Assemble at scale: build Claude into your product

You will be able to

• Explain how your app talks to Claude: your server, a key, a request, a response, your checks
• Set up the Claude Console safely: spend limit first, a key per environment, the key in .env
• Describe a Messages API request and response in plain English, including token usage
• Ask Claude for structured output, validate it in code, and say when tool use fits
• Build the AI slice behind a feature flag, with tests that use a fake Claude response

OUTPUT · AI slice working on staging behind a feature flag, with tests

You will be able to

• Run an eval set end to end and state the score with its base, against a threshold set in advance
• Choose a grader for each check: exact code, Claude with a written rubric, or a person
• Compare two prompts (or two model tiers) on score, cost and speed from real usage data
• Calculate cost per user per month and name the levers that would lower it
• Add timeouts, retries with back-off, rate-limit handling, a fallback and safe logging

OUTPUT · Eval harness + results + cost per user + reliability checklist in product/evals/