Over the last decade, the volume of signal flowing through GTM has changed completely. Google searches now exceed 5 million a minute. Social posts top 500,000 a minute. Video creation has grown 10x, with more than 500 new hours uploaded every minute. AI accelerated this shift by making nearly everyone a creator. When signals reach this scale, attention becomes the constraint.
We have already seen what happens when systems can’t reconcile surprises fast enough. Within 48 hours of the Jan. 3, 2026, capture of Nicolás Maduro, at least seven AI-generated or miscaptioned images and videos reached more than 14 million views on X before verified information stabilized. Competing versions of reality spread faster than institutions could resolve them.
This dynamic is no longer limited to organizations like the Secret Service. Go-to-market teams now operate in the same environment. Annual plans assume stability. GTM work does not.
Signals arrive early and unevenly. Messaging shifts mid-quarter. Sales adapts language deal by deal. RevOps encodes logic that few people remember agreeing on. Teams move quickly, but the system struggles to keep up. Most GTM plans do not fail outright. They slowly stop reflecting reality.
When GTM changes
Decisions start arriving earlier. They don’t get easier. They get riskier. People hesitate, looking for confirmation, alignment or air cover before acting.
When the system can’t make the call, teams fill the gap themselves. Meetings get added. Decisions get escalated. Judgment replaces structure because there is nothing else to rely on. This is where teams start replanning because they do not know how to rebalance.
At that point, the problem is no longer tooling. It’s the absence of a system that can absorb change. Moving faster does not fix this. It amplifies it. Whatever logic already exists gets applied more often, by more people, with less time to resolve disagreements.
The image above shows why control breaks down at high speeds. As signal volume increases, teams interpret reality differently. Decisions slow down even as activity accelerates. This is where GTM quietly loses weeks without realizing it.
Why execution alone is no longer enough
For years, improving GTM meant executing better — campaigns, handoffs and tools. That approach worked when planning cycles were longer than execution cycles. Today, the opposite is true.
When decisions arrive faster than plans can change, teams reforecast, reshuffle priorities and rewrite decks. Replanning feels responsible. It’s also expensive. It introduces lag, shifts attention from learning to justification and trains teams to wait rather than respond.
The issue is not that plans change. It’s that change arrives late and after decisions have already been made. What is missing is not better planning. It’s a way to adjust it without destabilizing everything else.
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Rebalancing instead of replanning
Other domains have faced this problem before. Portfolios are not rebuilt every quarter. They are adjusted. Allocation shifts as conditions change while direction holds. Taxes are harvested optimally.
GTM now requires the same logic. Rebalancing preserves intent while adjusting effort, budget and focus. It allows teams to respond early, before disagreements harden into conflict and before small changes require large resets. Some teams have already moved in this direction, often without naming it.
FORE is the framework that manages this shift. It stands for focus, observe, rebalance, and evaluate. It’s a self-learning way of managing GTM decisions as conditions change — the most straightforward way I’ve seen teams stay aligned.
Here’s how rebalancing works in practice.
- Focus defines what matters.
- Observation surfaces early signals.
- Rebalancing adjusts allocation without destabilizing execution.
- Evaluation feeds learning back into the system.
Direction holds while adaptation happens. FORE does not replace annual planning. It changes how plans behave once reality intervenes.
Detecting GTM dysfunction early
When decisions need to be made quickly, the data usually exists somewhere in the company. Getting to it, trusting it or agreeing on what it means is where teams get stuck.
Marketing drives positioning. Sales builds messaging daily. Product speaks in features. RevOps encodes scoring and routing. Customer success reframes value after the sale.
When there is no shared semantic core, each function adapts locally. Sales messaging wanders as sales teams make messaging decisions in the field. AI accelerates this by automating it.
This is why many teams anchor adaptation inside a GTM operating system. Not to add process, but to make definitions explicit. Systems can’t reason over ambiguity. Without shared definitions, automation multiplies divergence.
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Top-down intent, bottom-up reality
Most GTM breakdowns are not caused by bad strategy or poor execution. They happen in the handoff between the two. Leaders speak in outcomes and direction. Operators work inside constraints and tradeoffs. Leaders say, “Move faster.” Operators hear, “Figure it out.”
When leaders don’t make clear what must stay consistent, operators adapt. When that adaptation happens without guardrails, alignment slips. AI speeds up both sides. It doesn’t close the gap. It makes it easier to fall into.
What is missing is a shared system in the middle that answers basic questions — what stays fixed, what can change, who decides when signals conflict and how learning flows back into direction. This is where FORE fits.
Most teams start in the wrong place. They build outward. They deploy agents and automate workflows. The teams that make progress build inward first.
Before anyone builds, teams need to decide what to share. Four questions should have the same answers across marketing, sales, product and RevOps:
- What problem are we solving?
- What outcomes prove value?
- Which signals justify adjustment?
- What are we explicitly not optimizing for?
If those answers differ, automation will scale silos.
Next, build one decision loop, not multiple workflows. “When signal X changes, we shift Y effort for Z period of time.”
No tooling or AI required, just agreement. Adaptive systems need to be one. Teams can vary. Individuals can optimize.
Control is a systems outcome
This is not a return to moving fast and breaking things. In B2B, breaking things breaks trust. Capability allows teams to move. Management allows them to scale. AI is fuel, not strategy.
The teams that perform best in the coming years will not plan better. They will rebalance more effectively. They will align before they build. Their systems will absorb surprise without crumbling. That is how control is rebuilt when speed can no longer be slowed.
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