Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration.
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.
This skill guides building LangChain 1.x and LangGraph architectures for agents, memory, and tool integration to create robust LLM applications.
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This skill helps you design advanced LangChain applications with agents, memory, and tool integration for scalable, multi-step LLM workflows.
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This skill helps you configure LangChain CI/CD pipelines with testing, linting, and deployment steps for robust projects.
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This skill helps you build production-ready LangChain workflows by composing LCEL chains, prompts, and parsers with type-safe, reusable templates.
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This skill helps you build autonomous LangChain agents with tools for tool calling, decision-making, and multi-step task execution.
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This skill helps you deploy LangChain apps to production using containers and cloud platforms for scalable, reliable operations.
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This skill enables enterprise RBAC for LangChain apps with multi-tenant isolation, fine-grained permissions, and usage quotas to enhance security.
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Build production LangChain agents with create_agent(), tools, and middleware patterns. \n \n Use create_agent() with model, tools list, and system prompt; co…
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Builds LLM-powered applications with LangChain.js for chat, agents, and RAG. Use when creating AI applications with chains, memory, tools, and retrieval-augmented generation in JavaScript.
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Human-in-the-loop approval, custom middleware, and structured output patterns for LangChain agents. \n \n HumanInTheLoopMiddleware pauses execution before da…
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This skill helps you plan and execute LangChain migrations with phased strategies, tooling, and validation to minimize risk.
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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.