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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
If you've ever built ETL pipelines pulling data from MongoDB into Delta Lake using Spark, you've probably hit this wall. The pipeline works fine — until it doesn't. A single document with an unexpected shape is enough to break the entire write, leave the table in an inconsistent state, and send your on-call engineer digging through Spark logs at 11pm. I built and maintained more than 10 of these j
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