Chaos doesn't scale. It needs a ladder. And more often than not, that ladder is process.

Everyone wants to talk about AI right now, and that conversation is evolving into an agentic one.

Agents that book the meetings, write the follow-ups, update the CRM and tell you what to do next.

So here’s a question.

If you handed your go-to-market engine to an agent tomorrow, what exactly would it run?

For most businesses, the answer is whatever happens to be in the heads of three people. Plus a spreadsheet nobody trusts and a Slack channel where decisions go to die.

That’s the problem. You can’t apply AI to something that doesn’t exist. If you throw it at a process that hasn’t been designed properly, it won’t fix anything. It’ll just help you fail faster.

The fantasy of the self-driving engine

I hear a version of this almost every week. “We’re looking at agentic.

Once that’s in, we’ll just talk to the AI, and it’ll run things.”

I get why it’s appealing. The pitch is that you skip the hard work, describe what you want and let the machine work out the rest.

But that isn’t how it works. An agent doesn’t invent your operating model. It carries one out.

If you haven’t defined the operating model, the agent is just making it up as it goes. That’s exactly what your team has been doing, except now it happens at machine speed.

AI doesn’t fix chaos. It speeds it up

Automation does what it’s told, and it does it quickly. That’s the whole point of it, and it’s also the risk.

Automate a sequence that’s aimed at the wrong list, and you don’t just waste a few emails. You burn hundreds of prospects in an afternoon. They become dead data, and you don’t get them back.

Let AI write content with no positioning behind it, and you don’t build authority. You get more of that scratchy, static noise kind of content, and you get it faster.

Then hand an agent a workflow with no approval step. Something goes out to a client that nobody signed off. Well, good luck explaining that one.

None of these are technology problems.

They’re design problems that the technology has made louder and quicker to fail.

You can’t train it on a hunch

Most GTM teams get caught out with agentic with one major failing point.

An agent needs something to base itself on. Something to learn from. It needs to know what good looks like, who owns which decision, what happens next and where the line sits between “send it” and “check with someone first”.

If it isn't designed, what are you even teaching it? If it is designed, but isn’t written down, it can’t be trained. If it can’t be trained, you can’t trust it to deliver. If you can’t trust it to deliver, it isn’t saving you any time.

You’ve just added another thing to babysit.

You can’t automate a guess. You can’t train an agent on a hunch. You can’t delegate a process nobody has defined.

The boring bits are the engine

This is the part nobody wants to hear, because it’s not exciting. Before AI does anything useful in your go-to-market, you need the following:

Roles and responsibilities. Who owns pipeline, who owns content and who owns the handover between them. Write down names, not departments.

Workflows. What happens, in what order, and what triggers each step.

Approval flows. Who signs off what, and how quickly.

Quality gates. What “good enough to go out” actually means, defined clearly enough that someone other than you could apply it.

Production flows. How an idea becomes a post, a sequence or a proposal without six people touching it twice.

Operational flows. How your systems talk to each other, and what each one is expected to do when they do.

Is it glamorous? Not even slightly. But this is the engine. AI is the fuel injection. Brilliant when there’s an engine to fit it to, and pointless when there isn’t.

That’s not an AI problem. That’s an operating model problem.

The most literal new hire you’ll ever have

If you’re taking your first steps towards agentic GTM, this is the test I’d use.

Could you write your go-to-market engine down clearly enough that a new hire could run it properly in their first week? I don’t mean shadowing someone or “picking it up as they go”. I mean reading it and doing it.

If the answer is no, an agent can’t support it either.

An agent is the most literal new hire you’ll ever have. It’s fast, it doesn’t get tired, and it does exactly what it’s been shown. It won’t read between the lines or remember how Sarah likes it done. It has nothing to go on except the process you’ve defined.

So do the thinking first. You’ll either pay for it now in hours or later in rework, burnt relationships and a very awkward conversation about why the shiny new AI investment made things worse.

The upfront thinking feels slow. Skipping it is what actually slows you down.

Give every agent a job description

This is the shift most businesses haven’t made yet.

Stop thinking about agents as tools. Start thinking about them as virtual team members.

You wouldn’t hire someone without a job description. You wouldn’t bring them in and say “just help out with the sales stuff”. You’d tell them what they own, what they don’t, who they report to and how you’ll know they’re doing a good job.

Agents need exactly the same.

That starts with use cases. Not “we want to use AI in sales”, but specific jobs. One agent researches accounts before a first conversation. Another drafts follow-ups after a discovery call. Another keeps the CRM clean. Each one has a clearly defined job, and it’s a job you’ve already done well enough by hand to know what good looks like.

Then you need roles and responsibilities for every agent.

What the agent owns. What it’s not allowed to touch. Who it hands work to. Who checks its output before it goes anywhere near a client.

Get that wrong, and you haven’t built a team. You’ve hired a load of very keen interns with no manager and full access to your CRM.

Let’s wrap this up

So what’s the real opportunity here?

AI and agentic ways of working are going to change how go-to-market engines run. I’m not arguing against that. I’m all in on it. It’s transforming GTM engines right in front of our eyes.

But the businesses that get the most out of it won’t be the ones that adopt it first. They’ll be the ones that did the boring work before they switched it on.

Luck doesn’t scale. Chaos doesn’t scale. Systems do.

Build the engine first. Define it. Document it. Then go on the agentic journey.