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Build comprehensive model evaluation: benchmark selection, statistical significance, human evaluation protocols, and safety testing.

Audit crawlability, rendering, metadata, and structured data with evidence-backed fixes. Use for indexing problems, migrations, or pre-launch SEO checks.

Plan ML model deployment: serving patterns, A/B testing, canary releases, monitoring, and rollback for production ML.

Design zero trust network architectures: identity-based perimeters, microsegmentation, and continuous verification.

Choose the right chart form for a dataset and question, then build an honest, labeled, accessible visualization; use whenever data needs plotting.

Design rate limiting strategies for APIs: token bucket, sliding window, per-user limits, and 429 response patterns.

Design API products: endpoint design for developer experience, versioning strategy, rate tiers, and ecosystem growth.

Use when API reference docs must be generated or updated from source code, with verified schemas, runnable examples, and complete error catalogs.

Generate and run contract tests for REST and GraphQL APIs from OpenAPI specs or schema definitions.

Design cohesive animation systems: motion principles, timing curves, choreography rules, and accessible motion.

Manage AI agent products: capability roadmaps, eval-driven development, safety reviews, user trust, and launch criteria.

Audit codebases for i18n readiness: hardcoded strings, locale formatting, RTL support, pluralization rules, and translation workflow.

Design and implement safety guardrails for AI agents: input/output filtering, topic restrictions, PII redaction, and jailbreak resistance.

Design and implement ML feature stores: online/offline serving, feature freshness, training-serving skew prevention, and feature discovery.

Design ML experiment tracking: hyperparameter logging, model versioning, reproducibility, and experiment comparison workflows.

Manage Drupal in all popular forms: drush CLI, REST/JSON:API, module management, content types, Views, performance caching, and security hardening.

Design disaster recovery strategies: RTO/RPO targets, backup automation, failover procedures, and DR testing.

Optimize how context is assembled for LLM calls: system prompt design, few-shot example selection, context pruning, and token budget management.

Scan and harden container images: base image vulnerabilities, runtime permissions, distroless patterns, and admission policies.

Audit application configuration: environment variables, secrets management, config validation, and environment parity.

Audit code for race conditions, deadlocks, and thread safety issues in async and multi-threaded code.

Harden APIs against attacks: input validation, output encoding, rate limiting, CORS, CSP, and injection prevention.

Build automated test suites that exercise agent behavior across edge cases: adversarial inputs, tool failures, multi-turn conversations, and recovery.

Design micro-frontend architectures: module federation, route splitting, shared dependencies, and team boundaries.