preston-kwei

Having attended startup school this weekend, we were told how, in the past, companies were reluctant to try new technology from startups, AI products, etc., because they were unvalidated and unsure of how they would work. Now, companies are more worried that they're going to be left behind and that their competitors will beat them if they do not adopt these new technologies.

I'm curious about how the LLM-based detector worked. How often did you run into a false positive? (I'm assuming you leaned on the more sensitive side due to the importance of the data)

Do you think customers trust it either? I'm trying to differentiate between "good enough" and when enterprise customers actually care. I mean, it doesn't matter until a customer asks for their data.

I agree. I'm trying to sell to enterprise right now and this is a blocker. Basically, my product stores emails in S3, but metadata in Supabase, and caches in Redis. It's all fragmented and super difficult to keep track of. Plus Supabase isn't WORM compliant so it is hard to ensure data doesn't get deleted.

I think UI quality is going to stop being as important when anybody can just generate an "average" UI that is good enough in minutes.

Ultimately, this really just shifts the focus towards product design and ideation rather than UI design.

How many emails does it usually take for you to lock something in? And do you end up following up manually if they don’t respond?

How much of this issue is availability vs just getting them to respond and commit to the meeting?

I think the back and forth is one of the most time-consuming parts. How do you manage it?

Interesting. Do you end up just accepting the meetings or do you try to push back?

I’m more curious how this impacts trust than anything else.

In the span of basically a week, they accidentally leaked Mythos, and then now the entire codebase of CC. All while many people are complaining about their usage limits being consumed quickly.

Individually, each issue is manageable (Because its exciting looking through leaked code). But together, it starts to feel like a pattern.

At some point, I think the question becomes whether people are still comfortable trusting tools like this with their codebases, not just whether any single incident was a mistake.

Thank you for your response. I think the ICP needs some refinement. I've found it pretty hard to prospect because it is so broad.

> People generally don't have problem with email scheduling I think this stems from the fact that there is no existing tool that solves this problem. Clearly, tools like Calendly haven't solved it for execs or people with complex scheduling flows. A lot of it is caused by the fact that people tend to just tolerate scheduling because they don't know a better way, leading them to waste more time than they expect.

> The moment Persona is compared to a human EA, you lose on judgment, context, and trust. I agree with this. I'm trying to steer away from this actually, because a lot of companies sell an AI EA, even though their product doesn't even do anything related to EA tasks.

I think the landing page needs more work, copy wise. I'm certainly moving towards the control thing. The features are in place, so I need to tweak our marketing.

> Accept that this may not be a standalone company Totally. Scheduling alone cannot be a standalone company. That's just the first pain point I'm attacking. I have many more features that are in progress that move it more into it's own category. Think of it more as a email delegation layer for AI agents.

Thanks again for your thoughtful response.