O’Reilly Media

Identify, Scope, and Build an Agentic Workflow in N8n with Max Tkacz

The video walks viewers through building an AI‑driven, agentic workflow in n8n, starting with a live demo that automates a repetitive competitor‑monitoring task. Max Tkacz emphasizes a disciplined triage process—evaluating potential automations on time saved, feasibility, risk of damage, and the human joy‑or‑dread factor—before committing development effort. He introduces a practical “panic button” technique: whenever a manual step feels tedious, note it, estimate its time cost, and assess its automation viability. Applying this framework, he narrows a list of tasks (replying to comments, tracking competitors, distributing content) to the low‑risk, high‑value competitor‑watching use case, then scopes a V1 that scrapes LinkedIn posts, categorizes them with an LLM, and emails a summary. The walkthrough details constructing a reusable tool workflow: a trigger activated by another workflow, an Ampify actor to scrape LinkedIn, JavaScript‑style date expressions for dynamic windows, and an edit‑fields node to trim the payload. He then decouples this tool from an AI agent that runs on a weekly schedule, demonstrating how the agent can invoke the tool, process results, and send formatted Gmail notifications—illustrating modular design for future extensions. By modularizing the scraper as a standalone tool and the agent as a separate orchestrator, the approach enables rapid iteration, reuse across projects, and safe scaling of AI‑augmented automations. Organizations can thus capture insights faster, reduce manual overhead, and mitigate operational risk while maintaining flexibility for future workflow enhancements.