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Enhancing Workflow Efficiency with Claude Code and Haiku

Utilizing Haiku for subagents has improved my workflow, and I'm now exploring the jev-router in Claude Code for better efficiency.

Time saved
0h / week
Setup time
Not stated
Running cost
Not stated
Cost range
Free

The problem it solves

Managing workflows can often be cumbersome, especially when trying to optimize for efficiency. Traditional models may not always yield the desired results, leading to a need for innovative solutions.

How it flows
  1. Setup Haiku
  2. Implement Claude Code
  3. Explore jev-router
  4. Evaluate Efficiency

Step-by-step setup

  1. Configure Haiku for Subagents

    Set up Haiku in your settings to enhance the functionality of subagents, ensuring they operate smoothly within your workflow.

  2. Transition to Claude Code

    Shift focus from traditional workflow models to utilizing Claude Code, particularly the jev-router, to streamline processes.

  3. Assess Workflow Efficiency

    After implementing the new tools, evaluate the overall efficiency of your workflow and make adjustments as necessary.

Coding · Advanced
  1. Write migration plan
  2. Agent edits in batches
  3. Tests per batch

Ship a 40-file refactor with a coding agent

Plan, execute and review a cross-cutting refactor in small batches, with Claude Code making the edits and GitHub Copilot reviewing each PR.

Claude Code · GitHub Copilot
Coding · Advanced
  1. Run coverage
  2. Pick 3 riskiest files
  3. Write + run tests

Generate missing unit tests for untested modules

Claude Code reads your coverage report, picks the riskiest untested modules and writes unit tests that pass, one small PR at a time.

Claude Code · GitHub Copilot · Slack
Coding · Intermediate
  1. PR opened
  2. Copilot inline review
  3. Claude risk summary

Automated first-pass review on every pull request

Copilot and Claude review each PR for bugs, missing tests and risky changes before a human looks, so reviewers can focus on design.

GitHub Copilot · Claude · Slack