Show HN: Segue – Save context in one AI, load it in another by a short handle
Posted by csaguiar 4 days ago
Comments
Comment by fny 4 days ago
You're sending your context to someone's relay in plain text and loading it in plain text.
Comment by vulture916 4 days ago
I've got to send it to your server so you can spit it back when I say a fancy word? What's worse, I pay you to just store/retrieve text? Why wouldn't I just write to a file?
Comment by tracker1 4 days ago
I tend to spend a lot more time planning than what it takes to execute/build what I'm after.. then more time reviewing again than the produce step(s) and iterate.
For that matter, I'll track what I'm wanting and what has been done via TODO.md file in project(s).
I'm not sure I would ever use/trust a service like this myself. I barely trust the AI providers as it is.
Comment by csaguiar 4 days ago
Comment by planb 4 days ago
Comment by 44za12 4 days ago
Comment by pcpliu 4 days ago
I was having a similar product idea and quickly abandoned it after a demo ready.
Checkout https://memory.store/ (not affiliated). They target 2B users and focus more on centralized knowledge management for organizations, which I feel is more reasonable.
Comment by csaguiar 4 days ago
Comment by orsenthil 4 days ago
Comment by hsienchuc 4 days ago
My current workaround is to write the context as a Markdown file and save it to disk, then let both of two CLI to read. I'd like to ask you, what are the advantages of this tool compared to using a file as a bridge?
Comment by csaguiar 4 days ago
Comment by firasd 4 days ago
Comment by tracker1 4 days ago
Comment by telecuda 4 days ago
Comment by csaguiar 4 days ago
Comment by KetoManx64 4 days ago
Comment by jensabacik 4 days ago
Comment by rpicard 4 days ago
I don’t think I’d like using a third party server for this, but a skill that just handles it locally or something would be useful.
Comment by janrakete 4 days ago
But perhaps this could be used to build a local solution with a little more added value. It might be interesting to use the context to determine which AI solves the problem best or most cost-effectively.
Comment by codeprimate 2 days ago
Comment by outoftheweed 4 days ago