Migration Guide: Opus 4.5 → 4.6

If you have existing code built on Opus 4.5 or Sonnet, this lesson covers every breaking change and provides tested migration patterns. Skip this lesson if you are starting fresh.

Breaking Changes Summary

Feature	Opus 4.5	Opus 4.6	Action Required
Model identifier	claude-opus-4-5-20250101	claude-opus-4-6-20260205	Update all references
Assistant prefilling	Supported	Removed	Refactor to system prompts
Thinking mode	type: "enabled"	type: "adaptive"	Update thinking config
Structured output	Loose JSON	Strict schema validation	Add output schemas
Max context	200K tokens	1M tokens (beta)	Test with larger contexts

Change 1: Model Identifier

# ❌ Old
model="claude-opus-4-5-20250101"

# ✅ New
model="claude-opus-4-6-20260205"

Best practice — use environment variables so you can switch without code changes:

import os
model = os.environ.get("CLAUDE_MODEL", "claude-opus-4-6-20260205")

Change 2: Assistant Prefilling Removed

Opus 4.5 allowed you to pre-fill the assistant response to steer output format:

# ❌ No longer works in Opus 4.6
messages=[
    {"role": "user", "content": "Analyze this code"},
    {"role": "assistant", "content": '{"bugs": ['}  # Prefilling removed
]

Migration pattern: Move format instructions to the system prompt:

# ✅ Correct approach for Opus 4.6
response = client.messages.create(
    model="claude-opus-4-6-20260205",
    system="Always respond with valid JSON matching this schema: "
           '{"bugs": [{"line": int, "description": str}]}',
    messages=[{"role": "user", "content": "Analyze this code"}]
)

Change 3: Adaptive Thinking Mode

# ❌ Old (Opus 4.5)
thinking={"type": "enabled", "budget_tokens": 10000}

# ✅ New (Opus 4.6) — Let the model choose effort level
thinking={"type": "adaptive"}

# ✅ New — Or specify effort level explicitly
thinking={"type": "adaptive", "effort": "deep"}  # quick|standard|deep|maximum

Change 4: Structured Output Requirements

Opus 4.6 is stricter about output format compliance. If you request JSON, the model will produce valid JSON — but it also validates against schemas more strictly.

# ✅ Provide clear schema in system prompt
system_prompt = """Respond with JSON matching this TypeScript interface:
interface AnalysisResult {
  findings: Array<{
    severity: "critical" | "high" | "medium" | "low";
    description: string;
    line_number: number;
    suggested_fix: string;
  }>;
  summary: string;
  confidence: number; // 0.0-1.0
}"""

Migration Checklist

# migration_check.py — Run this against your codebase
import re
import glob

issues = []

for filepath in glob.glob("**/*.py", recursive=True):
    with open(filepath) as f:
        content = f.read()

    # Check for old model identifier
    if "claude-opus-4-5" in content:
        issues.append(f"{filepath}: Old model identifier found")

    # Check for assistant prefilling
    if re.search(r'"role":\s*"assistant".*content.*\{', content):
        issues.append(f"{filepath}: Possible assistant prefilling")

    # Check for old thinking config
    if '"type": "enabled"' in content and "thinking" in content:
        issues.append(f"{filepath}: Old thinking mode config")

for issue in issues:
    print(f"⚠️  {issue}")

if not issues:
    print("✅ No migration issues found")

Rollback Strategy

Always deploy with a rollback plan:

import os

MODELS = {
    "primary": "claude-opus-4-6-20260205",
    "fallback": "claude-opus-4-5-20250101",
}

def get_model():
    if os.environ.get("USE_FALLBACK_MODEL"):
        return MODELS["fallback"]
    return MODELS["primary"]

Test thoroughly before removing the fallback. In the next module, we explore the million-token context window — the capability that changes everything.