AI will be dramatically more capable in six months, so anything built today will be obsolete before the project is finished.
Wait. Prepare. Position the organization. Do not build yet.
That is the logic of the Scepter of Infinite Acceleration.
The Scepter is a roadmap or strategy document that turns projected AI progress into a reason for organizational paralysis. Its argument sounds sensible because part of it is true. Models are improving quickly. Some tasks that are difficult today may be easy in six months. A technical choice made now may look foolish later.
The Scepter takes that truth and applies it to everything.
There will be a better model next quarter. There will also be a better model the quarter after that. If the team keeps treating the next improvement as the proper time to begin, starting becomes impossible. The project remains in preparation, surrounded by thoughtful documents and unmade decisions.
This is procrastination with a trend line.
The argument is especially powerful in organizations that value strategic thinking. A plan that accounts for future AI capability sounds responsible. It sounds as if the team is avoiding wasted effort and preparing for the technology that will matter. That reasoning would be useful if it ended with a decision to build.
The Scepter's trick is replacing "build" with "prepare." Preparation can continue indefinitely without producing anything a user can touch. The team can conduct evaluations, compare vendors, revise the architecture, update the roadmap, and wait for the next model release. Every activity looks defensible. None of them creates evidence about the actual product.
Delay also has a convenient risk profile. A premature build that fails is visible. Someone can point to the decision, the cost, and the result. A delayed project fails more quietly. The consequences spread across missed learning, lost time, and opportunities that are hard to measure. Nobody has to explain why a specific technical choice was wrong because no choice was made.
You cannot be wrong about a decision you keep pending.
That does not mean every project should start immediately or that teams should ignore changing tools. Waiting can be rational when the current technology cannot meet a real requirement, when the cost of starting is unusually high, or when a short, defined evaluation will answer an important question.
The important words are "short" and "defined."
"Wait until the model is ready" is not a start condition. It is an escape hatch. A real condition would say what the model must do, how the team will test it, and when the evaluation ends. If the requirement is met, the project starts. If it is not, the team makes a different decision. Either way, the evaluation has an endpoint.
Most teams also underestimate what they learn by building. A small working version exposes data problems, user confusion, operational constraints, and missing requirements that no strategy document can fully predict. Those lessons remain useful even when the underlying model improves.
The model will be better in six months if you start today. You will also have six months of product knowledge, test cases, and feedback. The team that waited has only a newer model.
Set a date. Choose a narrow first version. Define what evidence would justify continuing, changing direction, or stopping. Build enough to learn something real, then revisit the assumptions with evidence in hand.
The future does not need your permission to improve. It will keep improving while you work.
The Scepter loses its power when a team treats progress as a reason to learn now rather than a reason to postpone learning forever.