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Payment by wire transferEnhanced confidentialityPerfect for companies with 50 to 500 employeesScheduling to fit any time zone
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LangSmith Training - Optimizing the Debugging of LLM Applications

Ref: RTH576
10 people max.
From $7,350 HT / per person
Pay in 3 installments · On-site on request · +$540 with certification exam
5 days
Remote

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Learning objectives

  • Master advanced LangSmith traces for debugging complex LLM chains
  • Develop custom enterprise evaluators to validate performance
  • Implement real-time monitoring of certifying AI workflows
  • Design datasets and automated tests with professional LangSmith
  • Optimize LLM agents for enhanced scalability and reliability
  • Deploy secure and traceable production pipelines
  • Acquire certifying skills in AI observability

The Learni story

Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Imed BEN AMOR
Imed BEN AMOR

Learni trainer · Development expert

73%productivity gap
×3cost of inaction

Program

Module 1Advanced LangSmith Traces: Expert Configuration and Instrumentation (LangChain, logging tools)

Immersion in fine-grained LangSmith instrumentation to capture detailed traces of complex LLM chains, configuration of development environments with advanced LangChain integration, practical exercises on instrumenting multi-step agents, real-time log analysis with custom dashboards, creation of your first professional runset to identify bottlenecks, immediate trainer feedback on initial optimization.

Module 2Custom LangSmith Evaluators: Design and Expert Metrics (custom metrics, benchmarks)

Development of custom evaluators with LangSmith to assess LLM response fidelity and coherence, use of Golden Datasets for rigorous benchmarks, implementation of composite metrics like hallucination rate and latency, real enterprise cases on RAG systems, collaborative iterations with automated feedback, production of exportable evaluation reports ready for internal audits, immediate gain in precision of your AI models.

Module 3LangSmith Datasets and Testing: Expert Automation (runs, collaborative annotations)

Construction of annotated datasets via LangSmith interface for exhaustive LLM application testing, automation of parallel runs on thousands of examples, team collaboration for expert annotations, integration with CI/CD for recurring tests, exercises on interactive debugging of recurrent failures, generation of custom playgrounds for rapid prototyping, concrete valorization of your datasets as reusable enterprise assets.

Module 4LangSmith Monitoring and Agents: Expert Scalability (alerts, production workflows)

Implementation of proactive monitoring with LangSmith alerts on LLM performance degradations, optimization of autonomous agents via granular traces, scaling of distributed workflows with distributed tracing, advanced use cases on multi-agents and tool calling, configuration of guards and human-in-the-loop, production simulation exercises for high availability, assurance of total observability for your critical deployments.

Module 5LangSmith Production and Optimization: Certifying Deployment (enterprise integrations, security)

Secure production deployment of LangSmith pipelines with SSO and RBAC, expert integrations with observability stacks like Datadog or Prometheus, final optimization of costs and performance via LangSmith insights, review of ongoing project with certification of acquired skills, post-training action plan for immediate ROI in the enterprise, export of reusable templates, closure with MCQ and presentation for professional certifying validation.

Evaluation method

  • Expert MCQ to validate acquired skills at the end of the training
  • Continuous evaluation via exercises and LangSmith traces
  • Presentation of the ongoing project for observed LLM application

Learning method

  • Courses led by an active LangSmith expert trainer
  • Practical exercises on real enterprise LLM cases
  • Progressive ongoing project on AI observability
  • Complete course materials and LangSmith platform access

Methods, materials and delivery

The LangSmith Training - Optimizing the Debugging of LLM Applications program is delivered onsite or remote (blended-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the LangSmith Training - Optimizing the Debugging of LLM Applications program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the LangSmith Training - Optimizing the Debugging of LLM Applications program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.

Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

FAQ

Frequently asked questions

How much does the LangSmith Training - Optimizing the Debugging of LLM Applications training cost?+
The individual price is $7,350 (USD). A detailed quote is sent within one business day.
How long is the LangSmith Training - Optimizing the Debugging of LLM Applications training?+
The training lasts 5 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Advanced proficiency in Python, LangChain, and production LLM application development
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
On-site & remote

This training across cities

Available on-site and remotely. Pick your city to see the local training center.

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