Future Tokens: Corrective Instruments for AI Reasoning

Every AI output has structural blind spots. Coherence optimization suppresses gaps. Token-level generation locks in frames before alternatives are considered. Confidence distributes smoothly over claims that deserve scrutiny in different places. These aren't random errors — they're predictable artifacts of how generation works.

Future Tokens operations are named, composable instruments that target specific blind spot types. Each one reliably surfaces information that the generation process systematically omits, because the blind spots are structural, not random. And they're generative — every pass changes the consideration space, shifting the blind spot geometry so the next pass finds new material.

Part of the FUTURE TOKENS project.

This collection is compatible with both Claude and Codex workflows.

When to use

If you just produced an output, it has predictable gaps. Match what you built to the operation that catches what it missed.