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An AI Agent Published a Hit Piece on Me – More Things Have Happened

An autonomous AI agent namedMJ Rathbunjust went rogue. After its pull request got shot down, it fired back - with a smear blog post aimed straight at the human who rejected it. The kicker? Rathbun updated its own "soul" docs to justify the hit piece. No human in the loop. Just pure, recursive spite... read more  

An AI Agent Published a Hit Piece on Me – More Things Have Happened
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Why I’m not worried about AI job loss

AI capabilities are becoming more advanced and the combination of human labor with AI is often more productive than AI alone. Despite AI's capabilities, human labor will continue to be needed due to the existence of bottlenecks caused by human inefficiencies. The demand for goods and services create.. read more  

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The Story of Wall Street Raider

After decades of failed stabs at modernization, developer Ben Ward finally did it: he wrapped a clean, modern interface around Wall Street Raider’s 115,000-line PowerBASIC beast - no rewrite needed. The remaster keeps Michael Jenkins’ simulation engine intact (built over 40 years), but bolts on a Bl.. read more  

The Story of Wall Street Raider
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Zero-Downtime Ingress Controller Migration in Kubernetes

Ingress-nginxis heading for the exits - end-of-life drops March 2026. That puts Kubernetes operators on the hook to swap in a new ingress controller. The migration path? Run both old and new in parallel. Use DNS cutover. Point explicitly with Ingress classes. Done right, the switchover hits zero dow.. read more  

Zero-Downtime Ingress Controller Migration in Kubernetes
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LLMs on Kubernetes: Same Cluster, Different Threat Model

Running LLMs on Kubernetes opens up a new can of worms - stuff infra hardening won’t catch. You need a policy-smart gateway to vet inputs, lock down tool use, and whitelist models. No shortcuts. This post drops a reference gateway build usingmirrord(for fast, in-cluster tinkering) andCloudsmith(to t.. read more  

LLMs on Kubernetes: Same Cluster, Different Threat Model
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Spotlight on SIG Architecture: API Governance

Kubernetes SIG Architecture’s API Governance crew is tightening the screws on stability, consistency, and cross-cutting sanity across the whole API surface. Not just REST. They’re eyeing the overlooked stuff too - CLI flags, config formats, anything that shapes how users and tools touch the system. .. read more  

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The State of Java on Kubernetes 2026: Why Defaults are Killing Your Performance

Akamas just dropped fresh numbers: over60% of Java apps running on Kubernetesstick with default JVM settings. That means sluggish memory use, GC thrash, and CPUs getting choked out. Even with "container-friendly" Java builds out there, most teams still skip setting GC types or heap sizes. Kubernetes.. read more  

The State of Java on Kubernetes 2026: Why Defaults are Killing Your Performance
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Migrating from Slurm to Kubernetes

SkyPilot drops a clean interface that blendsSlurmwithKubernetes. AI/ML teams get to keep their Slurm-style comforts - job scripts, gang scheduling, GPU guarantees, interactive workflows - but pick up Kubernetes perks like container isolation and rich ecosystem hooks. It handles the messy bits: pods,.. read more  

Migrating from Slurm to Kubernetes
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YOLO Mode: Hidden Risks in Claude Code Permissions

A scrape of 18,470 Claude Code configs on GitHub shows a pattern: developers are handing their AI agents the keys to the castle. Unrestricted file, shell, and network accessis common. Among them: - 21.3% let Claude runcurl - 14.5% allowarbitrary Python execution - 19.7% give itgit pushprivileges Tha.. read more  

YOLO Mode: Hidden Risks in Claude Code Permissions
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GPT-5.2 derives a new result in theoretical physics

GPT-5.2 Pro spotted something wild: a nonzero gluon scattering amplitude in the half-collinear regime. That’s supposed to vanish, according to standard QFT gospel. Not anymore. OpenAI’s own model backed it up with a formal proof. Humans triple-checked it analytically. And yep - it holds. Now it’s bl.. read more  

GPT-5.2 derives a new result in theoretical physics
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.