Anthropic: Claude 3.5 Haiku

Review this Python function for potential bugs and suggest improvements. Focus on edge cases and performance: ```python def merge_sorted_lists(a, b): result = [] i = j = 0 while i < len(a) and j < len(b): if a[i] < b[j]: result.append(a[i]) i += 1 else: result.append(b[j]) j += 1 return result ```

The function has a critical bug: it drops remaining elements when one list is exhausted. After the while loop exits, elements from whichever list still has items are never appended. Add `result.extend(a[i:])` and `result.extend(b[j:])` after the loop. For performance, consider that repeated `len()` calls are unnecessary—cache them upfront. The comparison logic is sound, but if lists contain non-comparable types, you'll get a runtime error. Consider adding type hints and validation if this runs in production. The algorithm is O(n+m) which is optimal for this problem.

Haiku excels at practical code review with the 200K context window allowing full codebases to be analyzed. This example shows its ability to identify logic errors and suggest concrete fixes. The response is direct and actionable, though it lacks the deeper architectural reasoning of larger Claude models—trade speed and cost for thoroughness.

I have a screenshot of an error message from our deployment pipeline. Can you identify what went wrong and suggest next debugging steps? [Image shows a CI/CD log with a Node.js build failure and dependency resolution errors]

The build is failing because `package-lock.json` references `node-sass@4.14.1` which doesn't have prebuilt binaries for Node 18. The error 'node-sass@4.14.1 postinstall: node scripts/build.js' indicates it's trying to compile from source but lacks Python 2.7. Two fixes: migrate to `sass` (the pure-JS Dart Sass implementation) by running `npm uninstall node-sass && npm install sass`, then update any `require('node-sass')` imports. Or downgrade to Node 16 in your CI config, though that's a temporary workaround. Check if other dependencies also assume older Node versions.

Haiku's vision capability handles technical screenshots effectively at $0.80/Mtok input—substantially cheaper than analyzing images with larger models. It correctly interprets log output and suggests practical remediation. The 200K context means you can paste entire build logs alongside the image without truncation, though complex visual debugging still benefits from Opus-level reasoning.

Summarize this 15-page legal contract and flag any clauses that deviate from standard SaaS terms. Focus on liability caps, data ownership, and termination rights.

**Key Terms:** Standard 12-month initial term with auto-renewal. Liability capped at 12 months of fees paid (typical). **Red Flags:** Section 8.3 grants the vendor perpetual license to your data for 'service improvement and analytics'—this is broader than standard anonymized telemetry clauses. Section 11.2 requires 90-day written termination notice even for cause, and Section 11.4 mandates you delete all data within 48 hours of termination (unusually aggressive). Data ownership reverts to you, but the perpetual license survives termination. **Recommendation:** Negotiate Section 8.3 to limit data use to anonymized aggregates only, and extend the 48-hour deletion window to 30 days.

The 200K token window makes Haiku viable for long-document analysis at a fraction of Opus pricing ($0.80 vs $15 input per Mtok). This example demonstrates competent contract review, catching non-standard clauses. However, for high-stakes legal work, the lack of public benchmark data means you're trading cost savings for less certainty about accuracy on complex reasoning tasks.

When Haiku's speed and cost beat GPT-4o for ticket routing

A 12-person SaaS support team handling 800+ tickets daily needs instant classification without burning budget. Claude 3.5 Haiku runs at $0.80/$4.00 per Mtok—roughly 5x cheaper than GPT-4o on input, 3x on output—and returns answers in under a second for typical 300-token tickets. The 200k context window means you can dump the last 50 customer interactions plus your entire help center into every call without chunking. Vision support lets you route screenshot-heavy bug reports without a separate OCR step. If your tickets average under 1,000 tokens and you're processing more than 500/day, Haiku pays for itself in week one. For complex escalations requiring deep reasoning, keep GPT-4o in the second tier; for everything else, route through Haiku and watch your API bill drop 60%.

Why Haiku wins on overnight report generation for compliance teams

A 4-person legal ops team needs to summarize 200 contracts every Monday morning before the weekly review call. Claude 3.5 Haiku's 200k token window handles most commercial agreements in a single pass—no recursive chunking, no context-stitching errors. At $0.80 input per Mtok, processing 200 documents averaging 8k tokens costs under $1.30 in API fees. The image modality means scanned PDFs with tables and signatures go straight in without preprocessing. Haiku won't match Opus on edge-case clause interpretation, but for extracting standard terms (parties, dates, renewal clauses, liability caps) it's 90% accurate at 20% the cost. If you're running this workflow nightly and your documents are under 180k tokens, Haiku is the only model where the math works at scale.

When sub-second latency matters more than benchmark scores

A 3-person community platform sees 2,000 user posts per hour and needs moderation decisions before content goes live. Claude 3.5 Haiku returns verdicts in 400-600ms for typical 150-word posts—fast enough to feel instant to users, cheap enough to run on every submission. At $0.80/$4.00 per Mtok, moderating 50k posts monthly costs around $15 in API fees versus $75+ for GPT-4 class models. The vision modality catches meme-based harassment that text-only models miss. Haiku won't outperform o1 on ambiguous satire or multilingual slang, but for clear-cut violations (spam, explicit content, doxxing) it's 95%+ accurate. If your moderation queue is under 100k posts/month and false negatives get caught in user reports, Haiku keeps your feed clean without requiring a separate budget line.