Design the Codebase Your Agent Can Read
The highest-leverage thing you can do for your agent isn't a better prompt - it's a better interface. Deep modules are context the agent reads at a glance.
Engineering Blog
Technical insights into multi-agent orchestration, local protocols, and
developer-centric terminal workflows.
Destination and Journey
Hand the agent two committed documents - a requirements doc that fixes the destination, a phased plan that fixes the journey - and a big feature still ships.
Full Autonomy Is Just a Small Blast Radius
The blocker to running an agent overnight is never capability - it's trust. And you don't earn trust with a smarter model, but with a smaller blast radius.
Flat agent swarms demo beautifully and ship terribly.
Let peer agents talk freely and a query hot-potatoes between them while your bill climbs. Route everything through one orchestrator with a turn cap instead.
Inject the Reminder When the Agent Forgets
Your rules file is necessary but not sufficient. Persistent context degrades as the window fills - move the ignored rule into a hook that fires when it matters.
When your agent reads a webpage, that webpage can give it orders.
Prompt injection is a context-engineering problem. Fence untrusted tool output as data, run a guardrail hook, and cap the blast radius with permissions.
The planning step's value isn't the document. It's the interrogation.
Your judgment lives in your head until something extracts it. A procedure that explores the repo, then grills you branch by branch, turns an idea into a spec.
Adding a system to your agent should be a config line, not a codebase.
Hand-writing an adapter per external system is the contextless agent's biggest tax. An MCP server collapses the blowup into one connection, configured once.
Package the Workflow, Not the Prompt
A plugin isn't a convenience wrapper. It's how a workflow survives leaving your laptop - the difference between a personal habit and a team standard.
'It worked for me' is not a test for a non-deterministic system.
Treat prompts like code: a golden dataset run headless on every change, gated by a hook that fails the build below baseline. Only a blocking eval works.