This skill helps you master production-grade LangChain orchestration across chains, agents, memory, and RAG patterns for scalable LLM applications.
Find, trial, compare, and govern AI agents before hiring
Design
Prototype, inspect, and improve product UI, UX, and design implementation flows.
What team job or business role does the user need filled?
Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.
- department or team-role discovery
- plain-language job briefs
- business outcome shortlists
- non-technical browsing
Start from user language
- Audit a product screen for UI, accessibility, and implementation drift.
- Turn a design brief into build-ready frontend tasks.
Sandbox-first next steps
Design candidates
Showing 12 of 4988. Adjust filters to narrow the review list without losing job context.
ALWAYS START HERE for any LangChain, Deep Agents, or LangGraph agent building project. Required starting point before choosing other skills or writing any…
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This skill helps you build robust LangChain applications by guiding chains, agents, memory, and RAG patterns across production-ready components.
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This skill helps you validate and approve LangChain production readiness by guiding configuration, observability, security, and deployment checks.
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This skill helps design production-ready LangChain architectures with scalable patterns, provider abstraction, and chain management for enterprise LLM
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This skill helps you implement LangChain security best practices from secrets management to prompt protection for safe production usage.
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This skill helps you create and integrate LangChain tools with robust schemas, enabling reliable function calling and resilient tool orchestration.
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This skill provides a concise LangChain 1.0 quick reference for building agents, tools, memory, and middleware workflows.
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Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
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This skill helps you build declarative, type-safe AI services with LangChain4j in Java, enabling memory, tool integration, and structured outputs.
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Complete Retrieval-Augmented Generation systems with LangChain4j for knowledge-enhanced AI applications. \n \n Document ingestion pipelines with configurable…
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This skill helps you implement Retrieval-Augmented Generation patterns with LangChain4j to build knowledge-rich QA and document-aware assistants.
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Review links
Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
4988 candidates for Design. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role familyOpen the focused review record
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.