Hi Pedro — you asked to see a session. This page is a quick look at how I teach: start with a live AI system, then put the tools in students' hands. Tuned to your Tecnocampus focus on AI applied to marketing strategy, and the EU AI Act obligations now reshaping martech.
This is the teaching format in practice: a working system demonstrated live, with the engineering explained as it runs. No slideware — the same way a session with your students would open.
Cisco DevNet podcast — live demo of a five-agent network operations system. The marketing-focused version of this demo swaps in campaign and martech scenarios.
Multiple AI agents coordinating to handle a real operational task — exactly the kind of working system I open every session with before students start building their own.
Watch on YouTube →Delivered to master's students at Politehnica Bucharest. A good reference for the depth and structure your postgrad cohort would get.
View the lecture slides →Each module works standalone as a guest lecture or as part of a co-developed track. For your programs, these two lead — the rest plug in as your curriculum needs them.
Applied use cases: AI-driven campaign analysis, content generation pipelines, customer segmentation with LLMs, and prompt engineering for real marketing workflows. Built around the scenarios your students will actually face.
Workshop 6–12 hrsRisk classification for martech tools, compliance obligations for AI-powered ads, profiling, and automated decision-making under EU regulation. The piece every marketing graduate now needs before entering the workforce.
Lecture + Cases 4–6 hrsHow LLMs, agents, and automation pipelines work — demystified for non-engineers. Students build and test a working AI agent in-session.
Hands-on 4–8 hrsMulti-agent architectures, tool use, RAG systems, and deployment. Students design and prototype an agent for a real business scenario.
Hands-on 8–16 hrsStructured prompting, chain-of-thought, system prompts, and evaluation. Participants build a prompt library for their specific professional domain.
Workshop 4–8 hrsBuild vs. buy decisions, AI ROI frameworks, vendor evaluation, and organizational readiness. Based on real enterprise deployments across telecom, MSP, and regulated industries.
Lecture + Cases 4–6 hrsEvery session follows the same principle: demonstrate with working systems first, then let students build.
Sessions open with a demonstration of a working AI system — not slides. Students see real agents handling real tasks before any theory. (The video above is exactly this.)
Students build, test, and break AI systems during the session. Exercises use industry tools: LangChain, LangGraph, Claude, GPT, open-source models.
Content, use cases, and difficulty calibrated to your cohort — digital marketing professionals, mixed business groups, or specialist tracks.
The EU AI Act is reshaping what every marketing professional must understand. We cover the obligations that matter to your students' careers — and to the martech tools they'll be expected to evaluate.
Sessions are taught by a practitioner who builds and deploys AI systems in production — not a researcher presenting theory.
20+ years building and securing enterprise infrastructure for some of the world's largest networks. Now building autonomous AI operations systems for telecom and regulated European enterprises.
Teaching approach: start with a live system, explain the engineering behind it, then put tools in students' hands. Every session ends with something participants built themselves.
A 20-minute call where I show AI agents working on marketing scenarios and walk through EU AI Act classification for martech tools — so you see exactly what your students would get.