Run Your Entire GTM as a Team of One With AI Agents

For founders and GTM leaders at early-stage B2B companies who do too much of the repetitive work themselves, this playbook shows how to hand 80% of the grunt work to AI agents while you stay in control of the 20% that matters. You get the 10-step Slice and Stack method, a quick-start checklist, and the exact prompts and templates Jacob Bank uses (webinar promo post, first-name extraction, YouTube video analysis, newsletter draft, churn follow-up email).

Created with

Jacob Bank

Founder & CEO at Relay.app

Free Playbook

Get the full playbook.

What you'll learn

Audit your repetitive work in one week and spot the signal that a task is ready to automate (doing the same thing 4 times)
Pick your first workflow by pain rather than ambition, so the ROI is time saved on guaranteed recurring work like webinar signup processing
Build the trigger first off an event that already fires in a tool you use (calendar event in 4 days, canceled Stripe subscription, new YouTube upload)
Add AI only for writing, extraction, and summarization, and use plain automation to move data between tools
Set two kinds of human checkpoints (review-and-edit, simple approval) so you catch the 20% that matters before anything goes to a customer
Match the model to the task using Jacob's cheat sheet (Claude 4 Sonnet for quality prose, Gemini 2.5 Flash for cheap parsing, GPT-4.1 for medium tasks)
Build research pipelines that monitor creators, turn customer calls into content, and repurpose webinar to YouTube to LinkedIn matched to funnel stage

Summary

The Slice and Stack method breaks every GTM function into the smallest repeatable tasks, hands the boring ones to simple agents, and stacks those micro-automations into workflows that run on their own. You start with one annoying weekly task, build the trigger first, add AI only for writing, extraction, and summarization, and put a human checkpoint before anything publishes or reaches a customer. Each agent does one boring thing; run 40 in parallel and you have a marketing department. The playbook also covers picking models by task (Claude 4 Sonnet for quality writing, Gemini 2.5 Flash for cheap extraction, GPT-4.1 in between), building research pipelines that monitor creators you admire, and turning customer calls into content. Catalyst client Emtrain scaled their GTM motion with an agent-driven stack to 1,500+ MQLs in 4 months, 500+ per month on autopilot, with the team reviewing and approving rather than executing.