GTM Live Podcast: "AI-Powered GTM Build Using Only ChatGPT in Under ONE HOUR"

Host: Amber (of Passetto)
Guest: Jordan Crawford (GTM Engineer, Cannonball GTM)
Date: November 17, 2025

Episode Overview

This episode of GTM Live showcases a radically new approach to Go-To-Market (GTM) strategy-building by leveraging AI—specifically, a live demonstration of how to use ChatGPT to ideate, research, and construct a targeted GTM campaign in under an hour. Host Amber is joined by Jordan Crawford, a widely recognized GTM engineer, to walk through this process in real time, challenging the audience to rethink conventional, inefficient sales and marketing tactics in B2B SaaS.

Main Theme

• Shifting from traditional volume-driven, ineffective funnel-based GTM tactics toward efficient, customer-first methodologies powered by modern AI.
• Focusing on root-cause insights (“the list is the message”), specificity, and demonstrable value—rather than broad, impersonal outreach.

Key Discussion Points & Insights

1. The Problem with Legacy GTM Playbooks

[00:00–06:00]

• B2B still clings to “top-of-funnel volume” thinking, creating wasted pipeline and investments in tactics that don’t convert.
• "Trying to be efficient with something that isn’t working doesn’t help at all"—Amber describes seeing companies investing in ineffective AI SDRs and arbitrary funnel metrics.
• Diversification of tactics, without understanding root causes, actually undercuts effectiveness.

Quote:
"Just pushing more volume isn’t going to help you. You need to really see what’s actually working for your business and engineer systems to help repeat that." — Amber [01:25]

2. Why List Quality and Message Specificity Matter

[06:00–09:00]

• Traditional segmentation (firmographics/demographics) leads to generic, useless messaging downstream.
• True personalization isn’t about random facts ("I wear a hoodie too, let's buy my SaaS"), but about understanding a customer's actual situation and pain using observable public data.

Quotes:
"We shape our tools and thereafter our tools shape us. We’ve gotten so used to thinking in Apollo/ZoomInfo filters that it’s crippled our creativity about why users buy." — Jordan [06:30]
"The list is the message." — Jordan [07:18]

3. The Move to AI-Enabled GTM Workflows

[08:45–11:30]

• Leaders, not just technical staff, can now use tools like ChatGPT to do high-value GTM research and target building.
• "Words can be code"—Jordan emphasizes how AI/LLMs have collapsed the gap between idea and execution. You don’t have to be an engineer to run this process.

Quotes:
"I'm not a coder. I think Python's still a snake...you don’t have to be one either to do this." — Jordan [09:10]
"Your imagination can become action very quickly." — Jordan [10:15]

4. Methodology: Working Backwards from the Customer

[12:47–16:39]

• Instead of abstract ICPs, start with your best customers, analyze their situations, and use AI to uncover observable, public indicators of pain.
• Drop transcripts and case context into ChatGPT and have it surface public signals pre-dating engagement.
• Build lists based on demonstrable evidence and craft messages that bring market-specific, timely insights to the prospect.

Quote:
"If you could say, 'You have a $10M fine up and coming—here’s the exact source, here are the properties, here’s the law'…now that’s a message." — Jordan [41:00]

5. The Power of Vertical SaaS

[16:39–20:13]

• Vertical SaaS companies have an edge: deep knowledge compounds, enabling more targeted, insightful messaging.
• Horizontal SaaS struggles—too many use cases, personas, and industries to synthesize insights.

Analogies:

• Trying to sell by describing everything about yourself (irrelevant in real life).
• Using chainsaws (power tools) vs. axes for the same task—executives must get comfortable using modern tools directly.

Quote:
"If you have a chainsaw, as an executive, you should at least cut down the first tree...You should go plant the first tree with that chainsaw." — Jordan [19:57]

6. Live AI-Powered GTM Build — Hands-On Workshop

[20:24–53:01]

Step-by-Step Breakdown with Timestamps

A. Selecting a Business & Using ChatGPT

• [20:27–24:37]
  • Jordan demonstrates using ChatGPT (with voice dictation tools) to analyze Arcadia—a clean-energy SaaS.
  • Asks ChatGPT to “create a dossier” on the company: segmenting industries, use-cases, buyer personas, and publicly available pain signals.

B. Creative Constraints for Powerful Output

• [24:45–26:16]
  • “Creative constraint with context” is key. Provide as much real-world specificity and desired outcome as you can in your prompts.

C. Segment Selection and Prioritization

• [26:16–34:43]
  • Of six segments (e.g., PropTech, EV charging networks, multi-site enterprise), ChatGPT and Jordan zero in on PropTech—specifically because of:
    • Demonstrable pain (explicit fines)
    • Rich structured public data (NYC carbon emission penalties)
    • Ability to create highly targeted, specific outreach

D. Building Playbooks and Messaging (“The Secret”)

• [33:02–46:00]
  • Example: NYC publishes building-level data on emissions and compliance related to Local Law 97.
  • A targeted play: build a list of PropTech buyers exposed to $X million in upcoming fines.
  • Export data, blend sources, and use ChatGPT to draft concise, high-value (not salesy, just insightful) introductions.
  • “The message is not ‘buy Arcadia’, it’s ‘Here’s a law, and here’s your fine exposure. If we could halve it, would that be worth a chat?’”

E. Testing and Iteration

• [49:31–53:01]
  • Rapid deployment: Send data-driven emails or scripts, leverage cold calling for immediate feedback.
  • If play fails, pivot quickly—“If it fails, it failed the first half of Thursday. Build a second campaign on the back half.”

Memorable Quotes:
"It’s not inventing words...the model is acting as a data scientist, not a token generator." — Jordan [49:31]
"If you have an amazingly good insight...do crazy things to get in front of them. You can afford to put a billboard in front of their office." — Jordan [54:26]

7. The Real Impact — Beyond Vanity Metrics

[54:51–59:16]

• Companies spend massive budgets on undifferentiated paid ads; this process enables ultra-targeted, high-propensity outreach, for dramatically less.
• Using AI to build GTM from first principles teaches you more about your market, exposes hidden value, and eliminates waste.

Quotes:
"Once you see it, it’s hard to go back." — Jordan [57:03]
"You don’t probably need more tech stack or more budget. You probably really just need to get down to first principles of who your TAM is." — Amber [57:33]

Notable Quotes & Moments

• On bad lists and messaging:
  "Bad list, bad message, or... too slow. Those are the three problems I solve." – Jordan [03:00]

• On segmentation fallacies:
  "The Persona-level messages actually aren’t useful because they speak to a fictional thing." – Jordan [13:37]

• On why executives must own targeting:
  "Management’s not going to cut it anymore. You now actually can go build something yourself." – Jordan [09:40]

• On channel tactics vs. insight obsession:
  "Don’t be obsessed with the channel, be obsessed with the targeting." – Jordan [54:17]

Timestamps for Major Segments

• Opening Rant on Broken GTM Model – [00:00–03:57]
• Jordan’s Methodology & “List is the Message” – [06:00–09:00]
• AI’s Impact – Enablement for Non-Engineers – [08:45–11:30]
• Segmentation & Customer Backwards Thinking – [12:47–16:39]
• Why Specialization Beats Horizontal – [17:14–20:13]
• Live Workshop: Choosing & Qualifying Segments – [26:16–34:43]
• Example Plays Using Public Data – [34:22–46:00]
• Rapid Testing, Feedback Loops – [49:31–53:01]
• Channel Choice & True ROI – [53:01–54:51]
• Recap & Where to Find Jordan – [57:03–58:54]

Where to Find More

• Jordan Crawford: jordancrawford.com → LinkedIn
• Cannonball GTM Live Workshop: Fridays, 9–10am Pacific (LinkedIn & Zoom), subscribers get historical access.
• GTM Live by Passetto: Find episodes on YouTube, Spotify, or connect via LinkedIn for feedback and to join future deep dives.

Summary Takeaway

This episode is a masterclass in how revenue and strategy leaders can skip "vanity personalization" and instead, wield AI as a scalpel: assembling lists and messaging rooted in real, public pain signals and value creation. By the end, you’ll recognize that ownership of segmentation and insight-finding should no longer be delegated—or reliant on outdated tools. Using the techniques demoed here, narratives become sharp, data-driven, and designed to open real conversations, not clutter inboxes with noise.