Results for “product”

Use this skill for performance, reliability, observability, SLO risk, production diagnostics. Trigger when the task involves agent profile work related to Performance SRE Agent, implementation, audits, debugging, strategy, or validation.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Engage Reddit, Indie Hackers, Hacker News and other communities for Product Hunt launches. Use this skill to identify relevant communities, craft appropriate posts, and drive cross-platform engagement without appearing spammy.

Design and build production-ready frontend interfaces with design systems, responsive layouts, accessible components, and dark mode support. Use when the user requests frontend design or provides relevant inputs for this workflow.

Deploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.

Product analytics through PostHog's official hosted MCP — insights, dashboards, HogQL queries, session replays, feature flags, error tracking. Use for funnel/retention questions, event deep-dives, and flag lookups.

Expert skill for building LLM applications with LangChain — LCEL chains, RAG pipelines, agent orchestration, LangGraph integration, LangSmith observability, and production deployment via LangServe. Use when working with LangChain or comparing LLM application frameworks.

Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when "langgraph, langchain agent, stateful agent, agent graph, react agent, agent workflow, multi-step agent, langgraph, langchain, agents, state-machine, workflow, graph, ai-agents, orchestration" mentioned.

Manage production secret infrastructure with HashiCorp Vault, cloud secret stores, automated rotation, and audit logging.

Build real-time streaming applications with the Azure Event Hubs SDK for Java, including sending and receiving events, batch processing, and production-ready event processors.

Identify and design growth loops (flywheels) for sustainable traction, evaluating five proven mechanisms: viral, usage, collaboration, user-generated, and referral.

Turn model work into a production ML system with data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring.

Provides production-grade Laravel architecture patterns for building scalable, maintainable applications with controllers, services, Eloquent ORM, queues, events, caching, and API resources.

Provides deployment strategies, CI/CD pipeline patterns, Docker containerization best practices, health checks, and production readiness guidance for web applications.

Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, tooling, testing, and production-ready practices.

Build production-grade stateful AI agents using LangGraph, covering graph construction, state management, persistence, and human-in-the-loop patterns.

Provides canonical patterns for MSBuild item groups: Include/Remove/Update semantics, item metadata, batching with %(Metadata), transforms, per-item filtering, and cross-product batching pitfalls.

Builds production-ready frontend pages with premium UI design, cinematic animations, AI-generated media assets, persuasive copywriting, and generative art.

Launch community-powered growth campaigns across social platforms: amplify posts with authentic engagement (replies, likes, reposts) and discover relevant conversations to join.

Create explainer videos from script to final cut using AI tools for voiceover, visuals, and assembly.

Write clear, helpful UI copy including microcopy, error messages, empty states, and CTAs that guide users and reinforce product voice.

Combine a human selfie and product image into a UGC-style video ad with a generated script and animated video.

Provides opinionated defaults and reference documentation for building production TypeScript applications with Effect v4, covering schemas, services, layers, configuration, scheduling, caching, streams, HTTP clients, and testing.

Builds production-grade web or mobile interfaces with distinctive design, modern CSS, and purposeful motion, inferring intent from the codebase without asking questions.

Provides a frontend design mode for strong visual direction, UI polish, redesigns, landing pages, and production-grade interface work, including shadcn-based surfaces.

Provides expert-level guidance for Rust 1.75+ development, covering async programming, advanced type system features, performance optimization, and production-ready systems programming.

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Operates Laravel applications in production, covering Horizon, queues, scheduler, Octane, Redis, Supervisor, PHP-FPM, cache, and deployment with safety gates for destructive commands.

Verifies that tests for already-implemented behavior are meaningful by temporarily breaking the production code and confirming the test fails for the expected reason.

Converts Stitch screen designs into production React components, fetching and caching assets locally, extracting design tokens, and archiving existing pages before replacement.

Runs an Opportunity Solution Tree workflow with a lightweight graph database and CLI, routing through outcome, opportunity, solution, and assumption phases.

Generates thorough project documentation by exploring the codebase, identifying the tech stack and deployment target, and writing a comprehensive README.md covering local development, architecture, and production deployment.

Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, testing, and production-ready practices.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.