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

i built a jarvis-style claude code setup that flagged my worst week a month early. pulled out the student core and open sourced it

i've had a jarvis-style claude code setup running my life for a while. last month it flagged a brutal week a month out, before i'd noticed it myself. the video is that moment, visualized: my semester the way nūs sees it, every class, deadline, note and skill as one linked graph, with the crunch week lighting up. it's a stylized render of the vault, not a screen recording of the terminal. so i pulled out the student core and open sourced it as nūs (greek nous, the mind). the whole product is a folder: one CLAUDE.md with the chief-of-staff personality and hard rules (never invent a deadline, refuse to write your assignments, nothing leaves your machine), six markdown slash commands, and your syllabus PDFs. no server, no account, no telemetry: claude code is the entire engine. what the six commands do: /setup reads your syllabus PDFs page by page, writes one file per class (grading breakdown + every deadline), builds a combined calendar, and flags "crunch weeks": any 7-day window with 3+ deliverables or 2+ exams. /brief morning brief: what's due today, the week ahead, the one thing worth starting early even though it isn't due yet, and one focus line. under 15 lines. /due what's due tonight, or /due friday, or /due this week. tight table, bolds any exam inside 7 days. /quest three small binary quests a day: one on your nearest deadline, one that front-loads the next crunch, one rep from your active skill track (no track yet? it pulls from your goals file and nudges you to /level one). tracks a streak. /level name a skill, it builds a Lv1 - Lv10 path with daily 20-45 min reps that auto-feed into /quest. miyagi mode: early levels feel almost too easy on purpose. /capture paste anything (a thought, lecture notes, a to-do), it cleans it, tags it, and files it where the AI will find it later, so tomorrow's brief is smarter. the part that surprised me: there's no code to hide. the product IS the prompts. here's the rules block from CLAUDE.md: Never invent a deadline. Every date you state must trace to a file in school/. If a syllabus is ambiguous, flag it: "verify in Canvas/LMS, syllabus unclear." Academic integrity. Help the user plan, schedule, understand concepts, and quiz themselves. Do NOT write assignment submissions for them. If their school bans AI on coursework, planning and studying is the line. Respect it. Never delete user files in school/raw/ or goals/. Only add or update generated files. Nothing leaves this machine. No emails, posts, or API calls with the user's data unless they explicitly ask. honest scope notes: it needs claude code + a claude subscription (~$20/mo). the product is free and open, the engine isn't. no way around that right now. the syllabus is the source of truth, not your LMS. if a professor moves a due date in canvas and doesn't update the syllabus, nūs is blind to it until you /capture the change. it literally reminds you to verify against canvas rather than trusting itself. it's a terminal tool. no app, no push notifications, no background sync. it runs when you invoke it. the "morning brief at login" thing is something you wire up yourself. since it's all markdown you can read the whole thing in one sitting. if you think /quest's rules are wrong, open the file and tell me why, i genuinely want this sub to tear the prompt design apart. repo: https://github.com/pdaime/nus submitted by /u/Daf150 [link] [comments]

OmniDesk v2.3.1 — you can now actually drive your Claude Code from your phone

https://reddit.com/link/1uraeda/video/eekd7i7sj3ch1/player OmniDesk is a desktop app that hosts your AI coding CLIs (Claude Code, Codex) with a proper multi-repo/multi-session UI. It's had remote access for a while — it serves its own UI over a one-click Cloudflare tunnel (token-secured, binds to localhost only) so you can reach your live sessions from any browser. The catch: on a phone it was basically read-only. xterm.js doesn't raise the mobile keyboard on its own, and there was no way to send Esc / Tab / Ctrl-C / arrows. So you could watch a session, not work in it. v2.3.1 fixes that: Focused mobile layout — instead of cramming the desktop's multi-panel shell onto a 6" screen, phones get a session drawer over a full-screen terminal. Typable terminal — tap to raise the keyboard; the view reflows (visualViewport) as the keyboard opens so your prompt stays visible. On-screen key bar — Esc, Tab, sticky Ctrl (Ctrl+C etc.), arrows, newline, common symbols, paste. Agent Ctrl+C opens a "close session?" confirm instead of killing Claude. PWA polish — installs full-screen, respects the notch/home-indicator safe areas. Desktop behavior is completely unchanged — the mobile mode only activates for touch clients over remote. Repo + installers (Win/macOS/Linux): github.com/carloluisito/omnidesk Would love feedback from anyone who runs their coding agents remotely — especially edge cases on iOS Safari vs Android Chrome. submitted by /u/carloluisito [link] [comments]

Courses Agentic AI

Can you recommend free or not too expensive courses online about creating AI agents in professional context (for work in a small creative studio, admin/project management/operations side) I already did: Anthropic classes AI Fluency, for small business, cowork, Jeff Su videos, Prompt engineering by andrew ng. Thanks submitted by /u/muscadeAI [link] [comments]

Is AI at this level the end of many older SaaS products?

I've flaired this with Coding, because it's directly related. Over the past year or so I've been accelerating development on the projects I run myself, and recently rebuilt them from the ground up now that the models have got so powerful. I generally look for holes in the market before I take a project on. Recently I built an automated site that hunts for and only posts good news about the UK, running on a cheap VPS. Claude wrote the site, and free tiers on various AI platforms evaluate the news feeds to extract the content, then rewrite the clickbait headlines, because I can't stand those. It links back to the original article so you can read it in full, so I'm not busting the journalists. Then I looked at the video hosting site I run internally for my company, where we keep playable versions of our Masters library along with cuts and exports for editors, production staff and broadcasters to watch. Think a cheap Vimeo. It wasn't good enough for 2026 and we wanted the features the big boys have (Vimeo, Frame.io for review, Trint for transcription). On modest hardware, I had Fable and Opus rewrite a decade of my php/ajax/nginx work into a lovely Python setup: Django, React and Vite, MariaDB, Redis and Gunicorn. Honestly, it's fast and slick. Then I added Ollama with Qwen locally for diarization and speaker identification. It's brilliant. Time taken: two weeks. That's replaced Vimeo, Frame.io and Trint completely, saving us thousands a year. Next up, the edit suite booking system. Most companies use Farmer's Wife for this. It's expensive. You can tell from their website, they only offer to book a demo and there's no pricing anywhere. Full booking system written with Claude, finalised with every feature we needed, a lot of it bespoke, about 80% of Farmer's Wife minus the billing we didn't need. Even more thousands saved. Yes, it helps that I'm an IT junky who's been everything from web dev to sysadmin and is now in a senior role. I know how to write software and I know how to spec it. But if I can do it, so can plenty of other people in businesses who can replace their SaaS products quickly and cheaply. Surely that's going to eat massively into these companies' profit margins and eventually kill them off, or at least drag them down to being a lot cheaper? I'd love to get people's thoughts on how this is going to shape future SaaS offerings from various businesses. Are we going to see a death knell to many? So much competition we don't know what to do with it? How does the next couple of years look? Massive players like M365 aren't being replaced any time soon, but the smaller systems... I cannot see them lasting. submitted by /u/archiekane [link] [comments]

The AI Coding Maturity Scale 🤖 if you're exploring loop engineering with Claude Code this is for you

Hey folks, I've identified 3 different stages of AI coding adoption and what they mean for code review and code maintainability. - The autocomplete stage, which is basically a throwback to 2024 and is mostly harmless - the traditional SAST and code review practices handle it. - Prompting agents to build whole features, which is where most people are today, comes with some security and maintainability concerns, but there are already solutions in place. - The big problem is that most teams are also starting to explore loop engineering with autonomous agents. 99% of teams currently have no guardrails in place, which is a recipe for disaster, as the boss man explains in the video. If you're exploring loop engineering with Claude Code, check this out 🤖 submitted by /u/CodacyOfficial [link] [comments]

My content scraper died to AI chat. Rebuilt it from scratch with Claude Code as an SEO agency tool

My old tool, SEO Content Machine, was a content scraper/research tool I ran for years. Usage collapsed when AI chat ate that use case. Instead of letting it die, I rebuilt it from the ground up with Claude Code into something different: a programmatic SEO workflow tool for agencies. The rebuild in numbers Started May 11, ~8 weeks of work 204 commits, ~950 files touched, +172k / -164k lines: essentially a ground-up rewrite In the last 6 weeks alone, Claude Code processed ~5.8 billion tokens on this rebuild (roughly $5k in API-equivalent value, on a Max subscription). That excludes the first two weeks, logs rotated out. The majority of it was on Opus, with some Fable sprinkled in during the first few days it came out and this week. What it does now The pain it solves: SEO data lives in three different places (Search Console, your keyword research, your actual site content), and none of them talk to each other. You end up eyeballing spreadsheets and guessing what to work on next. The tool pulls those 3 data sources into one workspace and puts an AI agent on top that can actually reason over it. The inspiration came when I saw a Palantir AIP video on Youtube. That tool basically takes messy operational data, unifies it into what they call "ontologies", then lets an AI agent reason and act over it. Same idea, but for SEO. So for SEO it means an agent that remembers the actions you took (what got written, linked, published), so it doesn't re-suggest work you already did, and instead guides you to the next thing worth doing. It moves my product positioning away from another "write 500 words AI article" tool into a "these 12 pages are the highest-leverage moves this week and here's why" advisor. Works with Claude, OpenAI, Gemini, OpenRouter, or fully local models (Ollama, LM Studio). Had to actually implement proper streaming and only support models that understood tool calls. How Claude helped Fixed old long-standing hard-to-fix bugs. eg: Had a handrolled element picker which broke on dynamic sites and frames. Claude was actually able to be really clever and instead use CDP to enable the native devTools picker and communicate with it over the wire to pull selectors directly from it. This is a hard one to have fixed via stackoverflow and github. Working element picker examples are years old. Performance. AntD v6 sucks with its native tables. The moment you add any controls into table rendering, table sorts and redraws take 100s of milliseconds. Very painful. This required actual perf profiling (via CDP) and lots of memoing. Best find: AntD's sticky prop on a table silently adds a StickyScrollBar that reads getBoundingClientRect + scrollWidth on every render (forced layout reflow), profiled at ~350ms per sort. Removing it took a sort from 855ms to 498ms busy time. On top of that: React.memo with custom props-equality on the whole table, fast row-equality checks, and lazy-mounting heavy per-row widgets. Instead of building the Agent from scratch, I pointed it to the codex repo (which is in Rust) and told Claude to read all the seams of the project and use that to design a proper already used and proven system. What it got wrong: As the project got bigger and I kept adding features, there were real problems with performance regressions and feature regressions. Unit tests can only catch so much. So I had to add real e2e live browser based testing. We are talking raw CDP over websocket to drive real app windows (Playwright itself choked on Electron's CDP). The upside? Less actual UI workflow regressions. The bonus? Now I have user workflow docs prebuilt, as the output of the e2e includes simple instructions AND actual screenshots of the app. Lessons from the rebuild Although painful, you need some kind of UI-driven, albeit brittle, e2e smoke and spec tests. The best although slowest way to build is to ask Claude to write a red test (ie a failing one), then to fix it so it's green. Ideally it's an actual e2e test hitting UI actions. Now you have documented features and tests will go red if it ever breaks. Ended up with an eyewatering ~1,240 unit/component test cases across 234 files, plus 7 e2e suites (16 scenarios) driving the real app window. I leveled up the build process by enabling CDP and giving Claude real access to the browser window running the app. This allowed Claude to replicate the exact UI bugs and code issues I was having without me having to send it screenshots and detailing steps in minute detail. It means it fixes the right bugs in real conditions. eg If you want it to adjust UI by making things smaller or bigger, it normally just guesses from code, but a real CDP connection means it can measure things with pixel precision and also take screenshots to make sure it looks "ok". A rewrite this size by myself coding it would have been a 6 month journey of pain. These 8 weeks have been a real learning experience. But its not "free" its been a real slog m

Quick experiment I ran while building tooling for Claude Code.

I took Django repo at a fixed commit, 542 files. Scored every file for defect risk using pure static analysis and git history without using any LLM. Then I pulled the next 6 months of real bug-fix commits and checked how many of my worst-scored files actually broke. 14 of the 20 worst files had real bugs, thats around 70% precision. But what I didn't expect was the strongest predictors were untested hotspots and developer congestion (lots of hands touching the same file). If you look at research in this area cyclomatic complexity is the metric everyone reaches for, and it ranked near the bottom. When you point Claude Code at a real repo, it reads files one at a time. It won't know which files move together, who owns what, or why a given pattern is deliberate. So it will happily rewrite a module three others depend on, because nothing told it that coupling exists. Getting the relevant structure in context is important which is missing from Agentic coding rn. So I've been building an open source MCP layer for exactly this, called repowise. It provides much richer context to AI coding agents through 5 layers and trust and provenance to the humans accountable for the code. it is self-hosted, can be installed through pip. Five layers sit between the repo and the model: Graph: AST dependency graph. Knows what depends on what before touching anything. Git: hotspots, ownership, co-change, bus factor. "This file always changes with these three." Docs: auto-generated, searchable living wiki from your code, the file that gets stale will regenerate on it's own. Decisions: mining architectural decisions through PR bodies, commit messages, code comments etc Health: the scoring layer above. 25 deterministic markers per file, pure static analysis, no LLM. On paired benchmarks against raw file exploration: 49% fewer tool calls, 89% fewer file reads, 36% lower cost, at the same answer quality. Across 21 repos in 9 languages, ranking files by this score surfaced 2.3x as many real bugs as a leading commercial tool in the market given the same review time. benchmarks are open sourced in the same org and fully reproducible Repo : https://github.com/repowise-dev/repowise The health experiment reproduces on any repo with enough git history if you want to run it on your own code. https://reddit.com/link/1upxgyv/video/ow6ii4s0ntbh1/player submitted by /u/aiandchai [link] [comments]

Graphical representation of tasks

Has anyone tried making a graphical representation of ongoing tasks? I saw some Tik Tok videos that someone made something that looked like a space ship that had workers moving around and doing things. These workers represent the ongoing tasks. I tried building one with a military theme that showed small battles for each task underway, but it didn’t really pan out that well. I think it would be cool to have a separate screen showing these AI workers working away. Has anyone had any luck in building something like this? submitted by /u/coaker147 [link] [comments]

Claude Code Subagents Explained

Subagents are specialized AI assistants that handle specific types of tasks in Claude Code. Each subagent runs in its own context window with a custom system prompt, specific tool access, and independent permissions. In this video, I will show you how to create a subagent, how to use it inside Claude Code, and how to leverage Claude Code to write its own subagents. submitted by /u/Special_Community179 [link] [comments]

We open-sourced a routing gateway that cuts LLM costs 4.7x–22x by matching each query to the right model (Apache 2.0)

I'm on the team at Regolo and we just released Brick — an open-source Mixture-of-Models router that reads every prompt's capability (coding, math, reasoning, creative, planning, world knowledge) and complexity, then routes it to the cheapest model in your pool that can actually do the job. One call per query, no cascade waste. Why we built it: we kept seeing teams burn $50k–200k/month on a single frontier model because most queries are simple lookups that don't need it. No dynamic selection = flat cost no matter what you send. How it works (step by step, with a real example): Let's say you send 1,000 queries/day to Claude Opus, and that costs $165/day ($4,950/month). But here's the thing — not every query needs Opus. Here's what Brick does with those same 1,000 queries: Step 1 — Capability classification: Brick reads each prompt and classifies it across 6 dimensions (coding, math_reasoning, creative_synthesis, instruction_following, planning_agentic, world_knowledge): Step 2 — Complexity assessment: a second classifier scores difficulty as easy / medium / hard: Step 3 — Routing decision: Brick computes a skill-distance score for each model in your pool and picks the cheapest one that can handle the job. One forward pass, one decision, no cascade. Step 4 — Result: same 1,000 queries, same quality on the ones that matter — but your daily cost drops from $165 → $35/day. That's a 79% reduction, or ~$3,900/month saved. Easy to use with Claude Code or any other OpenAI Compatible provider: brick claude on # wires ANTHROPIC_BASE_URL, starts the router brick claude status # live dashboard with routing metrics Also works as a standalone OpenAI-compatible gateway (model: "brick"), with Codex, and with any client. No GPU needed for the router itself — runs on CPU. Demo video: https://youtu.be/RXnYNxYwSKQ Links: GitHub: https://github.com/regolo-ai/brick-SR1 Paper: https://github.com/regolo-ai/brick-SR1/blob/main/docs/paper/paper.pdf Demo video: https://youtu.be/RXnYNxYwSKQ Weights on HuggingFace: https://huggingface.co/regolo What I'd love feedback on: the routing logic, the benchmark methodology, and whether the Claude Code integration is something you'd actually use day-to-day. Happy to go deep on any technical detail. submitted by /u/alexgenovese [link] [comments]

Claude MCPs

Hello Everyone, I am starting a new content on social media, and i want claude to help me in this. So i am thinking if can i use it for this. The workflow: - An MCP that does a research for the news of the content. - An MCP to generate images and videos. - An MCP to do an AI voice generated for the videdos. And generate the caution of the posts. First of all, is this a great workflow for starting and growing on social media? If you have any suggestions, advices, please share because i want to grow on social media with my new content, and can you tell me which MCPs(free ones), that are great for this workflow, or if you have a better workflow. submitted by /u/WideFalcon768 [link] [comments]

I have built an interesting way to learn for Claude Users - Beta users are welcome

Video courses and passive learning can be useful, but they rarely train you the way AI can. When you learn with AI, you're already working in your own domain while picking up new concepts. Instead of just watching, you're actively applying, questioning, and solving. To explore this idea, I built a Claude connector called Ripostiq. I'm the first user of the platform, and I've been enjoying the experience so far. Here's how it works: • Enroll in a course on Ripostiq (currently free) • Learn through conversations directly in Claude • Have your key learnings and summaries automatically stored in the platform • Progress toward certification by taking on a "Boss Battle" that tests your understanding The certification isn't something you get by simply completing lessons—you have to earn it by demonstrating what you've learned. It's not the easiest way to learn, but I believe it's a more effective one. If you're interested, I'd love for some of you to try it out and share your feedback: https://ripostiq.com submitted by /u/rajatnparth [link] [comments]

Spawn parallel CC sessions in multiple repos at once

tl;dr Have you ever needed to run the same prompt, but in multiple subdirectories to make a similar change? I built an MCP server that indexes all your repos, lets you query them, makes batch PRs, and gives you a summary of workflow runs. Here's what it does: 1. Indexing, which happens in 2 forms: - Codebase level: runs an agent CLI (with proper context) over all repos to extract what each one does, how they relate, and what the system looks like as a whole. - Repo level: Having the codebase context, it extracts logical info of each repo, and also the libraries, dependencies, etc for lexical search 2. Search, also in 2 forms: - Natural language: where it answers search queries with respect to the codebase and targeted repository context - Structured search: where it returns the result based on actual dependencies (eg "find me repositories that are written with Python, have requirements.txt, and are using FastAPI) 3. Batch change: Simply prompt "find my Python repositories and update library X from vY to vZ"; This will search and find the affected repos, clone them, run a CLI agent like CC on each with the context we already persisted, create and prepare PRs, and give you a report of the results. Tech stack Now it only covers ClaudeCode and Github: mongodb To store the repository tree, dependencies, and workflows redis To store the user's session to track the ongoing batch job claude-cli/Devin Used as the main engine docker-compose to build traefik for routing I would appreciate your feedback and thoughts on this Github: https://github.com/sorena-ai/service-catalog-mcp Demo video: https://infraas.ai/ PS: I reviewed all the code, so if it looks like slop, that's me ^^ submitted by /u/Terrible_Equivalent3 [link] [comments]

Built a UX tool on Claude. The hard part wasn’t what I expected.

Spent a few months building Blinx with Claude Code. You give it a URL, it sends a synthetic persona through the page and produces a heuristic UX report in the persona’s voice. To be honest, I assumed the hard part would be the browser automation. It wasn’t. The hard part was stopping the output from sounding like generic AI advice. Early versions returned “improve your visual hierarchy” type findings that are technically true but completely useless. Getting it to produce specific, senior-level critique took most of the actual work. There are a few live run demo videos on the homepage, if you’re curious: thinkblinx.com. Would love to hear your thoughts and feedback. Mostly posting because the “make AI output not sound like AI” problem felt like something this group would have opinions on. submitted by /u/i_x_l [link] [comments]

I'm building agent loops that auto-edit my videos, but the hard part has been finding a model to accurately grade the result

Quick context: I've been building agentic loops that edit my short-form videos for me. The editing works really well, but I found myself needing to check the process at several gates. The part that's been killing me is the grader. Without a reliable score, the loop either never stops or happily stops on garbage. So I went hunting for the best way to actually quantify a finished video, and tested 4 models as the judge: Claude (Opus 4.8), ChatGPT/Codex (GPT-5.5), Gemini 3.1, and Twelve Labs. Same clip, same prompt, each asked for a structured JSON breakdown (shots, transitions, on-screen text, pacing) so I could feed the score straight back into the loop. What I found: Gemini was way faster — ~3 min vs Claude's 30+. It reads video natively; Claude and GPT chop it into frames locally + audio with ffmpeg/whisper first. Consistency was rough. Same clip, and they disagreed on basic stuff like shot count. Not ideal when it's supposed to be your objective scorer. They were all bad at the cinematic details (zooms, punch-ins, camera moves), which is exactly the stuff I want graded. Claude didn't even notice the background music. Twelve Labs is free and caught a few effects the paid ones missed. where I'm probably wrong: it's one clip in the video (n=1), my prompt was bloated, and still experimenting with all this. But to be fair I have edited some 50+ videos now with Claude Code and Codex so I have a pretty good handle on what their problems are which is what inspired the video. Hopefully some people find it interesting TL;DR: trying to get an AI to grade my auto-edited videos so my loop has a win condition. Gemini's the best single judge so far, but I still most the work in Claude Code. submitted by /u/Wesley_at_home [link] [comments]