Naive question: how do factor models inform portfolio construction?

I have read plenty on the topic of factor modelling, but, in the end, after one has decided upon the factors to include in a model, how do all the Betas how tell one how to weigh each asset in a portfolio to maximize return?

For example: as a portfolio manager, I have $n$ (let's say 10) securities in the universe of securities that I can invest in, $k$ (let's say 20) factors that explain those securities, and the following factor model for each security:

$$r_i = \beta_0 + \beta_1*factor_{i,1} + \beta_2*factor_{i,2} + \ldots + \beta_k*{factor}_{i,k} + \epsilon$$

After having regressed the following factor model for each asset, for the current period $i$, how should one construct a portfolio with weightings for each asset? I imagine that the $\beta$'s are helpful in making this decision?

Thank you in advance.