CertSafari

    Free Practice Questions for LangChain Certified Agent Engineer Certification

    Guide checked for updates:
    9 Oct 2026
    Question bank created:
    29 Aug 2026
    Question bank last updated:
    7 Oct 2026

    Study with 400 exam-style practice questions designed to help you prepare for the LangChain Certified Agent Engineer.

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    Exam Details

    Key information about LangChain Certified Agent Engineer

    Official study guide

    View

    Question formats CertSafari offers
    • Multiple choice
    exam format:

    Semi-open book, allowing specific LangChain resources (LangSmith, Docs, Academy), with a dedicated LangSmith organization provided for the exam.

    prerequisites:

    Completion of recommended LangChain Academy courses is strongly recommended.

    retake policy:

    One free resit is included with the original exam fee. Additional resits require paying the full exam fee again.

    delivery method:

    Live proctored online exam

    allowed resources:

    smith.langchain.com (LangSmith), docs.langchain.com (Docs), academy.langchain.com (Academy)

    time limit minutes:

    120 minutes

    number of questions:

    40 questions

    not allowed resources:

    Google search or any other web search, AI tools (ChatGPT, Claude Code, etc.), The AI helper on docs.langchain.com, Browser agents or automation, Second screens (monitors or phones), Any outside communication

    Exam Topics & Skills Assessed

    Skills measured (from the official study guide)

    1: Build

    1.1: Differences between create_agent and deepagents

    Differences between create_agent and deepagents.

    1.2: Middleware

    Middleware.

    1.3: Context engineering for long-running agents

    Context engineering for long-running agents.

    1.4: AGENTS.md and SKILL.md

    AGENTS.md and SKILL.md.

    1.5: Sandboxing

    Sandboxing.

    2: Test

    2.1: Code-based evaluators vs. LLM-as-judge

    Code-based evaluators vs. LLM-as-judge.

    2.2: Online vs. offline evaluators

    Online vs. offline evaluators.

    2.3: Running and interpreting experiments

    Running and interpreting experiments.

    2.4: Evaluator alignment

    Evaluator alignment.

    2.5: Adding examples to a dataset

    Adding examples to a dataset.

    3: Deploy

    3.1: Deployment terminology: graph, deployment, revision, assistant, thread, run

    Deployment terminology: graph, deployment, revision, assistant, thread, run.

    3.2: Multi-region serving

    Multi-region serving.

    3.3: Secret handling

    Secret handling.

    3.4: Authentication vs. authorization

    Authentication vs. authorization.

    3.5: Storage durability

    Storage durability.

    4: Monitor

    4.1: Reading traces

    Reading traces.

    4.2: Grouping traces into threads

    Grouping traces into threads.

    4.3: Tracking costs and user sentiment

    Tracking costs and user sentiment.

    4.4: Online Evals vs. Insights

    Online Evals vs. Insights.

    4.5: Alerting

    Alerting.

    Techniques & products

    LangChain
    LangSmith
    create_agent
    deepagents
    middleware
    context engineering
    AGENTS.md
    SKILL.md
    sandboxing
    containers
    virtual machines
    code-based evaluators
    LLM-as-judge
    online evaluators
    offline evaluators
    experiment interpretation
    evaluator alignment
    dataset curation
    LangSmith Deployment
    graph
    deployment
    revision
    assistant
    thread
    run
    multi-region serving
    secret handling
    environment variables
    secret management services
    authentication
    authorization
    OAuth
    storage durability
    backup and recovery
    reading traces
    grouping traces
    cost tracking
    user sentiment analysis
    Online Evals
    Insights
    alerting

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