GTM OS is getting an Agentic team
GTM OS started as a framework I built because I had no idea how to sell anything. Now it is getting seven AI advisors and four simulation agents — because a structured process is not enough if nobody is challenging your thinking.
GTM OS is getting a team
When I built GTM OS I was trying to solve a specific problem. I kept reading GTM advice that assumed you already knew what you were doing. I did not. I had never sold anything, never found customers, never taken a product from zero to revenue. So I researched, talked to people, and built a framework. Seven stages from idea validation to first ten paying customers, each with entry criteria, specific steps, and exit criteria you have to meet before moving on.
Then I built the app. GTM OS is the framework turned into a working tool. It walks you through each stage, forces the right questions before you move forward, and keeps you honest about where you actually are versus where you think you are.
That was the original idea. A structured process to replace the blank page.
But the more I used it, the more I felt what was missing. The framework tells you what to do and in what order. It does not tell you if your thinking is wrong. It does not push back on your assumptions. It does not ask the question you are hoping nobody asks.
When you build alone, there is nobody to do that. No co-founder to say “have you actually talked to anyone about this?” No CPO to ask “what are you cutting to make room for this feature?” No devil’s advocate to try to kill the idea before you spend three months on it.
That is the problem I am building toward now.
The AI team
GTM OS is getting seven built-in advisors. Each one has a specific role, a specific personality, and a specific mandate.
The CTO asks whether this is the right technical approach and what the simplest thing that works looks like. The CPO asks whether this feature exists because a user asked for it or because it seemed like a good idea. The CMO asks who specifically this is for and what makes it different from what already exists. The CGO asks what the fastest path to one paying user looks like without spending money. The CFO runs the numbers and tells you when the math does not work. The Head of Content helps you tell the story honestly without sounding like a press release. The User Research Lead makes sure product decisions are based on real behaviour and not assumptions.
These are not generic chatbots. Each one reads your GTM OS project data before responding — your product brief, your ICP, your current stage, your decisions log, your backlog. They know the context. They respond to your specific situation, not a hypothetical one.
The simulation agents
Alongside the founding team there are four simulation agents for moments when you need to interact with a human but do not have one available yet.
The buyer persona agent responds as your target customer. You pitch to it. It pushes back. It tells you what it would need to hear to consider paying. The devil’s advocate tries to kill your idea. You give it your concept and your research and it finds every hole. The competitor customer embodies a frustrated user of your main competitor — you run a discovery conversation and find out what they wish existed. The pricing conversation agent simulates the moment a potential customer asks how much it costs.
None of these replace real humans. They are a way to pressure-test your thinking before you have access to real people, and a way to prepare for real conversations so you make the most of them when they happen.
Why this is the right feature
Most GTM tools give you templates and checklists. That is useful but it is not the hard part. The hard part is making good decisions under uncertainty with nobody to challenge you.
A framework tells you what stage you are in. A team tells you if your thinking at that stage is solid. Those are different things and you need both.
I am building the CTO agent first because it is the easiest to evaluate — I know my own stack well enough to know immediately if the responses are useful or generic. Once that loop is working end to end, the other six follow the same pattern.
The agents read from GTM OS. They have memory across sessions. They know what you decided last week and they will reference it this week. The goal is something that feels less like talking to an AI and more like having a conversation with someone who has been paying attention.
What this means for GTM OS as a product
I am still testing the framework on cv-tailor in real time. I do not know yet if it works. But I am increasingly clear on what GTM OS is trying to be. Not another productivity tool. Not a Notion template. A co-founder substitute for people building alone who need structure, challenge, and honest feedback at every stage.
The team feature is the most important thing I have built into it so far. Whether it works the way I am imagining it will depend on whether the agents are actually useful or just interesting. I will find out by using them myself first.
That is still the plan. Build it for myself. See what breaks. Write about it honestly.