All questions

Explain why a context window is not a word count, why a model does not remember earlier chats on its own, and why temperature zero does not make an answer true.

Work out why a model's answer looks cut off or incomplete by reading termination metadata, token budgets, and stream evidence before changing any setting.

Compare sending whole documents in a large context window with retrieving a few passages for two features of one product, using window fit, cost with prefix caching, latency, access, and a sliced pilot, and say what would change each choice.

Recommend a model or routing policy from measured quality, cost, and latency, say what evidence is still missing, and revise the decision when the traffic mix changes.

Rewrite a vague request into a testable extraction prompt with category rules, a missing-data policy, consistent examples, and a JSON output contract, then explain why parseable JSON can still be wrong.

Write a pure function that accepts a model's JSON review summary or returns every contract violation as a stable error code, predict its result for eight replies, and say what a valid summary still cannot prove.

Implement a dependency-free validator for a ticket contract, classify each fixture failure by layer, and design a two-attempt recovery that never commits invalid output.

Upgrade a ticket classifier to a versioned contract with multiple IDs, evidence, and review states, keep two v1-only consumers working, and decide from evaluation data whether a candidate prompt should ship.

Explain how embeddings and exact-term matching find candidates for a query, and why the top result is a ranking signal rather than a verified answer.

Rank four help articles by shared words and by cosine similarity, score both rankings against labels, and explain a dense miss and an accidental lexical success.

Design hybrid retrieval with reranking for a multi-tenant help center, choose a configuration from measured quality and latency gates, and keep access rules intact through timeouts and model migrations.

Explain how documents become evidence for a generated answer, and why an answer can be wrong even when it cites a real document.

Turn a follow-up message into a standalone retrieval query, keep access filters tied to the signed-in session on every turn, and decide which turns should not retrieve at all.

Trace a missing policy exception through ingestion, eligibility, and context packing without weakening access rules.

Design a support assistant that answers from help articles with citations the customer may see, or hands off to a human. Turn its requirements into metrics, plan its evaluation set, keep it fresh through updates and deletion, and check its token, cost, and latency budgets.

Design a private multi-tenant policy assistant whose answers and citations stay correct through asynchronous updates, retries, permission changes, and deletion.

Find why a partly failed re-embedding backfill left a help-center index missing, duplicating, and mixing vectors, then plan a repair and a cutover gate you could defend in a release review.

Follow one ticket lookup from tool declaration to answer: what the model proposes, what the application validates and executes, and what the assistant says when the result is unavailable.

Implement a get_ticket adapter that validates model-proposed arguments, takes tenant scope from trusted context, and passes a fixture table, then explain how a bounded orchestrator handles timeouts, invalid calls, and parallel lookups.

Extend the validated ticket adapter with a paginated search_tickets tool behind a tool registry under a 3-hour cap, hand in tests and a README, then review a sample submission as the interviewer would.

Compare a fixed workflow and an agent loop for a parcel-delivery assistant's rescheduling and stuck-parcel tasks using a pilot's success, cost, and latency figures, then recommend a design per task and say what would change it.

Design an agent that closes a ticket and sends one approved closure email safely across duplicate jobs, crashes, timeouts, and concurrent workers, and say exactly what the design can and cannot guarantee.

Use a request trace to tell retrieval, context-packing, and generation failures apart, and report answer quality with a named denominator next to operational signals.

Score a six-case evaluation set with a deterministic harness, report success, coverage, and answered accuracy with named denominators, and keep missing outputs visible in the totals.

Decide whether a candidate with better aggregate success but a regressed protected slice can ship, and design a release gate with calibrated graders, traces, and stated uncertainty.

Explain why a retrieved document cannot grant itself authority, and name the controls in trusted code that still hold when the model follows an injected instruction.

Implement a context selector that enforces tenant, group, and deletion rules before ranking, then design tests proving that forbidden records and internal notes never reach the model-bound payload.

Threat-model a multi-tenant assistant that reads private documents, keeps conversation summaries, and sends approved notifications, naming where each control is enforced and what risk remains.

Explain why a slow model provider raises concurrency and retry load, using latency, throughput, rate limits, deadlines, and a bounded response strategy.

Implement a pure, deterministic retry policy with attempt limits, capped jittered backoff, retry-after, and a deadline check, then fit it into an executor that handles cancellation, partial streams, and uncertain writes.