To trust an agentic AI, users need to see its work, just as a manager would with a new intern. Design patterns like "stream of thought" (showing the AI reasoning) or "planning mode" (presenting an action plan before executing) make the AI's logic legible and give users a chance to intervene, building crucial trust.

The next frontier for Neuralink is "blindsight," restoring vision by stimulating the brain. The primary design challenge isn't just technical; it's creating a useful visual representation with very few "pixels" of neural stimulation. The problem is akin to designing a legible, life-like image using Atari-level graphics.

Reinforcement Learning with Human Feedback (RLHF) is a popular term, but it's just one method. The core concept is reinforcing desired model behavior using various signals. These can include AI feedback (RLAIF), where another AI judges the output, or verifiable rewards, like checking if a model's answer to a math problem is correct.

Designing for users with motor disabilities who control interfaces with their minds presents a unique challenge. Unlike typical design scenarios, it's impossible for designers to truly imagine or simulate the sensory experience, making direct empathy an unreliable tool for closed-loop interactions.

The team obsesses over perfecting the BCI cursor, treating it as the key to user agency on a computer. However, the long-term vision is to eliminate the cursor entirely by reading user intent directly. This creates a fascinating tension of building a masterwork destined for obsolescence.

Cues uses 'Visual Context Engineering' to let users communicate intent without complex text prompts. By using a 2D canvas for sketches, graphs, and spatial arrangements of objects, users can express relationships and structure visually, which the AI interprets for more precise outputs.

For frontier technologies like BCIs, a Minimum Viable Product can be self-defeating because a "mid" signal from a hacky prototype is uninformative. Neuralink invests significant polish into experiments, ensuring that if an idea fails, it's because the concept is wrong, not because the execution was poor.

Neuralink's initial BCI cursor used color to indicate click probability. As users' control improved, the design evolved to a reticle that uses motion and scale for feedback. This change was more effective because the human eye is more sensitive to motion than color, and it better supported advanced interactions.

To help a participant with ALS who couldn't use voice commands to pause the BCI cursor, Neuralink created the "parking spot," a visual gesture-based toggle. This solution, designed for a specific edge case, was immediately adopted by all other participants as a superior, universally valuable feature.