GuideIntermediate

Debugging & Code Review with Claude Code

Only 3% of developers highly trust AI-generated code. This guide teaches the professional middle ground: calibrated trust. Learn to detect hallucinations, do code review with AI-specific checklists, debug with Claude Code as a tool (not an oracle), and decide when to regenerate vs edit. 8 modules, 43 capsules, and a project where you perform a complete professional code review of a codebase with real problems.

43
lessons
8
modules
English · Spanish
available in
Free
access
NIEVA

Outcomes

What you'll be able to do

  • Por qué solo el 3% confía en AI code y cómo calibrar tu confianza
  • Mental model "Managing an Intern" (MIT) para supervisar código AI
  • Circuit Breaker y Trust Calibration como frameworks complementarios
  • Detectar hallucinations sutiles: imports falsos, APIs inventadas, lógica fabricada
  • Checklist profesional de code review para AI-generated code
  • Patrones de error comunes: naming, edge cases, security holes
  • Debugging sistemático con Claude Code: log analysis, stack traces
  • Subagents (Explore agent) para investigar codebases
  • Framework de decisión: cuándo regenerar vs cuándo editar manualmente
  • Proyecto: code review profesional completo de un codebase con problemas

Before you start

What you need to bring

Requirements and materials

  • Guías 1-5 del Claude Code Agentic Development Path completadas
  • Experiencia escribiendo código propio (para tener criterio de comparación)
  • Familiaridad con debugging básico (print statements, logs)
  • Claude Code instalado y configurado

Content

The syllabus, module by module

Open any of them to see its lessons.

Common questions

What people usually ask

Start whenever you like

Reviews

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