Results for “production”

Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests, test migration, CI/CD testing, or test suites. Generate tests, fix flaky failures, migrate from C...

Design an application database schema from product flows and backend responsibilities. Use when the team needs core entities, relationships, lifecycle fields, indexes, audit needs, tenancy boundaries, and migration-minded schema planning for an MVP or production system.

Plan backend domains, services, jobs, integrations, and failure handling for a product or major feature. Use when UX and product scope are defined and the team needs a production-minded backend design without defaulting to premature microservices.

Debug and troubleshoot Azure production issues using AppLens, Azure Monitor, resource health, and systematic diagnosis flows for services like App Service, Functions, AKS, Container Apps, and Messaging.

Guide a team through writing a structured, blameless post-mortem after a production incident, covering timeline reconstruction, root cause analysis, impact quantification, and action item generation.

Generate paid-ad campaign concepts, messaging, copy, creative briefs, and production plans grounded in a validated brand profile, campaign objective, and platform requirements.

Migrates a Stitch screen to production React: fetches and caches wireframes, archives existing pages, converts to shadcn/ui components with semantic tokens, and documents the design system layers.

Activates for web scraping and Actor development, discovering APIs via traffic interception, recommending optimal strategies, and implementing iteratively. For production, it guides TypeScript Actor creation via Apify CLI.

Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models. Use when: azure function, azure functions, durable functions, azure serverless, function app.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models. Use when: azure function, azure functions, durable functions, azure serverless, function app.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.

Provides production-grade techniques for evaluating LLM outputs using LLMs as judges, covering direct scoring, pairwise comparison, bias mitigation, rubric generation, and confidence calibration.

Detects the project stack and generates production-ready multi-stage Dockerfiles with compose services, .dockerignore, non-root users, health checks, layer caching, and optional dev hot-reload profiles.

Produces a complete narrated, subtitled, scored explainer video from a single topic prompt using a six-stage pipeline with script, voiceover, keyframes, animation, music, and local assembly.

Master Julia 1.10+ with modern features, performance optimization, multiple dispatch, and production-ready practices. Expert in the Julia ecosystem including package management, scientific computing, and high-performance numerical code. Use PROACTIVELY for Julia development, optimization, or advanced Julia patterns.

Master Rust 1.75+ with modern async patterns, advanced type system features, and production-ready systems programming. Expert in the latest Rust ecosystem including Tokio, axum, and cutting-edge crates. Use PROACTIVELY for Rust development, performance optimization, or systems programming.

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.

Review whether a product, MVP, or feature is actually ready to launch. Use when the team needs a production-minded check across product quality, UX edge cases, auth and security, observability, support readiness, pricing readiness, and post-launch measurement.

Master Rust 1.75+ with modern async patterns, advanced type system features, and production-ready systems programming. Expert in the latest Rust ecosystem including Tokio, axum, and cutting-edge crates. Use PROACTIVELY for Rust development, performance optimization, or systems programming.

Generate optimized SQL queries from natural language descriptions across multiple database platforms including BigQuery, PostgreSQL, MySQL, and Snowflake. Reads database schemas from uploaded files or diagrams to produce accurate, production-ready queries.

Build and publish production-quality Chrome extensions using Manifest V3 best practices, covering service workers, content scripts, side panels, and Chrome Web Store deployment.

Provides production-grade TypeScript guidance for React and Next.js, covering type narrowing, component props, generics, runtime validation, data fetching, state management, performance, accessibility, and code review.

Generates production-grade Kubernetes manifests including Deployments with probes and security contexts, Services, Ingress with TLS, HPA, PDB, NetworkPolicy, ConfigMaps, and Secrets, with optional Helm charts, Kustomize overlays, Istio mesh, and ArgoCD GitOps.

Use when planning a PLDI campaign across its annual clock — backward-planning from the November deadline through winter reviewing, the February response window, March notification, post-acceptance artifact evaluation, PACMPL production, and the June conference, with owners for each deliverable.

Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests, test migration, CI/CD testing, or test suites. Generate tests, fix flaky failures, migrate from Cypress/Selenium, sync with TestRail...

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

Create distinctive, production-grade frontend interfaces with high design quality. Covers design thinking, typography pairing, color theory, motion design, spatial composition, and code quality. Generates real working code — HTML/CSS/JS or React — with intentional aesthetic direction, not generic AI output.

Cloudflare Pages and Workers deployment checklist for wrangler deploys, secret audits, D1 migrations, Worker-compatible SDK checks, and browser-auth verification. Use when shipping Cloudflare changes to production. NOT for general CI/CD architecture, non-Cloudflare deployments, or post-launch UX QA.

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.