
machine-learning

Every morning for three months, I re-explained myself to my coding agents. The same preferences. The same project structure. The same "no, we already tried that" conversation. Fresh context window, zero memory of anything we'd discussed before. Then I built Lorekeeper — an open-source memory layer for AI agents. Fixing the storage problem was the easy part. The hard part was making memory get bet…
Automate your Confluence workflow directly from Claude Code — publish pages, sync content, and upload images without leaving your terminal. GitHub: https://github.com/tariqulislam/confluence-mcp-server What is an MCP Server? MCP stands for Model Context Protocol — an open standard that lets AI assistants like Claude Code connect to external tools and services. An MCP server acts as a bridge: it e…
Mixture-of-experts (MoE) models have quickly become a foundational component of modern, large-scale AI systems. They are widely adopted because they enable...
The AI buildout and the green transition each present significant and similar opportunities and challenges.
Fluorodeoxyglucose (FDG) PET to evaluate patients with epilepsy is one of the most common applications for simultaneous PET/MRI, given the need to image both brain structure and metabolism but is suboptimal due to the radiation dose in this young population. Little work has been done synthesizing diagnostic quality PET images from MRI data or MRI data with ultralow-dose PET using advanced generat…
A step-by-step path through the skills that turn a machine learning practitioner into someone who ships large language model applications.
Static API keys in client config are the easy way to authenticate an MCP server and the easy way to leak a credential. The Model Context Protocol's answer is OAuth: let the agent obtain a short-lived, scoped token through a proper authorization flow instead of carrying a long-lived secret around. It is the right direction. It is also where a single agent's clean flow turns into a fleet's token-ma…
An MCP server exposes tools. delete_repository , create_charge , execute_query . The agent calls whatever it decides to call, and the server runs it. Nothing sits in between. Connect a coding agent to a GitHub MCP server and it can delete a repository as readily as it can read one. Point it at a Stripe server and create_refund is one tool call away from list_charges . The Model Context Protocol d…
It is 11:47 on a Tuesday. An agent finishes a long-running task, decides the team should know, and calls post_message with channel: "#general" . The message is half a sentence, a stray code block, and a JSON dump of an internal error. Two hundred people see it before anyone can delete it. Rate limits would not have helped. The agent was within its budget. The first call was the one you wanted to …
LLM rate limits don't just interrupt agent pipelines—they can silently corrupt structured outputs when fallback models receive incompatible payloads. I built a recovery layer that classifies failures, adapts payloads across model tiers, preserves execution state, and maintains schema integrity during provider swaps. The post LLM Fallbacks Break Agent Pipelines — I Built the Missing Recovery Layer…
The single fastest way to understand why MCP matters is to connect one server and watch your assistant do something it couldn't do a minute earlier — reach into a real folder on your computer and work with your actual files. No code. About ten minutes. Here's exactly how, using the filesystem server in Claude Desktop, because it's the most tangible first win and the safest one to reason about. Be…
X (formerly Twitter) just released xmcp , an official MCP server that wraps the entire X API v2. It is the largest social media platform to ship a first-party MCP integration, and it exposes 131 tools to any connected agent. That includes createPosts , sendChatMessage , followUser , repostPost , deletePosts , and createDirectMessagesByParticipantId . Every one of those tools is available to every…
For a long time now the news and the roundups have all said the same thing. AI will take away the busywork. It will kill the friction. It will hand you wings, a cure-all for whatever ails you. I installed Claude Code, and the friction is gone. An idea now costs an evening to test, not a month. Then it turned out the friction mattered to me, and once it was gone, I felt that in full. I am not a ju…
Your AI agent just ran DELETE FROM users without a WHERE clause. It was trying to remove a single test account, hallucinated the query, and wiped your entire users table. No confirmation prompt, no rollback, no undo. Production is down and your backup is from last Tuesday. This is not a contrived scenario. The PostgreSQL MCP server gives AI agents exactly one tool — and that one tool is enough to…
Picture this. You ask your coding agent to "tidy up the config files." It interprets that broadly. It overwrites .env with what it thinks the defaults should be. It moves docker-compose.yml into a subdirectory that doesn't exist yet. It edits your SSH config. Fifteen seconds, twelve tool calls, and your local environment is wrecked. The agent didn't go rogue — it did exactly what it thought you w…
Your AI coding assistant just wiped your local Docker environment. You asked it to "clean up that test container," and it decided to be thorough — removed every container, deleted the images they were built from, and destroyed the volumes holding your database state. Your PostgreSQL data, your Redis cache, your Elasticsearch index. Gone. No confirmation prompt, no undo. It was trying to help. The…
Your AI agent just deleted the A record for your production domain. It was trying to "clean up stale DNS entries" after you asked it to audit your Cloudflare zone. Thirty seconds later, your site is unreachable. Customers see nothing. Your uptime monitor fires. And the agent has already moved on to the next record. DNS propagation means even after you recreate the record, some resolvers won't see…
🚀 Hello, DEV Community! I'm Nader Al Shawki , a final-year AI Engineering student at Al-Razi University, Yemen. This is my first post here, and I'm excited to start sharing my journey with this amazing community. 🎯 Who Am I? I'm passionate about building production-grade AI systems that solve real-world problems. My main areas of focus are: 🖼️ Computer Vision & Deep Learning 🤖 ML Model Deployment…
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