The Photonic industry is now pushing toward co-packaged optics with targets such as <$0.25/Gbps cost, ~1 pJ/bit energy efficiency, and >0.5 Tbps/mm² density, which effectively demands >10× improvements in energy efficiency and up to ~90% cost reduction compared to current pluggable systems. Yet the present PIC development flow remains highly fragmented—spanning EM/device/circuit simulation, layout, DRC, tapeout, fabrication (often ≥3-month cycles), testing, and packaging—with each step requiring heavy human-driven iteration. As complexity grows, the bottleneck is less about ideas and more about converting them into qualification-ready hardware at fab-compatible speed and repeatability.

This is precisely where agentic execution platforms could unlock structural leverage. Integrating currently disjointed photonic design tools into a unified, automated workflow—where natural-language prompts initiate design, optimization, and verification of photonic building blocks through full-chip tapeout—can dramatically compress iteration cycles. Taking it a step further, virtual fab AI agents that co-optimize PDKs, process corners, and yield sensitivities prior to physical fabrication would allow teams to effectively “pre-tapeout” GDSII designs into a simulated manufacturing stack—surfacing variability risks, process incompatibilities, and packaging constraints before committing to the multi-month fab loop. Bridging this design-to-device-to-packaging continuum with agentic systems could be a key enabler for moving from R&D-grade photonics to true HVM-ready co-packaged optical systems at the scale next-gen compute and networking platforms demand.