Using PCA, I can capture about 95% of the variance of my data using 3 modes. If I wanted to make an autoencoder for my data would this mean that the size of my latent space should be $1 \times 1 \times 3$? I plot my data using the 3 modes against time and I'd like to be able to do the same with the latent representation of my data.

If it is the case that my latent space needs to be $1 \times 1 \times 3$, will the bottleneck be too small to get an accurate reconstruction?