AI-Driven Go-to-Market Strategies with Jordan Crawford

What if your best sales play isn’t a script - but a system you can engineer?

On this episode of Maxed Out: AI-Powered Selling for the Next Best Action, Heath Barnett sits down with Jordan Crawford, founder of Blueprint GTM, to unpack a shift many teams feel but few have named. Jordan argues that the future of revenue isn’t about predicting what might work - it’s about building the workflows, data, and messages that make it work, reliably and at scale.

Rethinking the Role: From RevOps to Go-To-Market Engineering

Traditional RevOps often reacts to sales requests. Go-to-market engineering flips that dynamic. It starts with outcomes, then designs the automations, data pipelines, and roles to deliver them. As Jordan puts it, imagination—not tooling—is now the constraint. If you can articulate the most valuable message to a specific customer situation, you can design the system to deliver it.

Move From Personas to Situations

Personas are helpful, but they’re not enough. Jordan’s push: start with the company’s situation—what’s changing, where the tension lives, and who owns the problem. That shift powers his two core frameworks:

• PQS (pain qualified segment): Identify accounts in a specific, urgent scenario tied to your product’s real outcomes.
• PvP (permissionless value proposition): Deliver a message so useful it stands on its own—before you ever mention your product.
  
  

This is where AI becomes real. Instead of spraying generic personalization, you blend public signals and proprietary insight to craft messages that actually matter.

Reverse-Engineer the Motion You Wish You Had
Jordan’s approach starts with a question most teams skip: if your entire team had a full week to craft one perfect message for one ideal account, what would it say—and what data would it need? Work backward from that bar. Then operationalize: data ingestion, enrichment, QA, channel formatting, and iteration. AI can 100x good fundamentals—or automate mediocre thinking. The leverage comes from structure.

Verticalization Beats Generic Scale
Horizontal tools face a perennial challenge: “Who don’t we sell to?” Vertical playbooks, by contrast, compound. When you pick a niche—plumbers with complex scheduling, fleet maintenance teams tracking regulatory changes, or mid-market pro services teams—you can build messages anchored in real-world proof and data you can reuse. That focus enables better targeting, faster tests, and clearer outcomes.

Experiment Like a Product Team
Jordan is big on shipping. His Cannonball sessions and the AI Barf live build reflect a clear bias: run more experiments, faster. Give a small team the mandate (and data) to test segments, craft PvPs, cold call, and validate. Measure learning velocity as much as pipeline. It’s not theory; it’s operations.

A few lines that stuck out:

“We must transform our strategies to match the evolving buyer’s journey. Our only limit is ourselves.” -Heath

“Imagination is the only limit. Define your impactful message and build systems to scale it. Don’t wait for the future—create it.”  -Jordan

Key Takeaways

• Engineer outcomes, don’t just adopt tools.
• Prioritize company situations over static personas.
• Use PQS and PvP to create relevant, defensible messaging.
• Work backward from the “perfect message” and operationalize it.
• Vertical focus compounds results; horizontal spray dilutes them.

If you’re building a modern revenue engine, this conversation is a blueprint worth studying. Listen to the full episode for deeper insights, and follow Heath Barnett for more conversations at the intersection of AI and go-to-market execution.