I think the key is to combine human and agent task tracking in one pane of glass.

I am also hoping / trying to put Claude code on top of a personal zettlekasten to automate more of my “personal life” tasks and get more stuff done for me. Haven’t gotten it really singing yet but I think that could also be really cool.

Blessed vs “bless-ed” for example

Camera can be said cam-ra or cam-er-a for example.

Comments URL: https://news.ycombinator.com/item?id=45017968

Points: 2

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=45017519

Points: 2

# Comments: 2

This isn't study mode, it's a different AI tutor, but:

"The median learning gains for students, relative to the pre-test baseline (M = 2.75, N = 316), in the AI-tutored group were over double those for students in the in-class active learning group."

The thing I think some enterprise customers are worried about in this space is that in many jurisdictions you legally need to disclose recording - having a bot join the call can do that disclosure - but users hate the bot and it takes up too much visibility on many of these calls.

Would love to learn more about your approach there

My takeaway is scaling in the enterprise is about making implicit information explicit.

From what I have seen most of these tools need to do more user research on how powerpoint slides actually look like in practice.

There's a lot of "you're doing it wrong, show don't tell, just keep the basics on the slide" but the people that use powerpoint to make $$$ make incredibly dense powerpoint materials that serve as reference documents, not presentation guides (i.e. they are intended as leave-behind documents that people can read in advance)

Presentations are also quite hard because:

1. It must "compile to" Powerpoint (it must compile to powerpoint because your end users will want to make direct edits and those end users will NOT be comfortable in markdown and in general will be very averse to change) 2. Powerpoint has no layout engine 3. Powerpoint presentations are in fact a beautiful medium in which VISUAL LAYOUT HAS SEMANTIC MEANING (powerpoint is like medieval art where larger is more important)

If anyone wants to help me build an engine that can get an LLM to ACTUALLY make powerpoints please let me know. I am sure this is a lot harder than you think it is.

Also curious if there might be some improvements if you dont rely on semantic similarity and just do all the pairwise "how related are these memories and in what way" LLM test like https://www.superagent.sh/blog/reag-reasoning-augmented-gene....