Domain 1: Claude Models & Capabilities

Claude Certified Architect Professional · 48 questions

An architect is designing a document analysis system that must process 150-page legal contracts (approximately 180,000 tokens) in a single pass, extracting key clauses and cross-referencing obligations across sections. Which Claude model configuration is most appropriate?
A team is building a customer-facing chatbot for a financial services firm. The system must handle 10,000 simultaneous users, respond within 500ms, and answer FAQs from a knowledge base. Cost is a primary constraint. Which model selection strategy is most architecturally sound?
An architect is evaluating Claude's vision capabilities for a medical imaging triage system that receives JPEG scans and must flag images requiring urgent radiologist review. Which statement most accurately characterizes Claude's vision capabilities and appropriate architectural constraints?
A software team is choosing between Claude 3 Haiku, Claude 3.5 Haiku, and Claude 3.5 Sonnet for a real-time code autocomplete service embedded in an IDE. The primary requirements are sub-200ms p95 latency, code correctness, and cost efficiency at high volume. Which model is the most defensible choice?
An architect is designing a research assistant that must synthesize information from 50 academic papers simultaneously, each averaging 8,000 tokens. The system must identify contradictions across papers and generate a unified literature review. What is the primary architectural consideration?
A production system uses Claude 3 Opus for complex reasoning tasks. The team wants to reduce costs by 60% without degrading output quality on their specific use case — generating structured JSON reports from unstructured sales data. Which approach should an architect recommend first?
An enterprise is building a multilingual document translation service using Claude to translate 500-word business documents between 15 language pairs. Which model capability characteristic is most important for this architectural decision?
A team is comparing Claude 4 Opus with Claude 3.5 Sonnet for a task requiring identification of flawed logical steps in graduate-level mathematical proofs. Which architectural consideration should drive model selection?
A fintech startup is building a document analysis pipeline that processes scanned bank statements and extracts structured data. Processing volume is 50,000 documents per day, and each document averages 8 pages. The team is evaluating whether to use Claude Haiku or Claude Sonnet for the vision extraction task. Accuracy testing shows Haiku achieves 94% field extraction accuracy and Sonnet achieves 97%. The downstream reconciliation system can tolerate up to 5% error rate before requiring human review. Which model selection strategy minimizes total cost while meeting accuracy requirements?
A media company runs a real-time content moderation system that evaluates user-submitted posts before publication. The system must respond within 200ms P99. Current Claude Sonnet latency for their prompt is 350ms median, 620ms P99. They are considering switching to Claude Haiku. Haiku median latency is 90ms with P99 of 180ms. Moderation accuracy drops from 96% (Sonnet) to 91% (Haiku). The false-negative rate (harmful content passing) increases from 2% to 6%. Their acceptable false-negative rate is 4%. What is the best architectural response?
An insurance company is designing a claims processing assistant that analyzes policy documents, damage photos, and adjuster notes simultaneously. A typical claim involves a 180-page policy PDF, 12 damage photos, and 8,000 words of adjuster notes. The architect must choose between (1) multiple specialized Claude instances processing each modality separately, or (2) a single multimodal Claude call with all inputs. The company prioritizes claim consistency and cross-modality reasoning. Which approach is architecturally superior and why?
A legal technology firm benchmarks Claude models for contract review. Their tests show that on standard commercial contracts under 50 pages, Claude Haiku and Claude Sonnet achieve nearly identical precision on clause extraction (within 1%). On complex M&A agreements over 200 pages with cross-references, Sonnet outperforms Haiku by 12% precision. The firm handles 10,000 contracts per month: 8,500 are standard commercial, 1,500 are complex M&A. Current spend with Sonnet on all contracts is $18,000/month. Haiku pricing is approximately one-fifth of Sonnet. What is the expected monthly cost with optimally routed model selection?
A SaaS company is migrating from Claude 3 Opus to Claude 3.5 Sonnet for their enterprise knowledge base assistant. Internal evaluations show Claude 3.5 Sonnet outperforms Claude 3 Opus on their specific tasks and is significantly cheaper. However, during shadow testing, they observe that 3.5 Sonnet occasionally produces more concise answers where Opus was more exhaustive, and enterprise customers have complained about missing detail. What is the correct architectural response before completing the migration?
A retail analytics platform processes product images to generate catalog descriptions and alt text at scale. The team is evaluating latency vs. cost for three approaches: (A) Claude Haiku with vision, (B) Claude Sonnet with vision, (C) Pre-classify images with a lightweight CNN, then route simple products to Haiku and complex lifestyle photos to Sonnet. Product mix is 70% simple product-on-white images and 30% lifestyle photography. Haiku cost is $0.25/1K images, Sonnet cost is $1.50/1K images. Which approach minimizes cost while maintaining catalog quality?
A scientific publishing platform needs to summarize research papers that frequently contain complex mathematical notation, chemical formulas, and domain-specific technical figures. The team debates whether to extract text from PDFs and send it to Claude, or to render PDF pages as images and send them to Claude's vision API. Papers average 15 pages with 8 technical figures. Which approach produces higher-quality summaries and why?
A healthcare platform architect is comparing Claude model tiers for a clinical decision support tool. The tool must process 500-page patient records (notes, labs, imaging reports) and generate differential diagnoses. Accuracy and recall of rare conditions are critical — missing a rare diagnosis has severe patient safety consequences. The platform can tolerate 3–5 second response times. Cost is secondary. Which model strategy is appropriate?
A financial services firm needs to process 10,000 legal contracts per month. Each contract is approximately 80,000 tokens. The processing involves: (1) extracting 40 specific clause types, (2) flagging regulatory non-compliance, and (3) generating a structured JSON summary. The firm's SLA requires 99.9% accuracy. Throughput is not time-critical — results are acceptable within 48 hours. The legal team reports that occasional hallucinations in clause extraction have caused $2M in downstream errors. Given these constraints, which model selection strategy is architecturally superior?
A healthcare startup is building a patient intake system where Claude must process uploaded medical images (X-rays, MRI scans, lab report photos) alongside the patient's text history — typically 15,000–25,000 tokens of clinical notes. The system must operate under HIPAA constraints with minimal latency (sub-3-second P95 response). A radiologist reviews every Claude output before any clinical decision is made. The startup has $0.02 per-interaction budget. Which model and architectural approach best satisfies all constraints simultaneously?
An enterprise deploys Claude as an internal knowledge assistant for 5,000 employees. The system must handle questions across HR policy (low stakes), IT troubleshooting (medium stakes), and financial regulatory guidance (high stakes). Average query complexity varies widely. The architecture team debates whether to use a single model tier or a dynamic routing strategy. Load testing shows 80% of queries are HR/IT, 20% are financial. The company's API spend is currently $120K/month with a single Sonnet deployment. Which routing architecture provides the best accuracy/cost tradeoff?
A media company processes video transcripts for content moderation. Transcripts average 150,000 tokens each. The moderation task requires nuanced judgment about context (a violent scene in a documentary vs. gratuitous content), cultural sensitivity across 40 languages, and legal compliance in 12 jurisdictions. Processing volume is 500 transcripts/day. The moderation team currently uses human reviewers at $18/hour taking 45 minutes per transcript. Which model architecture best handles the context length requirement while managing per-unit economics?
A defense contractor requires Claude for analyzing classified documents (operating on a private, air-gapped Claude deployment). The analysis task involves cross-referencing 180,000-token technical specifications against a 20,000-token regulatory framework document. The contractor's security team insists all analysis must happen in a single API call with no external retrieval. A junior architect proposes using Claude 3 Haiku because 'it's faster and the regulations are simple.' A senior architect disagrees. Which is the most technically sound basis for the senior architect's position?
A real-time fraud detection system uses Claude to analyze transaction patterns. The system must evaluate each transaction within 800ms end-to-end (including network round-trips). Input context per transaction is approximately 3,000 tokens including 30-day transaction history. The fraud team wants Claude to explain its reasoning for every flagged transaction. Current architecture uses Claude 3 Sonnet and achieves 1,400ms P95. Which architectural change most directly addresses the latency requirement without sacrificing explainability?
An e-commerce platform is building a visual product search system. Users upload photos of items they want to find (e.g., a photo of a lamp they saw at a friend's house). Claude must identify: (1) item category, (2) style attributes (mid-century, industrial, etc.), (3) approximate price range, and (4) 3-5 specific product recommendations from the platform's catalog. The catalog has 2 million SKUs. The team debates whether vision processing should happen in Claude or in a dedicated computer vision pipeline before Claude. Which architecture is correct?
A SaaS company is evaluating model selection for a code review assistant that processes pull requests. PRs range from 500 to 45,000 lines of diff. The assistant must: identify security vulnerabilities, suggest performance improvements, enforce style guidelines, and explain its reasoning. The company's P99 PR size is 8,000 lines. A product manager argues that Claude 3 Haiku is sufficient 'because code review is just pattern matching.' The engineering team disagrees. Which argument most precisely captures why the engineering team is correct for the P99 case?
An architect is designing a legal document analysis system that must process contracts averaging 180,000 tokens. The pipeline requires 30 sequential clauses to be cross-referenced against a regulatory database, generating detailed reasoning chains for each. The team is debating between claude-3-5-sonnet-20241022 and claude-3-opus-20240229. Latency is secondary; accuracy and completeness of reasoning is the primary requirement. Which model selection rationale is most defensible?
An architect is evaluating whether to use extended thinking for a financial modeling task where Claude must estimate a company's fair value using DCF analysis across 12 scenarios. The current non-thinking implementation produces correct formulas but makes arithmetic errors across multi-step calculations. Budget tokens for thinking are capped at 10,000. What is the most important tradeoff to communicate to stakeholders about enabling extended thinking?
A vision-enabled Claude integration must analyze diagrams embedded in PDF pages that have been rasterized to PNG at 72 DPI. During testing, Claude consistently fails to read small text labels on circuit diagrams. What is the most effective single intervention?
A developer tests both claude-3-5-haiku-20241022 and claude-3-5-sonnet-20241022 on a task that requires interpreting a 150,000-token codebase and identifying security vulnerabilities. Claude 3.5 Haiku returns results in 4 seconds; Claude 3.5 Sonnet takes 22 seconds. Both have 200K context windows. A stakeholder argues for Haiku to reduce latency. What is the architect's most important counter-consideration?
A developer notices that when using streaming with extended thinking enabled, the thinking content blocks appear before the text content blocks in the stream. The application needs to display the final answer to the user while optionally showing thinking to developers. What is the correct approach to handle thinking blocks in the stream?
A developer is processing a 50-image batch where each image is a photograph of a handwritten form. The images are sent as base64-encoded PNG in the API request. Average image size is 2MB. The team notices response latency is 45 seconds per API call for a batch of 10 images. What is the most effective optimization?
A developer is building an application that processes scanned architectural blueprints uploaded as multi-page PDFs. Pages must be analyzed for specific structural elements. The team converts each page to a separate PNG image. On complex blueprint pages, Claude accurately identifies major structural components but misses small annotation labels (font size ~6pt). What is the best solution that stays within the API's image handling constraints?
A developer is implementing an agent that uses extended thinking to solve complex math problems. The agent must expose its reasoning process to an internal audit log but must not show thinking blocks to end users. When reading the streaming response, how should the application differentiate thinking block content from final answer content?
A production customer support system processes 500,000 requests per day. Analysis shows 70% are simple FAQ lookups requiring basic comprehension, 20% involve multi-step troubleshooting requiring reasoning, and 10% involve complex escalations needing deep analysis. An architect is designing a routing layer. Which model assignment strategy best balances cost and quality?
An architect is building a document intelligence pipeline that processes mixed-content PDFs containing dense technical text, engineering diagrams, and data tables. The system must extract structured data from all three content types with high accuracy. The PDFs are converted to images before processing. Which approach yields the best extraction accuracy?
A code review system uses claude-3-5-sonnet with extended thinking enabled and a thinking budget of 800 tokens. During load testing, the team discovers that on complex pull requests, the model frequently exhausts the thinking budget before completing its reasoning, resulting in truncated analyses. What is the correct architectural response?
An AI product team is debating when to use claude-3-opus versus claude-3-5-sonnet. A senior architect is asked to define the decision criteria. Which set of criteria correctly identifies use cases that genuinely benefit from Opus over Sonnet?
A real-time voice assistant application requires responses within 800ms end-to-end (including network and TTS). The assistant handles both simple acknowledgments and complex scheduling tasks. Streaming is enabled. An architect measures that claude-3-5-sonnet averages 1200ms time-to-first-token for complex queries. What is the best architectural strategy?
A benchmarking team is evaluating whether to migrate from claude-3-sonnet to claude-3-5-sonnet for a legal document analysis system. The system extracts clause types, identifies obligations, and flags potential risks. What evaluation methodology gives the most reliable signal for this migration decision?
A medical imaging assistant uses Claude to analyze radiology reports alongside the corresponding DICOM images converted to JPEG. A radiologist notes that the model sometimes contradicts the written report when describing findings visible in the image. What is the most likely cause and correct mitigation?
A content moderation pipeline processes 2 million short social media posts per day using Claude. The posts average 50 tokens each. The system prompt is 800 tokens. An architect wants to reduce inference cost. Which optimization has the greatest leverage?
Your organization runs a production application pinned to claude-3-haiku-20240307. Anthropic announces a 6-month deprecation window for this model version. Your application processes 2 million classification requests per day with strict latency SLAs. What is the most operationally sound deprecation migration strategy?
An architect is designing a real-time content moderation pipeline that must classify 50,000 short social media posts per hour into 12 toxicity categories. The system has a budget constraint of $0.50 per 1,000 posts and a latency requirement of under 500ms per classification. Which deployment pattern best fits these constraints?
You are building a document analysis system using Claude's vision API. Your pipeline receives PDFs converted to images, with individual pages ranging from 800x600 to 4000x3000 pixels. Some pages contain dense technical tables. What constraint must the architect account for when designing the image preprocessing step?
An architect needs Claude to reason through a complex multi-step financial analysis, then call a getmarketdata tool with specific parameters derived from that reasoning, incorporate the tool result, and reason further before producing a final report. The team is evaluating extended thinking for this use case. What is the correct design for extended thinking with interleaved tool use?
A model versioning strategy at your organization pins Claude to claude-3-5-sonnet-20241022 across 12 production services. The team proposes moving all services to always track claude-3-5-sonnet-latest. An architect raises an objection. What is the most technically valid objection to the latest alias strategy?
You are building a vision-based invoice processing system. The pipeline receives scanned invoices as images. Testing reveals that invoices photographed under poor lighting conditions (high contrast shadows, overexposed regions) result in significantly lower extraction accuracy. Before sending images to Claude's vision API, what preprocessing should the architect implement?
A team is evaluating extended thinking for a supply chain optimization problem that requires Claude to evaluate 50+ variables across 12 supplier constraints. They are debating what budgettokens value to set. What principle should guide the thinking budget calibration?
A team is migrating from claude-3-sonnet-20240229 to claude-3-5-sonnet-20241022. During regression testing, they discover that 8% of previously passing test cases now produce different outputs — not wrong outputs, just different phrasing or structure. The PM wants to declare the migration failed due to behavioral change. How should the architect respond?