Blog

Hermes Agent runs on my mini-PC, drives my Mac, and handles the logistics around my blog, YouTube, and taxes, so I can spend my time on the parts that actually need me. Here is how it works.

Opus 5 shipped on July 24 as Anthropic's new default model. The benchmark table is a rounding error away from Fable 5 at half the cost. But the thing that will actually change your day is quieter: thinking is on by default now, and that breaks a few assumptions you have been carrying since 4.8.

A public endpoint went down twice in three days, and the same five-minute fix worked both times: delete an orphaned AAAA record. The real bug was a DNS record that can never own itself, sitting at the apex of a delegated zone.

Same instance type, half the pod density. Raising max pods on a live EKS cluster means a launch template the node group can never gain, a CNI setting that has to land first, and a Terraform plan carrying changes nobody asked for.

I wanted to know what changed architecturally between Sonnet 5 and Sonnet 4.6. Anthropic won't say. So I read the 146-page system card, and ended up writing a plain-English guide to every benchmark in it.

Every view that touched the cache returned 500 while the health check stayed green. The cause was a Service named redis and enableServiceLinks, a Docker-era Kubernetes default that injects environment variables you never asked for.

Databricks open-sourced Omnigent, a meta-harness that wraps any agent harness behind a unified API with policies, sessions, and shared state. If you have deployed stateful services to Kubernetes before, the path to self-hosting it is shorter than you think.

Every operator promises a simpler setup. The real payoff shows up later, when a replica loses its control file or a certificate is three weeks from expiring. Here is what StackGres and Strimzi actually changed about running PostgreSQL and Kafka on Kubernetes.

A green CI pipeline while the live gateway serves 404s is not a test failure. It is a silent reload gap. Here is the cross-release checksum pattern that closes it in helmfile.

I built a pipeline that reads my blog's RSS feed and posts informative Instagram carousels without me touching anything. The interesting part is not the automation. It is how agents built it and what they broke.

The government pulled the plug on Fable 5 and Mythos 5 seventy-two hours after launch over a jailbreak claim. If you build on closed AI APIs, this week should make you uncomfortable.

More than 25 open-weight model releases dropped last week across every modality. A breakdown of what each one does, which ones are actually deployable, and what the week means for infrastructure teams.

AI coding tools don't just write code faster. They generate dramatically more Git activity, pipeline runs, and context overhead than humans do. GitLab's Transcend 2026 announcements finally address that.

For years the advice was clear: pick a lane, go deep, become indispensable. Then AI agents arrived and quietly rewrote the rules.

Nous Research's self-improving AI agent running in a production-grade EKS setup. Private ECR, IRSA, API key secrets, and a custom Helm chart built from scratch.

Transit Gateway is the default everyone reaches for. For a handful of VPCs in a single region, peering is dramatically cheaper — and here's the math.

I built a full-stack Proxmox dashboard through vibe coding with Claude Code: 11K lines, 123 tests, 14 commits. Here's what the experience taught me about what actually matters in software engineering.

Attempting to delete a Kubernetes namespace and discovering it perpetually stuck in a Terminating state? The culprit typically involves finalizers — special metadata fields that prevent resource deletion until cleanup tasks complete.

Exploring Terraform's templatefile() function and its advantages over Jinja2 templating for infrastructure-as-code workflows. Why Terraform's minimalist approach to templating is intentional and beneficial.

How Kubernetes Operators automate complex operational tasks in containerized environments, addressing challenges that arise from managing microservices at scale.

The transition to WebGPU for AI and GPU computation represents a pivotal shift in how we'll experience artificial intelligence technology — democratizing access to advanced capabilities.

How Machine Learning Operations (MLOps) transforms AI development by streamlining model creation and deployment compared to conventional cloud-based approaches.