Evergreen content. Methods and configurations tested in production, not demo tutorials.
An agentic workflow isn't about "using AI to code faster" — it's a restructuring of how you break down, delegate, and verify work. The real gains come from three practices: decomposing tasks into verifiable units, actively managing context, and treating the agent like a competent junior who needs precise instructions.
Route mechanical tasks to budget or free models (MiniMax 2.5 via Kilo Gateway, Gemini Flash), reserve premium models for reasoning. Result: mechanical tasks (~65% of volume) cost nothing, with no perceived quality loss.
A good coding agent prompt has three components: what you want (precise task), how to validate it (verifiable exit condition), and what you don't want (explicit constraints). Most disappointing results come from instructions missing one of the three.
The context window is a finite resource that degrades. The key is treating it as such: short sessions with verifiable deliverables, persistent context files between sessions, splitting into specialized agents for parallel tasks. Multi-agent workflows aren't added complexity — they're the way to work at scale without losing quality.
OpenCode integrates naturally into a Neovim/tmux workflow: a dedicated tmux split, the agent in one pane, your editor in the other. The client/server architecture lets you start OpenCode server-side and connect via SSH with no extra configuration. Full setup in 30 minutes.