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AADP is a professional training and certification program covering the concepts, workflows, and engineering practices involved in building AI agents, voice agents, and automations using n8n — from workflow fundamentals and LLM integration through to voice systems, retrieval-augmented knowledge bases, and multi-agent orchestration. Unlike CPDP and IPDP, AADP is not organized into progressive levels; it is delivered as a single four-week program structured into four phases.
Foundations & LLM Integration introduces the fundamental concepts and workflow required to begin building automations and agents in n8n, guiding participants from the core item/JSON model and node-based workflow logic through to connecting large language model providers and producing reliable, structured output. The phase focuses on establishing a strong foundation in n8n's workflow model — nodes, expressions, branching, and data reshaping — alongside LLM fundamentals: how models function as pattern matchers, prompt design (system vs. user prompts, role/context/task/format), tokens and context windows, and schema-based structured output for downstream automation. It is intended to help participants move from zero n8n experience to building and reasoning about working, LLM-integrated workflows, closing with a critical-gate session on structured output that every later phase depends on.
Agents, Tools & Voice builds upon the foundations established in Phase 1 and develops the practical skills required to design agents that reason, call tools, and recover from failure, then extends that architecture into real-time voice interactions. The phase focuses on the reason–act–observe agent loop, memory and tool-calling design, reliability patterns such as retries, error workflows and idempotency, and the speech-to-text → LLM → text-to-speech voice stack, including exposing n8n workflows as callable tools and connecting a live phone number. It is intended to help participants move from single-shot LLM calls toward multi-tool, self-verifying agents, culminating in a live test call on a voice agent built and deployed during the phase.
Knowledge & Messaging Bots advances participants into grounding agents in real information and deploying them on the channels people already use, starting with retrieval-augmented generation and continuing into WhatsApp-based conversational bots. The phase focuses on embeddings and vector similarity, chunking and retrieval design, using Supabase/pgvector as a knowledge store with citation-aware responses, and building stateful WhatsApp bots with intent detection, per-contact session memory, and human handoff. It is intended to help participants combine retrieval and messaging into deployable, business-facing systems, including a live booking bot connected to a real calendar with escalation to a human agent.
Multi-Agent Systems & Capstone closes the program by introducing orchestration across multiple specialized agents and the security considerations that come with autonomous, tool-using systems, then bringing every earlier phase together into one assessed project. The phase focuses on the orchestrator–worker pattern, prompt-injection risk and the "lethal trifecta," approval gates and cost control in multi-agent systems, and — in the capstone session — scoping, pricing, and presenting an agentic system to a non-technical client. It is intended to help participants graduate with a working, documented, multi-agent system that combines CRM, voice, RAG, and messaging elements from the previous three phases, assessed against a rubric covering functionality, reliability, security, documentation, and presentation.
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Instant full access to all course levels simultaneously. Ideal for experienced engineers aiming for fast full-stack mastery.
Unlock levels one by one as you complete assessments. Recommended for structured step-by-step learners.
Pick and skip directly to any specific level (e.g. direct Level 3) tailored to your existing knowledge base.
Includes 1-on-1 live practical code reviews, direct instructor debugging, and custom project guidance.
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