Practical Claude Code Workflow for Development Teams

A developer on r/ClaudeAI is preparing an internal presentation about Claude Code best practices and seeking feedback from daily users. Their team has been experimenting with Claude Code for a few weeks with mixed seniority developers, observing that most use it very basically without awareness of model differences, plan mode, or workflows.

Core Recommendations

The presentation outlines a structured workflow:

• Model Selection: Default to Opus for anything non-trivial. Sonnet is fine for quick or simple tasks, but Opus is significantly more reliable for real development work.
• Structured Workflow: Instead of jumping straight to code:
  • Brainstorm or Interview: Discuss the feature with Claude first
  • Plan Mode: Always use it for non-trivial features. Iterate on the plan until it's solid
  • Implementation: Let Claude generate code from the validated plan
  • AI Review: Ask for a review in a fresh context. Optionally use another model for a second opinion
  • Human Review (mandatory): Always validate manually before merging

Additional Tips

• Prompt Wording: Words like "robust," "production-ready," and "industry standards" improve output quality
• Context Limits: Be aware that context isn't infinite and has a cost, so keep things focused
• Documentation: Claude is very strong at explaining codebases or generating docs
• CLI Capabilities: Leverage Git, GitHub or GitLab CLI, tickets, PRs, etc.
• Skills: Use for repetitive tasks like reviews, commits, and refactors
• Parallel Work: Use git worktrees to run multiple Claude instances on different branches
• Reduce Hallucinations: Ask it to say "I don't know" and request assumptions or sources when planning

Golden Rules

• Always read what it produces
• Use Opus and Plan mode for real work
• Stick to a consistent workflow

The developer is seeking feedback on whether this aligns with how others use Claude Code, if any high-impact but simple practices are missing, and if anything is overkill for a general development audience. The goal is to keep the presentation simple, practical, and adoptable rather than a lengthy AI lecture.