1_DevOps'ish

1_DevOps'ish

mobile-next/mobile-mcp
mobile-next/mobile-mcp
Model Context Protocol Server for Mobile Automation and Scraping (iOS, Android, Emulators, Simulators and Real Devices)
·github.com·
mobile-next/mobile-mcp
dirien/jev-router
dirien/jev-router
Pass-through model router for Claude Code and Codex CLI that picks a model tier per human turn with Jev, TypeSafe AI's decision model
·github.com·
dirien/jev-router
AMD joins $1 trillion club as chipmakers rally on AI-driven demand
AMD joins $1 trillion club as chipmakers rally on AI-driven demand
Advanced Micro Devices soared past $1 trillion ‌in market capitalization for the first time on Monday, joining a small group of chipmakers to reach the milestone, as investors bet on its expanding role in AI computing.
·reuters.com·
AMD joins $1 trillion club as chipmakers rally on AI-driven demand
NVIDIA/Model-Optimizer: A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
NVIDIA/Model-Optimizer: A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downs...
·github.com·
NVIDIA/Model-Optimizer: A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
Side-stepping the Secretary Problem, unwittingly.
Side-stepping the Secretary Problem, unwittingly.
Having played both parts in the kabuki play that is employee-employer matchmaking, I feel the way we play it is a zero-sum game. I wish it were not so. When this post started life in 2024, as a wall of text chat message, it was brutal out there, on both sides of the software industry interview table. The ZIRP had ended. As of 2026, post-ZIRP reality has properly set in and remains bad ("AI" is a Fig Leaf (Enterprise Edition) for structural damage they self-inflicted, and if you look at Hyperscaler GPU depreciation schedules, they are making it order-of-magnitude worse). Set to that backdrop, here is a hopefully hopeful hiring anecdote where I think we avoided the so-called "Secretary Problem", framed within Optimal Stopping Theory. It can be done. Non-zero-sum hiring ought to be default-mode for any industry, AI or no AI.
·evalapply.org·
Side-stepping the Secretary Problem, unwittingly.
aws-ec2-vpn
aws-ec2-vpn
An OpenTofu module that boots a tiny EC2 instance which acts as both SSH Socks proxy and Wireguard VPN
·forge.l3x.in·
aws-ec2-vpn
What I learned from joining the Blog team
What I learned from joining the Blog team
When I joined the Kubernetes blog team, I did not know quite what to expect. Here is everything I picked up along the way from finding your first PR to getting an article published. Everyone starts somewhere and I am glad you are starting here. Before I get into it, let me answer the question I had when I first joined. Am I actually qualified to do this?Yes. Genuinely.
·kubernetes.dev·
What I learned from joining the Blog team
We're making Tailscale faster
We're making Tailscale faster
Tailscale performance updates reduce memory use, increase throughput, and speed startup with multi-queue, writev, and netmap caching.
·tailscale.com·
We're making Tailscale faster
Google Open-Sources AX a Kubernetes Style Orchestrator for Autonomous AI Agents
Google Open-Sources AX a Kubernetes Style Orchestrator for Autonomous AI Agents
Google has open-sourced AX, an orchestrator designed for managing autonomous AI agent workloads. AX operates on a runtime, Agent Substrate, treating agents as stateful actors. It provides resource-efficient task suspension and resumption to optimise performance and reduce latency in idle phases. It features a control plane with Kubernetes-style primitives for managing agent tasks and resources.
·infoq.com·
Google Open-Sources AX a Kubernetes Style Orchestrator for Autonomous AI Agents
OpenAI gives AI cyber defence tools to Ukraine
OpenAI gives AI cyber defence tools to Ukraine
Ukraine will get access to OpenAI's advanced GPT 5.6 Sol model under the deal - a rival to Anthropic's Mythos and Fable
·bbc.com·
OpenAI gives AI cyber defence tools to Ukraine
Analyzing Jev, a new AI model
Analyzing Jev, a new AI model
A new AI model called Jev launched last week and went viral. It's not an LLM. It doesn't generate text or pictures, but could be very us...
·blog.senko.net·
Analyzing Jev, a new AI model