Workshop

AI for Forward Deployed Engineers

AI

CategoriesAI Tools & Frameworks
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Nathalia NelsonAI Educator | Practitioner
$500Enroll now

Limited-time: use code AFENATH for 20% off · ends 01 Sept 2026

Description

That requires a very different skill set. FDEs need to understand how LLMs behave, how RAG systems fail, how agents call tools, how enterprise APIs and knowledge bases fit together, and how to deploy systems that can handle latency, cost, scale, security, and reliability constraints

Learning outcomes

  • Develop agents with LLM APIs, tools, knowledge bases, and enterprise systems. Understand agent loops, tool calling, structured outputs, and guardrails. Build a working LangGraph agent that answers from real APIs and internal data
  • Reason through tokens, context, embeddings, RAG, and failure modes. Debug hallucinations, retrieval failures, bad tool calls, and brittle workflows. Evaluate agents using observability, evals, HITL, and production-grade checkpoints.
  • Move from local prototype to hosted endpoint on Google Cloud and Vertex AI. Understand deployment paths, Model Garden, scaling, and cloud operations. Make trade-offs across latency, cost, reliability, security, and customer impact.

What's included

  • Live session

    Learn directly from Nathalia in real time, not from a recording.

  • Recording access

    Rewatch for 14 days after each session is delivered.

  • 1-on-1 feedback

    Personal review time on your own work.

  • Maram Guarantee

    Your purchase is backed by the Maram Guarantee.

Your AI Practitioner

Nathalia Nelson
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Nathalia Nelson

AI Educator | Practitioner

An independent AI consultant and workshop facilitator based in London, with prior roles at BrightPath Learning Group and Northbridge Studio. She designs repeatable prompt systems, AI workflow playbooks, and adoption programmes for founders, consultants, and professional-services teams — bridging the gap between emerging AI capabilities and everyday knowledge work. She has delivered live training across prompt engineering, generative AI, AI-assisted research, and responsible AI use, working effectively with both technical and non-technical audiences.

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