Claude 3.7 Sonnet and Extended Thinking: When AI Reasons Before It Answers

Anthropic released Claude 3.7 Sonnet with extended thinking capabilities last month. Extended thinking means the model spends compute thinking through a problem step-by-step before giving an answer—similar to how you'd work through a difficult legal question on a yellow pad before drafting a memo.

This is genuinely useful for professional services. But it's not free, and it's not appropriate for everything.

What Extended Thinking Does

When you enable extended thinking, Claude allocates more compute to reasoning before answering. For a complex contract analysis, it might spend several seconds thinking through the implications of each clause, cross-referencing them, identifying risks, before synthesizing an answer.

The result: better answers on hard problems. More accurate reasoning. Fewer hallucinations.

The cost: it's slower and more expensive than standard inference.

What It's Good For

Complex Multi-Step Analysis A contract that references other agreements, incorporates by reference, has multiple conditional clauses. Extended thinking walks through each connection before answering.

Risk Assessment "Analyze this contract and identify all risks to our client." This requires reasoning about implications. Extended thinking helps here.

Statutory Interpretation When you're analyzing how multiple statutes interact or how a specific statute might apply to your fact pattern, extended thinking improves accuracy.

Deal Structuring Advice "What's the best way to structure this transaction given these constraints?" Extended thinking helps reason through trade-offs.

What It's Not Good For

Simple Classification or Summarization "What practice area is this matter?" or "Summarize this email." Extended thinking is overkill. Standard Sonnet is faster and cheaper.

Real-Time Applications If you need an answer in 2 seconds, extended thinking's latency (5-10+ seconds) is too slow. Use standard inference.

Routine Work Intake triage, document categorization, basic research—extended thinking doesn't add value here.

The Economics

Extended thinking costs roughly 3-5x more than standard inference (in both input and output tokens). For a complex analysis that would have taken a lawyer 2 hours, extended thinking might deliver 80% quality in 2 minutes. The ROI is huge.

For a simple task, paying 5x more for a marginally better answer doesn't make sense.

The Smart Approach Route simple work to standard Sonnet. Route complex work to Sonnet with extended thinking. Your cost and performance will be optimized.

Practical Deployment

If you're using Claude for professional services work, test extended thinking on 5-10 of your most complex analysis tasks. Measure:

• Quality of answers (vs. human review)
• Cost (time + money)
• User satisfaction

If extended thinking produces better answers, route those task types to it. For everything else, use standard Sonnet.

The Bigger Picture

Extended thinking signals that the reasoning model category (which OpenAI started with o1) is becoming mainstream. Both OpenAI and Anthropic now offer reasoning-level capability. This is healthy competition that benefits you through better models and price pressure.

By mid-2025, every major model will have some form of "deep reasoning" capability. It'll become standard. The question will shift from "should I use extended thinking?" to "what's the right reasoning level for this task?"