Route by model strengths, not just price — the task-splitting pattern that maximizes output

Your coding agent is using the wrong model for half its work.

Most people route tasks by cost: GPT-4 for the hard stuff, GPT-3.5 for the cheap stuff. That's backwards. Route by what each model is actually good at, and you'll ship faster and spend less.

The pattern that changes everything:

Claude Sonnet gets the architecture and planning work. It thinks through edge cases, writes comprehensive specs, and catches integration issues before they become problems. It's methodical.

GPT-4 gets the implementation sprints. It moves fast, writes working code quickly, and doesn't get stuck in analysis paralysis. It ships.

Here's the routing config I use:

CLAUDE_TASKS = [
  "architecture_review",
  "spec_writing", 
  "integration_planning",
  "error_analysis",
  "code_review"
]

GPT4_TASKS = [
  "feature_implementation",
  "bug_fixes",
  "refactoring",
  "testing",
  "documentation"
]

The difference is dramatic. Claude will spend 10 minutes thinking through a database schema and save you 3 hours of migration headaches. GPT-4 will bang out that CRUD API in 15 minutes without overthinking the abstractions.

The handoff protocol that makes it work:

Start every coding session with Claude doing a 5-minute architecture pass. Let it write the spec, identify the integration points, and flag potential issues. Then hand the implementation to GPT-4 with clear acceptance criteria.

When GPT-4 hits a wall or starts producing inconsistent results, route back to Claude for analysis. When Claude starts over-engineering, route back to GPT-4 for execution.

Real example: I needed to build a webhook processor. Claude spent 8 minutes designing the retry logic, error handling, and database schema. GPT-4 implemented it in 20 minutes. Total cost: $2.40. Total time: 28 minutes. Zero bugs in production.

Compare that to letting GPT-4 do everything: 45 minutes of back-and-forth, two failed approaches, and a race condition that took a day to debug. Or letting Claude do everything: perfect architecture, but 90 minutes to implement something that should take 20.

The routing triggers I actually use:

• Route to Claude when: You're starting a new feature, debugging something weird, or the current approach isn't working
• Route to GPT-4 when: You have clear requirements, need to implement something straightforward, or Claude is overthinking
• Route to both when: You need a second opinion on architecture decisions

The key insight: Claude thinks like a staff engineer. GPT-4 thinks like a senior developer. Use them accordingly.

Most teams waste months figuring out these model personalities through trial and error. The smart ones start with proven patterns and routing logic that already works.