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gabev

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Quite a lot of em dashes for the New Yorker...

[EDIT] Several commenters rightly noted that heavy em-dash usage is normal for the New Yorker (and common thanks to OS auto-replacement), so my “LLM giveaway” quip was off-base. Leaving this up for context—thanks for the corrections.

Hey, this is Gabe from zenfetch. Been following you guys for a few months now since your first launch. I definitely resonate with all the problems you've described regarding celery shortcomings / other distributed task queues. We're on celery right now and have been through the ringer with various workflow platforms. Only reason we haven't switched to Hatchet is because we are finally in a stable place, though that might change soon in which case I'd be very open to jumping ship.

I know a lot of folks are going after the AI agent workflow orchestration platform, do you see yourselves progressing there?

In my head, Hatchet coupled with BAML (https://www.boundaryml.com/) could be an incredible combination to support these AI agents. Congrats on the launch

Interesting to see Kagi on this list. One of our users for Zenfetch specifically requested the option to see their Zenfetch articles alongside their search results, so we naively developed that feature to appear beside Google SERPs...

Turns out, he was a Kagi power user. Not the worst mistake on our end, though pretty neat to see it in the wild

We're working on the ability to share folders of your knowledge so that others can search/chat across them.

We've been thinking of this as a "subscription" to the creator's folder. Similar to how you might subscribe to a Spotify playlist

Appreciate that and yes in the absolute worst case, you can email us and we can manually export your data on your behalf.

We are using a fixed price today and have no restriction on storage. This might change in the future if costs scale, though it’s not an immediate priority and we’d be sure to communicate those changes well in advance.

Once you’re onboarded, feel free to message us with the in app support widget. It’s a direct line to the team slack and we tend to respond almost immediately

Snapshot is taken from the actual content at that point in time. We haven’t enabled a reader format just yet where you could view the original text. Right now, clicking the card in the dashboard will redirect you to the URL.

If you were to chat with the article from the dashboard, it would be preserving the snapshotted content and leverage that information in the final answer (same with using the search functionality).

Thanks for bringing this up, as privacy is one of (if not THE) highest priorities for us.

Happy to answer any questions you have, here are some preliminary notes that might be helpful:

1. We don't sell your data. Our business model is subscription based and we have DPAs with model providers to ensure none of that data is used for training 2. All data you explicitly save to zenfetch is encrypted in transit and at rest.

In the future, we'd like to move to a local-first platform where the data storage and processing takes place on your own machine

We will enable an export data option soon where you can download a list of the bookmarks you saved to Zenfetch.

Our goal is not to become a vendor lock-in play. Instead, Zenfetch is a layer on top of your knowledge base goaled on helping you activate information that you forgot about.

If you're referring to being able to revisit bookmarks: from the dashboard, you can click on any of the articles to see the original article

Let me know if more clarity is needed

Thanks, we actually used Rewind in the past.

We simply found that there were things we didn't want in our first brain, let alone in our second brain. That's why we've taken a curated content approach.

Rewind captures everything, while Zenfetch only stores the content you've explicitly saved to signal there is value.

I don't need to be reminded of the accidental clickbait article I've opened :)

Have been using futureme for a few years now. Getting a letter every January 1st is a nice way to understand my headspace from the previous year.

This coupled with my daily journal entries offers an interesting reflective process around the holiday season :)

There's a fundamental challenge in simply not knowing at the reading point in time whether this knowledge will be valuable in the future.

The reason read-it-later apps exist is because we want to buy the insurance policy that IF there is a future situation in which the information is useful, we have it saved somewhere to access it.

The reality is, even if you have saved it at some point, there's no guarantee you'll be able to remember the knowledge when you need it.

This is precisely the problem I'm building a solution for.