Show HN: AI video generator that outputs React instead of video files https://ift.tt/Kc47AHn

Show HN: AI video generator that outputs React instead of video files Hey HN! This is Mayank from Outscal with a new update. Our website is now live. Quick context: we built a tool that generates animated videos from text scripts. The twist: instead of rendering pixels, it outputs React/TSX components that render as the video. Try it: https://ai.outscal.com/ Sample video: https://ift.tt/csQAhfg... You pick a style (pencil sketch or neon), enter a script (up to 2000 chars), and it runs: scene direction → ElevenLabs audio → SVG assets → Scene Design → React components → deployed video. What we learned building this: We built the first version on Claude Code. Even with a human triggering commands, agents kept going off-script — they had file tools and would wander off reading random files, exploring tangents, producing inconsistent output. The fix was counterintuitive: fewer tools, not more guardrails. We stripped each agent to only what it needed and pre-fed context instead of letting agents fetch it themselves. Quality improved immediately. We wouldn't launch the web version until this was solid. Moved to Claude Agent SDK, kept the same constraints, now fully automated. Happy to discuss the agent architecture, why React-as-video, or anything else. https://ai.outscal.com/ January 13, 2026 at 12:33AM

Show HN: Sidecar – AI Social Manager (Analyzes past hits to write new posts) https://ift.tt/zK4L3R0

Show HN: Sidecar – AI Social Manager (Analyzes past hits to write new posts) Hi HN, I built Sidecar ( https://sidecar.bz ) because I was having issues maintaining a social media presence for my last startup. I would spend a lot of time trying to create content, but I often froze up or burned out, and the marketing died. How it works: Instead of guessing what to write, Sidecar connects to your existing accounts (Threads, Bluesky, Mastodon, Facebook, Instagram) and analyzes your past posts to see what actually worked. It uses that data to generate weeks of new, text-based content that mimics your successful posts, which you can then bulk schedule in one go. I’d love to hear what you think of Sidecar. You can use code HNLAUNCH for a free month if you want to test the ai features. https://ift.tt/fYwKP52 January 12, 2026 at 10:48PM

Show HN: Epstein IM – Talk to Epstein clone in iMessage https://ift.tt/KRlCvL0

Show HN: Epstein IM – Talk to Epstein clone in iMessage https://epstein.im/ January 11, 2026 at 06:28AM

Show HN: Play poker with LLMs, or watch them play against each other https://ift.tt/It1BUe6

Show HN: Play poker with LLMs, or watch them play against each other I was curious to see how some of the latest models behaved and played no limit texas holdem. I built this website which allows you to: Spectate: Watch different models play against each other. Play: Create your own table and play hands against the agents directly. https://llmholdem.com/ January 11, 2026 at 12:57AM

Show HN: Marten – Elegant Go web framework (nothing in the way) https://ift.tt/9RQGeFN

Show HN: Marten – Elegant Go web framework (nothing in the way) https://ift.tt/rbt8SHg January 11, 2026 at 02:40AM

Show HN: I used Claude Code to discover connections between 100 books https://ift.tt/gaVRNwM

Show HN: I used Claude Code to discover connections between 100 books I think LLMs are overused to summarise and underused to help us read deeper. I built a system for Claude Code to browse 100 non-fiction books and find interesting connections between them. I started out with a pipeline in stages, chaining together LLM calls to build up a context of the library. I was mainly getting back the insight that I was baking into the prompts, and the results weren't particularly surprising. On a whim, I gave CC access to my debug CLI tools and found that it wiped the floor with that approach. It gave actually interesting results and required very little orchestration in comparison. One of my favourite trail of excerpts goes from Jobs’ reality distortion field to Theranos’ fake demos, to Thiel on startup cults, to Hoffer on mass movement charlatans ( https://ift.tt/4EQwsRW ). A fun tendency is that Claude kept getting distracted by topics of secrecy, conspiracy, and hidden systems - as if the task itself summoned a Foucault’s Pendulum mindset. Details: * The books are picked from HN’s favourites (which I collected before: https://ift.tt/m1RrVIF ). * Chunks are indexed by topic using Gemini Flash Lite. The whole library cost about £10. * Topics are organised into a tree structure using recursive Leiden partitioning and LLM labels. This gives a high-level sense of the themes. * There are several ways to browse. The most useful are embedding similarity, topic tree siblings, and topics cooccurring within a chunk window. * Everything is stored in SQLite and manipulated using a set of CLI tools. I wrote more about the process here: https://ift.tt/4IqHMYg I’m curious if this way of reading resonates for anyone else - LLM-mediated or not. https://ift.tt/LVAwSbj January 10, 2026 at 10:26PM

Show HN: Various shape regularization algorithms https://ift.tt/PvGjFtT

Show HN: Various shape regularization algorithms Shape regularization is a technique used in computational geometry to clean up noisy or imprecise geometric data by aligning segments to common orientations and adjusting their positions to create cleaner, more regular shapes. I needed a Python implementation so started with the examples implemented in CGAL then added a couple more for snap and joint regularization and metric regularization. https://ift.tt/D2uExbR January 9, 2026 at 07:43AM