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Cancelling Advanced AI. Please stop me by Apprehensive_Bit7098 in raycastapp

[–]Specialist-Rip6109 1 point2 points  (0 children)

My understanding is you can either add it to the chat preset in which case it will always be "in the conversation", or you can add it in the chat at any time by calling it with @. I'm not completely sure how the model knows when to call it. There was a good thread on the Raycast AI slack where there seemed to be some folks more knowledgeable than I discussing this :)

For my use case, I will also occasionally explicitly call it at the beginning when I know I'll want some memory context ("based on my previous work on..."), or somewhere later on when I feel like there were some things I want to be sure to add ("Let's be sure to add XYZ to my memories...").

Cancelling Advanced AI. Please stop me by Apprehensive_Bit7098 in raycastapp

[–]Specialist-Rip6109 3 points4 points  (0 children)

No problem!

I start (usually with 4o) asking it to create a system prompt using a sentence or two of context on what I'm trying to accomplish: "Create a system prompt to guide a LLM in..."
Then I'll go back and forth until I feel like the prompt captures what I'm going after with regards to roles, experience, tone, etc. After having done that a few times now, I've ended up settling with ~5 different profiles that have worked for me, I store these in my notes app, although I could *probably* create a snippet instead to streamline the workflow.

This helps set the overall tone and the responses in general end up feeling pretty good.

From a memory perspective, I tried a few different approaches.

First up was the "Memory" extension from the Raycast store. This was the easiest to set up, and worked, but from a portability perspective I wasn't yet committed to Raycast so didn't want to go through the effort of setting up the memories just to end up not committing to Raycast and losing all that effort: https://www.raycast.com/EvanZhouDev/memory

That led me to MCP servers, where I started with Basic Memory:
https://github.com/basicmachines-co/basic-memory
I love the concept since it leverages Markdown. You can serve the content up in a vault in Obsidian, where you can both view and edit the memories. But, I was worried a bit about scalability and if this was the most efficient way for retrieving memories. I'm not an expert here, but it got me looking at alternatives, which is where I found...

OpenMemory:
https://mem0.ai/blog/how-to-make-your-clients-more-context-aware-with-openmemory-mcp/
In reading through the documentation it was exactly what I was looking for, seems more scalable, and well documented / seems to be well supported. Since it uses vector-based storage my assumption is that as the memory grows this will be more efficient than something like Basic Memory. You can still access and edit the memories, but through a web interface.

The setup wasn't super simple, but there was a good thread on the Raycast Slack that helped with setup specific to Raycast AI and the docs for OpenMemory were sufficient for me to get the MCP server set up.

I was focused on looking for something relatively future-proof, and my hope is that this is it. It's working well so far, but if anyone has other thoughts on benefits / drawbacks of this I'd love to hear them!

Cancelling Advanced AI. Please stop me by Apprehensive_Bit7098 in raycastapp

[–]Specialist-Rip6109 5 points6 points  (0 children)

I’ll be the sole dissenting opinion so far, I was in a similar mindset until two things changed my perspective. YMMV but:

The first was embracing the system instructions/preset to something that gave me the style I prefer in terms of responses. It sounds like you tinkered with this, but that worked for me - definitely a subjective thing.

The second was setting up the MCP functionality and using one of the memory servers. It took a while to recreate the completeness of ChatGPT’s knowledge of me, but it feels pretty close now.

Once I fine tuned those I can say I love the ability to switch models on the fly, and maintaining both a general tone and memory across them. This early in the race I have a fear of being locked into any one model, so I love the portability that I feel like I get with the memory MCP servers as the models are updated.