Past experimental and computational work on azoarenes has shown an empirical inverse relationship between the λ max and t 1/2 . This leads to trade-offs during photoswitch design. This report describes how we have applied strategies to increase the λ max and t 1/2 metrics to design photoswitches a priori for photopharmacological applications. We designed a new class of hemi-azothiophenes with the diazo group bound to a p-substituted-phenyl and thiophene substituted at the 3position. This photoswitch was designed to maximize t 1/2 based on our recent discovery of the role of cross-conjugation on (3,3)vs. (2,2)-bis-azothiophenes and similar experimental reports by Perry and co-workers. We combined this powerful effect with known strategies to simultaneously increase λ max (i.e., increasing 𝜋-conjugation length and substituent effects). To this end, we computed the λ max and t 1/2 of 26 hemi-azothiophenes with quantum mechanical density functional theory calculations, enabled by our automated computational workflow, EZ-TS. The EZ-TS code first generates a set of 12 transition state guesses from an input Z-isomer geometry by rotating about the diazo bond. The 12 guess structures are optimized using B3LYP-D3BJ/6-31G(d), and the lowest energy guess structure is subject to a conformational analysis with the Conformer Rotamer Ensemble Sampling Tool (CREST). Next, a 5-step constrained relaxation using ORCA is run on all conformers to ensure a smooth convergence for the final set of optimizations and frequency calculations, which are performed on the 10 lowest energy conformers using B3LYP-D3BJ/6-31G(d). At the end of this final step, the 10 conformers are ranked by their energies. The lowest energy conformer with a vibrational frequency corresponding to the Z → E thermal isomerization reaction is determined to be the lowest energy transition state. We benchmarked this workflow for 11 azoarenes and 140 model chemistries. We found that the PBE0-D3BJ with either the cc-pVDZ or 6-31+G(d,p) basis sets provide the best balance between computational cost and accuracy.