Model Selection and Optimization

CCDV-F · 34 questions

• A city FAQ team must size a large ordinance corpus for Claude. Which LLM fundamental should guide the plan?
• A 311 lead notices the same complaint summary wording differs across identical retries. What LLM behavior explains this?
• A transit planner needs deeper deliberation for complex multi-leg detour narratives. Which model capability choice fits?
• A housing bot answers simple office-hours questions and nuanced eligibility edge cases. How should prompting intensity differ?
• A water utility must set Claude effort for routine meter FAQs versus regulatory interpretation drafts. What matching rule fits?
• Teachers expect Claude to guarantee identical lesson plans on every regenerate. What should the school district explain?
• A parks app needs quick trail-status rewrites under heavy weekend load. Which latency-oriented choice fits?
• A court clerk sees docket summary wording change across identical Claude requests. What concept explains the change?
• A county open-data agent faces queries that range from trivial field lookups to multi-dataset joins. Which thinking approach fits?
• A public-health team must call Claude on long encounter notes without overflowing capacity. What budgeting step fits?
• A library FAQ must steer Claude toward a preferred citation style. Which prompting technique fits?
• A city backend must call Claude Messages reliably from production services. Which technical approach fits?
• A 311 streaming UI must show Claude tokens as they arrive for resident chat. Which client pattern fits?
• A transit service must authenticate Claude calls without hard-coding credentials. What practice fits?
• A water SCADA historian bridge must send tool arguments through the Claude SDK. What serialization step fits?
• A housing microservice receives Claude SDK failures that must surface cleanly in the case UI. What mapping practice fits?
• A school district needs multiple campus apps to share consistent Claude client behavior. Which SDK design fits?
• A court integration must summarize long filings without blocking clerk workstations. Which SDK usage fits?
• A parks mobile app must send queued Claude requests after trail crews regain signal. Which client pattern fits?
• A county GIS tool must call Claude-related REST endpoints securely from the field. What validation step fits?
• A public-health Python service must keep Claude SDK behavior reproducible across clinic deploys. Which practice fits?
• A library catalog agent receives huge tool result sets that must feed Claude carefully. Which engineering practice fits?
• A municipal finance bot must keep Claude client waits aligned with gateway SLOs. What configuration fits?
• A city routes high-volume 311 intent labels and nuanced ordinance drafts to Claude. Which model split fits?
• A transit cost review evaluates Claude for simple stop-code lookups that Haiku already meets. What decision fits?
• A housing team sees eligibility edge cases shift after a Claude model release. What response fits?
• A court summarizer must compare Claude models for adaptive thinking support. What selection check fits?
• A water utility drafts regulatory nuance where quality outweighs per-call cost. Which model tradeoff fits?
• A county FinOps dashboard must attribute Claude spend across departments. Which practice fits?
• A 311 bot reuses a large static policy block on every Claude call. Which cost optimization fits?
• A transit analytics job must avoid runaway overnight Claude spend on long reports. What budgeting technique fits?
• A library runs multiple Claude skills that share a common catalog ontology preamble. Which caching approach fits?
• A school district must control cost spikes on student homework helpers. Which output control fits?
• A housing authority must estimate Claude spend under projected case volume before go-live. What planning step fits?