Vibe Coding lets developers create software by chatting with AI, skipping traditional coding. But the non-determinism of AI prompts poses significant risks for reliability and maintainability, potentially leading to addiction-like dependence on this new tool. Think twice before fully embracing this .. read more  

A developer rolled their own AI server for $1.3K—Ubuntu 24.04.2 LTS, an Nvidia RTX GPU, and a sharp eye on Tensor cores, VRAM, and resale value. The rig handles small models locally and punts big jobs to the cloud when needed. Local-first, cloud-when-it-counts... read more  

A long-dead Linux kernel driver for QIC-80 tape drives just got dragged into the present—with help from **Claude Code** and a lot of tinkering. It now builds cleanly and runs as a **standalone module** on **Linux 6.8**, playing nice with modern setups like **Xubuntu 24.04**. **The bigger picture:**.. read more  

Fastly says95% of developersspend extra time fixing AI-written code. Senior engineers take the brunt. That overhead has even spawned a new gig: “vibe code cleanup specialist.” (Yes, seriously.) As teams lean harder on AI tools, reliability and security start to slide—unless someone steps in. The re.. read more  

Agent engineering with **small language models (SLMs)**—anywhere from 270M to 32B parameters—calls for a different playbook. Think tight prompts, offloaded logic, clean I/O, and systems that don’t fall apart when things go sideways. The newer stack—**GGUF** + **llama.cpp**—lets these agents run loc.. read more  

GitHub's biggest debates right now? Whether to shut down AI-generated "noise" fromCopilot—stuff like auto-written issues and code reviews. No clear answers from GitHub yet. Frustration is piling up. Some devs are ditching the platform altogether, shifting their projects toCodebergor spinning upself-.. read more  

In the “Month of AI Bugs,” researchers poked deep and found prompt injection holes bad enough to run **arbitrary code** on major AI coding tools—**GitHub Copilot**, **Amazon Q**, and **AWS Kiro** all flinched. They didn’t stop at theory. They built **AgentHopper**, a proof-of-concept AI virus that .. read more  

LLMs generate text by predicting the next word using attention to capture context and MLP layers to store learned patterns. Mechanistic interpretability shows these models build circuits of attention and features, and tools like sparse autoencoders and attribution graphs help unpack superposition, r.. read more  

LinkedIn tore down its GenAI stack and rebuilt it for scale—with agents, not monoliths. The new setup leans on distributed, gRPC-powered systems. Central skill registry? Check. Message-driven orchestration? Yep. It’s all about pluggable parts that play nice together. They added sync and async modes.. read more  

The new **Model Context Protocol (MCP) Registry** just dropped in preview. It’s a public, centralized hub for finding and sharing MCP servers—think phonebook, but for AI context APIs. It handles public and private subregistries, publishes OpenAPI specs so tooling can play nice, and bakes in communit.. read more