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This week on the pod, Patrick sat down with Randi Deckard, SVP of Growth at Bessler, whose career path reads like a masterclass in “nonlinear advantage.” She started in clinical science, thought she’d be a forensic pathologist, and wound up selling precision medicine to pathologists—hitting $5M in year one and then scaling a 15-person team on the back of meticulous documentation and process design. Today, she’s channeling that same builder’s mindset into AI: stripping out admin, amplifying customer time, and reshaping marketing, sales, and CS output—without adding headcount. This is a practical playbook for leaders who want results, not AI theater.
Randi didn’t “find” sales; sales found her. A mentor noticed she was exceptionally good at explaining complex ideas simply. That matters in healthcare, where jargon is a moat—and often a wall. When she stepped into a startup selling cutting-edge precision medicine (long before payers widely covered it), she wasn’t a trained seller, but she was the ICP. She knew how pathologists thought, what their days looked like, and which words would land. So she approached selling as a conversation, kept language plain, and built momentum via social proof as the category matured.
The other edge to her blade was operational. Coming from clinical research, being a “documentarian” was second nature. She captured what she tried, what worked, and what didn’t—SOPs before SOPs were cool. That rigor made her impact portable. When leadership asked her to teach others, she had a ready-made framework, not just vibes. She gave reps guardrails without scripting the humanity out of the conversation, which let different styles flourish while outcomes converged. That combination—empathy for the buyer and respect for process—set the foundation for everything she does with AI now.
Three-ish years ago, Randi got serious about becoming AI-literate, and her first move was refreshingly unsexy: map the GTM system, find the admin, and cut it. If the job of sales, CS, and marketing is to be with people, then the system should obsess over reducing everything that gets in the way. Healthcare gives you plenty of targets—like 2,000-page regulatory reports. Before AI, digesting those into client-ready guidance took a high-paid SME six to eight weeks. With refined prompts and an exhaustively tested output format, her team shrank that to hours and could repurpose the analysis into blogs, newsletters, and campaign assets. That’s not hype; that’s throughput.
She layered in automations for the low-leverage, high-frequency work leaders love to ignore: competitive intel aggregation from the web and CRM, alerts on changes, and hygiene tasks. Zapier and Make were enough—no rocket science, just wiring. The effect wasn’t just faster; it was calmer. Leaders could enter one-on-ones fully briefed. Reps and CSMs got the same pre-read, so coaching conversations started at the second mile, not with five minutes of fishing through dashboards. Meeting recordings and transcripts flowed into templated summaries and CRM updates, and CS could prep for QBRs with more intention because the grunt work was already handled.
If there’s a controversial part of Randi’s method, it’s this: she built over 200 custom GPTs, ~150 of them for the business. Why so many? Because specificity wins. When you onboard a new hire and show them “the way,” their first attempt still needs feedback. AI is the same. One broad “do everything” assistant drifts; tightly scoped assistants with clear context hold shape. Many of hers are clones with small refinements for adjacent tasks. That’s how you get reliability without turning your team into prompt engineers.
Culturally, she paired this with explicit permission to experiment. She borrows ideas from peers, brings them back, and runs small hack-style sessions so frontline team members can propose use cases based on the pain they actually feel. That matters. Leaders don’t always see the micro-frictions that sap a day. When ICs are invited to fix those with AI—and celebrated for it—adoption stops being a top-down mandate and starts being a movement. Randi also pushed AI literacy beyond GTM, joining the company’s AI governance committee and advocating a simple truth: if only a few people understand AI, you’re bottlenecking the org. And if you think your company “doesn’t use AI,” someone already is—just not safely or consistently.
Here’s where this gets real. Marketing’s output went up even during a two-year hiring freeze, because three full-time roles are now handled by AI “digital twins.” The team isn’t displaced—they manage and QA these twins like high-leverage colleagues, iterating prompts, watching for drift, and enforcing quality. The shape of the work changed; the bar for craft went up.
Sales and CS didn’t spin up twins—yet—but their capacity expanded. CSMs who used to cap at ~30 accounts can now handle ~50 without sacrificing outcomes, and ABM doubled its active target set while keeping pace on follow-through. The company runs a full-cycle sales motion with no SDR layer, because hospital CFOs want trusted advisors, not hand-offs—and Randi’s team can support buying groups that swell to 30 stakeholders because prep and research are systematized. Crucially, she frames AI value on two levels. The first is efficiency—time saved, tasks automated. Helpful, yes, but not the point. The second is effectiveness—better coaching, sharper strategy, richer customer conversations. That’s what compounds. And because the admin is handled, Randi spends weekly time with customers—live calls, in-person visits, proactive outreach—without letting the rest of the machine slow down.
Randi’s “slow is fast” reminder is the governing principle. Sales is change management, and teams don’t adopt new muscles overnight. Start with no-risk internal use cases. Document ruthlessly. Make assistants hyper-specific. Wire the boring parts so prep shows up on time, every time. Then reinvest the reclaimed time in peopling—coaching your team, talking to customers, and making more thoughtful strategic calls. That’s how you earn the right to push the next wave of change.
She’s also refreshingly pragmatic about dogma. There’s no one true methodology; you flex to the buyer and the moment. Legacy qualification crutches like BANT don’t hold up in complex healthcare deals, so her team optimizes for trust, clarity, and stakeholder education instead. Even her “favorite tool” answer tells you a lot: an organized calendar is a force multiplier when your week is intentionally packed with customer time. And if you want to see how she operationalizes all this, she’s opening up her own operating system in a masterclass soon—because the point isn’t to hoard playbooks. It’s to level up the whole craft.
If you’re leading a GTM org and wondering where to begin, consider Randi’s sequence: shave the friction no one will miss, give your people permission to tinker, and trade generic “one AI to rule them all” for a bench of sharp, quiet specialists. In a year, you may find your output looks like you staffed up—without adding a single req. And your calendar? It’ll finally have the space for the work only you can do.
