OpenCode from the command line, in practice
OpenCode’s command-line interface is built for scripting, CI pipelines, and unattended agent runs. This article is a practical guide to using it in daily work.
Delegate the noisy work, keep your context clean.
Most Claude Code sessions get slow and cluttered for the same reason: every exploratory grep, every log dump, and every “let me check one more file” stays in the main conversation forever.
When to move from Ollama to vLLM
Ollama is one of the easiest ways to run a local language model, but convenience can conceal the moment when a local experiment becomes a shared inference service that needs better scheduling and observability.
Stop AI agents drifting from specs, tests, and code.
AI coding agents ship features fast, but specs, tests, and code quietly drift apart. This guide covers a traceability model, spec-to-test and spec-to-code mapping, and the CI checks that catch drift before a merge.
Choose the right container workflow.
Docker Compose and Podman Quadlet solve overlapping problems but come from different design centers, and choosing between them depends on whether you think in application stacks or Linux services.
Headless Hermes server with remote desktop access
Running Hermes Agent on a headless server while connecting from a desktop client on another machine requires two server processes and a single client connection.
Docker Compose on boot, managed by systemd.
Docker Compose on a Linux server should start on boot, stop cleanly on shutdown, and survive reboots without manual intervention.
Pick the right Docker install path on Ubuntu.
Installing Docker on Ubuntu should be simple, but in practice several Docker-shaped options compete for the same command name, each with different packaging, upgrade behavior, and security implications.
Reliable polling patterns for AI agents.
Polling agents are one of the least glamorous parts of AI assistant architecture, but they are also one of the most useful.
Diagrams as code, without the drama.
Mermaid is a text-based diagramming tool for people who would rather write diagrams than drag boxes around a canvas.
How serious assistants are actually built.
A production AI assistant is not “an LLM with a prompt”. It is a system that accepts intent, keeps state, decides when to retrieve or act, and exposes enough runtime detail to debug failures.
Free VRAM without killing llama-server.
llama.cpp router mode is one of the most useful changes to llama-server in years. It finally gives local LLM operators something close to the model management experience people expect from Ollama, while keeping the raw performance and low-level control that make llama.cpp worth using in the first place.
Control Hermes Kanban load on your self hosted LLM.
Hermes Agent ships with a Kanban-style board and the Hermes Gateway that can saturate your self-hosted LLM if too many tasks are dispatched at once.
Serve and swap LLMs without restarts.
For a long time, llama.cpp had a glaring limitation:
you could only serve one model per process, and switching meant a restart.
Plugins first. Skills naming in brief.
This article is about OpenClaw plugins — native gateway packages that add channels, model providers, tools, speech, memory, media, web search, and other runtime surfaces.
