Learning paths

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Three guided reading paths through the guides and essays on this site. Pick one, read in order, and check off what you finish — progress stays in your browser.

New to Claude Code

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From first install to a tool that fits your hand. Set up the CLI, learn the moves that matter, then decide how it stacks up against the alternative.

  1. Claude Code CLI Setup 2026: 5-Minuten-Schnellstart

    Install the CLI, authenticate, and finish your first working session in about five minutes.

  2. Claude Code Cheat Sheet

    Keep this open in a tab: every command, shortcut, and flag on a single page.

  3. Claude Code Leitfaden

    The complete reference. Skim the basics now, come back for the deep sections as you need them.

  4. AGENTS.md-Muster: Was das Verhalten von Agenten wirklich verändert

    Your instructions file is the highest-leverage config you have. These patterns actually change behavior.

  5. Claude Code Hooks Tutorial: 5 produktionsreife Hooks von Grund auf

    Build five working hooks from scratch. This is the step from using the tool to shaping it.

  6. Eigene Skills für Claude Code erstellen: Ein vollständiges Tutorial

    Package your own workflows as skills that switch on exactly when they are needed.

  7. Claude Code vs. Codex CLI 2026: Entscheidungsreferenz

    You know the tool now. See how it compares to its main rival, and when each one wins.

Agentic Engineering

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How to build, run, and trust AI agents that do real engineering work: the harness, the economics, the failure modes, and where the discipline is heading.

  1. Das Evidence Gate

    Start with the working discipline: never accept “it should work” from an agent. Require proof.

  2. Agent-Architektur

    The complete playbook for building an agent harness: skills, hooks, memory, subagents, and orchestration.

  3. Compounding Engineering: Wie meine Codebase beschleunigt statt zu verfallen

    Why harness work pays compound interest: each feature you ship makes the next one cheaper.

  4. Loop Engineering: Schleifen gewinnen dort, wo Verifikation billig ist

    The rule that decides what to automate: loops win only where checking the result is cheap.

  5. Was tatsächlich kaputtgeht, wenn Sie KI-Agenten unbeaufsichtigt laufen lassen

    Seven ways agents fail when nobody is watching, and the signal that catches each one early.

  6. Das Handbuch für Agent-Operatoren: Beaufsichtigen, was Sie nicht sehen können

    Running agents is a role of its own. What supervision looks like when you cannot read every line.

  7. Agents lösen den Reviewer ab, nicht das Review

    Where this is heading: the reviewer role is dissolving while the review itself moves into the pipeline.

iOS with Agents

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Ship Apple-platform apps with AI agents doing the heavy lifting, from wiring Claude Code into Xcode to the on-device models your app can ship.

  1. iOS-Agent-Entwicklung

    The end-to-end playbook for building iOS apps with agents. Start here and branch out.

  2. Wie zwei MCP-Server Claude Code in ein iOS-Build-System verwandelten

    Wire Claude Code into Xcode so it can build, run tests, and read crash logs on its own.

  3. Hooks für die Apple-Entwicklung: Muster, die das Projekt retten

    An agent working near your signing keys needs guardrails. Four patterns that bound the damage.

  4. Xcode 27 ist agentisch geworden

    What Apple ships natively: Xcode 27's built-in agents, and where they fit next to your CLI.

  5. Agentic Workflow mit Foundation Models: In-App vs. Tooling-LLM

    Two AIs touch your app: the agent writing the code and the model shipping inside it. Keep their jobs straight.

  6. Foundation Models LLM auf dem Gerät: Das Tool-Protokoll

    Put Apple's on-device model to work inside your app, starting with the Tool protocol.

  7. Foundation Models in iOS 27: Steuerung des Tool-Callings

    Control how the on-device model uses tools, with iOS 27's calling modes and built-in readers.