Cost-Effective Claude Code Workflow: Opus for Planning, Sonnet for Coding, Git Worktrees, and IDE Integration

Workflow value: 85/100
Status: active · Freshness: 70/100 · Confidence: 0.90 · Level: intermediate
Categories: Quality Control, Token Saving, Context & Memory, Debugging, MCP, Multi-Agent
Original source: r/ClaudeCode post/comment

What problem this solves

Optimizing Claude Code usage for cost-effectiveness, context management, and multi-agent development in a professional setting without Fable access.

Summary

A multi-faceted workflow for efficient Claude Code usage, involving strategic model selection (Opus for planning, Sonnet for implementation, with adversarial review), disciplined context management, isolating agents with git worktrees, and leveraging IDE-integrated MCP for enhanced code insights, all while monitoring token usage to stay within budget.

Why it is useful

This workflow provides practical, validated strategies for optimizing Claude Code usage in a professional environment, particularly for users without Fable access. It addresses key challenges like cost management, context bloat, and multi-agent coordination, offering concrete steps and tool recommendations that can significantly improve efficiency and effectiveness.

Workflow

1. Use Claude Opus for initial planning and requirement generation.
2. Delegate implementation tasks to Claude Sonnet agents.
3. (Optional) Have Opus perform an adversarial review of Sonnet's output for quality assurance.
4. Keep conversations short and focused, typically one user story/issue per conversation.
5. Monitor context usage; consider compacting context if it exceeds 30% and the conversation is ongoing.
6. If running multiple agents for different tasks, assign each agent its own git worktree to prevent collision of changes.
7. Utilize a JetBrains IDE with an integrated MCP server to allow Claude to leverage IDE index and code insights.
8. Diligently monitor token usage and delegate tasks appropriately to manage costs.
9. Perform trivial tasks (e.g., small code refactors, copy updates) manually instead of using an agent.
10. (For personal projects) Use multiple models to research the same task with the same prompt, then have a single model review and consolidate the outputs into a single report.

Tools / artifacts

• Claude Opus
• Claude Sonnet
• opusplan model (if available)
• /plan command
• git worktree
• JetBrains IDE
• MCP server (integrated into IDE)
• Cursor (for automated PR reviews)

Validation signals

• Author's work experience and consistent usage within a professional setting.
• Successfully operates within a $350/month budget, using 65-80% of it with this approach.
• Statement: 'If Opus has good requirements and the plan is thorough, the Sonnet agents work just fine.'
• Mentions Cursor for automated PR reviews as an external validation of quality control.

Limitations

• The 'opusplan' model might not be universally available or clearly defined for all users.
• The multi-model research strategy is less detailed for coding tasks compared to other parts of the workflow.
• Some advice is more general best practice than a strict step-by-step workflow, requiring user discretion.

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This post was generated automatically from the workflow library database.