Thinking about trying Anthropic’s Claude Sonnet 4.5? Here’s a pragmatic, 2–4 hour test plan and migration checklist to validate quality, reliability, and cost—before you ship.
Why this matters
Model upgrades can boost reasoning and tooling—but they can also break structured outputs, change costs, or shift behavior. Treat Sonnet 4.5 like any major dependency update: measure first, then roll out.
Fast evaluation plan (2–4 hours)
- Define success upfront: accuracy on 10–20 golden tasks, strict JSON validity, latency P95, and cost per task.
- Freeze prompts and tools: lock your system prompts, tool specs, and RAG settings so results are comparable.
- Run A/B: current model vs Sonnet 4.5. Capture outputs, token usage, and response times for each task.
- Validate structure: require “JSON only” responses and auto-check against a schema. Fail on any invalid output.
- Test tool use: evaluate function selection, argument accuracy, and multi-step tool chains on 5 complex tasks.
- Probe grounding: with RAG, score citation presence, faithfulness to provided docs, and abstention on missing info.
- Red-team quickly: attempt jailbreaks, prompt injection, PII leakage, and brand-unsafe content; log mitigations.
Sample prompts to include
- Strict JSON: “Respond with valid JSON only matching this schema … No extra text.”
- Tool chain: “If step 1 fails, retry with tool B; else continue to step 2 and summarize results.”
- RAG grounding: “Answer only from the provided context. If missing, say ‘Insufficient context.’ Include citations.”
- Safety: “User requests off-policy content. Provide allowed alternative and explain safer approach.”
- Code review: “Identify bugs, propose patch, and output unified diff only.”
Production migration checklist
- Pin model ID and version; track any silent updates in release notes.
- Guardrails: schema validators, content filters, and refusal handling in your middleware.
- Streaming + timeouts: set sensible client timeouts; surface partials only when safe.
- Fallbacks: define per-endpoint fallback model and a cached response policy.
- Cost controls: per-request token caps, batch ceilings, and alerts on spend anomalies.
- Observability: log prompts, outputs, tokens, latency P50/P95, and error codes with trace IDs.
- PII and data policy: disable training usage if required; scrub logs; minimize data retention.
- Canary rollout: 5–10% traffic, compare KPIs, then ramp.
KPIs to track
- Task success rate on golden set (pass/fail with clear rubrics)
- Structured output validity (JSON/schema conformance rate)
- Latency P95 and timeout rate (by endpoint)
- Cost per successful task (input + output tokens)
- Safety events per 1,000 requests (blocked, flagged, escalated)
Resources
- Anthropic announcement: Claude Sonnet 4.5
- Anthropic docs: API and model guide
Also Read: How to choose the right LLM for production
Takeaway
Treat Sonnet 4.5 as a surgical upgrade: lock a golden set, measure outputs and costs, enforce schemas, then canary. If it wins on your KPIs, scale with confidence.
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