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Learn how to split complex AI tasks into focused prompt stages, pass structured outputs between steps, add validation gates, control context, prevent cascading errors, and design reusable multi-step AI workflows.

Learn a practical framework for AI prompt evaluation, from defining success criteria and building representative test cases to scoring outputs, comparing prompt variants, testing across models, and preventing prompt regressions.

Explore Claude Code Dynamic Workflows, including agent(), pipeline(), Ultracode, /deep-research, workflow scripts, background runs, resumability, permissions, runtime limits, and reusable multi-agent orchestration patterns.

Explore Claude Code Agent Teams, including setup, team leads, teammates, shared tasks, messaging, models, permissions, hooks, parallel development patterns, and practical multi-agent examples.

Use these Claude Code subagent examples and reusable custom agent templates to isolate context, delegate specialized tasks, control tools and permissions, and coordinate complex development workflows.

Use these Claude Code Hooks examples and reusable templates to automate validation, enforce safety boundaries, run development tools, inject context, and respond to Claude Code lifecycle events.

Use these reusable Claude Code Skills and SKILL.md templates to package coding workflows, project knowledge, verification steps, tools, and supporting resources.

Use these AGENTS.md examples and reusable templates to give AI coding agents clearer project context, architecture rules, development commands, testing requirements, security boundaries, and review instructions.

Use these reusable Codex prompts to explore repositories, plan and implement features, delegate work across parallel agents, review changes, create Skills, and automate recurring development tasks.