Jason M. Lemkin built OpenAI's enterprise go-to-market team starting in early 2023. He consolidated 500 people into one unified organization instead of splitting sales and marketing, and argues companies should design teams around products, not legacy playbooks.
So this next and last section is intentionally punchy. It's a rapid fire set of the most common go to market mistakes that I see founders make or ask us about. Think of it as a practical checklist to help you avoid missteps and accelerate what's working. It was early 2023. OpenAI had hired me in to help build our ChatGPT enterprise go to market team from scratch. Our early team at OpenAI of our sales and go to market team was less than 10 people. No SDRs, no SCs, no CSMs, no sales ops, rev ops, marketing enablement, and not even a working Salesforce instance. We had about six account directors and one technical success partner who they were all on FHIR, but they were focused on selling the API. And we had the hypothesis that ChatGPT would have a distinct fire and and a distinct sales motion different from our API. So we made a deliberate choice to build a dedicated go to market Org from scratch. That approach gave us speed, clarity, and deep customer focus during a critical window. And it worked. OpenAI already had the fastest growing consumer application in history. And then this brand new team that we built, we believe launched the fastest growing enterprise app application in history. But despite this success, we saw an opportunity to go even further by evolving our structure. So earlier this year, we basically collapsed both of these orgs. We took 500 people, most people who had only been at the company for a few months, and we brought them into one single, unified go to market Org. Everyone had new roles, new workflows, new managers, and every single person had to learn a new product. They had to learn the opposite product they weren't selling. This was a hard change, but ultimately it drove faster execution, less duplication, and most importantly, a better customer experience. The key lesson here is that old playbooks don't always apply in AI. You need to design around orgs and product, not around legacy structures. So an example here might be, let's say you're releasing a new AI product at your company. An old way of doing it probably would have been teach and enable everybody how to sell it, and then everyone kind of bolts it on. Maybe the new way to do this might be create a small dedicated tiger team to really go focused and launch that product. Move fast, be willing to make mistakes and bold, uncomfortable decisions, and they will pay off in the long run.
