Memory is the moat, not the model.
I keep seeing agent products where the actual model is basically interchangeable, and the thing that makes one feel like it "knows you" is how much context it carries between sessions. Almanac's take stuck with me for that reason: they spend real compute up front compiling a wiki, so the agent starts every task already caught up instead of asking you to re-explain the company each time.
That's the part most tools treat as an afterthought. Integrations fetch on demand and forget. A persistent, self-updating knowledge layer is harder to build but it's where the defensibility lives, especially for tiny teams drowning in scattered context across Slack, email, and notes.
It's also a good pointer for anyone hunting micro SaaS ideas: the boring infrastructure of "remember my business correctly" is underserved. I built SoloVault to surface exactly these kinds of early signals and turn them into buildable directions.
Do you think context depth or task execution wins here?
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