Thinkingsand / 2026
Runtime control for AI in real workflows.
Researching how models can be steered inside the systems teams already depend on, where context shifts faster than prompts can hold.
AI gets dropped into workflows as a black box.
The prompt becomes the only control surface. That falls apart once the task, the audience, and the stakes start moving underneath the system.
Real work is conditional, shifting, and accountable.
We think there is a control layer between prompting and finetuning.
Runtime steering means intervening in how a model behaves, not only what it is told. That is where enterprise AI starts to become governable.
A usable system needs control that survives changing context.
The agenda is runtime behaviour that is precise enough to deploy.
Steering geometry, cross-model portability, minimal interventions, and drift forensics all point toward behaviour that can be measured, stabilized, and audited.
Less black box. More legibility, repeatability, and control.
Contact
Start the conversation.
For research updates, early collaboration, or direct inquiries.