The thing that inspired me was actually the operation of my #matrix homeserver that has *all* the bridges. The different protocols being their own services has been great. All the extra stuff and needing to run a server has kinda sucked. The matrix data model is also hard to build lightweight clients for which has also been hard for progress.
Look, oplogs are great as a datamodel for mostly online systems that need full replication, but they aren't great for performance and being able to quickly show a user just the data they need in the moment right as they start the sync. Waiting for an entire sync is just not reasonable when your message volume gets high. This is why we need indexing at the protocol layer. Blogged about it here: https://blog.mauve.moe/posts/peer-to-peer-databases
So, from here bridges and clients just need to know the rpc protocol, probably json rpc split by newlines since it's easy to parse in any language. Then HTTP servers for blobs like images since JSON sucks for binary data. Now I can use whatever language sucks the least for whatever alt client ecosystem.
Anyway, once I have some of the bridges set up I'll work on my audio based notification daemon. I'll use one of thos TTS models that do "voice cloning" and use my voice with different affects so I can assign voices to specific chats or app sources. Kinda like how I use SpeakThat to have all my chats and email notifs right in my ear. But better because I can ditch android and have more customization than the apps give.
Now from here we get into the dirty parts which is LLMs. The fact is that there are a lot of centralized chat apps with different data models and url layouts for their endpoints. My guess is that once I have a data model, I'll be able to convert a lot of the sdk example docs into using the system and my local Qwen3.8:27b setup. I'll still need to understand how they work but it might be less typing.