[ my public key: https://keybase.io/tdickman; my proof: https://keybase.io/tdickman/sigs/bXhMgkITkPcvMjb9XvO0rfev0wDzwDypxyU-hSDht-M ]
hn [at] tomdickman [dot] com
https://tomdickman.com
I am hunting for houses - I've used it as an assistant that catalogs them (but it has this stored in multiple places and will give me the wrong list a lot). I also had it read through my emails and create a doc with my upcoming trips.
I'd say it's right on the edge of being useful, but given the number of bugs, it's not really that practically useful. It's moreso a glimpse into the future.
I've found this to be the case as well. My typical workflow is:
1. Have the ai come up with an implementation plan based on my requirements
2. Iterate on the implementation plan / tweak as needed, and write it to a markdown file
3. Have it implement the above plan based on the markdown file.
On projects where we split up the task into well defined, smaller tickets, this works pretty well. For larger stuff that is less well defined, I do feel like it's less efficient, but to be fair, I am also less efficient when building this stuff myself. For both humans and robots, smaller, well defined tickets are better for both development and code review.
This project is an enhanced reader for Ycombinator Hacker News: https://news.ycombinator.com/.
The interface also allow to comment, post and interact with the original HN platform. Credentials are stored locally and are never sent to any server, you can check the source code here: https://github.com/GabrielePicco/hacker-news-rich.
For suggestions and features requests you can write me here: gabrielepicco.github.io