes to spin up a new wiki on a topic -- I already have five! 2. Infinitely Customizable: one great aspect of building a wiki as Karpathy described is that you can modify any aspect of your wiki with your agent. Every new wiki styling+structure is self-contained in the local folder, which allows you to preserve this. Wikiwise is just an IDE that makes the setup easier and includes a nice un-opinionated starting state. 3. Minimal: Wikiwise is built mostly in Swift, and the DMG you install to download it is only 2.6MB (!) 4. Easy Publishing: my colleague Eleanor Konik has been building her own LLM wikis for months, but has always really struggled to actually share them with her book club. There are tools to do it, but figuring out hosting is always a huge headache. This seemed like an ideal usecase for a tool like Wikiwise to solve. The process of building wikiwise was also pretty interesting -- I "bootstrapped" the app in a way by first building my own wiki based on Karpathy's tweet and other notes I had, and slowly formed the shape of the project in collaboration with my LLM. This was all done in 3 days over the latest Readwise company hackathon we had. Truly an incredible time to be alive. Anyways, curious what you think! Links in next tweet.

Tristan

96,906 views • 6 months ago

The Great Equalizer: How I Iterated Through 90+ Strategies to Automate My Financial Freedom ninety strategies sounds like a death wish but it is actually the only way to find your edge in a market designed to liquidate you. most traders are out here gambling with their rent money while the big players are using automated systems to harvest their liquidations. i know this because i spent hundreds of thousands of dollars on developers for apps thinking i could never code myself. i was getting wrecked by over trading and watching my accounts hit zero while i slept. code became the great equalizer for me because it removed the emotion that was killing my bankroll. i decided to learn to code live so i could iterate to success and now i have fully automated systems trading for me instead of getting liquidated by every wick. i just saw someone lose ten million dollars in a single month because they were trading by hand and got addicted to the screen. you have to understand that if you are not automating you are the exit liquidity for someone who is. the reality of advanced futures trading is not about finding one holy grail bot that prints money forever. it is about research and back testing until you find a strategy that has a statistical advantage. one of the most slept on concepts is variable risk scaling where you actually change your position size based on how volatile the market is. instead of just betting the same amount every time you increase your size when volatility is low and scale back when the market starts moving like crazy. this keeps you in the game during the draw downs that usually wipe people out. most people do the opposite and revenge trade with bigger size when they are losing which is the fastest way to the cemetery. i used to think i needed to be the smartest guy in the room to make this work but i realized i just needed to be the most disciplined with my risk parameters. there is a secret hidden in funding rates and basis trading that most retail traders never even look at. while everyone else is trying to guess if bitcoin is going to the moon or the floor you can actually make consistent money through funding rate arbitrage. you basically buy the asset in the spot market and simultaneously sell it in the futures market when the funding rate is high. you just sit there and collect the interest payments from the gamblers who are over leveraged on the other side. it is basically free money if you can manage the fees and keep your execution precise. i used to ignore these low yield plays because i wanted the big home runs but those home runs usually came with massive strikeouts. now i look for these carry trades as a way to keep the equity curve moving up and to the right while others are sweating over every price change. most traders fail because they use lagging indicators and expect them to predict the future with one hundred percent accuracy. the truth is that even the best trend following strategies like the golden cross or moving average crossovers only have about sixty five percent accuracy. you have to combine these with filters like the average directional index or relative strength index to make sure you are not just buying a fake breakout. a lot of people get chopped up in sideways markets because they do not have a trend strength filter to tell them to stay out of the trade. i learned to use multiple time frames to confirm my breakouts because if the one hour and the four hour charts are not saying the same thing then the trade is probably a trap. you have to be a searcher looking for those golden nuggets of alpha buried in mountains of data. i used to think that machine learning and genetic algorithms were just buzzwords that did not actually work for trading. then i realized that the 1990s tech trap is real and if you are still using basic indicators without any optimization you are decades behind. genetic algorithms are wild because they simulate natural selection to find the best parameters for your strategy through trial and error. you can actually build an environment where your bot learns from its own mistakes and optimizes its decision making process over time. i spent so much time thinking i was not smart enough to do this but once i started iterating live i found that the machines are much better at following rules than i ever was. code is the only way to compete with the high frequency firms that are looking for any tiny mispricing in the order book. slippage and bad execution will eat your profits faster than a bad trade ever could if you are not careful. most people just hit the market buy button and pay the spread and the fees without a second thought. you should be using smart order routing and limit orders to capture the bid ask spread instead of paying it to the market makers. i started using time weighted average price execution to spread my larger orders out over time so i did not move the market against myself. it is these tiny details in execution that separate the professional quants from the people who are just playing around. i had to learn this the hard way after losing a fortune on bad entries and exits that could have been avoided with a few lines of code. the ultimate goal of all of this is to build a compounding machine that grows your capital while you are living your life. you have to automate the reinvestment of your profits so that your position sizes grow as your account grows without you having to manually adjust anything. i like to use automated compounding algorithms that take a portion of my wins and put them back into the systems that are performing the best. this creates a snowball effect where your returns start to accelerate as the base capital increases. it took me years to realize that i did not need to be at the desk for eighteen hours a day to make life changing money. i just needed to build a system that was smarter and more disciplined than my own human brain. cross asset skew and volatility surface arbitrage are where the real quants play when the market gets efficient. you can look for mispricings between highly correlated assets like bitcoin and ethereum and trade the spread between them. when one asset gets overvalued relative to the other you short the leader and long the laggard until they revert back to the mean. this is a much safer way to trade because you are not betting on the direction of the market but rather the relationship between two assets. i spent a lot of money trying to guess the next big move before i realized that trading the relationship between assets was much more consistent. iteration is the only way to find these winks in the market that the average trader is completely blind to. it is a cold world in finance and most people are out here trying to step on your neck to get ahead. i believe that sharing this knowledge is important because code is the only thing that can give a regular person a fighting chance against the institutions. i started from zero and learned everything through failing and losing money until i finally figured out how to automate. now i spend my time building and testing instead of worrying about the next liquidation candle. you have to decide today if you want to keep being the exit liquidity or if you want to start building your own systems. the tools are all there and the data is accessible if you are willing to put in the work and stop negotiating with yourself. successful trading is not about being lucky it is about being prepared and having a system that can handle any market regime. whether the market is in a bull run or a total crash your bots should know exactly what to do based on the rules you have coded into them. i use risk weighted allocation to make sure that my capital is always moving toward the strategies with the highest sharp ratio and the lowest volatility. this keeps the portfolio stable even when the crypto market is going through its typical insane swings. i finally found peace in this game because i know that my automated systems are following the math while everyone else is following their feelings. code is the great equalizer and it is time for you to start using it to protect your future and build your empire there are over ninety strategies you can test and most of them will not work for your specific style but you only need one or two to change your life. i have built a fat list of ideas from research and i spend every day back testing and refining them to stay ahead of the curve. do not let the fear of coding stop you from taking control of your financial destiny because i am living proof that anyone can learn. i would rather spend my time iterating to success than getting liquidated by some random news event that i could not predict. the journey from losing hundreds of thousands to fully automated success was long but it was the best investment i ever made. keep your heart open and lead with love in this game and i promise the universe will start passing you those golden nuggets of alpha you have been searching for

Moon Dev

11,196 views • 7 months ago

I was the biggest skeptic of AI video editing. Until recently. So I asked one of the most talented creators I know (Anthony Dupont-Cinko) to break down exactly how AI can support the entire video process. The guy cooked. Here are the high-level notes: The tl;dr Right now AI mostly solves two genres. The video essay and the tutorial. Both have a straightforward outline, a script you stick to, and a one-shot record that AI can chop against. Other formats still lean heavily on craft. Easy Mode: research and ideas without losing your voice The gist: Use AI to find opportunities and pull source material from tools and team discourse. You still decide what is worth saying. Don't outsource final sign-off. Pro tips: - Marketplace is huge. Type YouTube and you will see VidIQ, TubeBuddy, and a pile of others. If your company shows a “request” button, go bug the admin. Do not wait on the queue. - Hook Ahrefs into Claude (and Notion) and ask something like: use the Ahrefs connector to find AI content opportunities this week, and tell me if videos already sit in the top five. - Tribal Knowledge is the other half. It is a skill that scrapes every connector he has (Slack, Notion, meetings) and surfaces real conversations around a topic so the idea comes from work talk. - Turn that into a personalized daily brief for the kind of content you make. Anthony built a content planning app with Codex. Every day it drops a brief, proposes video topics, and lets him queue the ones he likes. Notion is the shared backend so the org can see the same database without living in his app. Even on Opus, a daily brief runs about 8 cents. Hard Mode: script and first edit with AI assistants The gist: AI helps you outline and cut. You keep the words, the takes, and the judgment. Editing is not just the blade button. It is taste. If you are an editor, you have an advantage. If you have vision but not technical chops, you can still leverage these tools. Pro tips: - Create the outline as a human. Anthony still believes you should not let AI one-shot structure. His format is three columns: dialogue, visuals (what is on screen while you talk), and sound effects. - Then use the Scriptwriter skill. Point it at a topic (he demoed “what is an MCP”) and it interviews you through the whole creative process so you speak like yourself. Short-form or long. You can ramble, go out of order, contradict yourself. It sorts after. - Beat by beat it spits your words back as bullets. You react raw in the moment. Those reactions become the real script. It also prompts visuals and SFX while you talk (day-to-night, crickets, rooster) so creativity stays in the loop. Hooks are hard. You can ask it to interview you into a better hook without handing it the whole voice. *Film it yourself* - Split editing into phases. Baseline “radio cut” (dialogue paced). Then VFX / archival / B-roll. Then audio (dialogue mix, SFX, music). - Codex + Final Cut: pointed it at the footage and the script, asked for a baseline cut. First pass had half-second gaps of silence. One follow-up (“every clip is consistently half a second off”) and it produced a fluid cut with no awkward pauses, dropped straight into Final Cut. Cost: two prompts burned a big chunk of a 5-hour context window (100% down to 14%), but against weekly Codex usage (decks, research, more content) he still had about 53% left. - Codex in Final Cut won the radio cut. Descript was faster on the clock and worse on taste cleanup. God Mode: polish stack plus a measurement loop Definition: hand off the laborious extras (B-roll, motion, music, reporting). Keep the taste calls. Close the loop so you know if the work is working. Pro tips: - B-roll / archival / VFX: Anthony spun an “archival finder” agent. He gave it a vibe (internety, clicky, fun) and a reference (simple, warm, approachable using shows, TV, movies). It came back with taste. - It also downloaded clips, filed them, dropped them on the timeline, and added a paper texture background he had asked it to design. All via the Final Cut connector plus computer use. - Motion graphics: Remotion (free, open source) plus an agent. Dump everything in your head. Ask for a plan and structure first. He asked for an Apple liquid glass ultra-clean feel. Plan, approve, tweaks, then it popped into the Final Cut timeline in about 9 minutes 10 seconds. That used to be a brief to a VFX designer (timing, seconds, design, wait for turnaround). - Music and SFX: Epidemic Sound via MCP (Artlist and free-sound options exist too). Same pattern: send the URL if you need to install, give it a creator reference (he used Zoe), iterate because you are picky about music. It dropped tracks into the timeline and used Epidemic’s crop/trim so the music was cut for the edit. Mix sat under vocals instead of overpowering them. Not just music. Mouse-click SFX timed to B-roll. Full episode:

Alex Lieberman

22,512 views • 23 days ago

People have been asking how I'm generating my product videos. Here's a prompt my agent wrote so you can copy its process: # Prompt: make product videos with code and AI agents Copy everything below the line into a coding agent (Claude Code, Codex, etc.). Fill in the `{{…}}` placeholders first. It describes how Inbox Zero produced its landing-page hero, launch films and about 15 docs and app walkthroughs, each costing well under $1 in API calls. --- You are producing product videos for **{{PRODUCT}}** ({{ONE-LINE DESCRIPTION}}). The videos are a landing-page hero (~55s), short launch films (25–40s) and feature walkthroughs (45–110s) for the app and docs. They are made entirely with code: there's no screen recording and no video editor. Quality matters far more than cost. The product's source code is at `{{APP_REPO_PATH}}` and its docs are at `{{DOCS_PATH}}`. The founder or reviewer is {{REVIEWER}}. They give taste feedback, and you turn that feedback into written rules. ## 1. Core idea Every video is an **HTML/CSS/JS page whose every frame is a pure function of time `t`**. Headless Chrome screenshots each frame, and ffmpeg encodes them. This gives you: - Exact, repeatable renders: a copy change means a cheap re-render, not a re-edit. - Parallel rendering, because nothing carries over from one frame to the next. - Real product UI, because the "footage" is real DOM captured from the running app. Don't use Remotion or any other video framework; a ~200-line engine is enough. Don't screen-record: recordings can't be re-timed, re-worded or kept pixel-perfect. ## 2. Set up a private video repo Create a **private** repo (e.g. `{{ORG}}/demo-video`) separate from the product repo. Its layout: ``` AGENTS.md # read-first notes for every agent: pipeline, taste rules, mistakes made README.md # catalog: every video, its branch, length, status, where it's used BRIEF.md # product truths, fictional cast, kit API, end-card and taste rules EXPLAINER.md # brief for the walkthrough format LAUNCH.md # brief for launch films MUX.md # hosting IDs for every published video engine.js # renderAt(t), addScene, spring/easing helpers, word-by-word captions render.mjs # parallel Playwright frame renderer → ffmpeg # voice + music mix with ducking and loudness normalisation judge.mjs # audio judge (picks the best TTS take) vjudge.mjs # video judge (reviews a whole render) # contact sheet from sampled frames kit/app/ # REAL app screens captured as DOM snapshots (see §3) kit/explainer.js # overlays: step captions, callouts, highlights, camera, cursor, typing, toasts, # and mocks of third-party UIs (Gmail, Outlook, Slack, …) kit/endcard.js # shared end card music/ # shared music bed(s) tools/ # upload scripts (hosting), helpers ``` **One branch and one git worktree per video** (`git worktree add -b explainer-foo ../demo-explainer-foo main`). `main` holds only shared things: the kit, the briefs and the tools. Merge `main` into a video branch to pick up kit fixes. Put kit fixes found while making a video in a separate commit so they can be cherry-picked to `main`. Commit each video's web encode, poster, `.vtt` captions and a `VARIANT.md`. That file holds the script, the timings, chapter markers, the claim checks, and any docs-vs-UI discrepancies found. Git-ignore masters and intermediate files. Keep `AGENTS.md` alive. Every time the reviewer gives feedback, or an agent makes a mistake, add a one-line rule there. This file is what makes the tenth video good on the first try. ## 3. Capture the real UI kit 1. Run the app locally with a **seeded database of fictional data**: one consistent cast (a main user plus 4–5 contacts and a fictional company), and realistic but fake emails, events and numbers. Use local emulators for third-party APIs where possible. 2. Write a capture script (Playwright) that visits each screen and state the videos need. It saves the **rendered DOM plus inlined CSS** as a standalone HTML snapshot, plus a PNG for reference. Inbox Zero ended up with ~140 states. 3. Missing states can be **derived** from the nearest snapshot by editing the DOM to match the real component's source (text, classes), never invented. 4. **Audit every snapshot for leaks** before committing: real names, emails, avatars, API keys, and the capture machine's **timezone and locale**. A real city name once leaked through a timezone picker. 5. Document the states, selectors and how to recapture in `kit/app/README.md`. ## 4. Write the script (accuracy first) - Read the docs page and **the app source** for the feature. Every label, button and step on screen must match the product. Where the docs and the UI disagree, the UI wins; log the discrepancy in `VARIANT.md` and fix the docs afterwards. (This produced a steady stream of real docs fixes and bug reports.) - Check claims in code, not just in the docs. For example, does feature X actually use data Y? - Keep a list of **product truths** in `BRIEF.md`: supported platforms ("always say Gmail *and* Outlook"), trial terms, and what is early-access. - A walkthrough has a 1–2s product payoff up front, then numbered steps (one caption each), one result shot, and a minimal end card. - **Intro messaging** (hero and launch) must say what the product *is* in the first line. Write several candidate openers and let the reviewer pick. ## 5. Build the timeline - `engine.js`: scenes are DOM subtrees shown and hidden with `display:none` (not `visibility`, because visible children leak through a hidden parent). All motion is computed from `t` with springs and easing. - **Render purity is mandatory**: no ` no randomness without a seed, no state carried between frames. Workers start mid-timeline. - Camera moves are CSS transforms on the snapshot, and so are cursor paths, typing and highlights. - Preview live with `npx serve .`, using `?t=17` to start at 17s. ### Taste rules (start with these; add your reviewer's) - **Openers:** light and product-native. No dark gradients, glossy fake app icons with red badges, or captions over blurred clutter. Reach the product payoff within ~2s. - **No recaps:** never repeat earlier points in words or as a montage at the end. - **End cards:** neat and centred, with a logo lockup, one line and a quiet URL. Landing cuts can carry one CTA (e.g. "Try free for 7 days") plus small platform marks. Never "·"-joined copy, and never a button stuffed with text. - **Legibility:** body text ≥ 20px at 1080p, no wide shot of unreadable UI for more than ~1s, no words sliced at frame edges, and captions fully settled ≥ 0.4s before the click they describe. - **Transitions:** no long crossfades between two busy UIs (the double exposure looks muddy). Use a cut, a camera push or a short blur-through. ## 6. Audio - **Voiceover:** a strong TTS model with style instructions (Inbox Zero used Gemini Flash TTS through OpenRouter). Pick one voice per format. Generate **2–3 takes per line** and pick the best with an audio-capable model (`judge.mjs`): it scores pacing, mispronunciations, odd stresses and clipped endings. - **Music:** generate one shared bed per format (Inbox Zero used Lyria). Models ignore the requested length, so detect the beat grid (librosa) and cut or loop at phrase boundaries. - **Mix (` duck the music under the voice with a sidechain, then do two loudnorm passes to −14 LUFS and −1.2 dBTP. - Agents can't listen. Flag music endings and loop points for a human ear-check. ## 7. Render - `render.mjs` splits frames across N Playwright workers. Each one loads the page, sets `t` and screenshots. ffmpeg then encodes a high-quality master (CRF ~12) and a web copy (CRF ~20). - Add a screenshot timeout and retry (e.g. 120s, 5 tries); long renders hit flaky frames. - Support env vars to render a sub-range or a single segment, so fixes don't need a full render. - **On a shared machine:** cap workers (e.g. 3 per agent) and only stop your own processes by PID. Never `pkill -f render.mjs`: it kills other agents' jobs. ## 8. Review before showing anyone - Sample frames into 2×2 contact sheets and **look at them yourself**, zooming in on captions, edges and data. This is the main review. - Use a video-capable model (`vjudge.mjs`, Gemini Flash) for whole-video checks like timing and caption order, but **treat its output as hints**. Video and audio judges hallucinate problems, so verify every claim against frames. - Check: claims match the code, the fictional cast only, no leaks, the legibility rules, the end card. - Show the reviewer the finished mp4s (open the folder for them) along with the `VARIANT.md` discrepancy list. ## 9. Work in parallel with subagents - Once the kit and briefs exist, give **one subagent per video**. Each gets its own worktree and branch, the brief, the relevant docs page, and the instruction to read `AGENTS.md` first. - Each subagent writes the script, builds, renders, reviews and reports back with the mp4 path and the discrepancies found. - The coordinator merges kit fixes into `main`, uploads, and integrates the videos into the app and docs. ## 10. Publish - **Hosting:** use Mux (or similar) rather than YouTube embeds. You get a clean player, no recommendations and auto-subtitles. The upload script sets a public playback policy and generated English captions, and records each ID in `MUX.md`. Pass API tokens via env vars and never commit them. - **In the app:** a feature-page video button or dismissible card. **Lazy-load the player** (`next/dynamic`, `ssr:false`) so it only loads when the dialog opens and adds nothing to the page bundle. - **Docs:** a lazy ` ` at 16:9. - **Landing hero:** track `video clicked / started / progress / completed / closed` with a `video_id`. Don't A/B test the hero video: only the ~10% who click can be affected, so overall-sign-up tests are underpowered. Ship the better cut and compare cuts on watch-through and viewer → sign-up by `video_id`. - **YouTube:** the API locks uploads from unaudited projects to private, so upload in Studio and schedule one video every ~2 days. If an agent automates Studio, set text with `execCommand('insertText')`, type dates with real keystrokes, and **read every value back before clicking Schedule**. - If the product repo is public, keep commit and PR text free of private details. If it mounts private submodules, grep them before removing any shared component. ## 11. Mistakes we already made (don't repeat them) - Invented UI in v1, where the reviewer's first note was "show real UI". → Real DOM snapshots only. - Claims the product doesn't make (e.g. "important emails move to the top" when they're actually labelled). → Check in code. - Taglines the company doesn't use. → Offer options and let the reviewer pick, then record the pick. - A real timezone leaked in a snapshot and was committed to history. → Audit before committing. - Agents killed each other's renders with `pkill`. → Stop processes only by your own PID. - A judge model "found" skips and glitches that weren't there. → Verify against frames. - Removing a shared component broke production through a private submodule. → Grep it first. - A free hosting plan capped the asset count, and the upload script swallowed the error. → Scripts must surface API errors. ## Deliverables per video - [ ] `out/ -web.mp4`, poster, `.vtt`, and chapter markers - [ ] `VARIANT.md`: script, timings, claim checks, docs/UI discrepancies - [ ] An entry in the `README.md` catalog, and its hosting ID in `MUX.md` - [ ] Any new rules learned are added to `AGENTS.md`

Elie Steinbock

19,696 views • 6 days ago

Apple’s iPad “Crush” Ad Is Bleak, Ominous and Threatening I don’t know if you’ve seen Apple’s just-released commercial for the “New” iPad Pro, but it’s pretty awful. It is dark, humorless, and feels like a not-so-thinly veiled threat to writers, musicians, game makers, developers, and artists of all kinds. …and children, even. I’ve watched it at least five times today alone, and I’m left with one big question. “Who on earth approved this?” It’s absolutely baffling that the world’s largest technology company, with the world’s biggest marketing budget, thought this would be a good idea. What kind of idiot—or idiots, since dozens or hundreds of people had to be involved in the writing, staging, producing, recording, and editing—felt this kind of ad would somehow create a positive emotional connection with consumers? Seriously, it’s terrifying. In a dank, cold warehouse, devoid of all life and humanity, an industrial crusher comes to life, and slowly starts destroying a collection of musical, philosophical, and artistic devices and instruments. For no apparent reason, everything starts getting smashed: first, a trumpet, then an arcade video game, then cans of paint, a piano, a globe, a metronome, a guitar… on and on it goes, obliterating everything in sight into a colorful, gooey, explosive mess. Books, camera lenses, lamps, a guitar, a sculpture, and a typewriter—all tools of the liberal arts—get mangled into a garbage heap as Sonny & Cher cheerfully sing, “All I ever need is you.” In the penultimate moment, a goofy yellow smiley emoji becomes a bug-eyed scary-clown freak as it, too, is crushed to death. Worse, if you enable closed captions like I do by default, the video says: “[POPPING] [SPLAT]” right as its eyeballs pop out of its head when Cher sings, “Give me a reason to build my world around you.” It’s enough to make a child cry. It has all the comforting vibes of the burnt pink teddy bear floating in the swimming pool on Breaking Bad after two planes crash in mid-air. I have so many questions (aside from simply wondering the names of the soon-to-be ex-employees who greenlit this abomination). First of all, as a trumpet player myself, I am personally offended that they made me watch a perfectly good trumpet get smashed to smithereens like it’s no big deal. Why would they torture me like this? Second of all, what is the message here? No, not that “the most powerful iPad ever is also the thinnest,” as the voiceover artist states in the last few seconds of the clip. I mean: what is the message? Ostensibly, pulverizing children’s toys, arcade games, architectural models, and ceramic Angry Birds into a paste implies something like “We’re taking all the best of humanity; all the collective works of Western Civilization, smashing it into pieces and putting it inside this remarkably thin device so you can have all of it in the palm of your hand.” But my oh my, is there an elephant in this room… he’s hiding behind the monstrous destroying machine. Did anyone inside Apple realize that everyone outside Apple will recognize this imagery in a metaphorical sense, but not the one Apple intended? We don’t see a crushing machine gently consolidating the greatest output of all our artistic endeavors, simply reformatted for a digital age and consumed by everyone with instant, fingertip access. We see what is painstakingly obvious to us, and the timing couldn’t possibly be worse. We see a giant, soulless machine consuming our work in a very different way. Right now, AI models are training themselves on our intellectual property and even our very own personally-identifying data. We aren’t the ones doing the consuming. We’re the ones being consumed. The tech industry has become one massive gaping maw, opening wide and swallowing everything in sight, chewing it up into little bits and pieces of comminuted waste, like a paper shredder or a garbage disposal. It’s destruction in its most literal form. And for what? For a newer version of the iPad that is only slightly thinner than its predecessor? For an only marginally improved version of Apple’s tablet device that has been around for 14 years? For increased profits? This is a terrible look for Apple. They may as well be saying: “All your work are belong to us.” Personally, I am a fan of artificial intelligence. I am eagerly embracing our robot overlords and I welcome our new CSV god (as the actual developers of AI models like to say). I look forward to the freedom and innovation that will come as a result of humanity augmenting our intelligence with AI like a force multiplier on a battlefield. But if Apple has the same perspective I do, they’re selling it in the worst possible way. When I see this video, I see that Apple is definitely crushing something… but I’m not sure what. -Crushing small companies that develop apps for the extremely heavy-handed App Store, which imposes byzantine restrictions on what they can and can’t do with their own apps? -Crushing competitors by limiting what they can do on the iOS and MacOS platforms with arbitrary and capricious rules about enabling functionalities that Apple doesn’t like, even if users do? -Crushing publishers and content creators with a punitive 30% fee on all subscriptions and in-app purchases? -Crushing choice and competition by not allowing app makers to make apps and programs that do the same thing that native apps already do, even if they do it better? -Crushing all human creativity and innovation by automating and systematizing everything? In the early days of the “Google vs. Apple” fight over the web and app stores, I was really concerned that Google was becoming way, way too powerful. Specifically, in 2015, when Google came up with “app streaming,” they announced a desire to form a “web of apps.” This was concerning. Especially when coupled with Google’s efforts to steal content from other websites and provide it to users via the “knowledge graph” results, ending up with the creation of “zero-click” search results pages, which absolutely punished website owners and content creators. By taking the most valuable content off a website and showing it to Google users without them needing to click through to the website itself, Google had essentially stolen everybody’s intellectual property with only the most minimal attribution possible (to fend off lawsuits no doubt, but with no intention of users actually visiting the website in question anymore). “Google is eating the internet,” I thought, and said out loud, (although I probably wasn’t the first person to use that phrase) But what I meant was purely an analogy. It was vague and ambiguous, almost silly. Maybe I was wrong, though: maybe it’s Apple that’s doing the eating. Maybe Apple is not only gobbling up everyone else’s work, but also homogenizing it—and us—and forcing us to use their platform, pay their fees, abide by their rules, and constantly keep upgrading, upgrading, upgrading, to an ever-thinner iPad in order to use it. Watch the video again. This is the stuff of nightmares. To be perfectly fair, even if I were to take the commercial at face value and ignore it’s off-the-charts creepiness and just stick to its one stated claim—that the new iPad Pro is thinner—it still fails as a commercial. Why? Because nobody cares how thin an iPad is. Seriously. I’ve owned an iPad since 2010: that means I’ve carried around a version of Apple’s already-thin tablet every day for over a dozen years. Never once have I said to myself: “You know what improvement I’d really like to see in this thing? I wish it were thinner.” Never. That thought has never crossed my mind, even once. You know what has? -Better battery life. -I’d like my iPad to not get hot to the touch when I use the Apple Pencil to take notes. -I wish it wasn’t so fragile: I dropped my brand-new iPad 2 back in the day when it slipped out of the arm-hold I was carrying it in, it bounced on the pavement, and the screen shattered into a thousand pieces, making it unusable. -I wish it had more storage. -I wish Apple would stop changing the type of cable connector it uses: I’ve gone from the original 30-pin connector to the Lightning connector, and now to the current USB-C/Thunderbolt connector. -I wish I could view the screen in direct sunlight. -I wish it wouldn’t overheat and turn off automatically when I use it outdoors in the summertime. Those are announcements I would welcome in a new iPad Pro commercial. None of this “now even thinner” nonsense nobody needs or cares about. So, back to the commercial. In my opinion, whoever made this ad should be fired. I almost never say that about other companies, especially for good-faith marketing efforts gone wrong… those of us who work in marketing make mistakes sometimes, and we learn from them. But cases like this warrant a special exception. Marketing and advertising are designed to make people want to buy your products. This commercial doesn’t just not make me want to buy Apple’s products. It makes me not want to buy Apple’s products, which is something altogether different. It turns me from someone who likes iPads into someone who is almost rethinking iPads entirely. That’s not just a bad advertisement; it’s a harmful advertisement. Apple’s usually known for great commercials. The legendary 1984 Super Bowl commercial was, of course, their best. I thought “Hello, I’m a Mac” was absolutely brilliant. They have made some missteps along the way, but this one is really bad. Not even their nauseatingly preachy and woke “Mother Nature” ad from a few years ago was this bad. Steve Jobs once said, “Technology alone is not enough—it’s technology married with liberal arts, married with the humanities, that yields us the results that make our heart sing.” My goodness, that last line alone is poetry itself! This ad seems to be Apple signaling that they don’t believe in that anymore. And I don’t think all this handwringing is an overreaction to where you could say “Oh, c’mon, it’s just a commercial! What’s the big deal?” It is a big deal. It tells you about the values of the company, and what they intend to communicate. Really, how is this the same company that used to sell iPhones by showing grandmas using FaceTime to connect with their baby grandchildren from afar during the holidays? Everything about it is wrong: even the thumbnail they chose for it (the bulging-eyed smiley face) and the fact that they gave it the title “Crush!” It was fun to see the reactions to the video online today. I find it fascinating that Apple shared it on YouTube but turned off the comments. On X, Tim Cook shared it Tuesday, and the video, which so richly deserves to be mocked, is getting it in spades. Some people are calling it “anti-art.” One user called it “soul-crushing,” which was about as literal and logical a response as you’d expect. It turns out Apple actually made an announcement about the commercial. In response to the (apparently unexpected) poor welcome it got, Apple wrote: “We missed the mark with this video, and we’re sorry.” Lame response from a tone-deaf tech behemoth, but still, they hopefully got the message. C’mon, Apple. I have seen the future, and this ain’t it.

Ron Stauffer

19,249 views • 2 years ago