Results for “ai-product”

Screen products for FDA, EPA, USDA, CPSC, FCC, and other government agency requirements using AskRosetta. Use when checking regulatory compliance for US imports.

Enforces production-grade Python and AI engineering standards for FastAPI, LangChain/LangGraph, RAG pipelines, and LLM integrations, covering type safety, error handling, testing, and security.

Generates conversion-focused marketing copy using direct-response frameworks like AIDA, PAS, BAB, and StoryBrand, grounded in the product's ICP and positioning.

Generate visual storyboards with AI image generation, covering shot types, camera angles, movement, continuity rules, and panel layout for video planning and pre-production.

Design pricing, packaging, and monetization strategy for a software or AI product. Use when the team needs plan structure, free-tier logic, usage vs seat pricing tradeoffs, paywall timing, or monetization guardrails tied to product value and costs.

Provides strategic and operational guidance on ITIL 4 and ITIL 5 frameworks, focusing on AI governance, sustainability, and product-centric lifecycle management.

Builds distinctive, production-grade frontend interfaces with bold aesthetics, avoiding generic AI design patterns.

Builds distinctive, production-grade frontend interfaces with bold aesthetic direction, avoiding generic AI design patterns.

Generate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.

Master of defensive Bash scripting for production automation, CI/CD pipelines, and system utilities. Expert in safe, portable, and testable shell scripts.

When the user wants to create, generate, edit, or optimize images for marketing — blog heroes, social graphics, product mockups, profile banners, listing visuals, or brand assets. Also use when the user mentions 'AI image generation,' 'generate an image,' 'create a graphic,' 'product mockup,'...

>- Advanced Product Quality Planning (APQP) — plan and track a new product launch through all 5 phases, identify deliverables per phase, run gate reviews, and ensure quality outputs are complete before Start of Production (SOP). Use when launching a new part, managing an APQP project, or auditing APQP completeness. Covers AIAG APQP 2nd edition and IATF 16949 §8.3.

Use when designing AI product first-run or blank-slate UX — chat empty state, example prompts, capability discovery, templates, nudges, or follow-ups. Trigger on "users don't know what to ask", onboarding, suggestion chips, or discoverability.

Optimize content to get cited by AI search engines — ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, Copilot. Use when you want your content to appear in AI-generated answers, not just ranked in blue links. Triggers: 'optimize for AI search', 'get cited by ChatGPT', 'AI Overviews', 'Perplexity citations', 'AI SEO', 'generative search', 'LLM visibility', 'GEO' (generative engine optimization). NOT for traditional SEO ranking (use seo-audit). NOT for content creation (use content-production).

Optimize content to get cited by AI search engines — ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, Copilot. Use when you want your content to appear in AI-generated answers, not just ranked in blue links. Triggers: 'optimize for AI search', 'get cited by ChatGPT', 'AI Overviews', 'Perplexity citations', 'AI SEO', 'generative search', 'LLM visibility', 'GEO' (generative engine optimization). NOT for traditional SEO ranking (use seo-audit). NOT for content creation (use content-production).

Optimize content to get cited by AI search engines — ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, Copilot. Use when you want your content to appear in AI-generated answers, not just ranked in blue links. Triggers: 'optimize for AI search', 'get cited by ChatGPT', 'AI Overviews', 'Perplexity citations', 'AI SEO', 'generative search', 'LLM visibility', 'GEO' (generative engine optimization). NOT for traditional SEO ranking (use seo-audit). NOT for content creation (use content-production).

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpoin...

Operates AI infrastructure as a production dependency: manages GPU utilization, MCP servers, LLM gateways, inference pipelines, token costs, semantic caching, and model observability.

When the user wants to create, generate, or produce video content using AI tools or programmatic frameworks. Also use when the user mentions 'video production,' 'AI video,' 'Remotion,' 'Hyperframes,' 'HeyGen,' 'Synthesia,' 'Veo,' 'Sora,' 'Runway,' 'Kling,' 'Seedance,' 'Hailuo,' 'MiniMax,' 'Pika,' 'Hunyuan,' 'Wan,' 'video generation,' 'AI avatar,' 'talking head video,' 'programmatic video,' 'video template,' 'explainer video,' 'product demo video,' 'video pipeline,' 'copy this edit,' 'match this video style,' 'reverse-engineer this video,' 'edit like this reference,' or 'make me a video.' Use this for video creation, generation, and production workflows. For video content strategy and what to post, see social. For paid video ad creative, see ad-creative.

Instrument LLM applications with OpenInference tracing for Phoenix AI observability, covering setup, custom spans, and production deployment.

Full-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.

Full-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.

Full-cycle AI coding skill: plans, builds, tests, lints, fixes bugs, and writes production-grade docs. Auto-detects project state and adapts its 8-phase pipeline.

Create professional marketing videos for ads, promos, product launches, and brand content using AI video generation models and voiceover tools via the inference.sh CLI.

Expert guidance for Zed, the high-performance code editor built in Rust with native collaboration, AI integration, and GPU-accelerated rendering. Helps developers configure Zed, create custom extensions, set up collaborative editing sessions, and integrate AI assistants for productive coding.

Edits real video footage through a structured pipeline: transcribe and plan with an AI agent, cut with FFmpeg, compose with Remotion, generate voiceover and music via ElevenLabs and fal.ai, then polish in Descript or CapCut.

Use when designing or auditing AI product human-in-the-loop — write approval, proposal accept/reject, action confirm, spend caps, run detail, memory capture, or any AI action with irreversible blast radius. Trigger on confirmation UX, undo, cost-before-act, show-the-plan, citations, or keeping the owner in control.

Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations from Arize AI.

Transforms rough sketches or text descriptions into photorealistic 3D renders using Vizcom's AI rendering modes and prompt weighting.

Production-grade accessibility skill for WCAG 2.2 AA compliance. Covers auditing, remediation, component authoring, and validation workflows. Auto-invoked for UI implementation, a11y fixes, and accessibility testing.

Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.

Audits and iteratively fixes chat-based AI user interfaces against production best practices drawn from Claude, ChatGPT, and modern conversational AI, covering layout, rendering, input, responsiveness, scrolling, streaming, and accessibility.

Explains machine learning model predictions using SHAP values, covering feature importance, visualizations, debugging, bias analysis, and production deployment.

Turns product ideas into structured specs for AI tools or stakeholder review, with quick feature specs and full project scopes.

Generate songs, instrumental tracks, and covers using the MiniMax Music API with basic or advanced control modes.

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.