I spent 5 years as founding engineer at a fintech managing $20B+ in infrastructure assets, running their AI team. I left to build the tool I always wished existed for my own portfolio.

The idea: an AI that reads SEC filings, earnings transcripts, news, and social sentiment overnight, then delivers one briefing before market open, personalized to your actual holdings. Not a chatbot you have to query, not a dashboard you have to check. It just tells you the 3-5 things that matter today.

Example of what a briefing looks like: https://personal-investment-agent-landing-p.vercel.app/ (haven't bought a url yet, still deciding on the name)

A few design decisions I'd love feedback on:

1. Briefing-first vs chat-first. Most tools in this space (Astor, FinChat) are chat-based. I think most retail investors don't know the right questions to ask, so the AI should present findings proactively. Am I wrong?

2. Thesis tracking. When you buy a stock, you usually have a reason ("I think cloud revenue will reaccelerate" or "this is undervalued relative to peers"). What if you could log your thesis and the daily briefing explicitly flags signals that support or contradict it?

3. Like "you bought MSFT because of Azure growth, but this quarter's 10-Q shows deceleration from 29% to 23%." Would that change how you use something like this?

4. Financial metrics in the briefing. Would you want things like P/E ratio shifts, earnings yield vs treasury spread, or forward P/E divergence from estimates surfaced in your daily briefing? Or does that make it feel too noisy and you'd rather just get the narrative?

5. Free tier = follow sectors without connecting accounts. Paid = connect brokerage via Plaid for personalized briefings. Does that free tier feel useful enough to try?

6. Six signal types synthesized in one briefing (market data, news, filings, earnings transcripts, sentiment, macro). Is that the right set or am I missing something?

For those of you who pick individual stocks: what would actually make you open this every morning?