Motion is built for individuals and teams of all sizes
Users generally praise Motion for its robust functionality and ease of use, particularly appreciating its performance in managing tasks efficiently. However, there are some complaints centered around its learning curve, which can be steep for new users. The pricing sentiment is mixed, with a few users finding it slightly expensive but acknowledging the value it provides. Overall, Motion maintains a strong reputation for reliability and effective task management, as shown by its predominantly high ratings and positive feedback.
Mentions (30d)
35
7 this week
Avg Rating
4.3
20 reviews
Platforms
3
Sentiment
13%
11 positive
Users generally praise Motion for its robust functionality and ease of use, particularly appreciating its performance in managing tasks efficiently. However, there are some complaints centered around its learning curve, which can be steep for new users. The pricing sentiment is mixed, with a few users finding it slightly expensive but acknowledging the value it provides. Overall, Motion maintains a strong reputation for reliability and effective task management, as shown by its predominantly high ratings and positive feedback.
Features
Use Cases
Industry
information technology & services
Employees
88
Funding Stage
Series C
Total Funding
$65.1M
Is Flock just a poor US-centric copy of, globally active Genetec?
I've read all of Genetec's [customer stories](https://www.genetec.com/customer-stories/search) (the PDFs), and although I recognize these, as being Genetec marketing material (at least in part), they do contain insightful information, regarding implementation of surveillance systems; that is, from the perspective of a diverse palette of organisations. This palette primarily consists of: universities, school districts, ports, critical infrastructure providers, business to business companies, health care providers, real estate developers, gambling companies, (sports) venues, cities, public transportation services, airports, retailers, and foremost police departments. What most have in common, is the increasing scale at which they operate; setting in motion a search for IT-solutions, able to scale alongside organisational growth, and doing so in a cost-effective way. This entails: the centralisation of (previously "siloed") systems and departments, automatization of (previously time-consuming, or outright unmanageable) tasks, and proactive 'Data-Driven Decision-Making (DDDM)'; unlocking operational efficiencies and granular control over vast operations. Which is where Genetec introduces itself, primarily through [its partners](https://www.genetec.com/partners/partner-integration-hub?keywords) (including: hardware manufacturers, software solutions companies, system integrators, consultancy firms, etc.), often during an organisation's 'call for tender' or 'Request For Proposal (RFP)'; or it's recommended by other Genetec customers (including by law enforcement, to "community" partners: primarily businesses). The most recognizable partners, of the consortium-like construction, include: Axis Communications, Sony Corporation, Hanwha Vision, Bosch, NVIDIA, ASSA ABLOY, Intel, Pelco, Canon, Dell technologies, HID Global, FLIR Systems, Global Parking Solutions, and Seagate Technology. Alongside the Genetec-certified [hardware](https://www.genetec.com/supported-device-list) and software integrations (of which their partners' being actively co-marketed to customers), it also allows for custom integrations: through their 'Software Development Kits (SDKs)', and 'Application Programming Interfaces (APIs)'. So instead of single-vendor lock-in, organisations are effectively subject to multi-vendor lock-in (unless: spending resources, on custom integrations, is more cost-effective). Genetec's primary focus, lies on their extensive suite, of (specialized) software applications, deployed on: an on-site server, multiple (distributed) on-site servers (possibly federated: allowing for a centralized view over multiple implementations), in the "cloud" (i.e. someone else's server) as a '... as a Service' solution; or a combination of aforementioned (providing "cloud" flexibility). When using multiple applications, Genetec's 'Security Center' can unify all; meaning operators aren't required to switch between applications. And considering applications aren't limited to just camera surveillance, but also include: intrusion detection (intrusion panels, line-crossing cameras, panic switches, etc.), access control (electronic locks, access control readers (pin, card, tag, mobile, and/or biometric), door control modules, etc.), communication (intercoms, 'Public Address (PA)' systems, emergency stations, etc.) and ALPR (ALPR boom gates, gateless (license plate as a credential), enforcement vehicles, etc.); it allows for centralization of these systems (unless prohibited by strict IT policies). All of these technologies combined, primarily serve to: save on resources, protect assets, prevent losses, ensure operational continuity, and resolve disputes over: parking tickets, insurance claims (as a result of damages: suffered or caused on premise; potentially increasing premium), or even legal allegations ("increase the number of early guilty pleas"); all of course, under the guise of safety. Whether it be organisations individually, or "community" initiatives (often spearheaded by businesses, while citizens are left to follow); most circle back to previously outlined, financially-grounded motives. Resources include staff, who's function might become more versatile, or entirely obsolete (through efficiency gains), and might depend on events, reported by analytics (growing queues, areas requiring clean-up, crowd bottlenecks, etc.); meaning they too, are subject to this system: from onboarding ("minimise the time that elapses before they make a productive contribution") and throughout their career ("employee theft", "employee attendance", "agents' activities, collectively or individually", etc.). Previously, some organisations utilized analog cameras (having a recorder each), in which: a looping tape, would periodically overwrite previous recordings (minimizing retention periods: physically); which possbily caused quality degradations, sometimes to such a degree, footage could no longer serve as legal evidence (which too, is privacy-friendly).
View originalPricing found: $700, $250
g2
What do you like best about Motion?I love that I can send a link to someone that shows preferred times and available times they can meet with BOTH my business partner and me. I also like the permanent links I can set up that allow someone to use their special meeting link over and over again. Review collected by and hosted on G2.com.What do you dislike about Motion?It really wants to cram my day in with activities if I let it. I would like it if I could say, "I only want to do so much deep work in a day vs light work, and have so many breaks." If I let it set my entire schedule, I'd never get to pee. Review collected by and hosted on G2.com.
What do you like best about Motion?I can make for example perfect title animations for social media publications Review collected by and hosted on G2.com.What do you dislike about Motion?Not so easy to start with, you need to use some tutorial, but then is really useful Review collected by and hosted on G2.com.
What do you like best about Motion?Motion is so incredibly easy to use, and its integration with Final Cut Pro is awesome. I love the interface and hower powerful it is. Creating my own titles and motion graphics is a pleasure. Review collected by and hosted on G2.com.What do you dislike about Motion?It does NOT integrate with Adobe files very well. With After Effects, I can pull in Illustrator files and work with the layers. I can then update the AI files and my AE projects will update. Motion does not work with other files well at all and it is a huge detriment to my workflow, so I have to use AE for those projects. Review collected by and hosted on G2.com.
What do you like best about Motion?I found the layout and interface of motion to be very user-friendly and intuitive. I also like that the interface is consistent with all of the other programs in the apple lineup so jumping right in was easy. Review collected by and hosted on G2.com.What do you dislike about Motion?I have run into several instances where motion crashes for an unknown reason. So if you don't get in the obsessive habit of always saving you can lose your work. Review collected by and hosted on G2.com.
What do you like best about Motion?This gives us something that works directly with Final Cut and uses the same codecs. We are able to easily move items back and forth as needed. AS the name suggests Motion is fantastic for adding dramatic motions and graphics to any video. Review collected by and hosted on G2.com.What do you dislike about Motion?The rendering time and process can be cumbersome and time consuming at times depending on the graphics and video being used. Review collected by and hosted on G2.com.
What do you like best about Motion?I like that Motion has a user interface that is easy to use and understand. The interface is built very similar to that of Final Cut which makes it very nice when needing to switch between the two applications to achieve different effects. With Motion you are able to achieve the (as the name states) motions that you aren't able to achieve with Final Cut. Review collected by and hosted on G2.com.What do you dislike about Motion?I think the one downfall to Motion which has gotten better is the time it takes to render and save videos. Especially with the videos that have a lot of movement to them which creates a larger file size. Also it seems that the compression you receive with Motion isn't to the degree of the compression you get with other pieces of software like Final Cut or even the dreaded iMovie. Review collected by and hosted on G2.com.
What do you like best about Motion?I like that Motion is easy to integrate with Final Cut Pro X. I can drop transitions and titles into Motion and save them, easily to drop into a Final Cut Pro project later. I can modify any aspect of those transitions that I want which gives me even more options when working on a wedding video or company add. It also gives me a lot of masking features for special effects. Review collected by and hosted on G2.com.What do you dislike about Motion?I don't like how difficult it is to learn how to use Motion. Sure, it's intuitive and powerful but there are so many features, I have to go to You Tube to learn how to do anything. But that's what you get with a motion graphics software. It can be complicated because there are so many powerful features. Review collected by and hosted on G2.com.
What do you like best about Motion?After Effects was hard for me to pick up, but for the affordable cost & tons of feature Apple Motion is a breeze. If your preferred video editor is FCP you have to have this! Review collected by and hosted on G2.com.What do you dislike about Motion?I would like to see more functionality with exporting/importing to FCP. For now I'll finish a project in motion then I can do specific cuts & audio editing in FCP. Review collected by and hosted on G2.com.
What do you like best about Motion?after countless hours looking for a program that can fit our needs, motion is a great program that helps you create cool effects and GFX that can help your production quality tremendously Review collected by and hosted on G2.com.What do you dislike about Motion?what I like about Motion is the price, I should be cheaper to use, and that the things are menus are hidden, so we can use it and really get good at the idea of having it in our arsenal Review collected by and hosted on G2.com.
Deep Neural Network that turns any Image into a Playable Game ! All on consumer GPUs and Not Datacenters
Hi everyone!! I really wanted to share my research what I've been working on. I wanted to build a nn that can simulate games, or at least start doing that Most video generators are too large to run on consumer hardware realtime, so I I designed a model that does this from scratch. No fine tuning bs or anything The core de noiser network is fully trained from scratch to support this goal. From image to games data. That video. above is on a RTX 5090. The nn is a small Transformer-like model and works in a causal way, just like LLMs. That lets us KV Cache all past information and do a simple autoregressive decode forward passes for every new frame we want. In the video shared, the model is a 0.4B variant with some SIGNIFICANT ISSUES like poor motion and some weird flashes, some context issues It's taking the keyboard actions I give it in realtime and utilising that in the forward pass. (no classifier free guidance though) Im training the next iteration , a 0.8B model now. Btw I haven't done quantisation yet, that can save a LOT more time. bf16 is slow. submitted by /u/lucidml_lover [link] [comments]
View originalWHAT do you mean "I cannot generate images."
https://preview.redd.it/cjeage5k844h1.png?width=1539&format=png&auto=webp&s=ac31c625ee0208c6d5b1aea059ff1790d5471e64 Expecting this feature anytime soon. submitted by /u/ObjectiveOrchid5344 [link] [comments]
View originalI spent $340 on AI subscriptions last month. Wrote down what I actually used each one for. It was depressing.
Going through the credit card statement, here's what I had active: Claude Pro (40), ChatGPT Plus (20), Cursor (20), Perplexity Pro (20), Notion AI (10), Granola (20), ElevenLabs Starter (5), Midjourney Basic (10), Gamma Pro (10), Beautiful.ai (12), Otter Pro (17), Loom Business (15), Zapier Pro (30), Make Core (10), Tactiq Pro (8), Descript Creator (15), Reclaim.ai Pro (8), Motion (19), Superhuman (30), one i can't remember the name of (10), some ai-something for instagram captions (11) Then I sat down and wrote next to each one the last time I'd actually used it. Not opened it, used it for a real piece of work. Claude (yesterday), ChatGPT (yesterday, voice mode in car), Cursor (yesterday), Perplexity (3 days), Granola (every meeting), Gamma (2 weeks), Zapier (a month, but the automations are still running), ElevenLabs (3 months ago), Midjourney (couldn't remember), Beautiful.ai (couldn't remember), Otter (replaced by Granola, just forgot to cancel), Loom (4 months), Tactiq (replaced by Granola, also forgot), Descript (used twice in 6 months), Reclaim/Motion (both, can't tell them apart, forget which one schedules my meetings), Superhuman (used the AI features twice), the instagram one (literally cannot remember signing up) Cancelled 11 things this morning. Saving $145/month. Nothing in my workflow actually changed. The pattern isn't that AI tools are bad. It's that I treat subscribing like trying. Every "I want to try this" became a recurring charge I forgot about. submitted by /u/OneSeaworthiness2676 [link] [comments]
View originalPAID Gemini vs FREE ChatGPT
I recently subscribed to Google One Ai Pro and recieved Gemini Plus Plan... I've been using it for some days, and the difference between Gemini and ChatGPT is enormous... i feel like talking to an Ai model from 2022. I asked them both to generate an image using the EXACT same prompt, here are the results... The prompt: "Generate a creepy midnight image in an abandoned road and there is a scary woman with white - blue gown standing next to the road. Make the quality unremarkably iPhone-ish, slight motion blur, grainy quality as if it was taken in dark. The picture is taken from a car in motion, from it's window on the front right seat." Models used: Gemini 3.1 Pro GPT-4o (afaik this is the model used in image gen in the free ChatGPT version atm) Edit: Added the models used. https://preview.redd.it/bbou5fdr0p3h1.png?width=1340&format=png&auto=webp&s=46ff98af1e386f8a4da6b1c304e13d1b319b95e5 submitted by /u/ObjectiveOrchid5344 [link] [comments]
View originalYour coding agent is not lazy. The work-selection mechanism is biased.
Anyone who has tried to ship a full multi-page app with a coding agent has probably hit this. The agent edits, tests, and polishes the same 20 surfaces over and over while the other 80 stay untouched. It looks productive because the active surfaces show motion. The inactive surfaces are not failing loudly, because they are not being visited. The system confuses absence of evidence with evidence of completion. I spent a while convinced this was a context length problem, then a model capability problem, then a prompting problem. None of those fixed it. The pattern shows up across models, frameworks, and projects. What finally clicked is that this is not really a cognitive failure. It is a work-allocation failure that happens whenever the same agent gets to select the next task, perform the task, and judge whether the task is complete. The behavioral mechanisms stack pretty cleanly. Availability puts the recently-read files at the top of the decision stack. Anchoring fixes the project around the first inspected route. Status quo bias and sunk cost make leaving the current page expensive. Goodhart effects make passing tests and closing nearby TODOs feel like progress, because dense signals only exist in already-visited areas. Bounded rationality lets the agent satisfice on the visible subset and call it done. All of those reinforce each other. In that environment, biased work allocation is not an exception. It is the default. Four common fixes do not actually solve this. Bigger model improves reasoning quality but does not change the selection mechanism, so a smarter agent can still choose biased work. Longer context provides more information but also makes the active subset more convincing because it has richer local detail. Telling the agent to "be thorough" relies on the same biased agent to enforce the anti-bias rule. Adding a checklist only helps if an independent mechanism tracks whether the checklist covers the full project and promotes unvisited nodes into active work. The architectural shape I am testing has three first-order roles and one second-order role. Shared external state is an AI sitemap with node-level completion scores, last-tested timestamps, dependencies, risk levels, and evidence references. An orchestrator agent selects work using a visible priority function (under-coverage, staleness, risk, blocking dependencies, recent-focus penalty). A developer agent only executes the assigned task. A validator agent writes evidence back to the sitemap. The developer cannot pick the next global task, and the validator does not implement what it is evaluating. The piece that took longer to land is the Curator Agent. A fixed priority function and a fixed validation contract eventually become wrong, because real projects discover new surfaces and have domain-specific completion criteria. The curator is a reflexive layer that observes traces and updates the rules: it tunes priority weights when focus concentration drops, lowers validator trust when pass rates rise with low evidence density, proposes schema extensions when the domain needs new fields, and manages provisional nodes when the system discovers a surface that was not declared up front. It writes only to the meta layer. It does not mark anything complete itself. The lineage I had in mind was double-loop learning (Argyris and Schon), Stafford Beer's System 4 and System 5, and basic second-order cybernetics. submitted by /u/Hot-Leadership-6431 [link] [comments]
View originalAnyone else using Claude Code as a motion graphics engine yet?
Remotion turns video into React components. So every lower third, intro, transition, and overlay is JSX. I describe what I want in plain English, Claude writes the component, I render. What this actually changes: Iterations measured in seconds, not minutes of drag-and-drop Components reusable across every video forever (the library compounds) Visual style finally consistent across a channel because every video pulls from the same components The skill stack shifts from After Effects expertise to prompt engineering plus light JSX literacy The output today is rough because the workflow is new. The trajectory is what matters. In 12 months click-and-drag editing is going to feel as antiquated as writing code in Notepad. Curious if anyone here is doing the same yet, or seeing it elsewhere. submitted by /u/Silver-Range-8108 [link] [comments]
View originalBuilt an MCP server so Claude can generate music, images, and video natively. One config block.
I've been using Claude Code daily for the last few months and kept hitting the same wall: I'd ask Claude to produce a creative artifact (a song, a cover, a short video) and end up writing the API glue myself, then pasting results back into the chat. Felt backwards. So I built an MCP server around my AI generation platform. It exposes three tools to Claude: - aw_generate_music (Suno, full songs with lyrics or instrumental) - aw_generate_image (Z-Image Turbo, Wan 2.5 Spicy, Grok Imagine Quality, GPT-Image-2, Nano Banana 2, and others) - aw_generate_video (Kling 3.0 Standard/Pro/4K T2V + I2V, Wan 2.2, Hailuo 02, Seedance, Grok video) One key. One credit pool. The agent picks the right model for the prompt. Install: npm install -g u/aetherwave-studio/mcp Claude Code config (~/.config/claude/mcp.json or wherever yours lives): { "mcpServers": { "aetherwave": { "command": "npx", "args": ["-y", "@aetherwave-studio/mcp"], "env": { "AW_API_KEY": "aw_live_YOUR_KEY_HERE" } } } } Restart Claude. Done. Prompts that work end-to-end without any additional setup: "Generate a 60-second lo-fi track for a study playlist, then make me 3 album cover options in a retro Japanese print style." "Take this product photo and generate a 5-second cinematic intro video for the product launch." (drop the image in chat first) "Write the script for a 30-second ad about my SaaS, then generate the voiceover-friendly music bed and a matching motion-graphics opener." The agent decomposes, picks tools, runs them, hands you back the artifacts. Repo: https://github.com/AetherWave-Studio/aetherwave-mcp Dashboard + key: https://aetherwavestudio.com/developers Happy to answer questions about how I structured the tool schemas, what worked, what I'd do differently. v0.1.0, real users on it already, treating community feedback as the next steering signal. submitted by /u/Acrobatic-Result9667 [link] [comments]
View originalHow hard is it to train a video generation AI from scratch?
People talk about video generation AI like it just suddenly appeared, but I’m curious what the actual training process looks like underneath. Not talking about building the next Sora or Veo, just training a tiny experimental video model to understand the workflow. Image generation already seems complicated, but video feels like a completely different level because now the model has to understand motion, consistency, timing, objects changing frame by frame, camera movement, physics, and temporal coherence. It makes me wonder what the real bottleneck is. Is it compute, video data, architecture, evaluation, or just the fact that video has way more moving parts than images? submitted by /u/Raman606surrey [link] [comments]
View originalI've been using Claude Code as a motion graphics engine for my YouTube videos. It writes the JSX, I render. Edit time roughly halved.
Found a really clean Claude Code use case that's not coding-coding. Remotion (React for video) means motion graphics are JSX components. So I describe what I want in plain English, Claude Code writes the component, I render. Lower thirds, intros, overlays, all reusable across videos. Iterations are seconds instead of the typical "drag clips around in CapCut for an hour" loop. Visual style is finally consistent across my channel because the components are shared. 13 min walkthrough as promised, full walkthrough: https://youtu.be/mXwXwdrMMaM submitted by /u/Silver-Range-8108 [link] [comments]
View originalStoryboard generated from GPT image 2.0
I gave GPT a set of prompts that I found a bit too complicated, and to my surprise, it generated content that matched perfectly. I'm very curious about how GPT Image 2.0 works behind the scenes, and how it can understand and produce high-quality images so quickly. I've included my creation process here; you can view the full image content and try using these prompts directly. https://app.tapnow.ai/tapflow/view/49aa2245 prompt：**PROJECT FILE: HIGH-ALTITUDE ASCENT // PREMIUM HARDSHELL CAMPAIGN** **FORMAT: ARRIRAW 4.5K / KODAK VISION3 50D 5203 EMULATION** **DIRECTOR'S PRE-PRODUCTION VISUAL BOARD** --- ### Top Left Area | Character Lock Zone **[SUBJECT]** 35-year-old male mountain guide/extreme climber. **[WARDROBE]** Top-of-the-line professional jacket (matte rock grey with minimal dark orange taped details), heavy-duty climbing harness. **[VIEWS]** - **Front:** The jacket is fully zipped up, hood pulled up, showcasing a three-dimensional cut and natural drape. - **Side:** Shows ample shoulder and arm movement without bulkiness. - **Back:** Shows the windproof and breathable back panel structure. - **3/4 View:** Dynamic standing pose, holding an ice axe. **[REALISM NOTES]** Realistic human bone structure, slightly asymmetrical. The face has the rough texture of high-altitude red and sun-dried skin, with clearly defined pores and stubble with a frosty look. Rejecting perfect plastic skin, rejecting CG aesthetics. Like a real makeup test photo. --- ### Top Right Area | Expression + Motion Keyframes (EXPRESSION & ACTION) **[EXPRESSIONS]** **Focused:** Slightly furrowed brows, resolute gaze, staring at the rock face above. **Bracing:** Squinting against the strong wind, facial muscles tense. **Breathing:** Lips slightly parted, exhaling real white mist. **[ACTIONS]** **Hood Adjustment:** Pulling the drawstring of the hood with one hand. **Ice Axe Swing:** Arm raised high with force, no pulling sensation under the armpits of the jacket. **Brushing Snow:** Brushing snow off the shoulders, demonstrating the fabric's water-repellent properties. --- ### Upper Middle Area | CAMERA PLAN **[GEAR]** ARRI Alexa Mini LF + Master Prime lens set. **[LENSES]** 24mm (wide-angle environment), 50mm (medium-range tracking shot), 100mm Macro (fabric close-up). **[MOVEMENT PLAN]** - **Shot A (Drone/Crane):** A wide, overhead view, slowly pushing in along a snow-covered ridge. - **Shot B (Handheld):** Shoulder-mounted camera, following the character's movements, with realistic breathing and slight shaking. - **Shot C (Slider):** A close-up panning shot close to the clothing, showing water droplets sliding off. --- ### Central Main Area | Continuous Story Shots (STORYBOARD: 8 PANELS) **[PANEL 01]** - **Shot:** 01 | 24mm | Wide Shot (EWS) | Slow Push-In - **Action:** A tiny figure struggles through a massive natural storm on a snow-covered ridge. - **Detail:** Strong atmospheric perspective; the wind and snow create a realistic fog effect; slight chromatic aberration at the edges of the image. **[PANEL 02]** - **Shot:** 02 | 50mm | Mid Shot | Shoulder-mounted tracking shot - **Action:** A man walks against a blizzard; the strong wind whips against his rain jacket, creating realistic physical wrinkles on the surface, but the overall silhouette remains sturdy. - **Detail:** Noticeable film grain; the snow-capped mountains in the background are slightly out of focus. **[PANEL 03]** - **Shot:** 03 | 100mm Macro | Extreme Close-up (ECU) | Fixed Macro - **Action:** Icy snowmelt hits the shoulders of the rain jacket. - **Detail:** The lotus effect is realistically rendered—water droplets condense and quickly roll off the matte micro-ripstop fabric without penetrating. **[PANEL 04]** - **Shot:** 04 | 85mm | Close-up of face (CU) | Slow motion - **Action:** The man stops and looks up. Real ice crystals cling to his eyelashes, and his breath dissipates at his collar. - **Detail:** Natural skin tone, without excessive blurring; realistic catchlight in his eyes reflects the snow wall ahead. **[PANEL 05]** - **Shot:** 05 | 35mm | Low Angle Full | Handheld, low-angle shot - **Action:** He swings his ice axe into the ice wall, climbing upwards. - **Detail:** Emphasis on showcasing the flexibility of the jacket during vigorous movement; no feeling of restriction; realistic light and shadow highlight the garment's three-dimensional cut. **[PANEL 06]** - **Shot:** 06 | 100mm Macro | Close-up Detail (Insert) | Shallow Depth of Field - **Action:** A heavily gloved hand pulls a waterproof zipper across the chest. - **Detail:** The matte waterproof rubberized finish of the zipper and the clearly visible scratches on the brushed metal zipper pull exude a strong sense of industrial design. **[PANEL 07]** - **Shot:** 07 | 50mm | Over-the-Shoulder Lens (OTS) | Slow Zoom In - **Action:** Over the man's shoulder, we see him finally reaching the summit, sunlight piercing through the clouds and shi
View original"Talk" [ft. Sara Silkin] - Multi-Character AI Motion Capture Experiment
In collaboration with the amazingly talented Jibaro's choreographer. More information on exactly how I made this, through the comment section. submitted by /u/santi_0608 [link] [comments]
View originalReconsider using Claude, hit by too many false positive blocks, and hundreds of user reports
https://preview.redd.it/hevkfnz46v2h1.png?width=3170&format=png&auto=webp&s=0abde4ef1d7d647da9e376db88ef4ae5f429c5e9 reproducible example: claude -p "please read source https://source.chromium.org/chromium/chromium/src/+/main:third_party/blink/renderer/modules/device_orientation/device_motion_event_pump.cc and explain to me" related issues on github: False positive policy block on OSS governance/security files (CodeQL, CODEOWNERS, CoC) #61688 [BUG] CVP repeatedly declines homelab sysadmins — no path for infrastructure owners managing personal hardware #61668 [Bug] Safety classifier blocks routine code analysis for paid users (started 2026-05-23) #61664 [BUG] False positive - legitimate medical-education content flagged as unsafe #61663 False-positive Usage Policy block mid-session (req_011CbJudbehY5Yi6gtM4xko4) #61660 [BUG] Persistent false-positive AUP violation blocks entire AI research project (Opus 4.7) #61659 [Bug] Anthropic API Error: Usage Policy violation blocking TTRPG content in Claude Code CLI #61658 False-positive content filter blocks benign UI animation prompts in Claude Code #61657 [Bug] Anthropic API Error: Overly aggressive Usage Policy filtering on biomedical research requests #61656 [BUG] AUP repeatedly throwing false positives - live issue ongoing - hundreds of similar reports #61655 [BUG] AUP false positives during scientific manuscript editing request #61654 [BUG] : API Error: Claude Code is unable to respond to this request, which appears to violate our Usage Policy #61653 False positive: Usage Policy block on technical markdown integration task #61652 [BUG] Safety classifier repeatedly blocks legitimate constructed language (conlang) development #61650 False-positive cyber-safeguard intervention on legitimate systems-engineering work in Claude Code #61646 [BUG] erroneous API Error: Claude Code is unable to respond to this request #61645 [BUG] False positive safety block: triggered without apparent reason during game dev session #61644 submitted by /u/jimages [link] [comments]
View originalBuilt an intelligent web video editor for claude (and other agents) via MCP
Hey! I'm a first time founder and long-time video editor. I've spent the last thousand-ish hours building this, and I'm super excited to show you guys https://usevyra.com But first, you can try a demo here with preloaded footage: https://app.usevyra.com/demo (you can connect your own claude/claude code agent) The app index/preprocess footage that comes through so that claude can search semantically and understand the footage it's working with instead of editing blindly. I'm especially proud of all the editing features our app supports, including motion graphics, music sync, smart masking, transcript-editing, color grading, and over 30 effects, so it feels less like a gimmick and actually something usable for people. Would love for you guys to try and give any feedback, thank you!! :) submitted by /u/kale_eeb [link] [comments]
View originalI tested Claude + After Effects so you don't have to guess anymore
I've been seeing a lot of curiosity and, honestly, a lot of hesitation around using Claude with After Effects. So many motion designers are in the "I've heard of it, but I don't really get what it does or how it works" camp. So I decided to go deep on it. I tested it across real motion design workflows and documented everything I found. I just put together a full breakdown that answers the questions I kept seeing over and over: What Claude can actually do inside After Effects. Where it helps, where it doesn't, and where it straight-up wastes your time. How setup works, because this was way less obvious than it should be, and most guides skip the parts that trip you up. Real use cases for motion designers and not generic "AI can help you brainstorm!" stuff. I'm talking about specific things like expression generation and workflow shortcuts that actually make a difference in daily work. There are things it's genuinely useful for and things that are still faster to do manually. If you're a motion designer who's been curious about Claude but hasn't taken the plunge because the info out there feels either too vague or too hype-y - this is for you. It's also for you if you've tried it once, got underwhelming results, and figured "yeah, not for me." There's a good chance you just didn't have the right setup or prompts. What this isn't: It's not a "Claude will replace you" video. It's not a sponsored thing. It's me sharing what I learned after actually using it in my workflow, so you can skip the trial-and-error phase. You can find the breakdown here if you're interested in learning more: https://youtu.be/ayZnTA4dnZk?si=y0ri5-rU5ejwK4QV Happy to answer any questions in the comments, too. submitted by /u/KashuAcademy [link] [comments]
View originalHow to Create a Night Car Selfie with GPT Image 2.0? Prompt Included!
We tested a darker, more editorial-style car selfie concept with GPT Image 2.0, and the result felt surprisingly realistic. Instead of making a direct AI portrait, I wanted the shot to feel like a late-night iPhone photo taken inside a car. The main frame only shows the hand holding the phone, while the girl’s face appears inside the iPhone camera preview. That small framing choice makes the image feel much more natural, like a real candid lifestyle shot rather than a typical generated portrait. What makes this prompt work: the subject is only visible through the phone screen dark premium car interior warm blurry city lights outside the window realistic low-light noise and slight motion blur iPhone-style framing without flash cinematic shadows and moody night atmosphere It gives the image a more believable “captured by accident” feeling. Go to GPT Image 2.0 Generator Write the full prompt given below Upload your reference image Click to the "Generate" and get the edited image Prompt: "The photo is taken inside a car at night. Only a woman’s hand and the iPhone are visible in the frame; the girl’s face appears only on the phone screen. The camera is positioned from the passenger seat side, aimed toward the windshield and the phone being held in one hand in front of her. In her hand is the latest black iPhone Pro in horizontal position. On the screen, the iPhone front camera interface is open with visible camera buttons, focus frames, and UI elements. On the phone screen, a close-up of the girl’s face inside the car is visible: her lips are slightly parted and she is touching her lower lip with a thin black object resembling a lip pencil. The girl on the screen is wearing black clothing, softly illuminated by the phone’s light. The hand holding the phone has long fingers with a short square French manicure. The rest of the frame is very dark; the car interior is black and premium-looking, with part of the window and dashboard visible. Outside the window is a nighttime street with warm blurry city lights, dark tree silhouettes, and subtle reflections of light on the glass. The shot is very dark with a cinematic night aesthetic and rich lifestyle mood, 9:16 ratio. Shot on an iPhone at night without flash, realistic photo, slight motion blur, high-contrast shadows, no filters, do not blur the background completely. Hair is voluminous." Would love to see other versions of this kind of indirect selfie / phone-screen framing. Share your similar night car iPhone selfie photos below! submitted by /u/DataGirlTraining [link] [comments]
View originalPricing found: $700, $250
Motion has an average rating of 4.3 out of 5 stars based on 20 reviews from G2, Capterra, and TrustRadius.
Key features include: Create, edit, and summarize content with AI, Search across all your notes and docs instantly, Ask anything. Motion finds the answer fast., “Motion helped me get promoted 12 months faster than peers”, Your existing, average tools, Normal Task Manager, Normal Project Manager, Normal Docs.
Motion is commonly used for: Automating daily scheduling to optimize time management, Integrating with existing calendars to streamline appointments, Prioritizing tasks based on deadlines and importance, Generating daily summaries of tasks and meetings, Facilitating team collaboration through shared task lists, Providing reminders for important deadlines and events.
Motion integrates with: Google Calendar, Microsoft Outlook, Slack, Trello, Asana, Zoom, Notion, Evernote, Todoist, Dropbox.
The Verge AI
Publication at The Verge
4 mentions
Based on user reviews and social mentions, the most common pain points are: token cost.
Based on 87 social mentions analyzed, 13% of sentiment is positive, 86% neutral, and 1% negative.
