We’ve already seen what happens when systems can’t reconcile surprises quickly enough. Within 48 hours of Nicolás Maduro’s arrest on January 3, 2026, at least seven AI-generated or miscaptioned images and videos were viewed more than 14 million times on X before the verified information stabilized. Competing versions of reality are spreading faster than institutions can solve them.
This dynamic is no longer limited to organizations such as the secret service. Go-to-market teams now operate in the same environment. Annual plans assume stability. GTM does not work.
Signals arrive early and unevenly. The reporting changes halfway through the quarter. Sales adjusts the language deal by deal. RevOps codes logic that few people remember agreeing on. Teams move fast, but the system struggles to keep up. Most GTM plans don’t fail right away. They slowly stop reflecting reality.
When GTM changes
Decisions come sooner. They don’t get any easier. They become riskier. People hesitate, looking for confirmation, alignment or air cover before they act.
When the system can’t make calls, teams fill the gap themselves. Meetings are added. Decisions are escalated. Judgment replaces structure because there is nothing else to rely on. This is where teams start rescheduling because they don’t know how to rebalance.
At that point, the problem is no longer the tool. It is the absence of a system that can absorb changes. Moving faster doesn’t solve this. It strengthens it. Whatever logic already exists is applied more often, by more people, with less time to resolve disagreements.
The image above shows why the steering breaks down at high speeds. As signal volume increases, teams interpret reality differently. Decisions slow down even as activity speeds up. This is where GTM quietly loses weeks without realizing it.
Why execution alone is no longer enough
For years, improving GTM meant better executing campaigns, transfers, and tools. That approach worked when the planning cycles were longer than the execution cycles. Today the opposite is true.
When decisions come faster than plans can change, teams must redo their forecasts, reorder their priorities and rewrite the maps. Replanning feels responsible. It’s also expensive. It introduces delay, shifts the focus from learning to justification, and trains teams to wait rather than react.
The problem isn’t that plans change. It is that change comes late and after decisions have already been made. What’s missing isn’t better planning. It’s a way to adjust it without destabilizing everything else.
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Rebalance instead of replan
Other domains have encountered this problem before. Portfolios are not rebuilt every quarter. They have been adjusted. The allocation shifts as conditions change while maintaining direction. Loads are optimally harvested.
GTM now requires the same logic. Rebalancing maintains intention while adjusting effort, budget, and focus. It allows teams to respond early, before disagreements escalate into conflict and before small changes require big resets. Some teams have already moved in this direction, often without mentioning it.
FORE is the framework that manages this shift. It stands for focus, observation, rebalancing and evaluation. It’s a self-learning way to manage GTM decisions as conditions change – the simplest way I’ve seen teams stay aligned.
Here you can read how rebalancing works in practice.
- Focus determines what is important.
- Observation reveals early signals.
- Rebalancing adjusts the allocation without destabilizing execution.
- Evaluation feeds what has been learned back into the system.
The direction is maintained while adjustment takes place. FORE does not replace the annual planning. It changes how plans behave once reality intervenes.
Early detection of GTM dysfunction
When decisions need to be made quickly, the data usually exists somewhere in the company. Getting into it, relying on it, or agreeing on what it means is where teams get stuck.
Marketing drives positioning. Sales builds messages every day. Product speaks in features. RevOps encrypts scoring and routing. Customer success reframes post-sale value.
If there is no shared semantic core, each function adapts locally. Sales messages wander while sales teams in the field make messaging decisions. AI accelerates this by automating it.
This is why many teams embed customization into a GTM operating system. Not to add processes, but to make definitions explicit. Systems cannot reason about ambiguity. Without shared definitions, automation increases divergence.
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Top-down intention, bottom-up reality
Most GTM failures are not caused by poor strategy or poor execution. They happen during the transfer between the two. Leaders talk about results and direction. Operators work within constraints and tradeoffs. Leaders say, “Move faster.” Operators hear: ‘Just figure it out.’
When leaders don’t make it clear what needs to remain consistent, operators adapt. When that adjustment occurs without guardrails, the alignment shifts. AI accelerates both sides. It doesn’t close the gap. It makes it easier to fall into it.
What is missing is a shared system at the center that answers fundamental questions: what remains fixed, what can change, who decides when conflicts are identified and how learning flows back in the right direction. This is where FORE fits in.
Most teams start in the wrong place. They build outwards. They deploy agents and automate workflows. The teams that make progress build inward first.
Before anyone starts building, teams must decide what to share. Four questions should have the same answers for marketing, sales, product, and RevOps:
- What problem are we solving?
- Which results prove value?
- Which signals justify adjustment?
- What do we explicitly not optimize for?
If these answers differ, automation will scale silos.
Then build one decision loop, not multiple workflows. “If signal X changes, we shift Y effort for a Z period.”
No tooling or AI required, just agreement. Adaptive systems must be one. Teams may vary. Individuals can optimize.
Control is a system outcome
This is not a return to moving quickly and breaking things. In B2B, breaking things damages trust. The capabilities allow teams to move. Management allows them to scale up. AI is fuel, not a strategy.
The teams that perform best in the coming years will not plan better. They will balance more effectively. They will align before they build. Their systems absorb surprises without crumbling. This way, control is rebuilt when the speed can no longer be slowed down.
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