AI Coding Agents Need a Source of Truth
Bigger prompts do not fix drifting agent plans. A good workflow starts with a small brief, human review, task sizing, and checks against real artifacts.
I write about backend systems, coding agents, infrastructure, CLI tools, and the boring details that decide whether software works in production.
Bigger prompts do not fix drifting agent plans. A good workflow starts with a small brief, human review, task sizing, and checks against real artifacts.
· cli
A CLI is both a user interface and an API for scripts. Quiet mode, stdout, stderr, colors, and exit codes need real contracts.
Docker cache problems are often Dockerfile problems: unstable inputs, bad COPY order, and layers that depend on too much.
A backend engineer with no game dev background picked up Godot 4 and built a horror FPS. Then a 13-year-old played it, grabbed a tablet, and decided the game needed real monsters and lore.
The pitch is obvious: per-PR environments, live links, faster feedback. Then a multi-service stack needs twenty restarts and the pitch meets operations.
Your CI pipeline builds the same Docker image three times, a dependency bot eats your runner fleet, and nobody fixes it because nobody owns the system.
Production has dashboards, alerts, and logs. Test environments have SSH. CI runners have a re-run button. That gap quietly eats engineering time.
Four months ago I asked ChatGPT a dumb question while walking my dog. It told me building a programming language wasn’t that hard. Now I have a compiler, a type system, generics, structured concurrency, and a garbage collector.
· go
pin is a Go spinner with colors, prefixes, message updates, pipe detection, and no external dependencies. It exists because a spinner should not drag a UI framework into a small CLI.
· docker
Docker networking gets a lot easier once you separate internal ports from host port mappings. Containers talk by service name and internal port. The outside world uses the mapped port.