Deploying Workflows On-Demand with Railway

I sit down with Cody Schneider, growth engineer and co-founder of Graph, for a live, hands-on crash course in GTM (go-to-market) engineering powered by Claude Code. Cody walks through how he runs multiple AI agents simultaneously to handle everything from bulk Facebook ad creation and LinkedIn outreach to cold email campaigns and live data analysis — tasks that used to require a team of dozens. By the end of the episode, you'll have a full understanding of how to set up your own agent workflow, the specific tools involved, and why domain expertise paired with AI is the real competitive advantage right now.

Cody’s GTM Toolkit:

AI/Agent Tools: Claude Code, Perplexity API, OpenAI Codex

Marketing & Outreach: Instantly AI (cold email), Phantom Buster (LinkedIn scraping/automation), Apollo API (data enrichment), Million Verifier (email verification), Raphonic (podcast host scraping):

Advertising: Facebook Ads API, Facebook Ads Library (competitor research), Nano Banana Pro (AI image generation), Kai AI (bulk image generation), HeyGen API (UGC/video generation)

Infrastructure & Deployment: Railway.com (servers, on-the-fly databases/Postgres), Vercel (deployment)

Data & Analytics: Graphed / Graphed MCP (data warehouse, live data feeds), Google Analytics 4

CRM & Communication: Salesforce (mentioned as comparison), Intercom, SendGrid API, Slack, Cal.com API

Productivity & Design: Notion, Super Whisper (voice transcription), Claude Code front-end design skill, HTML to Canvas (for converting React components to PNGs)

Timestamps

00:00 – Intro

02:02 – What Is GTM Engineering?

05:12 – Setting Up Your Agent Workspace & Environment File

07:54 – Live Demo: LinkedIn Auto-Responder

09:56 – Live Demo: Bulk Facebook Ad Generator

12:31 – Live Demo: Cold Email Campaign Automation (Raphonic + Instantly)

14:47 – Live Demo: Creating Notion Documents via Claude Code

16:46 – Live Demo: Bulk Ad Creative Generator

26:05 – Live Demo: LinkedIn Engagement Scraper to Cold Email Pipeline

28:16 – Context Switching Across Tasks

29:19 – Live Demo: Bulk Ad Generator

31:41 – Live Demo: Data Analysis: Turning Off Low-Performing Ads

35:28 – Summary of GTM Engineering Workflow

37:48 – Deploying Agents and On-the-Fly Databases with Railway for Data Analysis

41:28 – The Dream of Autonomous Marketing

48:50 – Building API-First Products and Agent-Native Infrastructure

Key Points

• GTM engineering has evolved from Clay-style data enrichment workflows into full-stack agent orchestration — where one person running multiple Claude Code agents can replace the output of a large team.

• The practical setup starts with a single folder containing your environment file (API keys for every tool in your stack), transcription software like Super Whisper, and Claude Code.

• Cody demonstrates running seven or more agents simultaneously across LinkedIn outreach, Facebook ad creation, cold email campaigns, Notion document generation, and live data dashboards.

• Code-generated ad creative (React components exported as PNGs) costs nearly nothing to produce at scale and allows rapid testing of messaging variations before investing in polished visuals.

• Deploying proven workflows to Railway turns one-off agent tasks into always-on, autonomous processes that run 24/7.

• Domain expertise is the real multiplier — the vocabulary you bring from your field determines the quality of output you can extract from these tools.

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The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

FIND ME ON SOCIAL

X/Twitter: https://twitter.com/gregisenberg

Instagram: https://instagram.com/gregisenberg/

LinkedIn: https://www.linkedin.com/in/gisenberg/

FIND CODY ON SOCIAL:

Cody’s startup: https://www.graphed.com/

X/Twitter: https://x.com/codyschneiderxx

Youtube: https://www.youtube.com/@codyschneiderx