{"id":166,"date":"2026-08-28T16:19:16","date_gmt":"2026-08-28T15:19:16","guid":{"rendered":"https:\/\/aigtmstudio.com\/blog\/what-happens-to-your-gtm-systems-after-you-raise\/"},"modified":"2026-10-01T14:45:06","modified_gmt":"2026-10-01T13:45:06","slug":"what-happens-to-your-gtm-systems-after-you-raise","status":"publish","type":"post","link":"https:\/\/aigtmstudio.com\/blog\/what-happens-to-your-gtm-systems-after-you-raise\/","title":{"rendered":"What Happens to Your GTM Systems After You Raise"},"content":{"rendered":"

This piece is for founders first, because you make the final decision. <\/p>\n

It’s also for the rest of go-to-market leadership who live with the consequences of that decision: CROs, VPs of sales, CMOs and RevOps. It’s about what happens after you’ve raised a milestone funding round, predominantly seed, Series A and Series B, and how that impacts building your go-to-market systems and your go-to-market motion. <\/p>\n

I’ll cover the patterns I typically see at each stage of scale, how AI plays a role in that, and how it changes your overall go-to-market strategy and motion.<\/p>\n

Where the money goes, and what gets missed<\/h2>\n<\/p>\n

Usually, there’s a big push for hiring and adding headcount, which is where a large amount of the fundraising money goes. There is probably a decent amount of rethinking strategy too. I’m not sure there’s always enough joined-up thinking between product market strategy and the go-to-market strategy that supports it.<\/p>\n

This is where Brian Balfour’s Four Fits framework is worth revisiting. In The Four Fits: A Growth Framework for the AI Era<\/a>, Balfour sets out Product Market Fit, Product Channel Fit, Channel Model Fit and Model Market Fit, and argues that a company must achieve all four to reach $100 million at venture speed. As he puts it: “Everyone knows about Product Market Fit. And while it is one of the Four Fits, it’s only one of them.”<\/p>\n

He describes the companies where all four click as Smooth Sailers, “a little effort for lots of speed”, and the ones where they don’t as Tugboats: “It feels like pushing a boulder uphill. Despite executing the best growth practices, picking the low-hanging fruit, and having a great team, they struggle to grow.”<\/p>\n

I think the Four Fits is probably rarely, if ever, used post-funding, and certainly not revisited, when it comes to making sure all four fits of go-to-market fit are in place, which, as I said, also includes product market fit. Balfour himself wrote that “The fits are always evolving\/changing\/breaking. When that happens, you can’t simply change one element, you have to revisit and potentially change them all.”<\/p>\n

What got you here won’t get you there<\/h2>\n<\/p>\n

Another mistake founders often make is expecting that what got them to this fundraise is what will get them to the next one, when actually they often have to re-discovery product market fit in new areas. <\/p>\n

For example, they have to land new ICP customers, which is a whole new adjacent extension of their current go-to-market, or they need to launch into new markets, or they need to launch new products or product extensions. Sometimes, they’re doing all three together!<\/p>\n

Those are all challenging, because it’s actually not just scaling what’s already worked. It’s trying to do that and not take your eye off the ball. So not killing the golden goose while also finding ways to win in those new areas. It’s the startup’s versions of the Innovator’s Dilemma.<\/p>\n

The other thing that I frequently see, is that teams don’t mature their go-to-market systems fast enough. Key processes and the foundations that allow for smoother scaling don’t mature in lockstep with the growth in headcount and growth in uncertainty as they’re exploring new areas, which means everything gets incredibly messy and ambiguous. <\/p>\n

This is often where teams start pulling apart. What seemed like a well put together and smooth operation is suddenly feeling like there’s lots of fires burning, and no one can quite figure out why.<\/p>\n

Why founders don’t see it coming<\/h2>\n<\/p>\n

Of course, not every founder is blindsided by GTM system failures. Some can see it because they might have really struggled to produce the data, the trends and the insights they needed in the run up to their fundraise.<\/p>\n

However, on the whole, I think most founders are probably at the height of their systems maturity curve for that level of growth prior to the fundraise, and therefore their systems are probably in the best place they will be until the next wave of growth. So they probably think it’s in a pretty good place and are surprised at just how quickly those systems strain under the pressure and stop being fit for purpose.<\/p>\n

Headcount isn’t a linear complexity curve<\/h2>\n<\/p>\n

I think it’s easy to misunderstand just how complex an organisation can become as it scales. Adding headcount is actually not a linear complexity curve, because you’re adding nodes. And each node has a multi-directional relationship with every other node.<\/p>\n

Let’s say you’ve already got 15 people in your go-to-market team and you add one more: that’s now 16 different nodes plus different pathways between this extra person and all the existing ones. And it shifts the dynamic of those existing ones as well. So you can see how it becomes very nonlinear in terms of the complexity curve.<\/p>\n

The nature of those roles also tends to change. Whereas at the beginning you might just have three or four account execs, suddenly they become more nuanced. You might have SMB reps and enterprise reps. You might have US reps and UK reps. You might have AEs aligned to one industry or another industry. Potentially, you have all of those different distinctions. Each one of those reps might need slightly different things from your systems, from your CRM and so on. They might have slightly different ways of working. And where they are in their own go-to-market motion and maturity is going to be different.<\/p>\n

Hard-won lessons don’t always transfer<\/h2>\n<\/p>\n

One thing that does surprise founders and revenue leaders is how little overlap you sometimes get between the hard-won lessons in one motion and the next. You might be going after a mid-market tier of account in industry X. Then, post-fundraise, you decide to go upmarket in industry Y. Even though you had product market fit in the first industry and sector, you really don’t in the next one, and what helped you win in that first segment doesn’t necessarily help you win in the second one. I think that’s often a chastening lesson for founders and their revenue leaders.<\/p>\n

The old guard pushes back<\/h2>\n<\/p>\n

Founders and the leadership team can also get a bit blindsided by some of the resistance their team shows to upgrades or updates in systems and ways of working. The ‘old guard’ might consider that the new ways of working being imposed are the business becoming more bureaucratic and less flexible, and they might hanker for those good old days, and to an extent that may well be true. It doesn’t mean it’s not necessary. (And it doesn’t have to be stifling – if anything, good AI systems meet reps where they’re already being productive…but in the past the ‘scaling system’ could often be suffocating with discipline they called for).<\/p>\n

Regardless of the merits of that pushback, it’s surprising for founders how resistant older, more tenured employees can be to those changes.<\/p>\n

Building the plane while flying it<\/h2>\n<\/p>\n

Overall, it’s that problem of jumping off a cliff and building the plane while trying to fly it at the same time. As your go-to-market is being executed, what the system needs to look like to deliver changes almost daily, certainly weekly. So it becomes this changing goalposts, movable feast. I think that complexity of building the thing while executing against it really surprises a lot of leaders.<\/p>\n

Where AI earns its keep<\/h2>\n<\/p>\n

AI is definitely the thing that should and could be absorbing some of that complexity. Where AI and agentic systems can really earn their keep is where it becomes too difficult to legislate for every single edge case and build deterministic systems that keep up with the pace and complexity of a growing go-to-market team.<\/p>\n

So building systems flexible enough that they don’t need every rule and edge case hard coded into them in order to work, and can instead rely on strong agentic decision making, becomes a huge compounding advantage. That’s especially true if it’s coupled with a loop that allows the managers of that system to feed back to it and calibrate it, making it essentially self learning and self improving. That is then the basis of a dynamic, AI-based system that can underpin a team’s growth for potentially many years and multiple rounds.<\/p>\n

This is also the best way to avoid the recalcitrance of tenured team members pushing back against a rigid new system.<\/p>\n

When to install it, and what has to be true first<\/h2>\n<\/p>\n

The obvious pushback is that AI can only enhance what is already working. I think if the team have reached the point of successfully fundraising, there’s a very strong chance that is off the back of a go-to-market that is already working. So that’s a good place to start to install your AI system.<\/p>\n

The reason you need the feedback loop is that you need to start to see as and when it does break, or starts to break, as you expand and grow the team, move into new markets or test out different motions. So I think it’s never too early to start installing an AI system that, at the very least, captures and helps codify and understand what is working.<\/p>\n

I don’t think AI should replace humans, so I’m not advocating that you install an AI system that executes the go-to-market strategy. Rather, it helps to coordinate it and inform it. It can help with things like lead classification, routing, segmentation and TAM mapping. It can help with coaching the team, brainstorming, positioning, coming up with ad concepts, sales enablement and signals. All of these are incredibly powerful piping that almost no human ever has the time, resources or willpower to execute properly as a team scales.<\/p>\n

That’s where AI can do an amazing job, as well as capturing everything that’s going on at the execution layer, routing it back in the right way, systemising it, classifying it, and pulling up any interesting findings for managers and senior leaders to review: potential discrepancies, outliers where it thinks things are working really, really well, or areas that are potentially breaking. Those are all fantastic candidates for AI implementation.<\/p>\n

Where I don’t think you want to throw it in, possibly ever, but certainly not straight after a fundraise, is things like getting it to write your emails, conduct calls, do any kind of customer outreach or run your actual marketing campaigns. Those are all areas where I still strongly advocate that you have a human certainly in the loop, and ideally entirely in the driving seat.<\/p>\n

The biggest mistake at each stage<\/h2>\n<\/p>\n

Seed.<\/strong> Trying to make things too complex before it’s needed. Arguably you’re still proving out PMF in your core market and product, so you don’t want to be building for multiple GTM motions, markets and products, despite the allure of “doing more and going faster”.<\/p>\n

Series A.<\/strong> Expecting too many lessons to be easily transferable, and mistaking the success of your current team for super repeatable processes and frameworks, when often it’s still hard-won individual lessons and heroic efforts that are driving results. It means there isn’t enough put into enablement for the new wave of hires.<\/p>\n

Series B.<\/strong> Now there’s a chance you underestimate the complexity of your near-future GTM teams, and don’t allow for enough flexibility and dynamism in the systems you’re building.<\/p>\n

You fall to the level of your systems <\/h2>\n<\/p>\n

In Atomic Habits, James Clear famously wrote “You do not rise to the level of your goals. You fall to the level of your systems.”<\/p>\n

I believe this is true of GTM teams too.<\/p>\n

Post-fundraise, everyone is giddy with excitement and flushed by the potential ahead. Goals are lofty. <\/p>\n

But 6-months later, many teams are in the trough of the despair, struggling to meet the incredible demands needed to make those aspirations happen.<\/p>\n

Often it’s because the foundations were not put in place, and it becomes impossible to hit huge milestones from willpower alone at some point.<\/p>\n

Where to start<\/h2>\n<\/p>\n

I’d love to help you avoid any (and all) of the failures highlighted above.<\/p>\n

If you’ve just raised, or you’re about to, speak to me about a GTM Systems Diagnostic, so I can help pinpoint any weak points and help you build resilience into the foundations that underpin your scaling GTM motion.<\/p>\n","protected":false},"excerpt":{"rendered":"

This piece is for founders first, because you make the final decision. It’s also for the rest of go-to-market leadership who live with the consequences of that decision: CROs, VPs of sales, CMOs and RevOps. 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