Exec

If the only reps who can succeed at your company are the ones who've already sold to your buyer, you're fishing in a very small pond. And you're paying a premium for it. I hear this a lot. Sales leaders convinced that new hires need "industry experience" when what they actually need is a more reliable way to train new reps on the industry. When ramp takes six months and requires tribal knowledge to survive, you have no choice but to hire people who show up pre-loaded. That limits your candidate pool, drives up comp, and makes you dependent on a very narrow talent market. More reliable training changes your recruiting economics. You can hire athletes. Smart, coachable people who learn fast but haven't spent five years selling in your space. That's a fundamentally different hiring strategy, and it's available to any org that treats ramp time as a problem worth solving instead of a cost of doing business.

The word "coaching" has a lot of different meanings. Some people think it's feedback. Some think it's accountability. Some believe it's asking questions. But there isn’t one right way to coach. It’s a broad toolkit that's situation-dependent. Harvard Business Review's Coaching Styles Framework breaks coaching down into four styles. And all four should be tools in your belt. 1. Telling (high push, low prep) 2. Collaborating (high push, high prep) 3. Asking/Listening (high pull, high prep) 4. Hands-off (low pull, low prep) While the pull method will serve you better most of the time, the real skill isn't choosing between push or pull. It's knowing which style fits the situation.

We analyzed 40+ enablement roles last week from companies like OpenAI, Figma, Rippling, and CrowdStrike and here were some of the trends we found: – Ramp time reduction appears in 90% of all postings as the most universal KPI – New hire onboarding was a focus across 40/40 postings (100%) – 38% of roles involve building enablement from scratch  – Multiple postings explicitly demand AI-powered enablement experience. – MEDDIC/MEDDPICC is the dominant methodology (12/40 postings) – "GTM Enablement" is the most common title (replacing revenue and sales) – CRO is the most common reporting line (35%), followed by VP Sales (25%) and RevOps (20%) Check out all the findings in the full post 👇

Front-line sales managers are the most over-leveraged people in any sales org. Sure, they should probably be reviewing more calls, sitting in on more deals, and spending more time coaching the middle of the roster. But there are only so many hours in a day. And most of those hours are spoken for. The best enablement orgs solve this by equipping managers with technology that increases their span of control. They surface the insights so managers can act on what matters. They make interventions easy so coaching fits into the day, even on a packed calendar. A manager with real-time visibility into 10 reps at once is a fundamentally different asset than one flying blind between 1-on-1s.

In the last 3 weeks… – Our head of design started commiting code. – Our head of growth replaced 3 marketing agencies. – Our head of learning created 5 agentic automations. Feels like we’re getting 5x more done with the same team. It's upending a lot of my assumptions about what it takes to build a successful company.

Everboarding used to be a nice concept you'd see in enablement trend reports. AI is making it mandatory. If you're a software company, your devs are shipping product faster than ever. You have new competitors launching every quarter. The objections reps heard six months ago have already been replaced by entirely different ones. The old model of cramming training into one month and hoping it sticks was already fragile. Now it's unworkable. There's also a cultural thing that happens when you treat onboarding as a one-time event. When you need reps to adapt later to a new product launch or competitive threat, you encounter resistance. It feels remedial, like something reserved for new hires. The orgs that are handling this well treat training as a rhythm that keeps going. The bar keeps moving. Practice has to keep up.

Sales reps don't quit because onboarding was bad. They quit because by month 4, they still can't see a path to making money. And once that doubt sets in, they start looking. When they leave, you don't just lose a half-ramped rep. You lose everything you invested to get them there. The recruiter fees. The manager hours. The ramp salary. The pipeline they were building. Then you restart the clock from zero. The fix isn't more workshops or better slide decks. It's practice and coaching tied directly to their performance on calls. New rep retention doesn't improve with better onboarding content. It improves when reps start closing faster.

Most founders are terrible at handling objections. I definitely was. Every pushback felt like a personal attack on what we'd built. I'd get defensive, over-explain, and watch the deals slip away. The turning point was realizing objections aren't attacks. They're buying signals disguised as resistance. Once I started treating them that way (and using actual frameworks instead of winging it), everything changed. Here are 6 frameworks I teach my team that helped bring structure to how I handle objections 👇

Most skill data is useless. Not because skills aren't important, but because we haven't had the right tools to collect the data. We've used: – Manager impressions – Peer surveys – Self-assessments. All of it filtered through incomplete visibility and subjective bias. And because the data wasn't reliable, companies have never trusted it for real decisions. When's the last time you saw a sales forecast built on rep skill levels? Or CSAT predictions based on how good your support team actually is at handling tough conversations? Or retention projections tied to manager capabilities? It doesn't happen. And when it has, the predictions fell apart, because the inputs were flawed from the start. But AI has changed all of that. We now have the ability to assess skill the way it should have always been done, via structured observation against a rigorous rubric, at scale. Imagine having the world's best evaluator watch every practice conversation, every live customer call. Consistent evaluation. No fatigue. Zero bias. That's what's now possible. And when you finally have accurate skill data? You can actually correlate it to outcomes. You can predict. You can invest in the right development with confidence. We're moving from "skill data" as a nice-to-have HR artifact to skill data as a real operational input. That's a big shift.

Excited to share a new advisory chapter: I’ve started advising Exec on Strategic Partnerships. I’ll be working closely with co-founders Nick and Sean to help shape Exec’s partnership motion as the platform continues to expand across AI roleplay, feedback, and certification. Exec sits at a compelling intersection of coaching, AI, and experiential development. The opportunity here is not building more content, but helping partners scale practice, feedback, and real behavior change in ways that are measurable and operationally lightweight. My focus will be on partner value propositions, enablement, and early pilots with firms that already teach, coach, or certify critical conversations. Looking forward to building this alongside the team and learning with partners along the way. #partnerships #gtm #learning