Get the open-source incident response workflow here: https://go.n8n.io/incident-response

Anthropic's Mythos AI just found a 27-year-old security bug in OpenBSD that no human ever caught. Days later the US government pulled both Mythos 5 and the public Fable 5 model, worried that same power could be weaponized into cyberattacks. The threat is no longer theoretical, and if your defense isn't automated too, you're already behind.

Dylan sits down with Viraj, a former n8n team member turned forward-deployed engineer, who now helps enterprise companies build AI-powered security systems. They walk through a live demo of an open-source cybersecurity workflow built with n8n and backed by real incident data.

The conversation covers how to bring AI into SecOps without letting it run wild, why historical incident data and playbooks matter more than the model you choose, and how Anthropic's Mythos is changing the threat landscape by chaining multiple vulnerabilities in a single attack. They also dig into real-world social engineering scams, phishing tactics, and why good data hygiene is the unsexy foundation that makes any AI system actually work.

The bigger takeaway: the models will keep getting smarter, but the companies (and individuals) who win are the ones with clean data, solid playbooks, and a workflow harness that can plug in whatever model comes next. This is a practical blueprint for fighting AI-powered threats with your own AI-powered defense.

🎙 Chapters:
00:00 - AI Found a 27-Year-Old Bug
00:37 - What the Demo Covers
02:43 - Test Incidents, Playbooks & Data
06:11 - Live Phishing Workflow Demo
07:08 - Three Branches of Analysis
09:35 - Threat Intelligence Explained
12:31 - Mythos and Zero-Day Threats
15:20 - Why Data Hygiene Matters
16:36 - Workflow Results Walkthrough
21:07 - Social Engineering and Scams
25:07 - Actionable Remediation Steps
30:53 - Data Ingestion for Companies
34:50 - Forward-Deployed Engineering
38:51 - Local Models and Personal Security
40:41 - Where to Find Viraj

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Most people hear about Claude's Cowork features and wonder how it actually fits into a real automation stack. This episode is the answer: a full walkthrough of connecting Claude Cowork to n8n, building a production-ready email classifier from scratch, and the token-saving tricks that make it all sustainable.

Ryan Nolan, who runs a data science YouTube channel and deploys AI automations at his day job, joins the n8n podcast to share his exact playbook for pairing these two tools.

The conversation covers setting up the n8n connector in under 60 seconds, calling external APIs through n8n workflows, building an email classifier with human-in-the-loop approval and error handling, and the new Google sign-in flow that eliminates the painful credential setup process. They also dig into why Claude's computer control is too slow for real scraping, and how n8n workflows are a better fit.

On the enterprise side, Ryan explains why compliance teams need structured execution logs (not just Cowork skill histories), how to roll out AI automation department by department, and the hackathon where a team with zero n8n experience built a driver's license verification workflow in two days.

🎙 Chapters:
00:00 - Introduction and episode overview
02:23 - Connecting n8n to Claude Cowork
04:21 - Calling APIs from Cowork via n8n
10:27 - Building an email classifier workflow
14:51 - Tips for prompting and iterating
13:42 - Compliance and audit logging
24:10 - Saving tokens with n8n workflows
32:31 - Enterprise security and skills vs workflows
36:48 - Reviewing the built workflow
39:41 - Quick Google credential setup
42:10 - Execution history and debugging
44:01 - The hackathon story
46:45 - Advice for getting started
51:43 - Running with David Goggins

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🎁 Link to Enterprise Playbook 👉 https://go.n8n.io/n8n-enterprise-playbook

Most companies trying to roll out AI get stuck at five or ten workflows. Fullscript, a health tech company with over a thousand employees, built more than 1,500 in under a year (with over a hundred in production) and saved tens of thousands of hours doing it.

Sahar Rahmani is the Director of Internal AI at Fullscript. She walks through exactly how they went from engineering-bottlenecked automation requests to company-wide self-service AI adoption using n8n.

The conversation covers their hackathon launch strategy, the template library and global credentials trick that removed barriers for non-technical teams, and the highest-value workflows they built across sales, finance, legal, and customer support. If you're looking for a practical enterprise AI automation playbook, this is it.

Sahar also shares how they shifted their messaging from "AI first" to "people first, AI powered," and why that cultural reframe was the key to getting real buy-in across every department.

🎙 Chapters:
00:00 - Intro and Fullscript's AI results
02:12 - The state of automation before n8n
03:56 - Workshops, templates, and credentials
06:33 - Why the templates actually worked
09:44 - The company-wide AI hackathon
13:31 - Hackathon advice: start small
20:05 - Sales lead scoring automation
24:37 - ROI: tens of thousands of hours saved
27:20 - Finance invoice reconciliation
32:48 - The Director of Internal AI role
33:48 - Overcoming employee resistance to AI
38:00 - Customer support call automation
42:22 - Legal contract review with local AI
44:56 - Keeping momentum after launch
48:42 - Final advice and where to find Sahar

Get 30% Off n8n Cloud Starter or Pro Plans!
Want to get started with n8n? Visit n8n.io/pricing and use code 2025-N8N-PODCAST-729C416E at checkout for 30% off your first month or year.