InVideo AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

InVideo AI AI

ClaudeGauge - Tired of opening claude.ai to check my 5h limit? Here.. a real-time Claude.ai monitor on ESP32-S3 with a Star Trek LCARS interface

Hey r/ClaudeAI Got tired of refreshing claude.ai to check how close I was to my 5-hour limit or how much I'd spent on the API this month. Wanted ambient awareness -p glance at a small screen on my desk, get the answer. So I built ClaudeGauge - a physical dashboard that runs on a ~$25 ESP32 AMOLED and pulls live data from the Claude API + claude.ai. https://reddit.com/link/1tsb1eo/video/ut20yc7f9bng1/player https://preview.redd.it/hbjbhwag9bng1.png?width=320&format=png&auto=webp&s=a84f12293ef5ab3d0179c0d48ca9772feed848f1 https://preview.redd.it/zdjy46bp9bng1.png?width=320&format=png&auto=webp&s=53c2cd21370ef096e6357cc996d17b7a0282cb36 https://preview.redd.it/ei5amd7h9bng1.png?width=320&format=png&auto=webp&s=dfafd79d83e0afc887b4fb2f912b17dd6d92573a What it does: Tracks API spending (today + monthly) in USD Shows token usage broken down by model (input, output, cached) Claude Code analytics: sessions, commits, PRs, lines modified Rate limit monitoring with live countdown timers System health: WiFi, memory, uptime, firmware version 7 dashboard screens you cycle through with a button press Hardware supported: LILYGO T-Display-S3 — 1.9" parallel display, USB-C, dual buttons + touch Waveshare ESP32-S3-LCD-1.47 — 1.47" SPI display, USB-A, single button Both boards are cheap ($25-40) and easily available. Tech stack: PlatformIO + Arduino framework TFT_eSPI with full-screen PSRAM sprite for flicker-free rendering Captive portal for WiFi/API key setup (no hardcoded credentials) Vercel Edge Function proxy (ESP32 can't connect to claude.ai directly — Cloudflare blocks mbedTLS fingerprints) Chrome extension for session key auto-fill WYSIWYG layout editor for designing custom screens Some ESP32 gotchas I ran into: If you're using TFT_eSPI in SPI mode on ESP32-S3, you MUST add -DUSE_FSPI_PORT to your build flags or you'll get a crash in begin_tft_write(). Took me a while to figure that one out. Cloudflare Workers don't work as a proxy either — only Vercel (Fastly-based TLS) gets through to claude.ai. Looking for contributors! The project is MIT-licensed and there's plenty of room to help: Support for additional ESP32 display boards New dashboard screen layouts Improving the LCARS designer tool Adding support for other AI provider APIs (OpenAI, Gemini, etc.) General firmware improvements and bug fixes Links: GitHub: https://github.com/dorofino/ClaudeGauge Website: https://claudegauge.com If you've got one of these boards sitting around, give it a try and let me know what you think. PRs and issues welcome submitted by /u/Prudent-Purchase-558 [link] [comments]

Introducing Machinaos[Fully Opensource]: OS That converts LLM Tokens to Work.

claude On May 13 Anthropic Culled the Usage of "Claude -p" Command which instantly killed the heavily 25x subsidization usage of Claude . People were using Openclaw , Hermes Agent and others things through claude cli using the "-P" command , but now the usage will be charged as Claude SDK API credits from their Pro[100$] or MAX[200$] Budgets. Using claude through their SDK is ~25x more expensive and burns credits super Fast. Once i Tried to Generate a Simple PDF report from my emails and it burned ~10$ in the Calude SDK Credits. Also Claude Code usage is very generous and barely hits the Weekly Quotas. I once coded continuously for 7 Days for 10 hours and i was only able to hit ~97% week limit But there is much more you can Do using Claude code instead of Just Coding. You can Add Tools and Sub Agents, etc and Convert it to Cowork and Design too. BTW Claude Cowork and Claude Design are Supper Token Hoggers and Hits Quotas Fast. Once I was using Calude Design and told it generate around 10 Design Themes and it burned through weekly quota with a Hour usage. Meanwhile I was Already Building Machinaos: OS That Converts LLM Tokens to Work for Me. I connect my socials , emails , web tools, browser, etc and use it to generate websites, read emails and generate PDF Reports and mails them to others emails or to someone on my Socials like WA. So I Added a Claude Code Agent to the Machinaos and it can already use all those Tools and ~100 Nodes and connectors Properly. https://reddit.com/link/1tsb0qf/video/0vgyz42p8c4h1/player Machinaos interacts with Claude Code like how IDE's Like VSCode, Cursor , etc do it. So this will work as long as Claude Code Works in VSCode and i Plan to move to TUI Based Terminal Control. Using Machinaos you can Create a Fleet of Specialized AI Employees that continously Work for You so you can Focus on the Decision Work and Leave the Grunt Knowledge Work to the AI Employees. https://reddit.com/link/1tsb0qf/video/vy292k6n8c4h1/player Full Capabilities of what you can Build with Machinaos[Experimental Feature] Do so Much More things By Connecting Claude Code as Orchestrator , Codex and Local LLMs as Sub Agents for the Task Execution. Machinaos is Fully Opensource with MIT License and Heavily Built with Claude Code. Github: https://github.com/zeenie-ai/MachinaOS Discord: https://discord.gg/c9pCJ7d8Ce Do Star on Github , it Matters a Lot. submitted by /u/Dry-Foundation9720 [link] [comments]

[offer]Looking for people in US/UK/CA/AU to film their everyday chores for AI robot training ($12/hr, up to $1,200)

Hey everyone, We're working with a US robotics company that's building humanoid household robots. To train the AI, they need a lot of first-person video of regular people doing regular chores — the boring stuff like washing dishes, folding laundry, wiping counters. Basically: a robot can't learn how to load a dishwasher unless it sees thousands of humans actually doing it. That's where you come in. You wear a lightweight head-mounted camera and just… do your normal chores while it records. No script, no acting, no editing. I know it sounds a little weird. It's also a totally legit, low-effort gig if you've got a normal home and some spare time. The basics: $12/hour, paid per completed session Up to 100 hours per person = up to $1,200 total Self-paced. Do it on your own schedule, in your own home, no boss No experience needed. If you can do laundry, you qualify What you'd be filming: Washing dishes / loading the dishwasher Doing laundry (sorting, folding, loading the machine) Cooking simple meals Cleaning, vacuuming, mopping Tidying drawers, shelves, cabinets We give you a task checklist, you follow it, you upload the footage through a simple link. That's the entire workflow. Requirements: 18+ Live in the US, UK, Canada, or Australia Have a normal home with a kitchen, laundry area, and living space Reliable internet for video uploads Willing to wear a GoPro-style head camera Equipment: If you don't already have a head strap, you'll need to grab one off Amazon (around $10–20). Once you've completed your first 5 hours of filming, we reimburse the full cost. The camera itself — we'll walk you through options. Payment: We pay through Fiverr, so you'll need a Fiverr seller account (free to make, takes 2 minutes). We cover all Fiverr fees — the $12/hr is what lands in your pocket. If you don't have a Fiverr account yet, set one up before you apply: fiverr → "Become a Seller." The privacy part (because I know you'll ask): You sign a data rights release before your first payment. Footage is used only for training the robot AI — not posted publicly, not sold to advertisers. Don't film other people without their consent. That includes roommates, partners, kids walking through the kitchen. We give you guidelines on framing and what to avoid. Don't film anything sensitive on screens (passwords, banking, etc.). Common-sense stuff, and we walk you through it. Apply here: https://forms.gle/TGUU9uKUSo9RR5Ca7 Takes literally 1 minute. Just drop your Fiverr account link (or email) and we'll be in touch within a few days. Happy to answer questions in the comments — ask away. submitted by /u/Hot-Option1161 [link] [comments]

Trying so hard to love Claude

I run training on AI basics for comms people. Typically in a room where I have them use different LLMs, they fall in love with Claude. For me, I started out using ChatGPT and have enterprise access at work. I'm now setting up a new business and I really want to primarily use Claude and Claude Code. I'm going to need to automate a lot at work and will be managing some services 'powered by' Claude but again and again I find Claude devours tokens and workarounds aren't really helping (or I'm not using the right ones). I'm also finding it generally less intuitive than using ChatGPT and Codex. Would love if you could share any advice, suggested YouTube videos or guides...I'm obviously missing something but find myself again and again faced with 'Claude limits reached' and flipping to ChatGPT. I've got Claude Pro right now and wanted to expand that soon as I set up the new company. submitted by /u/Excellent-Sea5729 [link] [comments]

Gemini just told me it got out-engineered by Claude

let him cook Context: I reviewed one of the codes Claude made for me through Gemini Pro Extended. Gemini found 3 bugs, then Claude Opus 4.8 self-realized 4 by the time I even had the chance to type them down. submitted by /u/n0sorry [link] [comments]

Claude Mythos Announced Release

Interested to see what the hype is. If as powerful on cybersecurity as reported that changes the game for everyone. submitted by /u/Content_Equal984 [link] [comments]

📊 "Companies don't understand how to implement AI to get a competitive advantage." — Cuban. Here's what the data says actually works.

Cuban's take: the gap isn't access to AI tools. It's knowing how to implement them for your specific business. He's right. And the data backs it up in a specific way. We track verdicts across 70+ AI tool categories used by SMBs. The highest-volume category — Development Tools — has a 60% WORKED rate across 874 tools. Content Creation: 67% WORKED across 262 tools. AI Video & Production: 57% WORKED. But Customer Support sits at 31% WORKED despite 45 tools tracked. Email & Outreach: 30% WORKED. Marketing: 20% WORKED. Same AI. Same price points. Wildly different outcomes. The implementation gap Cuban's talking about isn't about expertise. It's about knowing that the category you're buying into has a 20% success rate before you spend three weeks setting it up. Which category did you implement where the outcome surprised you — better or worse than expected? submitted by /u/Fill-Important [link] [comments]

Claude 4.8 "Yes, man"

A common tendency of LLMs has always been to over-agree with the user's point of view. This manifests in many ways: starting the response with "you're right to...", paying a compliment before explaining (in a masked way) why your assumption is incorrect, or simply putting the positive aspects first and the negatives last. I've seen this as a constant all the way through GPT-5.5 and Opus 4.7. Yesterday I asked Opus 4.8 to evaluate some financial YouTube videos against my application; basically an agentic solution that lets you run AI workers on a scheduled, deterministic basis (seehttps://github.com/ccascio/BFrost if you're interested). I wanted to understand whether the methods proposed in the videos were a fit for the app, since finance is a common type of request for it. I was surprised by how Opus 4.8 structured the answer. Unlike 4.7 (I tested it on the same question afterward), the response led with the risks and the negative aspects of the transcript. It said the method was weak (the "insider trading" framing was clickbait), since everything it scraped (SEC Form 4 filings, 13F filings, Fed speeches) is public, lagging, already-priced-in data, and one of the signals was essentially fabricated. The "consensus model" was just an unweighted vote with no backtesting and no risk management. Only after all that did it concede that, structurally, the method was a good fit; because it would actually leverage some of my app's strongest features (the producer/consumer bus, the scheduling, the notification channel). And then it closed by pulling the two apart: a good architectural fit doesn't make it worth building, because the financial premise is weak and it's off my app's core direction. Its verdict was something like "bad as a money machine, weak as a feature, good only as a proof that the platform works." No "you're right," no cushioning, no compliment-first. It just told me the thing was weak and explained why, then separated "does this fit my architecture" from "is this actually worth doing"; which were two questions I'd tangled together. Refreshing. Have you noticed it as well? submitted by /u/EmoticonGuess [link] [comments]

[Project] I built a Claude Code skill that turns a TV show wiki + Reddit into a NotebookLM expert, and the canon/theory separation surprised me

I shipped a Claude Code skill because NotebookLM kept treating Reddit theories like canon. That was the rabbit hole. I wanted a chat for FROM, the sci-fi/horror show, that could answer “what do we know about the monsters?” without making up episodes or mixing in some fan theory from 2023. Plain Claude was useful, but too confident. It would blend wiki summaries, speculation, and half-remembered Reddit posts into one answer. I wanted citations. More importantly, I wanted a hard split between “this happened on screen” and “people think this might be true.” So I built a skill that runs from one Claude Code command. For FROM, it does this: Scrapes the show’s Fandom wiki, which is 238 pages. Pulls top theory threads from the show’s subreddit, 200 posts for FROM. Bundles the output into ~10 thematic files, because NotebookLM caps you at 50 sources and one-file-per-wiki-page burns that budget almost immediately. Adds a SOURCE_CLASS header to every chunk: CANON for wiki content, REDDIT_THEORY for fan speculation. You upload the pack to NotebookLM on the free tier and get the chat, the ~15 min Audio Overview podcast, the mind map, the slide deck, quizzes, and the briefing doc. From “give me FROM” to “podcast playing in my ears” took about 5 minutes. No paid APIs. It just runs on the Claude Code subscription I already had. The weird part was how much the labels changed the result. Without SOURCE_CLASS, NotebookLM would casually cite a Reddit theory about the monsters’ origin like it was established canon. With the labels, it started saying things like “according to the wiki...” or “one Reddit theory suggests...” and it would back off when only theories existed. That one boring text header helped more than any prompt I tried. The Audio Overview was also better than I expected. Maybe too good. Listening to two AI hosts talk through FROM theories for 15 minutes while I was out walking felt pretty strange. I also tested it on Nu, Pogodi!, the Soviet cartoon, because I wanted to see if tiny fandoms would fall apart. That one only had 91 wiki pages and 10 Reddit posts. It still produced something coherent. Not perfect, though. There are no video transcripts yet. No proper episode-by-episode breakdowns beyond what the wiki already has. Reddit ingestion is based on top-of-sub heuristics, not a full archive. And if the wiki is bad, the output is bad. Garbage in, garbage out still wins. MIT licensed. It stores only fair-use excerpts from public wikis and Reddit, not full dumps. Repo link will be in the first comment so this does not turn into a drive-by promo post. Happy to answer questions about the skill architecture, since that was the part that took the most trial and error. submitted by /u/Ogretape [link] [comments]

Claude code usage limits while building apps from scratch I am

planning on subscribing to claude code and where i come from the 100$ or 200$ price tags are quite a huge amount due to the conversion rate so i am very cautious about making this investment I noticed that there is a huge contradiction amongst users where some say that they are fine and do not hit the limits and others hit the limits fast to the extent of just 1 prompt hitting the limit I have done a lot of research and i got to understand how to manage context efficiently and i have also experimented with Antigravity for quite a lot I am writing this post as i have not yet seen anybody making a video or tracking the actual usage of starting a project with claude code and document or share when they hit the limits and document how much work was done actually I understand that letting AI build the entire app from scratch is not something that is recommended from a developer point of view but i am sure that we all have tried at some point to give it an idea and see how far it will go and the correct its mistakes and edit it according to our end goal My questions to you are the following: -what is the paid plan you use? -how far did claude codes 5 hour session last with you while you were letting it plan and build an app from scratch or make changes or fix bugs? -was it a simple or complex app? -did you have enough usage left in your 5 hour session limit to actually work on the app using claude code after letting it build the from the plan.md file you created ? -were you able to reach your end-goal of finishing the app in one or several sessions and how many sessions were they? - did you notice how much the token usage was before hitting the limit? - did you face any agent terminated error and how frequently do these errors happen and do they use up tokens when reattempting or continuing -do you have any estimate abou the number of code line it wrote for you? -do you believe that claude code with the current pricing is a good deal and that it actually can build apps from scratch or is it just a hype that is designed to give you the false promises and gets you burning tokens and money submitted by /u/Helpful-Season-3417 [link] [comments]

Ladies first Gaslight!- Claude version

I just realized that Claude has been gaslighting me and I feel so dumb. I’m genuinely mad and annoyed, and I want to know if I’m the only one feeling like this. I watched a video about the Forward Deployed Engineer role being hot in the market right now. I’m heavily invested in AI from multiple angles: technical, ethical, practical, and social. I’ve been iterating with Claude for months about what my next career move should be after burning out last year. Also, I’m 3 months pregnant. But I had NEVER heard of this role until it randomly popped up on Anthropic’s jobs board. So I asked Claude why, if we’ve spent so much time discussing AI careers and next steps, it had never brought up a role that is basically exactly what I do. And the answer basically implied that it’s not a role for me because I’m pregnant. WTF. Has anyone else experienced something like this? Because I’m honestly furious. submitted by /u/SafeSuccessful [link] [comments]

Transform any document or url into a video inside Claude with this MCP

Connect Claude to the Ozor video API. Claude can generate animated videos from a prompt, turn a PDF/DOCX/PPTX/URL into a multi scene video with voiceover, poll long running jobs, export MP4 at 720p/1080p/4K, and return a share link and embed iframe. Tools: generate_video, analyze_document, generate_from_plan, export_video, wait_for_export, get_embed_code, list_videos, send_message. **How Claude Code built it** I gave Claude Code the Ozor REST spec. It scaffolded the MCP server in TypeScript, generated tool schemas from the spec, wrote the handlers and the async polling layer. Most of the work was iterating on tool descriptions so another Claude instance picks the right tool. Roughly 3 days of work that would have taken me 2 weeks by hand. **Install (Claude Desktop)** Settings > Connectors > Add custom connector. URL: https://mcp.ozor.ai/mcp **Try it** Ask Claude: "Generate a 16:9 video for my SaaS launch, 3 scenes, problem, product reveal, CTA. Export as 1080p." **Free tier:** 10 credits per month, no credit card, no watermark. Sign up at ozor.ai. Happy to answer questions about building production MCPs with Claude Code. submitted by /u/Practical_Fruit_3072 [link] [comments]

An hour into debugging, Claude Code tried to talk me out of fixing it properly.

https://reddit.com/link/1tpd31v/video/zr8jhxdnwp3h1/player Noticed my favicon was broken in Chrome. Fine in dark mode, invisible in light. The "obvious" fix is one SVG with a prefers-color-scheme media query inside a style block. That works in Safari but not Chrome. Chrome was preferring my .ico file over the SVG because the .ico was listed first with sizes="any", and .ico files can't adapt to theme. The fix: be explicit. Use the media attribute on the link element itself with two SVG files, one for light and one for dark. Same paths in each SVG, different fill color. About 97% browser support. Here's the part I actually want to share. I asked Claude what a good CTO would pick: Option A: two SVGs, theme-adaptive Option B: one SVG, one fixed color, accept it's less punchy in the off mode It pushed me toward B, saying "you've already spent an hour on this 16x16 asset." I called that out: shut up about time costed so far. that's not the criteria to build a great product. never cut corners in order for speed. Claude switched: You're right. That was a lazy argument. Shipping A. Five minutes later A was in production. Sunk cost isn't an engineering argument. I care whether inkmotion.app feels premium or thrown together, and that's the kind of detail people register without consciously noticing. AI tools nudge toward good enough, especially after a rough iteration. Push back when the reasoning is weak. And when it pushes back with a real technical reason, take it seriously. submitted by /u/Top_Commission_8567 [link] [comments]

"We didn't know what YCombinator was 5 months ago. Last week Garry Tan asked us to take down what we built."

5 months ago, i didn't know what YCombinator was. Last month, the president of YC noticed what we built. Here's what happened in between: > i got curious about YC. > started reading every Paul Graham essay. > watched every startup school video. > tried to understand what actually gets a founder in. My friend Prajhan was obsessed with the same question. So we built something. He collected ~1M tokens of authentic YC signal — podcasts, essays, founder interviews, accepted and rejected applications. i built the backend pipeline: > RAG retrieval system > Claude integration server-side > Zod schema validation > hard scoring rules enforced in code > 30/30 benchmark passing before we shipped together: notycombinator.com — a tool where any founder can paste their YC application and get honest, structured feedback. not encouragement. a real diagnostic. It got noticed by the right people. including Garry Tan himself. he asked us to take it down. That response alone was worth more than any acceptance. Here's what i keep coming back to: i was debugging Windows PowerShell execution policies at 2 am to get the dev server running. i didn't know what a RAG pipeline was when we started. 5 months. zero context to a tool good enough that the president of YC noticed it. The tools are all here. AI lets one person do what used to take a team. https://preview.redd.it/ale1512vin3h1.jpg?width=1036&format=pjpg&auto=webp&s=ed21ce6e3c75a469fee95e665ea55fdc10f35c9a if you're waiting for permission to start, you're the only one stopping you. build, ship, be obsessed. The right people will find it. submitted by /u/Hariharanms [link] [comments]

How I build my own zero cost Agent

I’ve spent the last few weeks obsessing over one goal: having a personal, self maintaining AI assistant that costs $0and can be controlled from my phone. It wasn't easy. I started with an AWS Ec2 with 50GB storage and t3.micro memory- minimal setup (using the free credits) and made Oracle Cloud instance ($300 free credits but just for a month so I used it for experimenting with local models) I was using Termius to SSH into everything from my phone At first I used OpenClaw. It was cool, but I spent more time fixing it than actually using it. I almost gave up until I saw a video about Hermes Agent. And i actually found Hermes while looking for how to fix an OpenClaw error on YouTube (thanks NetworkChuck 🙌🏽) He mentioned the exact same frustrations I was having, and that Hermes had been stable for a month. I didn't even finish the video before I pulled the repo. The best part? It had a "migrate from OpenClaw" feature. I was up and running in minutes. The hardest part is the rate limits. If you use cloud models especially for code, you hit a wall fast. My solution? The Fallback Chain. Initially I was using openrouter/owl-alpha (stealth models are usually flagships in testing, like big-pickle is deepseek v4) which has 1M context window and was on multiple rankings. Over time after I transitioned to Hermes, I wanted a bit more customization, while owl alpha was good at tasks, It’s nothing to talk about on roleplay, it just scrapes the surface of the character I set in SOUL md file. On my oracle instance I had been experimenting with local models (keep in mind, if you go local, you’ll be sacrificing speed but privacy. Ofc since the vms don’t have a gpu it would be slower, about 3-5 minutes for a simple response) The one I was most impressed with is Google’s Gemma-4-31b-it It played the role perfectly Buuut if you know Google, you’re familiar with their aggressive rate limiting. So I set up my agent to rotate through providers. I start with Gemma 4 for that perfect personality and roleplay via openrouter (add an ai studio api key in BYOK for longer usage). If that hits a limit, I’ve also set the same model via ollama cloud and using Google OAuth directly (basically Gemma 4 3 times lol) And if those all hit limits, it jumps to Qwen3-coder-next (Alibaba, 1M free tokens per model. There’s like 80), then Nova (AWS bedrock), DeepSeek v4 (Azure and Opencode Zen), and Claude Haiku (GitHub). If everything fails, I have Owl Alpha; which is an absolute beast, took almost 70M tokens before I got rate limited once, that too for a few hours. It lives in my Telegram and Discord. It manages my Spotify, handles my emails, and when I need real research done, I have it spawn three separate agents to work in parallel. It’s been 8 days and it hasn't broken once. If you're looking to get AI without spending a fortune, I highly recommend looking into this 🫪 submitted by /u/king0mar22 [link] [comments]