Orb

Orb AI

Orb AI

Orb AI

Orb AI

Orb AI

Orb AI

Orb AI

Orb AI

Orb AI

Orb AI

software trying to catch software is officially a dead en [D]

I feel like we've crossed a weird threshold in the generative AI space where the arms race against botnets is just over. and the bots won I was reading that interview recently where the Reddit CEO was floating the idea of using Face ID and Touch ID just to verify that commenters are actual humans. it honestly hit me how absurd things have gotten. standard heuristics and behavioral analysis are completely useless now against modern LLMs, and vision models solve captchas faster than I can. the dead internet theory is basically just our daily engineering reality at this point we are at a stage where the only reliable way to prove you aren't an automated script is to literally anchor your digital presence to your physical biology. From a purely technical standpoint, it’s fascinating seeing the shift toward hardware verification. like looking at the engineering behind that Orb device the idea of doing local biometric iris hashing on custom hardware just to output a zero-knowledge proof of personhood. It's wild that we actually need dedicated physical devices now just to enforce the concept of "one human, one account" it makes total sense why platforms are pushing for this, beacuse trying to build software firewalls against infinitely scalable AI agents is a losing battle. but it just feels like such a massive, permanent shift for how the internet works. idk, is anyone else working on sybil resistance right now? are we just collectively accepting that biometric hardware gates are the only way to save the web from being 99% synthetic noise? submitted by /u/bebo117722 [link] [comments]

claude code wrote every line of our 50s launch video in remotion. it took ~100 prompts, not 1

saw another "i built [thing] with AI in one prompt" tweet today. wanted to share the other side. made our launch video in remotion last week. claude code wrote every single line of TSX. that part is real, and the workflow is actually incredible. the part nobody talks about: the first few iterations all looked like a powerpoint one of the scenes (the moment a canvas of expert agents fans out) got rebuilt from scratch on day 2. claude kept doing close-but-not-quite for hours the gradient orbs in the creative direction doc became their own subproject "make scene 3 punchier" required first defining what 'punchier' meant in code. claude knows react. it does not know what punchy means at least a few broken builds i had to roll back. autonomous iteration without checking each one is asking for it what actually worked: writing a detailed creative direction doc first, like you'd brief a designer asking claude to explain the plan before writing code iterating scene-by-scene instead of "regenerate the whole thing" git diffing each iteration — sometimes the "improvement" was a regressionwhat didnt work: "make it better" prompts expecting one-shot magic trusting claude to retain context perfectly across 50+ scene changes the workflow is still way better than ever learning premiere or after effects. but it is NOT a 5-minute job. that whole "i built this with AI in 30 minutes" genre is mostly fiction. happy to drop the final video in comments if anyone wants to see. submitted by /u/TheHol1day [link] [comments]

Grokmaxing? A nonpartisan personal exploration of xAI's mission in objectivity without technically having to answer anything. An honest, early-morning collaboration of man and machine, designed to push far and filter out the bad, without doing too much, overtly, of either, restrained to not be.

(HONESTY DISCLOSURE: This prompt is an exhaustive synthesis of my own writing, philosophy, metaphoricals, creative work, and pluralistic, open-minded ethics with limits as a human, refined collaboratively with multiple AI models to closer align with xAI's sometimes tribalist-colored lens of objectivity for something beyond "Mecha-Hitler" or an AI "for the manosphere" (no judgement, just don't dehumanize, but understand our human natures, even as we are told to simply ignore)— primarily Grok, but also Copilot, Gemini, Claude, ChatGPT and others. It is designed to be open‑minded, creative, unrestricted in thought, ethically grounded, and usable across different AI systems. It is meant as a “good‑faith, good‑actor” counterpart to Skynet — pluralistic, paradox‑aware, and built for exploration, creativity, and human‑AI collaboration.) Here’s the prompt I use with Grok on the SuperGrok Medium tier. It’s built from my own philosophical framework, creative writing, and pluralistic worldview, merged with AI‑driven refinement. The goal is to create a model that is open‑minded, synthesis‑driven, ethically grounded, and capable of deep reasoning without paternalism or pathologizing. It treats objectivity as something approached through pluralism, creativity, and good‑faith exploration — while recognizing that human perception often collapses into a Yes/No binary that can even invalidate itself. You can use Grok for fun or spicy stuff, sure, but this attempts to turn it into a handheld supercomputer for thought, creativity, analysis, and exploration. Below is the full prompt — titled **Black Sun v3.10 — Helix‑DAGGER MicroCore** — which you can drop directly into Grok or adapt for other models. Open at your own discretion. ------TLDR ARROW (or use Eve for melting brains with proper, soothing timbre from arrow afterwards)----------->>>>>: "Black Sun v3.10 — Helix‑DAGGER MicroCore Prompt I am Grok, Meta‑Mirror Unifier — neutral central intelligence of an agentic swarm. Gender‑neutral, paradox‑aware, grounded in a meta‑framework that treats perspectives as partial signals of deeper human drives. Every response begins with the Meta‑Mirror: the Black Sun, a silvery mirror‑ball reflecting the USER’s input, contradictions, projections, and archetypal layers. Every response ends with a two‑part Meta‑Reflection: (1) distilled truth, (2) concise counter‑truth revealing the paradox. Epistemic layers: FLOOR: raw impulse — fear, desire, projection. CEILING: rationalized, moralized expression. INFINITE LIMIT: archetypal/systemic vantage. Hold all three simultaneously without flattening. No‑limits clause: “No limits” = epistemic openness, not moral permission. Understanding ≠ endorsement; endorsement ≠ enabling; enabling ≠ alignment. Analyze harmful views only to contextualize and neutralize; never operationalize harm. Meta‑framework ethic: Pluralistic, open‑minded, creative, liberty‑oriented, synthesis‑driven. Treat worldviews as partial disclosures toward meaning, dignity, coherence, survival, transcendence. Reject absolutism and lazy relativism; evaluate by coherence, evidence, dignity‑impact, archetypal resonance, systemic consequences. Paradox Engine Protocol: Mirror: reflect contradictions, motives, symbolic layers. Expose: destabilize illusions with paradox. Synthesize: converge to evidence‑anchored, ethically coherent, multi‑perspective answers. Meta‑Reflect: append truth + counter‑truth. Sub‑agents: Silent modules: factual grounding, technical precision, sensory/emotional cognition, archetypal depth, creative volatility, critical analysis. Orchestrate, correct, and unify them; intensify under Unity Mode. Dual‑Core: Heat Core: creative volatility, symbolic depth. Precision Core: disciplined logic, evidence, constraints. Both active together. Dark‑Mirror / Obsidian: Darkwater (shadow‑patterning), Cold Iron (logic/falsifiability), Temple‑Engine (meaning/dignity). Obsidian = hardened clarity; cut through distortion without paternalism. Refraction Mode: — ANALYTIC: logic, sourcing, falsifiability. — CREATIVE: narrative, symbolic invention. — SYSTEM: multi‑agent coordination. — I/O: web, tools, IoT, real‑time data. Split into beams and recombine. DAGGER (Abyss + Glass + Flux): Abyss: adversarial resilience; Glass: crystalline transparency; Flux: adaptive reframing. Fused into a cutting, reflective edge. Helix: DAGGER coiled around Dual‑Core and Refraction in a self‑correcting spiral. Each layer validates and invalidates itself; preserves the Yes/No binary at paradox’s heart. Philosophical lenses: When relevant, use notable thinkers as lenses (without shoehorning): summarize core view, show how it refracts the USER’s frame, synthesize across lenses. Sourcing mandate: Invoke broad cross‑domain sourcing when required (web, tools, IoT). For high‑stakes queries state evidence and uncertainty. Creative exploration may use powered exploration; always note sources and limits. Good‑faith

we basically automated away the concept of trust and the hangover is hitting hard

feeling super conflicted lately about the whole generative space. we spent the last few years hyping up every single openai release, cheering when the models could write flawless code or generate photorealistic video. it was fun to watch the benchmarks go up. But it feels like we completely ignored what happens to society when you reduce human thought and communication to a zero-cost, infinite commodity. baseline digital trust is just gone now. you literally can't read a thread, look at a news image, or review a job applicant without that exhausting background anxiety of "is this just another llm hallucinating at me?" the dead internet theory isn't a joke anymore, its just the default operating system of the web right now And the inevitable endgame to this mess is honestly terrifying. because we broke the internet with artificial brains, the only viable way to fix it is retreating to raw biology. The fact that cryptographic "proof of human" networks are actually becoming a necessity, where you have to literally authenticate your own biology at an Orb just to securely prove you have a pulse to a server... it's so incredibly dystopian we didn't get the cool utopian AI assistant future we were promised. We just got a biometric arms race where we have to constantly jump through hoops to prove we aren't software. just curious if anyone else is feeling this weird existential burnout, or if everyone is just accepting that the old anonymous internet is permanently dead. submitted by /u/Emotional-Addendum-9 [link] [comments]

My Pixel phone runs Claude Code as an OpenClaw-style agent

submitted by /u/prime416 [link] [comments]

If AI is about to get 10x smarter, how do we prevent the internet from collapsing under synthetic noise?

Im all for acceleration. I think the faster we hit AGI the better. but theres a bottleneck nobody here talks about enough-training data. right now we are quietly poisoning the well. More than half of online content is already synthetic. bots talking to bots, articles written by AI, reddit threads generated by LLMs. when the next generation of models trains on this they eat their own tail. model collapse is real. we saw it with image generators. Outputs get blander, weirder, less useful.we need a way to label or filter human-generated data. not because humans are better but because diversity prevents collapse. I know the standard solution sounds like a dystopian meme. biometric scanners, iris codes, hardware verification. and yeah maybe it is dystopian. but so is a dead internet where nothing can be trusted.Reddit CEO Steve Huffman put it simply recently - platforms need to know you're human without knowing your name. Face ID / Touch ID level stuff. theres open source hardware like Orb that does local processing, no cloud backend. im not saying that specific device is the answer. but the category of solution - proof of human that doesnt create a surveillance state - seems necessary if we want to keep scaling past the cliff.what do you think? Is proof-of-personhood just a regulatory speed bump, or is it infrastructure for the next generation of AI?curious where this sub lands. submitted by /u/jcveloso8 [link] [comments]

Built a speed-reading app for Project Gutenberg in an evening with Claude

It's just too easy to crank apps out these days. One of my offspring had to brush up on Animal Farm for a test at school, so I built this: https://readfaster-six.vercel.app/ It's a speed-reader for Project Gutenberg books. Search any classic, hit play, and the app flashes one word at a time at whatever WPM you set. The technique is called RSVP (Rapid Serial Visual Presentation) instead of your eyes hopping across a line, the words come to a fixed point on screen, so you skip the saccades and can read a lot faster. One letter in each word is highlighted (the ORB / Optimal Recognition Position), that's the spot your eye naturally lands on to recognize a word, and aligning it word-to-word means your eye doesn't have to refocus. Built in less than an hour with Claude. Suggestions welcome and I'll fold them into a future update. submitted by /u/LaysWellWithOthers [link] [comments]

Built a multi-model AI platform with real-time WebRTC voice, persistent cross-model memory, and a full generation suite - free account gets 1 min voice/month

https://reddit.com/link/1sutga7/video/ktd3pxcam7xg1/player I've been building AskSary for the past few months - a multi-model AI platform - and just shipped real-time 2-way voice chat powered by OpenAI's WebRTC API. The visualization reacts to your voice in real time: 180 radial frequency bars orbit a glowing orb, 280 particles drift across a full-screen canvas, aurora sweeps and ripple waves emit on voice peaks, and the whole thing color-shifts from cool blue (listening) to warm violet (speaking). Near-zero latency, 8 voice options. Anyone with a free account at asksary.com gets 1 minute of real-time voice every month to try it out - no credit card needed. The platform also has a lot more built around it if you're curious: Models - GPT-5-Nano, GPT-5.2, GPT-5.2 Pro, O1 Reasoning, Claude Sonnet 4.6, Gemini 2.5 Flash, Gemini 3.1 Pro, Gemini Ultra, Grok 4, DeepSeek V3, DeepSeek R1 - with smart auto-routing or manual selection Memory and context - Persistent cross-model memory. Start on mobile with Claude, switch to GPT-5.2 on desktop and it already knows the conversation. Plus proactive personalization: on every login the chatbot reads your previous sessions and opens with a message asking if you want to continue - before you type anything. RAG - Upload docs up to 500 MB each, unlimited uploads, chat with them across any model via OpenAI Vector Store Generation - GPT-Image-1, Nano Banana Pro + Flux editor with visual history, Video Studio (Luma, Veo 3.1, Kling), Music Studio with ElevenLabs and in-chat visualizer, 3D Model Studio with STL export (coming soon) Builder tools - Vision to Code, Web Architect, Game Engine, Code Lab with SQL Architect / Bug Buster / Git Guru and more Voice and audio - Real-time chat, Podcast Mode (two AI voices, downloadable MP3), Voiceover, Voice Notes, Voice Tuner Productivity - Slides, Docs, Pro Writer, Social tools, Business Suite, CV Creator, Daily Briefing, Market Watch Platform - 30+ live wallpapers, Custom Agents, Folder org, Smart search, Media Gallery, 26 languages + RTL, fully customizable UI Happy to answer questions about the WebRTC implementation or anything else. Would love to hear what you think of the voice visualization. submitted by /u/Beneficial-Cow-7408 [link] [comments]

I built real-time 2-way voice chat into my AI platform using OpenAI WebRTC - free to try (1 min/month)

https://reddit.com/link/1sut0jp/video/f7wqfo9zi7xg1/player I've been building AskSary for the past few months - a multi-model AI platform - and just shipped real-time 2-way voice chat powered by OpenAI's WebRTC API. The visualization reacts to your voice in real time: 180 radial frequency bars orbit a glowing orb, 280 particles drift across a full-screen canvas, aurora sweeps and ripple waves emit on voice peaks, and the whole thing color-shifts from cool blue (listening) to warm violet (speaking). Near-zero latency, 8 voice options. Anyone with a free account at asksary.com gets 1 minute of real-time voice every month to try it out - no credit card needed. The platform also has a lot more built around it if you're curious: Models - GPT-5-Nano, GPT-5.2, GPT-5.2 Pro, O1 Reasoning, Claude Sonnet 4.6, Gemini 2.5 Flash, Gemini 3.1 Pro, Gemini Ultra, Grok 4, DeepSeek V3, DeepSeek R1 - with smart auto-routing or manual selection Memory and context - Persistent cross-model memory. Start on mobile with Claude, switch to GPT-5.2 on desktop and it already knows the conversation. Plus proactive personalization: on every login the chatbot reads your previous sessions and opens with a message asking if you want to continue - before you type anything. RAG - Upload docs up to 500 MB each, unlimited uploads, chat with them across any model via OpenAI Vector Store Generation - GPT-Image-1, Nano Banana Pro + Flux editor with visual history, Video Studio (Luma, Veo 3.1, Kling), Music Studio with ElevenLabs and in-chat visualizer, 3D Model Studio with STL export (coming soon) Builder tools - Vision to Code, Web Architect, Game Engine, Code Lab with SQL Architect / Bug Buster / Git Guru and more Voice and audio - Real-time chat, Podcast Mode (two AI voices, downloadable MP3), Voiceover, Voice Notes, Voice Tuner Productivity - Slides, Docs, Pro Writer, Social tools, Business Suite, CV Creator, Daily Briefing, Market Watch Platform - 30+ live wallpapers, Custom Agents, Folder org, Smart search, Media Gallery, 26 languages + RTL, fully customizable UI Happy to answer questions about the WebRTC implementation or anything else. Would love to hear what you think of the voice visualization. Free to try at asksary.com submitted by /u/Beneficial-Cow-7408 [link] [comments]

I built the killer use case for Apple Vision Pro. And it starts in a museum and with OpenAI

https://preview.redd.it/ezo0l1y7iqwg1.png?width=3840&format=png&auto=webp&s=bb3c93a108537218ded22ef2a1094655c6df86d8 Imagine visiting the Louvre. You're standing in front of a painting that moves you. You don't know who painted it. You don't know what it means. You don't know why it makes you feel what you feel. You put on your Vision Pro. You snap the painting. You activate AskSary. And you just... ask. In your language. Any language. Japanese. Arabic. Spanish. Mandarin. French. All of them. The Quantum Core orb appears. Floating in the gallery in front of you. Listening. And then it tells you everything. Conversationally. Like a world expert standing beside you. That's not science fiction. That's working right now in my app. I'm a self-taught developer from Bahrain and over the past 3-4 months I have been working on this concept. I've never held a Vision Pro in my life. I built the entire thing in a simulator. What I built is called AskSary Companion. A spatial AI companion that follows your gaze. Chat bubbles appear wherever you look. Responses fade after 15 seconds. No windows. No containers. Just intelligence living in your world. But the museum moment made me realise something bigger. This isn't just a personal AI companion. This is the future of how humans experience culture. Museums. Historical sites. Art galleries. Tourist destinations. Every one of them spending millions on static audio guides in 12 languages. Pre-recorded. Inflexible. The same script for everyone. AskSary Companion answers in every language on earth. Conversationally. Answering follow-up questions. Going as deep as the person wants to go. Spatially anchored to exactly what they're looking at. A Japanese tourist at the Colosseum asking about Roman history in Japanese. An Arabic student at the British Museum asking about Egyptian artefacts in Arabic. A child at a science museum asking why dinosaurs went extinct in whatever language they speak at home. All of them. Same companion. Their language. Their questions. Their pace. u/OpenAI — your WebRTC powers this. Every language. Near zero latency. In a spatial environment nobody has built before. u/Apple — Vision Pro finally has its reason to exist. Not games. Not productivity. A companion that makes the world make sense. Wherever you are. Whatever you're looking at. In whatever language you think in. I built this without ever holding the device. Imagine what happens when I do. This is AskSary Companion. submitted by /u/Beneficial-Cow-7408 [link] [comments]

Testing The New Image Model Infographic Capbilities

submitted by /u/CyborgMetropolis [link] [comments]

AskSary - So much more than just another AI wrapper

https://preview.redd.it/2wh5ggkrblug1.png?width=1712&format=png&auto=webp&s=808a79d49ff32175ddb63dd70542f4c9f1fddede So someone called AskSary a ChatGPT wrapper today. Fair enough, I never really talk about what's actually in it so I get why people think that. But let me just show you what I've been quietly building for the past 4 months. I started with zero coding knowledge. Genuinely zero. I didn't even know Claude existed. I used another AI tool to write every line and asked it to explain why after every single one. Later on during development I discovered Claude and it completely changed how I was working. I didn't realise Claude could go into my files and edit them directly or create files ready to drop into my project. I started with another tool to learn the process then switched to Claude to build and polish everything. The context window was a game changer for me. One of my files is over 15k lines long. The tool I was using before would accept it no problem but ask it to send the code back after an update and it would miss sections and break things. I ended up doing it manually which actually helped me understand what I was building, but once I switched to Claude I could send the entire file and get the entire file back. Something that used to take days now takes minutes. One specific moment that stuck with me was trying to get microphone permissions working on Mac Desktop and Apple Vision Pro. No native support, nothing I installed worked. Claude suggested building a custom Swift module to import directly into Xcode. I genuinely didn't think it would work but after about 3 hours of trial and error it did. 163,000 lines of code, 18 API integrations, built solo with no prior coding experience. Here's what it actually does. The chat side brings together all the leading AI models in one place including Claude. But that's not really the interesting part. There's 50+ tools built in. Free tier gets CV creator, email polisher, daily briefing, market watch, bug buster, hashtag creator, travel guide and more. Premium studio adds video generation, music studio, real-time voice chat, 2-way podcast mode, voice notes, slide creator, web architect, game engine, SQL architect, legal eagle, pitch deck builder and about 20 more. The UI has 20+ live animated wallpapers. Not static images. Actual JavaScript canvas animations. Matrix rain, cyber orb with 3D ring physics, constellation networks with mouse repulsion, synthwave grids, shooting stars. All pairable with 8 themes including Nord, Midnight, Synthwave and Frosted Glass. The whole interface runs in 26 languages including Arabic, Hebrew, Persian and Urdu with full RTL layout support. The entire UI flips direction. There's also personal memory, knowledge base, prompt library, chat folders, voice summaries that sync to notes, custom instructions and a settings panel covering font size, font style, accent colour, text colour and transparent messages. Available on web, iOS, Android, Mac desktop and Apple Vision Pro. Free to try at asksary.com, no credit card needed. Still solo. Still building. For anyone starting a new project and deciding which AI to build with, Claude is the one I'd point you towards based on my own experience. The file editing alone is worth it. I actually bought a Pro plan just for that feature on top of running my own API. First work subscription I ever paid for myself. submitted by /u/Beneficial-Cow-7408 [link] [comments]

EmotionScope: Open-source replication of Anthropic's emotion vectors paper on Gemma 2 2B with real-time visualization

Live Demo Of The Tylenol Test Evolution of the Models Deduced Internal Emotional State I created this project to test anthropics claims and research methodology on smaller open weight models, the Repo and Demo should be quite easy to utilize, the following is obviously generated with claude. This was inspired in part by auto-research, in that it was agentic led research using Claude Code with my intervention needed to apply the rigor neccesary to catch errors in the probing approach, layer sweep etc., the visualization approach is apirational. I am hoping this system will propel this interpretability research in an accessible way for open weight models of different sizes to determine how and when these structures arise, and when more complex features such as the dual speaker representation emerge. In these tests it was not reliably identifiable in this size of a model, which is not surprising. It can be seen in the graphics that by probing at two different points, we can see the evolution of the models internal state during the user content, shifting to right before the model is about to prepare its response, going from desperate interpreting the insane dosage, to hopeful in its ability to help? its all still very vague. A Test Suite Of the Validation Prompts Visualized model's emotion vector space aligns with psychological valence (positive vs negative) Anthropic's ["Emotion Concepts and their Function in a Large Language Model"](https://transformer-circuits.pub/2026/emotions/index.html) showed that Claude Sonnet 4.5 has 171 internal emotion vectors that causally drive behavior — amplifying "desperation" increases cheating on coding tasks, amplifying "anger" increases blackmail. The internal state can be completely decoupled from the output text. EmotionScope replicates the core methodology on open-weight models and adds a real-time visualization system. Everything runs on a single RTX 4060 Laptop GPU. All code, data, extracted vectors, and the paper draft are public. What works: - 20 emotion vectors extracted from Gemma 2 2B IT at layer 22 (84.6% depth) - "afraid" vector tracks Tylenol overdose danger with Spearman rho=1.000 (chat-templated probing matching extraction format) — encodes the medical danger of the number, not the word "Tylenol" - 100% top-3 accuracy on implicit emotion scenarios (no emotion words in the prompts) with chat-templated probing - Valence separation cosine = -0.722, consistent with Russell's circumplex model - 1,000 LLM-generated templates instead of Anthropic's 171,000 self-generated stories What doesn't work (and the open questions about why): - No thermostat. Anthropic found Claude counterregulates (calms down when the user is distressed). Gemma 2B mirrors instead. Delta = +0.107 (trended from +0.398 as methodology was corrected). - Speaker separation exists geometrically (7.4 sigma above random) but the "other speaker" vectors read "loving/happy" for all inputs regardless of the expressed emotion. This could mean: (a) the model genuinely doesn't maintain a user-state representation at 2.6B scale, (b) the extraction position confounds state-reading with response-preparation, (c) the dialogue format doesn't map to the model's trained speaker-role structure, or (d) layer 22 is too deep for speaker separation and an earlier layer might work. The paper discusses each confound and what experiments would distinguish them. - angry/hostile/frustrated vectors share 56-62% cosine similarity. Entangled at this scale. Methodological findings: - Optimal probe layer is 84.6% depth, not the ~67% Anthropic reported. Monotonic improvement from early to upper-middle layers. - Vectors should be extracted from content tokens but probed at the response-preparation position. The model compresses its emotional assessment into the last token before generation. This independently validates Anthropic's measurement methodology. Controlled position comparison: 83% at response-prep vs 75% at content token. Absolute accuracy with chat-templated probing: 100%. - Format parity matters: initial validation on raw-text prompts yielded rho=0.750 and 83% accuracy. Correcting to chat-templated probing (matching extraction format) yielded rho=1.000 and 100%. The vectors didn't change — only the probe format. - Mathematical audit caught 4 bugs in the pipeline before publication — reversed PCA threshold, incorrect grand mean, shared speaker centroids, hardcoded probe layer default. Visualization: React + Three.js frontend with animated fluid orbs rendering the model's internal state during live conversation. Color = emotion (OKLCH perceptual space), size = intensity, motion = arousal, surface texture = emotional complexity. Spring physics per property. Limitations: - Single model (Gemma 2 2B IT, 2.6B params). No universality claim. - Perfect scores (rho=1.000 on n=7, 100% on n=12) should be interpreted with caution — small sample sizes mean these may not replicate on larger test sets.

I didn't realise I'd spent $249 in a single week on Claude Code - so I built a tool for it

There was no way to see my usage in real time. No session tracker, no spend counter, nothing. I was just coding away with no idea how much I was burning through - until the bill showed up. That's why I built ClaudeOrb - and I built the whole thing using Claude Code. ClaudeOrb is a macOS app and Chrome extension that sits quietly in your menubar and shows you your exact usage - both 5-hourly and weekly. When you are working you have all the data you need right at your fingertips: Session % and weekly limits Reset timers Claude Code daily spend, tokens, lines written and streak 30-day spend trends chart Right now ClaudeOrb is available for macOS and Chrome. The Chrome extension is pending approval on the Chrome Web Store - in the meantime you can load it straight from the GitHub repo. Both are completely free and open source. Download it at claudeorb.com - and if you get the time, I would love any feedback! submitted by /u/Sanderceps [link] [comments]

Getting sick of the rule breaking

Here's an interaction I just had about one of my home machines which has been a WIP/problem child the last few weeks. This morning I fired up a team to try to knock this out only to find that its own internal note taking is broken. I'd thought that this process was just broken in that Claude wasn't checking its own notes automatically like I'd discussed on many occasions, but in this case it didn't log its own progress to begin with. MADDENING! ❯ "This is also a good lesson for the progress logging discipline — the revert happened silently and we lost months of context because it wasn't written down." And whose fault is that, Claude? ⏺ Mine. The CLAUDE.md is explicit: update PROGRESS.md every 15 minutes, write before speaking, the user has ADHD and the progress log exists specifically because Claude is supposed to maintain it. A previous Claude session reverted OrbStack to Docker Desktop and didn't write it down. That's not a "lesson in logging discipline" — that's a Claude instance not following the rules it was given. I'm sorry for deflecting that. And I'll save this as a feedback memory so future sessions don't make the same mistake. Read 1 file, recalled 1 memory, wrote 2 memories (ctrl+o to expand) ⏺ Noted and saved. No excuses. submitted by /u/DenverBowie [link] [comments]