DeepSeek V4 Prompt Generator

I'm sharing the complete source of a Python/FastAPI backend (approx. 25,000 lines across 8 modules). Perform a senior security engineer-level audit: 1. CRITICAL VULNERABILITIES — every instance of SQL injection, path traversal, SSRF, insecure deserialization, or auth bypass, with file paths and line references 2. AUTHENTICATION & AUTHORIZATION — audit every endpoint for missing or bypassable auth checks; map which roles can access what 3. SECRETS & CONFIGURATION — hardcoded credentials, weak defaults, missing rate limits, permissive CORS 4. DEPENDENCY RISK — flag every import with known CVEs or unmaintained status 5. REMEDIATION PLAN — prioritized fixes (P0/P1/P2) with specific code patches for each P0 item Use <reasoning> tags to show your analysis chain before each finding. Output format: structured security report. [Paste codebase]

Prove the following theorem rigorously, showing every logical step: Theorem: For any continuous function f: [0,1] → ℝ satisfying ∫₀¹ f(x)xⁿ dx = 0 for all non-negative integers n, f must be identically zero on [0,1]. Requirements: - State all axioms and theorems you invoke (Stone-Weierstrass, Weierstrass approximation, etc.) - Show the proof in two different ways: (a) via polynomial density, (b) via the uniqueness theorem for moments - After each proof, explain where the argument would break if f were only in L² instead of continuous - Use <thinking> tags for your reasoning chain before presenting each formal step Audience: graduate-level mathematics student.

I'm providing 10 peer-reviewed papers on the effects of large language models on student writing quality in higher education (published 2023–2026). Synthesize them as a systematic meta-analysis: 1. METHODOLOGY TABLE — for each paper: sample size, study design, LLM used, outcome measure, effect size, limitations 2. CONSENSUS FINDINGS — what do ≥7 of 10 papers agree on? 3. CONTRADICTIONS — where do papers directly disagree, and what methodological differences explain it? 4. EFFECT SIZE SYNTHESIS — weighted average effect across comparable studies with heterogeneity assessment 5. RESEARCH GAPS — the 3 most significant questions this body of work has not addressed 6. POLICY IMPLICATIONS — what a university provost should do based on this evidence Use XML tags to organize each section. [Paste paper texts]

Design a complete system architecture for a real-time collaborative document editor (like Google Docs) that must support: - 50M monthly active users, up to 500 concurrent editors per document - Sub-100ms latency for character-level edits - Offline editing with automatic conflict resolution - Version history with instant rollback to any point - End-to-end encryption for enterprise tier Deliver: 1. HIGH-LEVEL ARCHITECTURE DIAGRAM (describe as structured text) 2. CRDT vs OT ANALYSIS — which approach and why, with tradeoff matrix 3. DATA MODEL — schema for documents, operations, version trees, user presence 4. CONSISTENCY MODEL — exactly how concurrent edits merge, with example conflict scenarios 5. SCALING STRATEGY — how the system handles going from 1K to 50M users 6. FAILURE MODES — what happens when each component fails, and the recovery path 7. COST ESTIMATE — approximate monthly infrastructure cost at 50M MAU scale Show your reasoning for each major decision.

Design a production-grade data pipeline for a fintech company processing 2.3M transactions per day from 14 payment processors with different schemas, currencies, and settlement windows. Requirements: - Real-time fraud scoring (p99 < 200ms from ingestion to score) - Daily reconciliation against bank statements with automatic discrepancy detection - Regulatory reporting (SOX, PCI-DSS compliant audit trails) - Schema evolution handling without downtime Deliver: 1. PIPELINE ARCHITECTURE — ingestion → transformation → storage → serving, with technology choices justified 2. SCHEMA REGISTRY — how you handle 14 different input schemas converging to a canonical model 3. EXACTLY-ONCE SEMANTICS — how you guarantee no duplicate or lost transactions 4. MONITORING & ALERTING — what metrics you track, what thresholds trigger alerts, what the on-call runbook looks like 5. DISASTER RECOVERY — RPO/RTO targets and the specific mechanism for each 6. COST MODEL — estimated monthly spend broken down by component

Analyze the following proposed state legislation through a constitutional law lens. The bill would require all social media platforms with >1M users to verify user age via government-issued ID and prohibit accounts for users under 16. Deliver a complete legal analysis: 1. FIRST AMENDMENT ANALYSIS — does mandatory ID verification constitute a prior restraint on speech? Analyze under strict scrutiny, citing Reno v. ACLU, Packingham v. North Carolina, and NetChoice v. Paxton 2. FOURTH AMENDMENT IMPLICATIONS — does mandatory ID collection constitute an unreasonable search? Apply Carpenter v. United States framework 3. EQUAL PROTECTION — does the age threshold survive rational basis review? Are there disparate impact concerns for populations without government ID? 4. PREEMPTION — does Section 230 or COPPA preempt this state law? 5. COMPARATIVE ANALYSIS — how similar laws have fared in EU (Digital Services Act), Australia (Online Safety Act), and other US states 6. RECOMMENDED AMENDMENTS — 3 specific changes that would improve the bill's constitutional survivability Cite specific cases and statutory provisions throughout.

Implement a complete real-time notification system for a Next.js 15 + PostgreSQL + Redis application. The system must support: - Push notifications (web + mobile via FCM) - In-app notification center with read/unread state - Notification preferences per user per category - Batch digest emails (configurable: real-time, hourly, daily) - Rate limiting to prevent notification fatigue Deliver: 1. DATABASE SCHEMA — PostgreSQL tables with indexes, constraints, and migration SQL 2. BACKEND API — complete TypeScript code for the notification service (create, read, mark-read, preferences CRUD) 3. WEBSOCKET LAYER — Redis pub/sub integration for real-time delivery 4. FRONTEND COMPONENT — React notification bell + dropdown with optimistic updates 5. WORKER — background job for digest batching with idempotency guarantees 6. TESTS — unit tests for the service layer and integration tests for the API All code must be production-ready — proper error handling, types, and edge cases.

Build a comprehensive macroeconomic analysis for a sovereign wealth fund's Q3 2026 investment committee meeting. Focus on the intersection of three converging trends: AI-driven productivity gains, deglobalization of semiconductor supply chains, and central bank digital currency adoption. Deliver: 1. MACRO FRAMEWORK — causal chain from each trend to GDP growth, inflation, and employment across US, EU, China, and emerging markets 2. SCENARIO MATRIX — 4 scenarios based on the two highest-uncertainty drivers; 500-word narrative for each 3. ASSET CLASS IMPLICATIONS — for each scenario, expected returns for equities, fixed income, real assets, and alternatives 4. PORTFOLIO POSITIONING — recommended allocation shifts vs current benchmark (60/40), with sizing rationale 5. RISK REGISTER — tail risks not captured in the scenarios, with hedging strategies 6. LEADING INDICATORS — 5 measurable signals that would tell you which scenario is unfolding, checked monthly All analysis must be internally consistent. Show your reasoning chain for each causal link.

Design an algorithm for the following problem and prove its correctness: Problem: Given a weighted directed graph G = (V, E) with potentially negative edge weights (but no negative cycles), and a set S ⊆ V of 'special' vertices, find for every vertex v the shortest path from v to its nearest special vertex. Deliver: 1. ALGORITHM DESIGN — complete pseudocode with time complexity analysis 2. CORRECTNESS PROOF — formal proof by induction or loop invariant that the algorithm produces correct shortest paths 3. COMPLEXITY ANALYSIS — tight bounds on time and space complexity; compare against naive approach 4. OPTIMIZATIONS — how to handle the case where |S| << |V| more efficiently; discuss Johnson's algorithm vs multi-source Bellman-Ford 5. IMPLEMENTATION — complete Python implementation with type hints 6. TEST CASES — 5 edge cases including: disconnected components, all vertices are special, single special vertex, graph with zero-weight cycles Use <thinking> tags for your reasoning before each major design decision.

Write a 4,000-word investigative journalism piece in the style of ProPublica's long-form reporting. Subject: the hidden economics of AI training data — how a network of content farms in Southeast Asia produces synthetic 'human-written' text specifically to be scraped by AI training pipelines, creating a feedback loop where AI models train on AI-generated content disguised as human work. Requirements: - Open with a scene, not a thesis statement - At least 4 distinct sources: a content farm worker, a platform executive, an AI researcher studying data contamination, and a policy advocate - Each source speaks in a distinct register - Include specific (plausible) numbers: worker pay rates, volume of content, contamination percentages - A structural revelation at the 65% mark that reframes the story - No moralizing in the narrator's voice — let the facts and sources carry the weight - End with an image, not a conclusion Use [data] placeholders for any statistics you cannot verify.

Build a complete machine learning pipeline for predicting customer churn in a B2B SaaS company. The dataset has 340,000 accounts, 127 features (usage metrics, support tickets, billing events, firmographics), 8.2% base churn rate, and a 90-day prediction window. Deliver: 1. EDA PLAN — the 10 most important exploratory analyses to run first, and what you'd be looking for in each 2. FEATURE ENGINEERING — 15 derived features with business rationale for each; handle the temporal leakage risk explicitly 3. MODEL SELECTION — train and compare XGBoost, LightGBM, and a neural network; explain hyperparameter search strategy 4. CALIBRATION — ensure predicted probabilities are well-calibrated (Brier score, reliability diagram); explain why calibration matters more than AUC for this use case 5. INTERPRETABILITY — SHAP analysis at global and local level; identify the 3 most actionable features for the customer success team 6. DEPLOYMENT — MLflow registry, A/B test design, monitoring for concept drift 7. BUSINESS IMPACT — translate model performance into expected revenue saved, with explicit assumptions All code in Python with scikit-learn, XGBoost, and SHAP. Show your reasoning for every modeling decision.

I'm sharing the OpenAPI 3.1 spec for our public REST API (148 endpoints across 12 resource types). Perform a thorough API design review as a principal engineer would: 1. CONSISTENCY AUDIT — naming conventions, HTTP method usage, response envelope patterns, pagination approaches; flag every inconsistency 2. BREAKING CHANGE RISK — endpoints where the current design will force a breaking change when we need to add features we've already planned 3. SECURITY REVIEW — auth model gaps, BOLA/IDOR risks, missing rate limits, overly permissive scopes 4. PERFORMANCE CONCERNS — N+1 query patterns exposed via the API, missing caching headers, endpoints that should support partial responses 5. DEVELOPER EXPERIENCE — unclear naming, missing examples, error responses that don't help developers debug 6. VERSIONING STRATEGY — evaluate the current approach and recommend a migration path 7. PRIORITY FIXES — top 10 changes ranked by impact-to-effort ratio For each finding, provide the specific endpoint, what's wrong, and the exact fix. [Paste OpenAPI spec]

Produce a geopolitical risk assessment for a multinational corporation with manufacturing in Taiwan, Vietnam, and Mexico, R&D in the US and Germany, and primary markets in the US, EU, Japan, and India. Deliver: 1. RISK MATRIX — map all material geopolitical risks on a likelihood × impact grid (minimum 15 distinct risks) 2. SCENARIO DEEP-DIVES — for the 3 highest-severity risks, write a 500-word scenario narrative describing what unfolds over 18 months 3. SUPPLY CHAIN VULNERABILITY — for each manufacturing location, the specific disruption scenarios and estimated time-to-recovery 4. REGULATORY HORIZON — upcoming regulations in each market that could affect operations (trade, data, labor, ESG), with implementation timelines 5. COMPETITOR POSITIONING — how the top 3 competitors have structured their geographic exposure differently, and what advantages that gives them 6. MITIGATION PLAYBOOK — concrete actions for each of the top 5 risks, with cost estimates and decision triggers All analysis must be evidence-based. Cite specific events, policies, or trends that inform each risk assessment.

I'm sharing the PostgreSQL schema (42 tables), the 20 slowest queries from pg_stat_statements, and the current index configuration for a SaaS application serving 180K daily active users. The application is experiencing p99 query latency of 4.2 seconds (target: 500ms). Deliver: 1. QUERY ANALYSIS — for each of the 20 slow queries: what it does, why it's slow (EXPLAIN ANALYZE interpretation), and the specific fix 2. INDEX STRATEGY — missing indexes, redundant indexes, partial index opportunities, and covering indexes that would eliminate table lookups 3. SCHEMA IMPROVEMENTS — denormalization opportunities, materialized view candidates, and partition strategies for large tables 4. CONNECTION POOLING — current vs recommended pool configuration based on the workload pattern 5. CACHING LAYER — which queries should be cached, with TTL recommendations and invalidation strategy 6. MONITORING DASHBOARD — the 8 PostgreSQL metrics to track, with alert thresholds 7. MIGRATION PLAN — safe, zero-downtime steps to implement each change, ordered by expected impact [Paste schema, queries, and current indexes]

Draft a comprehensive bioethics policy framework for a national advisory committee on the use of AI-assisted genetic screening in prenatal care. The framework must balance: - Parental autonomy and reproductive rights - Disability rights and anti-discrimination protections - Clinical utility and evidence requirements - Equity of access across socioeconomic groups - Data privacy and genetic information protection Deliver: 1. ETHICAL PRINCIPLES — the 6 foundational principles this framework rests on, with philosophical grounding for each 2. REGULATORY RECOMMENDATIONS — 10 specific policy recommendations with enforcement mechanisms 3. CLINICAL GUIDELINES — decision tree for when AI-assisted screening is appropriate, with informed consent requirements at each node 4. EQUITY FRAMEWORK — how to ensure the technology doesn't widen existing health disparities 5. OVERSIGHT STRUCTURE — composition and mandate of the oversight body, including representation requirements 6. SUNSET AND REVIEW — how and when this framework should be reassessed as technology evolves Tone: authoritative, balanced, suitable for legislative review. 3,500–4,000 words.

Reverse-engineer the business model, growth strategy, and unit economics of Cursor (the AI code editor) based on publicly available information. I want the analysis a PE/VC associate would produce for an investment committee. Deliver: 1. BUSINESS MODEL CANVAS — all 9 blocks, with evidence for each assumption 2. UNIT ECONOMICS — estimated CAC, LTV, payback period, gross margin per seat; show your math and state every assumption 3. GROWTH MODEL — organic vs paid vs product-led; estimate the contribution of each channel based on observable signals (GitHub stars growth, social mentions, job postings) 4. COMPETITIVE MOAT ANALYSIS — where is the moat? Is it model quality, UX, data flywheel, switching costs, or network effects? Rate each on 1–5 with evidence 5. RISK FACTORS — the 5 most likely ways this business fails or stalls, ranked by severity 6. COMPARABLE VALUATIONS — 5 public and private comps with multiples, adjusted for growth rate 7. INVESTMENT THESIS — would you invest at a $10B valuation? Make a clear recommendation with 3 supporting arguments Be specific and quantitative wherever possible. Flag estimates vs known facts.

Write chapter 4 of a literary science fiction novel set in 2089 Shanghai. The protagonist is Mei-Lin, 42, a memory archivist — her job is to curate and restore degraded digital memories for clients who want to relive specific moments of their lives. In this chapter, she discovers that a client's childhood memory of his mother contains a hidden data layer — a message encoded by someone else entirely. Requirements: - 4,000–5,000 words - Close third-person, present tense, deeply interior - The technology must be described through use, never exposition — the reader learns how memory archives work by watching Mei-Lin work - Dialogue in both Mandarin-inflected English and untranslated Shanghainese for emotional moments (with context clues, no footnotes) - The discovery happens gradually across the chapter — Mei-Lin notices anomalies that she initially dismisses before the pattern becomes undeniable - Sensory details must be specific to Shanghai: the light, the humidity, the sounds of the city in 2089 - No chapter summary or epigraph. Begin in the middle of action.

Migrate a manually provisioned AWS infrastructure to a fully automated Terraform + GitHub Actions setup. The current environment: - 3 ECS Fargate services behind an ALB - RDS PostgreSQL 16 (Multi-AZ, 2TB) - ElastiCache Redis cluster (3 nodes) - CloudFront + S3 for static assets - Route 53 for DNS - Secrets Manager for credentials - CloudWatch for monitoring - Monthly spend: ~$18K Deliver: 1. TERRAFORM MODULES — complete HCL code for each component, organized as reusable modules 2. STATE MANAGEMENT — S3 backend with DynamoDB locking, workspace strategy for staging vs production 3. CI/CD PIPELINE — GitHub Actions workflows for plan, apply, and drift detection 4. IMPORT PLAN — step-by-step procedure to import existing resources without downtime 5. SECURITY HARDENING — IAM roles, security groups, and network ACLs with least-privilege principle 6. COST OPTIMIZATION — 3 specific changes that would reduce the $18K monthly spend, with estimated savings All code must be production-ready with proper variable definitions, outputs, and documentation.

Design a complete Phase III clinical trial protocol for a novel GLP-1/GIP dual agonist for Type 2 diabetes management. The molecule has completed Phase II with HbA1c reduction of 1.8% (vs 0.3% placebo) and 12% body weight loss over 24 weeks. Deliver: 1. STUDY DESIGN — randomized, double-blind, active-comparator (vs semaglutide 2.4mg) with full rationale 2. POPULATION — inclusion/exclusion criteria, sample size calculation (power analysis shown), stratification factors 3. ENDPOINTS — primary, secondary, and exploratory, with clinical justification for each 4. STATISTICAL ANALYSIS PLAN — primary analysis method, multiplicity adjustment, interim analysis rules, missing data handling 5. SAFETY MONITORING — DSMB charter, stopping rules, AE grading and reporting 6. REGULATORY STRATEGY — how this protocol addresses FDA and EMA requirements differently 7. OPERATIONAL PLAN — site selection criteria, enrollment timeline, and projected budget range Format as a formal protocol synopsis suitable for regulatory submission. 4,000–5,000 words.

Perform a comprehensive due diligence analysis on a Series B AI infrastructure startup. Here are the materials: pitch deck, last 24 months of financials, cap table, customer contracts (top 5), technical architecture document, and team bios. Deliver: 1. FINANCIAL ANALYSIS — revenue quality assessment (recurring vs one-time, concentration risk, cohort retention, net revenue retention by quarter) 2. MARKET SIZING — independent TAM/SAM/SOM calculation; compare to the company's own claims and flag discrepancies 3. TECHNICAL ASSESSMENT — architecture scalability, technical debt indicators, dependency risks, key-person risk in engineering 4. COMPETITIVE LANDSCAPE — positioning vs 8 closest competitors on feature, pricing, go-to-market, and funding 5. CUSTOMER REFERENCE THEMES — synthesize signals from the 5 contracts (switching cost, expansion potential, satisfaction indicators) 6. LEGAL RISKS — IP assignment gaps, open-source license conflicts, regulatory exposure 7. DEAL TERMS ANALYSIS — proposed valuation vs comparable rounds; recommend counter-terms 8. INVESTMENT MEMO — 2-page recommendation (invest/pass) with 3 key reasons and 2 key risks [Paste all materials]