CDFAM Computational Design Symposium — Tokyo 2026
Sarat Babu · SARAT
Computational design approaches to optimization are often constrained by the tools available and the established methods for generating optimal forms. With AI coding tools, the barrier for designers to develop their own software and pipelines has dropped considerably.
Sub-Optimal reframes optimization around two priorities: preserving the original designer’s macro intent, and using geometry to address the anisotropic surface roughness of additive manufacturing. The result is neither lattice application nor topology optimization, but a grown internal structure driven by simulation, surface texture and build orientation that remains largely invisible at the macro level.
The talk covers the trust gap senior engineers face with optimized DfAM parts, the use of surface texture to mask layering defects and build orientation, and how the pipeline was built in six weeks for about $400 in AI tokens using open-source libraries including geometry3Sharp and OpenVDB, with 3MF as the output format.
Links
Talk page with full transcript
