... voices, and edit subtitles right on the timeline. 5-Minute Video-to-Video (V2V) You can now transform real videos up to 5 minutes long. To prevent timeouts and memory crashes, our engine automatically slices videos into editable chunks, maintains temporal consistency across cuts, and stitches them back together. You can even inject your own generated AI characters into real-world footage. Cost-Effective Auto-Foley & Music Mode Top-tier video models with native audio are expensive. To keep ... ... able to hook RedBoy's backend directly into your favorite LLMs to build storyboards, trigger animations, and make editor tweaks through natural conversation similar to OpenArt's flow. Building the orchestration behind granular entity swapping and long-form V2V chunking

... kept forgetting DSA patterns between interview cycles, but opening a laptop for a full coding session was too much friction. I built AlgoBite as a smaller review loop: reconstruct a real Python solution from scrambled chunks, run browser tests, then let spaced repetition bring it back before you forget it. It is designed for a five-minute phone session, not to replace solving from scratch. You can try Valid Parentheses without an account: https://algobite.app/try?problem... The honest baseline ...

... both content and   product work.   2. Google Search Console I basically live in it. For anything SEO, it's the only honest source of truth   about what's actually happening vs. what I assume is happening.   3. Ahrefs keyword and competitor

... made them succeed or fail? For those who've sold into small/mid-sized businesses, what's usually the biggest blocker to adoption price, integration effort, or something else? Is there a feature here that seems like a "nice to have" versus something that would actually change behavior? Would appreciate any perspective, whether from experience building similar things or just as someone who's dealt with this as a customer or business owner. Comment from Tommy Kang(@sjtkang): What I'm building ... ... right audience. Comment from Nolan Vu(@nolan_vu): @thenameisarian  Interesting, alternative

... Something I built led to a design decision I want to get feedback on. LineageLens is a free VS Code extension that captures every AI code insertion and scores it for risk on a 0 100 scale. Works with Cursor, Copilot, ClaudeCode, Gemini CLI. Zero config on install just start using your AI tools and your insertions start showing up in the sidebar. The scoring is deterministic rules: +28 for credential-like material, +24 for eval/exec patterns, +22 for subprocess ... ... This solves a problem I didn't realize I had until I read this. We've been using AI-generated code in production for months and honestly have no clear picture of which parts were written by AI vs

... word listener. It was using Google Speech Recognition. Worked fine, but broke the "nothing leaves your machine" promise. Replaced it with openWakeWord - an open source, on device wake word library. Runs a tiny ONNX model locally, processes 80ms audio chunks through sounddevice, fires a callback when confidence crosses a threshold. Zero network calls. The tradeoff: no pretrained "computer" model exists yet, so the default is "hey Jarvis". You can train a custom keyword using their pipeline if you want something ...

... Chunk v2  is finally out after months of work and I wanted to share it here since this community gave me some really useful feedback on v1. It s a menubar time-blocking app for  macOS . The core idea is simple, plan your day in focused chunks

... best of two worlds: Speed: Classical NLP ( spaCy ) for initial NER (10-50x faster than BERT). Reasoning: State-of-the-art LLMs ( AWS Nova Pro v1 ) to validate complex semantic relationships and refine extraction. 3/ Semantic & Adaptive chunking Forget about arbitrarily cutting text every 500 characters. Our algorithm respects natural paragraph boundaries and evaluates semantic coherence . If a fragment loses the thread, the system detects the topic shift via embedding similarity to decide exactly where ... ... Secret sauce": Context preservation This is where NeuroBlock transforms the data. We don't just store vectors; we build a Contextual Knowledge Graph in Neo4j . We create `NEXT_CHUNK

... stays human-controlled for me. Convenience isn t worth that risk. Comment from nim(@sup_nim): honestly i think the trust issue comes down to scope. i trust ai way more when its doing one specific thing really well vs trying to be a general assistant that touches evrything. like i built speakeasy which uses ai to convert articles to audio - its just doing text to speech, nothing else. and astrologica generates daily horoscope podcasts from your birth chart ... ... weeks and honestly I m really happy with it, as long as it stays in copilot mode (I review everything before it ships). I ve leaned on it heavily for a new side project I m building ( BenchCanvas ): market + competitor

... update is live for One Dot focused on customization and planning clarity. Been working on updates and fixes last week. What s new: Quarterly View see your year in 3-month chunks for better seasonal planning Custom Themes new black & white Solutions themes with custom icons Background Upload set your own wallpaper Start of Week choose Monday or Sunday Visual Toggles toggle date numbers and progress indicators Special Dates Highlight highlight any date or date range with color Blog ...

... sparked an interesting thought experiment: how likely is it that we ll see AGI (AI that thinks and learns like a human) within the next five years? The report highlights a fascinating divergence: the view from money vs. the view from science. Money : the probability inferred from trillions poured into data centers, Nvidia chips, and servers. Investors seem to be betting that AGI is inevitable. Science : the probability inferred from research papers and AI development models. Experts are far more ... ... might be ahead of reality. Expect volatility, overpromised outcomes, and valuable lessons along the way. Meanwhile, AI continues reshaping work, attention, and human behavior. I d love to hear the community s perspective: Are you seeing this money vs

... Hello, I ve been working on a passion project I called Sapling (use.sapling.mobi) on and off since 2016. I have spent the last 12 months improving it because I kept seeing small charities lose huge chunks of their donations to complex platforms that take high fees or guilt-trip donors into "tipping" the software. It felt wrong, so I decided to build a cleaner, simpler alternative

... under 30 seconds while maintaining quality. The Solution - Streaming Pipeline Architecture: Stream the script - GPT-5 Real-time API writes and streams segments as it goes Parallel processing - Voice synthesis (Kokoro-82M) and sound design run simultaneously Music-aligned chunks - Content segments match natural music bed durations Progressive assembly - Chapters become playable as soon as they're done Low-reasoning script drafting - Less time spent figuring out script length means faster processing Key Insights: Don't wait for full script ...

... launched an open-source LLMOps platform for building reliable AI apps Claude workflows that work We talked about Anthropic last week, so I enjoyed reading how Viktor optimizes their workflow with Claude. TL,DR: Break tasks into small, manageable chunks Always test after each change to catch silent errors Be explicit Maintain rigorous version control, be prepared to revert changes Always verify and challenge suggested modifications Last but not least? Be patient Join the discussion The job board Recent ...

... still a mess of spaghetti code. So we built Raptor Data to be the "Stripe for RAG Ingestion." What is Raptor Data? Raptor is a developer-first API that turns unstructured documents (PDF, DOCX) into version-controlled, AI-ready chunks. We don't just "parse" files. We treat them like code repositories. The "Git-Like" Magic (How we save you 90%) When you upload a file to Raptor Data, we use Structure-Aware Chunking

... currently supports Hindi). What s new: Backend speedups: Skip transcript fetch + vector storage for repeat videos (1 20 ms check). Faster quick-question generation with a lighter prompt + Gemini 1.5 Flash. Reduced similarity search work. Translation reliability: Translate larger chunks instead of every caption line. Hard timeout per translation + circuit breaker to avoid stalls. Bound input size for faster, predictable calls. YouTube Video GitHub ...

... instantly turn it into a true AI-readable format. Why this matters: Most AI support agents like Chatbase struggle with real-world files. We ve built a pipeline that: Extracts text with high accuracy Breaks it into AI-optimized chunks Makes it instantly searchable and useful You can follow my journey right here on LinkedIn as we make ChatQube smarter every ...

... anything radical; it was just using a tool to save time. Little did I know I was participating in a budding movement. As AI coding assistants improved, my vibing only increased. I started letting GitHub Copilot auto-complete whole chunks of code while I casually tabbed through its suggestions. I d begin writing a comment like // function to shuffle a deck of cards and before I could finish my thought, Copilot would offer to generate the entire function ... ... best practices for vibe coding sanely: Break Problems into Bite-Sized Pieces: Don t ask the AI to build your entire app in one go; that s a recipe for disappointment. Instead, split the work into small chunks

... stories for kids - vibecoded it over a weekend! - Gramms.ai Comment from fzero17(@fzero17): My first vibecoded project was OpenFolder a macOS menu bar app that turns your desktop into a calm personal launchpad. I built it using GitHub Copilot + VS Code, which felt like coding with a quiet partner who always had my back. The hardest part wasn t the code, but building something truly minimal yet delightful to use. I released it commercially on the Mac App Store ... ... launching on PH this week, so full circle. Wouldn't call it "money from that first version" though, that one barely resembled what exists now. Curious how many other people here started completely outside software like I did vs

... What s New We just launched a native integration between LangChain and Tensorlake! Now you can pass unstructured documents to a LangGraph agent and trust that parsing, chunking, and field-level accuracy are handled by Tensorlake s document engine no hacky pipelines required. Why it matters Many LangChain projects break down when document structure is inconsistent, or field extraction needs to be accurate and explainable. Tensorlake s integration provides: Reliable document ingestion Schema-driven field extraction Native support ... ... pipelines Built-in SDK + Playground for fast iteration It s now super simple to use documents (like SEC filings, contracts, or invoices) as context in LLM apps with structured outputs and markdown chunks

... Text2Note now processes whole books (like The Metamorphosis ) in chunks for detailed, comprehensive notes, all in the background with no clicks needed. Shared context between chunks

... LLMs! Anyone else building cool stuff like PDF Q&A or custom bots with RAG, but finding the context retrieval step... frustrating? Most AI app data stacks these days use vector search (Pinecone, Weaviate, etc.) to grab text chunks for the LLM. But sometimes it feels like it finds stuff that's keyword-similar while totally missing the actual point the user asked for. Leads to those slightly weak or "confidently wrong" LLM answers. So, what's your single ... ... biggest headache right now in getting truly relevant context for your RAG pipeline? Is it nailing the chunking

... later. a big fan of Gall's Law, me). 3. set up my Obs system that is both a note-taking and task tracking tool that allows me to work, basically, on everything in one place I migrate chunks of notes from Notes to Obs as and when I need to make progress on something that is housed in both tools. decided not to do a whole sale move from Notes to Obs. feels like a time-sink that ...

... specifications is crucial. Existing tools like ChatGPT and Claude often generate overly generic PRDs. That s why we built AtomicPRD a smarter way to create detailed, structured PRDs quickly and effortlessly. It breaks requirements into AI-friendly, consumable chunks, making it easier for AI tools to convert them into actual code ...

... driven code development. Existing tools like ChatGPT and Claude often generate overly generic PRDs. That s why we built AtomicPRD a smarter way to create detailed, structured PRDs quickly and effortlessly. It breaks requirements into AI-friendly, consumable chunks, making it easier for AI tools to convert them into actual code. Learn more about AtomicPRD: https://www.producthunt.com/post... ...