Show HN: How to get 100 customers building in public https://ift.tt/eJhkLQy

Show HN: How to get 100 customers building in public https://ift.tt/uSHYUbG March 28, 2026 at 06:49AM

Show HN: NUPA is Pax Economica, 6,480x more stable than current US economy https://ift.tt/t0A2UPa

Show HN: NUPA is Pax Economica, 6,480x more stable than current US economy NUPA: private post-scarcity OS using BLM land leases + contract law. 100M Monte Carlo runs show 99.999999% survival, 6,480x more resilient than US GDP under systemic noise. Fixed Cost Arbitrage beats AI job loss—humans cheaper than robots. No taxes, no strikes. Python scripts on repo in /simulations folder. Repo: https://ift.tt/4YDOycE... Short explainer video: https://youtu.be/RE560yVFb0I?si=UlVPkmCkrsg24Dzj March 28, 2026 at 03:44AM

Show HN: VizTools – 16 free tools for PMs and freelancers, deliberately no AI https://ift.tt/bah1NjX

Show HN: VizTools – 16 free tools for PMs and freelancers, deliberately no AI I've been building AI products for a while. For this one I made a deliberate choice: none of the 16 tools use AI. Meeting cost calculators, freelance rate calculators, PRD generators, runway calculators, sprint retro boards — these problems don't need a language model. They need a well-designed form and correct arithmetic. Built on Nuxt 4 + Vue 3, fully static, runs in your browser. No account required to use anything. Optional Firebase auth only kicks in if you want to save output. Irony worth naming: Claude Code was my pair programmer throughout. The choice wasn't anti-AI — it was about using the right tool for the right problem. Happy to talk stack, the non-AI tradeoffs, or anything else. https://viztools.app/ March 28, 2026 at 02:36AM

Show HN: Superfast – Cognitive Memory Graphs for Enterprise AI Agents https://ift.tt/xJqyoUD

Show HN: Superfast – Cognitive Memory Graphs for Enterprise AI Agents Superfast is an evolution of the Superpowers agent framework, now integrated with FastMemory—a concurrent Rust engine that maps unstructured text into a CBFDAE (Component, Block, Function, Data, Access, Event) functional ontology. While RAG has become the standard for "adding knowledge" to LLMs, it often fails at scale due to semantic noise and the destruction of logical boundaries during chunking. Superfast treats memory as an architectural layer. It utilizes Louvain community detection to mathematically derive functional clusters, giving agents a deterministic "Logic Layer" that persists across sessions. We’ve maintained the strict TDD and Socratic discipline of the original framework but scaled it for environments like Microsoft Fabric and AWS Glue where "token waste" is a primary bottleneck. Check it out here: https://ift.tt/r618lIY March 27, 2026 at 01:38AM

Show HN: New Causal Impact Library https://ift.tt/klz2y4u

Show HN: New Causal Impact Library https://ift.tt/hxLru4Z March 27, 2026 at 12:12AM

Show HN: Scroll bar scuba dude swimming as you scroll https://ift.tt/FtC9DGI

Show HN: Scroll bar scuba dude swimming as you scroll Hi! Instead of a boring scrollbar I made a scuba dude that swims down the page when you scroll. The idea came from nostalgia; remember SkiFree game on Windows? I wanted a skier skiing down my site. Building the skier mechanics in pure javascript turned out to be difficult so I started with a runner, added a santa hat, and recently built scuba buddy. You can try it directly as soon as you start to scroll down the page, and see the other animations with the "Change Animation" button. Technical details: entirely javascript, takes scroll depth value (window.scrollY) and inputs that into math.sin() functions. This lets CSS (transform: rotate() property) create rotations of the various stick-figure's html elements, giving the character animation based on the input which is a user scrolling. It is pretty cumbersome to sync correctly when building the animations. It's difficult to get the upper and lower arms / legs to stay connected and have the animation transitions appear smooth. Posted the runner about year ago here on hn. https://ift.tt/nPrKcqE Should I re-try the skiier or something else? Thank for checking it out! https://ift.tt/7Y3a5Lm March 27, 2026 at 12:12AM

Show HN: Sup AI, a confidence-weighted ensemble (52.15% on Humanity's Last Exam) https://ift.tt/zZ9haPO

Show HN: Sup AI, a confidence-weighted ensemble (52.15% on Humanity's Last Exam) Hi HN. I'm Ken, a 20-year-old Stanford CS student. I built Sup AI. I started working on this because no single AI model is right all the time, but their errors don’t strongly correlate. In other words, models often make unique mistakes relative to other models. So I run multiple models in parallel and synthesize the outputs by weighting segments based on confidence. Low entropy in the output token probability distributions correlates with accuracy. High entropy is often where hallucinations begin. My dad Scott (AI Research Scientist at TRI) is my research partner on this. He sends me papers at all hours, we argue about whether they actually apply and what modifications make sense, and then I build and test things. The entropy-weighting approach came out of one of those conversations. In our eval on Humanity's Last Exam, Sup scored 52.15%. The best individual model in the same evaluation run got 44.74%. The relative gap is statistically significant (p < 0.001). Methodology, eval code, data, and raw results: - https://sup.ai/research/hle-white-paper-jan-9-2026 - https://github.com/supaihq/hle Limitations: - We evaluated 1,369 of the 2,500 HLE questions (details in the above links) - Not all APIs expose token logprobs; we use several methods to estimate confidence when they don't We tried offering free access and it got abused so badly it nearly killed us. Right now the sustainable option is a $5 starter credit with card verification (no auto-charge). If you don't want to sign up, drop a prompt in the comments and I'll run it myself and post the result. Try it at https://sup.ai . My dad Scott (@scottmu) is in the thread too. Would love blunt feedback, especially where this really works for you and where it falls short. Here's a short demo video: https://www.youtube.com/watch?v=DRcns0rRhsg https://sup.ai March 26, 2026 at 12:45PM