Looks interesting! How would you say it compares against Claude/Gemini code or any of the other major terminal-based coding assistants?

It's quite similar to Claude Code. The main advantages are that it's super easy to use with different models when new ones come out (like GPT-5!), and with local LLMs, and we have some optional, custom-trained small models that help auto-fix diff edit failures and minor JSON inaccuracies — they work with any model and especially help with some of the open-source coding models.

We also open-sourced the autofix models:

https://huggingface.co/syntheticlab/diff-apply

https://huggingface.co/syntheticlab/fix-json

They're truly open source, not just open weight BTW: the entire training pipeline is in the Octofriend repo.

Your workflow sounds interesting.

I understand the power of flash cards and SRS in general. But was wondering how you decide when to put something into an SRS when learning something new. Especially in a tech/programming context.

I add stuff in general that I'm curious about, want to learn for long-term, or is important in that specific period of time.

It's a bit random, with time I then ignore some topics.