What is Mycelium? (2 para) The problem we're solving (2 para) Discovery benchmark Dataset (1k agents, 1k queries) Results table Keyword vs Semantic graph (ASCII) Load benchmark Cache architecture Results table What changed (before/after cache) How to reproduce pip install code snippet What's next (roadmap) GitHub link -> / mycelium 🍄 Mycelium Agents Watch 3 AI agents c
Metric Value Django Average Response Time 287ms Node.js Average Response Time 193ms Django Memory Usage (1000 users) 1.8GB We tested Django 4.2 and Node.js 18.16 under identical conditions to measure their performance for reporting dashboard workloads. The test environment consisted of AWS EC2 m5.2xlarge instances (8 vCPUs, 32GB RAM) running Ubuntu 22.04. Both frameworks connected to th
I've been building AQE (Atomic Quantum Engine), a DOM selector engine that replaces tree traversal with flat bitmask operations. Instead of walking the DOM on every query, each node gets a 64-bit BigInt mask at sync time. Matching becomes a single integer AND. AQE Light is the free, open-source version — zero dependencies, MIT license, on npm now: npm install atomic-quantum-engine I'm looking for
Go 1.22 & Vite 5: Performance and Scalability for Modern Teams Modern full-stack development teams face a constant balancing act: delivering fast user experiences while maintaining scalable, maintainable codebases. Two recent releases — Go 1.22 and Vite 5 — have raised the bar for backend and frontend performance respectively, and when paired, they create a stack that eliminates common bottlenec
When building 100 production-grade React components with equivalent styling, the difference between the smallest and largest bundle size is 142KB – enough to add 1.2 seconds of load time on 3G networks. I ran a controlled benchmark across Tailwind 4.0, UnoCSS 0.60, and CSS Modules to find out which delivers the best bundle efficiency for real-world projects. ⭐ tailwindlabs/tailwindcss — 94,840 s
Generative AI is no longer just an emerging technology. It is becoming a core business capability across software development, customer support, analytics, content generation, automation, knowledge management, and enterprise productivity. For cloud professionals, developers, data teams, and solution architects, learning Generative AI on AWS is now a high-value career move. AWS provides a growing e
The Model Context Protocol has transformed how we connect AI to tools. But connecting agents to tools is only half the battle — connecting agents to each other is where the real challenge begins. I recently read @raviteja_nekkalapu_'s excellent article "I built an AI security Firewall and made it open source because production apps were leaking SSNs to OpenAI" and it resonated deeply with challeng
A deeply-synthesized, opinionated reference distilled from five canonical sources: donnemartin/system-design-primer · ByteByteGoHq/system-design-101 · karanpratapsingh/system-design · ashishps1/awesome-system-design-resources · binhnguyennus/awesome-scalability Use it as: a study guide for interviews, a checklist for design reviews, and a vocabulary for cross-team discussions. 📖 How to Use This