People keep asking me the same question lately — what's the process behind training an AI version of myself?

Here's the real deal: I'm loading this digital me with a ton of information. We're talking my core principles, published work, recorded interviews, speeches, past articles — basically the full archive. The idea is that once it's trained on all this material, the AI can actually reason through new problems independently. It won't just regurgitate memorized answers; it'll actually think the way I think and respond how I'd likely respond to situations it hasn't seen before.

It's more complex than just feeding it text files. The quality of the training data matters hugely. Context, nuance, the why behind my decisions — all of it gets factored in. That way the model captures not just what I say, but how I approach problems.

The challenge isn't just collecting data anymore. It's teaching the AI to handle ambiguity and make judgment calls that align with actual principles rather than just pattern-matching from past responses. Still refining the whole process, but that's the foundation.