Page 3 of 8~112 min topic

Cost optimization lab

Implement the happy path

One clean transaction through **POST /v1/answer** must match the oracle: replay day shows −32% $ with groundedness drop ≤ 0.01 vs all-frontier baseline.

~14 min this pageHappy path

1Learn the idea

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Order the successful transaction

Code the narrow path that serves finance partner capping July LLM spend at $12k: accept → authorize/normalize → call dependency → validate → record. Keep stages named so a trace can show which boundary passed. Success must emit evidence useful to usd_per_successful_answer and groundedness, not only a 200 with prose. Predict the observable for POST /v1/answer before running: replay day shows −32% $ with groundedness drop ≤ 0.01 vs all-frontier baseline.

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Run with fakes first

Drive the path with recording fakes or local stubs. Assert call order and arguments. Idempotency keys or stable ids should keep retries from duplicating costly work where the product requires it. Product under test remains token+router cost controller for mixed FAQ vs complex research traffic — resist adding unrelated features mid-path.

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Implementation artifact

decision = route(question)
assert decision.class_ == "faq" and decision.model == "mini"

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Compare prediction to result

For Cost optimization lab, paste the CLI/HTTP transcript beside your prediction for POST /v1/answer. If the oracle is unmet (replay day shows −32% $ with groundedness drop ≤ 0.01 vs all-frontier baseline), stop and debug this page; do not compensate with prompt folktales. Re-run once after a clean process start to catch hidden global state that would invalidate COST-ROUTER-MISCLASS-14.

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Stage depth

Performance sketch: measure local p95 for the fake-backed path so later regressions are obvious. Keep concurrency modest until failure-handling proves limits. Log a single structured event per success with request id, revision, and the evidence field behind usd_per_successful_answer and groundedness. Avoid hidden global caches in the happy path unless the lab is about caching — and even then key by tenant. If the path calls a model, pin model id in config and echo it in the response for auditability. Remember finance partner capping July LLM spend at $12k experiences wall-clock time, not your debugger’s single-step comfort.

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Field notes for `cost-optimization-lab` / `happy-path`

Prefer explicit function names over a single god-object handleRequest. Thread a correlation id from ingress to the last log line. When streaming, define what partial failure means before coding. Snapshot one successful response body in fixtures after redaction. If the path writes to a queue, assert message attributes in the fake. Stop adding retries on this page; that is the next concern. In this chapter the product is token+router cost controller for mixed FAQ vs complex research traffic, the human stakeholder is finance partner capping July LLM spend at $12k, and the incident id you design against is COST-ROUTER-MISCLASS-14. Re-state the oracle in your notes — replay day shows −32% $ with groundedness drop ≤ 0.01 vs all-frontier baseline — and keep the invariant visible: simple FAQs route to mini model; monthly forecast alerts at 80% budget. Track usd_per_successful_answer and groundedness as the scoreboard. Surface under change control: POST /v1/answer. If you only have forty minutes, finish the fixture for router sends long research prompts to mini — quality collapses, retries inflate spend before polishing UI. Promotion language stays ternary: promote, hold, or roll back based on evidence, not hope.

Go deeper

Before you start

Why this matters

Without calling production, order the steps a single success takes for finance partner capping July LLM spend at $12k. Circle the first irreversible side effect. Your prediction should mention POST /v1/answer and the evidence field that proves replay day shows −32% $ with groundedness drop ≤ 0.01 vs all-frontier baseline.

In the wild

See how this idea shows up as a product and a company — then come back to the lesson. Skills transfer across vendors.

Check your understanding

Page assessment

Answer from memory. Completion is saved from this evidence, not from opening the next page.

1. Is call order asserted, not assumed?
2. Does success evidence support usd_per_successful_answer and groundedness?
3. Did you compare prediction vs transcript?

All responses are required.