Show HN: Moltty – Organized, Persistent AI Coding Sessions https://ift.tt/TeZ3YJd

Show HN: Moltty – Organized, Persistent AI Coding Sessions https://moltty.com/ March 6, 2026 at 01:43AM

Show HN: Markdown-to-Book – Convert Markdown to KDP Ready PDFs and EPUBs https://ift.tt/1azJSEI

Show HN: Markdown-to-Book – Convert Markdown to KDP Ready PDFs and EPUBs Author here. I'm a software engineer who started writing hard science fiction on the side. I built this tool because I wanted to write in plain Markdown and go straight to Amazon KDP without touching Word, InDesign, or Vellum. The workflow: I write stories in .md files, one heading per chapter, --- for scene breaks. When I'm ready to publish, I run one command and get a paperback PDF, hardcover PDF, and Kindle EPUB with correct margins, typography, and scene breaks. The tool wraps Pandoc and XeLaTeX with a custom LaTeX template and a Lua filter that handles the scene break conversion. Commander.js is the only Node dependency. I used this to publish my first novelette, a hard sci-fi story called "The Pull" about an astrophysicist mapping the Zone of Avoidance behind the Milky Way. The science in the story is grounded in real astrophysics (the Great Attractor, large scale cosmic flows, the Zone of Avoidance). I also built an author website at 'alanvoss.me' with Next.js and Payload CMS, deployed as a static site on Vercel, where you can read the first chapter and see the characters. On AI use and Graphics: The story concept and science are mine. I used Claude Opus 4.6 to help with some character dialogue and for grammar and spelling checks. Character portraits on the website were generated with Midjourney and OpenAI image models. Book covers were made in Canva. The tool itself is simple (~200 lines of JS), but it solved a real problem for me. The KDP margin requirements are fiddly, especially the difference between paperback and hardcover inner margins, and getting scene breaks to render correctly in both LaTeX and EPUB needed the Lua filter approach. Hopefully useful to other developers who write. Please let me know if you have any questions about the tool, the publishing process, or KDP in general. https://ift.tt/sDc1VCw March 6, 2026 at 01:02AM

Show HN: PenguWarpOS – OS SIM made in py for Linux newbies https://ift.tt/ARCepI5

Show HN: PenguWarpOS – OS SIM made in py for Linux newbies I made an OS sim in Python so linux newbies can learn how to navigate their system from terminal and break stuff without messing their system https://ift.tt/c8YSZBt March 5, 2026 at 11:14PM

Show HN: DevTrack – A personal dashboard to track your developer growth https://ift.tt/kMqz0lG

Show HN: DevTrack – A personal dashboard to track your developer growth https://devtrack-rose.vercel.app March 5, 2026 at 01:30AM

Show HN: Anaya – CLI that scans codebases for DPDP compliance violations https://ift.tt/b9KDaVi

Show HN: Anaya – CLI that scans codebases for DPDP compliance violations I built Anaya to solve a problem I kept seeing: India's DPDP Act is now enforceable (rules notified Nov 2025, deadline May 2027) but compliance is a code problem, not just a legal checklist. No tooling existed for it. Ran it on Saleor (open-source Django e-commerce, 107 models): found 4 violations in 82 seconds — no consent mechanism, 70 PII fields stored plaintext, zero DELETE endpoints for any PII model. pip install anaya && anaya compliance . Code: https://ift.tt/Zx29KPL Happy to discuss the AST parsing approach or the DPDP section analyser design. https://ift.tt/Zx29KPL March 5, 2026 at 12:50AM

Show HN: AlifZetta – AI Operating System That Runs LLMs Without GPUs https://ift.tt/wAY4mK2

Show HN: AlifZetta – AI Operating System That Runs LLMs Without GPUs Hi HN, I’m Padam, a developer based in Dubai. Over the last 2 years I’ve been experimenting with the idea that AI inference might not require GPUs. Modern LLM inference is often memory-bound rather than compute-bound, so I built an experimental system that virtualizes GPU-style parallelism from CPU cores using SIMD vectorization and quantization. The result is AlifZetta — a prototype AI-native OS that runs inference without GPU hardware. Some details: • ~67k lines of Rust • kernel-level SIMD scheduling • INT4 quantization • sparse attention acceleration • speculative decoding • 6 AI models (text, code, medical, image,research,local) Goal: make AI infrastructure cheaper and accessible where GPUs are expensive. beta link is here: https://ask.axz.si Curious what HN thinks about this approach. https://axz.si/ March 5, 2026 at 12:06AM

Show HN: An MCP server for the docs of any repo that uses Sphinx https://ift.tt/GyrCUs7

Show HN: An MCP server for the docs of any repo that uses Sphinx It's a fairly simple stdio MCP server that provides AI agents a faster way to search through docs for any Sphinx-powered documentation. It builds Sphinx text docs and indexes them in SQLite (FTS5). There is also an optional hybrid search mode which creates embeddings and a vector db (sqlite-vec) and uses both approaches via RRF to get the best answer to your agent. I've run this on several repos of varying size and complexity (pandas, celery, cpython) and have been impressed with the resulting answers. https://ift.tt/ZLVd9xg March 4, 2026 at 01:33AM