Your job is to proofread and edit the following email draft.
Don't make it longer, more formal, or more "polished" than it needs to be.
Fix anything that's actually wrong (grammar that changes meaning, tone misreads).
Leave stylistic roughness alone if it fits the voice.
If the draft is already fine, say so.
That preserves voice way more than the default "Hello computer, pls help me write good" workflow. - grab weather, calendar, Todoist data using APIs or MCP
- grab news from select sources via RSS or similar, then filter relevant news based on my interests and things it has learned about me
- synthesize the information above
The steps that explicitly require an LLM are the last two. The value is in the personalization through memory and my feedback but also the ability for the LLM to synthesize the information - not just regurgitate it. Here's what I mean: I have a task to mow the lawn on my Todoist scheduled for today, but the weather forecast says it's going to be a bit windy and rain all day. At the end of the briefing, the assistant can proactively offer to move the Todoist task to tomorrow when it will be nicer outside because it knows the forecast. Or it might offer to move it to the day after tomorrow, because it also knows I have to attend my nephew's birthday party tomorrow.
This isn't surprising to me at all.
The World Cup is on, and it draws attention away from politics. This has been a pretty common observable pattern for as long as I can remember.