Cuando una aplicación necesita leer un archivo, escribir en una conexión TCP o esperar datos de un disco, el kernel de Linux ofrece tradicionalmente dos caminos: bloquear el proceso hasta que la operación termine, o usar interfaces como epoll y Linux AIO para manejar múltiples operaciones concurrentes. Durante casi tres décadas, esas fueron las opciones dominantes. Pero desde la versión 5.1 del ke
When Google announced the Manifest V3 deadline, the developer community had a lot to say — most of it negative. The service worker model was rightly criticized as a regression for ad blockers and complex extensions. I've now migrated 18 extensions from MV2 to MV3, or built them MV3-native from the start. The commonly documented issues (no persistent background pages, limited webRequest) are real.
Hey DEV community 👋 I recently built and deployed a full-stack AI system that predicts medical specialties from clinical text using ClinicalBERT, and I wanted to share the full journey from training to deployment. This is part of my project under GradienNinja / Astrolabsoft. Link https://astrolab-medical-ai.netlify.app/ I built an AI system that: Takes clinical notes as input Predicts the most l
The Autonomous Paradox In 2026, we’ve moved past simple chatbots. We are building Production-Grade RAG pipelines and autonomous agents that can plan, execute, and iterate. But as an architect, I’ve noticed a glaring hole in our "Agentic" future: Identity Sprawl. We are giving agents non-human identities (NHI) with "Full Admin" permissions just to ensure the RAG works smoothly. We are effectively
1. What AGI Actually Requires (A Structural Definition) In open discussions, “AGI” is often described as: a very large model, a universal problem solver, a human‑level agent, a system based on subjective experience. These definitions contradict each other and do not provide an engineering criterion. A structural definition of AGI: AGI = a system with a stable vertical cognitive architecture c
🧠 I Built a AI Assistant with Multi-Model Fallback, Voice Chat & a Personal Data Analyst — Here's How What happens when your AI goes down mid-conversation? You lose users. I built Hero's AI to make sure that never happens — and added a whole lot more along the way. Live Demo Have you ever used an AI tool that just... stopped working? Maybe it hit a quota limit, the API went down, or the mod
Today we're open-sourcing the AI Model Directory, the most comprehensive, automatically updated list of AI models and their metadata available today. It's the data layer that powers model selection in AgentOne, and now it's free for anyone to use, fork, or contribute to. If you'd rather just look at models, we also built a browser for the directory at models.agent-one.dev where you can search, sor
Most agency onboarding fails before the kickoff call happens. Not because the team isn't good. Not because the client is difficult. Because nobody collected the right context upfront, and the kickoff call becomes the place where everyone discovers what they don't know yet. The intake form is the fix. Not a 3-question "tell us about your project" form. A real one. Here's the framework we use — 27 q