Toronto — January 9, 2026 — SideSpin Inc. today announced the filing of U.S. and Canadian provisional patent applications covering a System and Method for Deterministic Interactive Experience Execution with Asynchronous Content Preparation and Controlled State Progression

Patent-Pending Deterministic State Machine for Human Perception on Digital Devices: Makes Interactive AI Experiences Stable, Predictable, and Future-Proof**

This invention enforces a clean split between execution control logic and presentation content. It uses a strict state machine to advance experiences only when declarative conditions are met—never because background work finished early or late.

Future content is prepared asynchronously and held safely in a constrained buffer containing only presentation payloads. Control logic is forbidden from leaking into content. Progression stays deterministic, replayable, and identical across runs, devices, and network conditions—no flicker, no races, no “works on my machine” bugs.

Key features

• Progression is locked to explicit rules, not timing.
• AI can prepare next frames/scenes/states ahead of time without showing them too soon.
• Content is validated and stripped of anything that could hijack control.
• Every visible step is logged in an append-only record → exact replay of what the user saw.

Why this becomes a killer invention as ML/LLM models improve Better models will forecast future states, predict user actions, and generate upcoming frames or content with high accuracy. This system lets them prefetch and pre-render aggressively—while guaranteeing nothing appears until the exact right moment. The faster and more accurate prediction gets, the bigger the performance and smoothness gain, without sacrificing safety or determinism.

Atif Rashid quote
“Modern interactive systems mix control, state, and content in ways that create flicker, races, and unpredictable results. This invention separates them completely—making progression deterministic and safe, while still letting powerful AI prepare future content as early and aggressively as possible.”

What it unlocks

• Rock-solid AR/VR, games, simulations with heavy AI generation
• Reliable real-time personalization and forecasting
• Deterministic experiences on edge devices with spotty networks
• Audit-proof replay for training, debugging, compliance
• Safe acceleration as predictive ML/LLM capabilities explode

Key capabilities (high-level)

• Render-tick execution: Progression decisions occur on render ticks using declarative gating conditions rather than background completion timing.
• Constrained buffering: The buffer holds prepared presentation payloads only, preventing prepared content from taking control of routing, permissions, or side effects.
• Self-healing preparation: Buffer management can handle readiness tracking, timeouts, retries, and request scheduling without compromising deterministic progression.
• Deterministic reconstruction: Recorded presentation-sequence indexing supports precise replay of the user-perceived experience.
• Safer integration with variable-latency systems: The architecture tolerates asynchronous and distributed computation while maintaining predictable UX.

Performance advantages and UX stability

The invention is designed to improve both actual and perceived performance by preventing asynchronous work from destabilizing what the user sees:

• Improved perceived latency through controlled gating: The user-visible experience advances only when conditions are satisfied, preventing “half-ready” screens, flicker, and reflow that degrade perceived quality.
• Prefetching without correctness risk: Asynchronous preparation enables aggressive prefetch and ahead-of-time computation, while constraints ensure prepared payloads cannot alter control flow.
• Reduced jank from race conditions: By separating perceptual time (what is presented) from compute completion time (when preparation finishes), the system avoids timing races that often cause missed frames, duplicated transitions, or inconsistent navigation.
• Predictable resource usage: A buffer manager can maintain a bounded working set (current + upcoming states), improving memory locality and reducing unnecessary recomputation.
• Replay-driven debugging efficiency: Deterministic reconstruction reduces time spent reproducing “rare timing” bugs, improving long-term UX stability and performance regression control.

It's the best and only way to handle human perception from AI

Many existing UI and workflow runtimes implicitly let asynchronous completions drive what happens next (e.g., “when the fetch resolves, navigate,” “when render completes, advance,” “when the promise finishes, update state”). In these models, control logic and prepared content often intermix, and late-arriving results can produce nondeterministic outcomes.

This invention is different in that it enforces a controlled execution model:

• Control-plane separation is structural, not conventional: Prepared content is architecturally constrained to be presentation-only; it is not “trusted application code.”
• Progression is declarative and deterministic: Advancement occurs when declared interaction/gating conditions are satisfied, not when compute happens to finish.
• Validation is a first-class mechanism: Schema validation, provenance checks, and index bounds checks explicitly prevent malformed or adversarial payloads from influencing execution.
• Replay is built in: The system records what was presented using presentation-sequence indexing, enabling deterministic reconstruction independent of backend timing.

The result is an interactive experience runtime that remains predictable under real-world latency and concurrency, while supporting auditability and long-lived reliability.

Availability

The disclosed invention is the subject of filed provisional patent applications in the United States and Canada. For inquiries or to request a technical briefing, contact press@atifrashid.com.

About the invention

The invention relates to computer-implemented systems and methods that execute interactive experiences using deterministic state machines while asynchronously preparing future presentation payloads in constrained buffers, enforcing schema-based separation between control logic and prepared content, and generating replayable audit logs indexed to user-perceived presentation sequences.