# Technical authorship

All knowledge hub articles in Technical authorship.

URL: https://dylanengelbrecht.dev/insights/category-authorship.html

- [Why Mirror for Unity multiplayer](https://dylanengelbrecht.dev/insights/mirror-multiplayer-unity.html): Mirror is a pragmatic default when Unity teams need a complete networking architecture.
- [Progressive disclosure for learning: maps, not memorization](https://dylanengelbrecht.dev/insights/progressive-disclosure-learning-with-agents.html): Orchestrate agents across a navigable map — learn foundations deeply, index everything else, verify with the environment.
- [Getting started with Cursor: automate the loop](https://dylanengelbrecht.dev/insights/getting-started-with-cursor.html): Treat Cursor as an automation surface — rules, tests, MCP, and agents run the boring parts so you keep one thread for judgment.
- [The AGENTS.md standard for AI coding agents](https://dylanengelbrecht.dev/insights/agents-md-standard.html): One open Markdown file per repo — closest AGENTS.md wins; user prompts override.
- [Organizing knowledge for AI agents](https://dylanengelbrecht.dev/insights/organizing-knowledge-for-ai-agents.html): Pair a public site with a private brain — progressive disclosure, lifespans, verification metadata.
- [Building MCP servers with search and execute](https://dylanengelbrecht.dev/insights/mcp-search-execute-codemode.html): Two MCP tools — search and execute — beat hundreds of per-operation tool definitions.
- [Reinforcement learning for tool calling in agent models](https://dylanengelbrecht.dev/insights/rl-tool-calling-composer.html): RL specializes models for the tool loop — Composer is the public case study.
- [Keep the thread: why plan–critique–build pipelines fail modern coding agents](https://dylanengelbrecht.dev/insights/single-agent-coding-loops.html): One agent, one thread, small units — verify with tests, not lossy handoffs.