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• When an AI Maintains Your Code, Write for Humans Anyway

  On July 10, 2026, Scott Robinson revived an old maxim with a twist: an LLM reads your codebase as its style guide, so every shortcut you merge becomes training data it repeats back at machine scale. We walk through his d

  2026-07-11 · 6 min read #ai#llm#code-quality#maintainability#craft

• Practical Stoicism: Applying an Ancient Philosophy to Modern Life

  Stoicism began in Athens around 300 BCE, yet its core tools fit today's anxieties surprisingly well. Grounded in the actual texts of Epictetus, Seneca, and Marcus Aurelius, this post lays out practices you can use: the d

  2026-07-11 · 8 min read #philosophy#stoicism#self-improvement#life-advice

• Habits Aren't Built in 21 Days: Re-reading Micro-Habits Through the 66-Day Study

  'It takes 21 days to build a habit' is folklore that traces to a 1960 surgeon's observation, not a habit experiment. Lally and colleagues' 2010 study, which tracked real behaviour, found a median of 66 days to automatici

  2026-07-11 · 6 min read #self-improvement#habits#psychology#productivity#behavior-change

• Japanese Walking vs the Real Science: What Interval Walking Training Actually Shows

  The 'Japanese walking' that spread across social media in 2026 is really Interval Walking Training (IWT), a protocol that researchers at Shinshu University have refined for nearly two decades, repackaged under a new name

  2026-07-11 · 4 min read #fitness#health#walking#exercise#cardio

• Manage Your Energy, Not Your Time — a grounded read on the 2026 wellness trend

  2026 self-improvement coverage is shifting its center of gravity from time management to energy management, nervous-system regulation, and emotional fitness. But the framing is actually an old idea from a 2007 Harvard Bu

  2026-07-11 · 6 min read #self-improvement#wellness#productivity#energy#recovery

• Building Effective AI Agents: A Reference on the Five Workflow Patterns and Agents

  A practical reference distilled from Anthropic's engineering guide "Building Effective Agents." It covers the precise distinction between workflows and agents, the building block underneath everything — the augmented LLM

  2026-07-11 · 8 min read #ai#agents#llm#engineering#anthropic

• Building a Kubernetes GPU Operator in Rust — Diagnosing a Real Cluster with kube-rs ♪ Listenable

  Against a production 8-node homelab cluster (k8s v1.32.5), I used kube-rs to build and run a GPU operator in Rust myself. I defined a GpuInventory custom resource and launched two controllers (node scan → record CR statu

  2026-07-11 · 6 min read #rust#kubernetes#operator#gpu#kube-rs

• Separating Signal from Noise When You Evaluate AI Coding Models — Why SWE-bench Got Shaky

  OpenAI's evals team argues that SWE-bench Verified, the most widely used coding benchmark, no longer gives meaningful signal because of contamination and design flaws. Look at benchmarks through two axes — signal (the po

  2026-07-11 · 6 min read #llm-evaluation#coding-benchmarks#swe-bench#benchmarks#ai-coding

• Preparing to Become a Forward Deployed Engineer: A Map of the Software Knowledge That Matters

  A Forward Deployed Engineer (FDE) is a role Palantir invented: an engineer who embeds with a customer and deploys, integrates, and configures the product inside the client's real environment. The role is surging again as

  2026-07-11 · 6 min read #career#fde#software-engineering#palantir#solutions-engineering

• Production RAG Patterns — Why Naive RAG Fails and the Techniques That Actually Help

  A demo RAG system takes half a day to build, but the place it quietly breaks in production is almost always retrieval, not generation. This reference walks through chunking, embeddings and hybrid search (BM25 + vector),

  2026-07-11 · 9 min read #ai#rag#llm#retrieval#embeddings

• The Three Tribes of Automation — Zapier/Make/n8n, RPA, and 2026 Agentic Automation

  When someone says "just automate this," people often reach for the wrong tool. That is because automation has three distinct tribes — workflow automation that connects APIs (Zapier/Make/n8n), RPA that operates screens li

  2026-07-09 · 6 min read #automation#rpa#zapier#n8n#ai-agents

• GPU Operator × KubeVirt Complete Guide — Components, Configuration, Versions, Partial MIG, and Manual MIG

  The two pillars of GPU infrastructure on Kubernetes, all on one page. Covers the GPU Operator operands, ClusterPolicy configuration, and versioning scheme, plus a custom config that applies MIG to only some of the GPUs o

  2026-07-09 · 9 min read #kubernetes#gpu#kubevirt#mig#nvidia

• The Complete Guide to LLM Training Data Preprocessing — From Web Crawls to Token Packing, with the Latest Papers

  Good models come from good data, and good data comes from a preprocessing pipeline. This post walks through the entire pretraining data process step by step — web crawl collection → text extraction → language identificat

  2026-07-09 · 7 min read #ai#llm#data-engineering#preprocessing#training

• The 2026 Robotics Company Map — The Humanoid Showdown, VLA Models, and the Engineer's Way In

  2026 is the inflection point where humanoid shipments jump about 7x year-over-year to a forecast of 50,000+ units. From Figure, valued around USD 39B with its in-house VLA model Helix, to Tesla Optimus Gen 3 entering mas

  2026-07-09 · 7 min read #robotics#ai#vla#trends#career

• Two Paths to 3D — Reconstruction (NeRF & Gaussian Splatting) and Generation (TRELLIS & Hunyuan3D)

  The phrase "make a 3D model" hides two completely different problems. Reconstruction brings a scene that actually exists back to life from a handful of photos, while generation conjures something that does not exist from

  2026-07-09 · 9 min read #3d#ai#gaussian-splatting#nerf#computer-vision

• Building SSO with Keycloak — From Realm, Client, and Flows to the 2026 New Features

  Instead of bolting a separate login onto each of 20 internal apps, SSO lets a single identity server stand in for all of them. This post makes sense of Keycloak — the open-source standard — through four core concepts (Re

  2026-07-09 · 9 min read #keycloak#sso#oidc#security#devops

• Multi-GPU, Multi-Node Training Platforms: The Complete Map — from the Framework Ecosystem to Hands-On Slurm and Kubeflow Guides

  A one-page map of the full landscape of training models across multiple GPUs and multiple nodes. The AI library and framework ecosystem map (PyTorch, JAX, HuggingFace, DeepSpeed, Ray), when to pick which parallelization

  2026-07-09 · 8 min read #ai#ml#distributed-training#slurm#kubeflow

• From Docker to Podman — the Complete Guide to Switching to a Daemonless Container Engine

  Podman differs from Docker at the level of architectural philosophy: daemonless (fork-exec) operation and rootless by default. Internals (conmon, crun), config file locations and meanings, CDI setup for GPUs, the two way

  2026-07-08 · 8 min read #docker#podman#containers#devops#linux

• LLM Caching, Explained — Why Prompt Caching and Prefix Caches Save You Money

  Why does a matching prompt prefix cut costs to a tenth? The answer lives in the transformer's KV cache. Because attention is causal, the Key/Value vectors of earlier tokens never change no matter what comes after — so th

  2026-07-08 · 7 min read #ai#llm#caching#inference#performance

• The State of LLM Quantization — From GPTQ and AWQ to FP8, MXFP4, and KV-Cache Quantization ♪ Listenable

  Quantization represents a model's numbers in fewer bits to cut memory and cost. Why quality survives fewer bits (outliers and scaling), how GPTQ and AWQ differ in approach, llama.cpp GGUF k-quants, QLoRA's NF4, the 2026

  2026-07-08 · 7 min read #ai#llm#quantization#inference#optimization