Reprogramming approaches often produce heterogeneous cell fates and the mechanisms behind this heterogeneity are not well-understood. To address this gap, we developed scTF-seq, a technique inducing single-cell barcoded and doxycycline-inducible transcription factor (TF) overexpression while quantifying TF dose-dependent transcriptomic changes. Applied to mouse embryonic multipotent stromal cells (MSCs), scTF-seq produced a gain-of-function atlas for 384 murine TFs. This atlas offers a valuable resource for gene regulation and reprogramming research, identifying key TFs governing MSC lineage differentiation, cell cycle control, and their interplay. Leveraging the single-cell resolution, we dissected reprogramming heterogeneity along dose. We thereby revealed TF dose-dependent and stochastic cell state transitions, unveiling gene expression signatures that enhance our understanding and prediction of reprogramming efficiency. By exploring the relationship between TF dose and function, scTF-seq also allowed us to classify TFs into three sensitivity classes: low- versus high-capacity TFs with the latter split into ‘low’ and ‘high’ dose-sensitive groups. Finally, in combinatorial scTF-seq, we observed that the same TF can exhibit both synergistic and antagonistic effects on another TF depending on its dose. In summary, scTF-seq provides a powerful tool for gaining mechanistic insights into how TFs determine cell states, while offering valuable perspectives for cellular engineering strategies. For analysis and more details about this data, you can check our GitHub: https://github.com/DeplanckeLab/TF-seq