AI Learning Roadmap Generator with n8n

Generate a personalized, day-by-day learning roadmap from a plain-language request by orchestrating n8n and an AI model with Kestra. A learner submits a goal such as "I want to learn Kubernetes in 60 days with hands-on practice", Kestra forwards it to an n8n workflow that uses AI to draft a structured plan, then Kestra validates the AI output and exports a ready-to-use CSV. This solves the common problem of trusting raw AI responses: the model handles creative planning while Kestra enforces structure, validation, and reliable file outputs.

How it works

1. The prompt trigger (io.kestra.plugin.core.trigger.Webhook) accepts an inbound HTTP request carrying the learning goal, so the flow starts on demand from any app, form, or chatbot.
2. The call_n8n task (io.kestra.plugin.n8n.TriggerWorkflow) POSTs the prompt input to your n8n webhook (uri from N8N_WEBHOOK_URL), where AI converts the request into a roadmap as JSON.
3. The validate_roadmap task (io.kestra.plugin.scripts.python.Script) parses outputs.call_n8n.body, asserts it is a JSON array, and checks every entry has the keys day, focus, topics, practice, and outcome, failing fast on malformed AI output.
4. The create_csv task adds a status column set to Pending, builds a pandas DataFrame, and writes learning-roadmap.csv as a downloadable output file.

What you get

• A schema-validated roadmap rejected automatically if the AI returns the wrong shape.
• A learning-roadmap.csv with day, focus, topics, practice, outcome, and a status column.
• An on-demand webhook entry point you can wire to a form, Slack, or internal tool.

Who it's for

• Developer advocates and learning teams building guided study plans.
• Platform engineers who want AI suggestions under deterministic control.
• Anyone combining n8n automations with orchestration-grade reliability.

Why orchestrate this with Kestra

n8n is great at chaining AI calls, but its built-in scheduler offers limited retry semantics, validation gates, and execution lineage across systems. Kestra adds event-driven triggers, declarative YAML you can version control, automatic retries, and full run history and outputs for every execution. The validation step turns "the AI usually returns good JSON" into a hard contract, and the CSV becomes a tracked artifact instead of a transient n8n response.

Prerequisites

• A running n8n instance with an AI-backed workflow that returns roadmap JSON.
• Python with pandas available to the script tasks.

Secrets

• N8N_WEBHOOK_URL: Webhook URL of the n8n workflow that returns the roadmap JSON array.

Quick start

1. Build an n8n workflow that takes a prompt and returns a JSON array of roadmap entries.
2. Add N8N_WEBHOOK_URL as a secret in your Kestra instance.
3. Add this blueprint and copy the webhook trigger URL.
4. Send a request with your learning goal and download learning-roadmap.csv.

How to extend

• Push the CSV to Google Sheets, S3, or a database with the matching Kestra plugin.
• Add a Slack or email task to notify the learner when the plan is ready.
• Enrich validate_roadmap with stricter rules, such as date ranges or topic counts.
• Schedule periodic refreshes or chain follow-up flows per roadmap day.

Links

• Kestra n8n plugin