The solid-state battery dendrite demo is different from the motion-control demos, but the structure is similar. A fixed formation control policy leaves residual risk signals. TightLoop attempts to reduce those residuals through adaptive correction.

The digital twin tracks residual, overpotential, and dendrite-risk proxy behavior. These are not direct production claims. They are simulation proxies for a control problem where small persistent deviations can matter.

The useful framing is not “AI solves dendrites.” It is that formation and process-control policies may benefit from a residual layer that watches how risk proxies evolve under the current control action.

A real validation path would need experimental data, electrochemical constraints, domain-specific safety limits, and a much stricter cost function. The demo is early-stage compared with the motion and Sentinel lines.

Still, it belongs in the archive because it shows the same architectural bet: residuals are not noise to ignore. Sometimes they are the remaining structure the product should learn from.