Maximiliano Contieri - Software Design

TL;DR: Split every skill description into three sentences: when to read it, when to use it, and what it does.

TL;DR: Audit your AGENTS.md and skills on a schedule, or you keep paying context rent on rules the model has outgrown.

TL;DR: Write the failing test first and ban deletions, or the AI deletes your test, reverts your fix, and calls it done.

TL;DR: Don't reuse an existing getter to bolt on new business logic from outside the object.

TL;DR: Run your pipeline like a dark factory: automated, sampled, and policed by an adversarial model.

TL;DR: Reasoning models already verify and pace themselves, so drop those prompts and set real effort, scope, length, autonomy.

TL;DR: Turn repeatable skill steps into tested scripts instead of prompts, so behavior stays deterministic and cheap.

TL;DR: Assign a different model to each pipeline stage since none excels at planning, coding, reviewing, and testing alike.

TL;DR: Wire a skill into your company's live systems so every answer carries a source and a freshness check.

TL;DR: Wire your standards into hooks, skills, and a judge, so the harness blocks violations before a human opens the diff.

Know who speaks before the skill runs TL;DR: Always define a clear role at the top of every skill file so you know whose perspective drives the execution.

Everyone is talking about Loop Engineering.

TL;DR: You write tests that touch every line but verify nothing, creating false confidence in a broken system.

TL;DR: Add a PITFALLS.md next to every SKILL.md so your AI never repeats the same mistake twice.

TL;DR: Spawn a fresh subagent after every task to check your rules, because the AI that did the work can't audit itself.

TL;DR: Tell your AI to split work into small reviewable pull requests before it writes any code.

TL;DR: Install your harness before prompting: the structure you set up first is what turns an impulsive AI into a safe, steerable collaborator.

TL;DR: Merging code you don't understand creates comprehension debt that compounds until your team can no longer maintain it.

TL;DR: Use Obsidian with Markdown notes, YAML metadata, and direct AI file access to build a Second Brain with LLMs that gives your tools persistent project context.

TL;DR: Tell the AI your reason before your request to get solutions that match your real constraints.