A few friends & I have just spent the past ~2 years building a new kind of email app for iOS. It's now available in GA and we think some of you might find it interesting.

Why another email app, you ask? We think that while many interesting attempts at one-upping Gmail were made in the past 25 years, no one could really solve the core problem we all experience with email: information overload.

Of course, LLMs have completely changed that, as they finally offer a path to do refined triage of your inbox. However, as anyone who's tried the AI features most email apps offer nowadays, they feel tacked-on and rarely are useful.

That is why this took us ~2 years: we rebuilt an email app from the ground up, thinking about where we could thoughtfully and usefully leverage LLMs. Some of our faves:

- AI-based prioritization

- Voice-based email drafting that takes a few words from you and embellishes them into a polished email

- Very actionable, to-the-point notifications that don't force you to open the app to know what's up

Ultimately, while we tried hard to make a really great app, our goal is for you to spend as little time in it as possible. Ergo our tagline: we'd like to let you handle your inbox in seconds and get back to your life.

You can download it on the App Store at https://avec.ai/download (US & Canada), or on TestFlight at https://avec.ai/testflight in the rest of the world. You need a Gmail/Google Workspace account to try it out, and should you just be curious to kick the tires without committing, you'll be able to delete your account (& all associated data) directly within the app.

Don’t want to download anything? Check out our website at https://avec.ai for a walkthrough :)

Some things of potential interest to HN readers:

- It is not local-first. We run a complex pipeline to process emails on our servers, as in our experience local models that can run on an iPhone are not yet good enough to support our core features.

- We use a variety of LLM vendors. One thing we've found is that no model is a magic bullet. Some features (like voice-based drafting) require extremely low latency, which others (like personalization) require the smartest model available. We end up having to stitch a lot of these together through trial and error.

- It is not yet available on Android, but we hope to release an Android version in the future :)

We'd love to hear folks' feedback and questions!

Comments URL: https://news.ycombinator.com/item?id=47780199

Points: 22

# Comments: 3

I love reading the comments under HN submissions but I often get overwhelmed when I'm skimming threads to find interesting ones. To make my life easier, I built a Chrome extension that generates small summaries for each comment in a thread.

When you load an HN submission page, the extension reads comments (with their context), pushes them to gpt-4o-mini for summarization, and inserts the resulting summaries into the page as a heading for each comment. It makes it easy to quickly see where a thread is headed and focus on the ones that interest you most. The result looks something like this: https://github.com/jnnnthnn/hn-comment-summaries/raw/v1.0/sc...

The extension requires you to provide an OpenAI API key, which is then used to make requests directly from your browser. I've been using the extension for a few days now and it's only cost me a couple cents/day, making it well worth it.

I hope you'll find it useful! Feedback and questions welcome!

Jonathan

PS: You can install it directly from the Chrome Web Store at https://chromewebstore.google.com/detail/hacker-news-comment...

Comments URL: https://news.ycombinator.com/item?id=41392233

Points: 1

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=40461271

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=40442039

Points: 4

# Comments: 0

Yes, the underlying dataset very much conditions the quality of the responses. Additionally, the retrieval strategy is also a really important factor (and that is something which I haven't had time to extensively optimize).

I'm writing a blog post that will answer your questions! Will post it here when it's fully baked.

Tech stack is https://news.ycombinator.com/item?id=40238913 + the addition of turbopuffer for the new functionality.

- https://x.com/janleike/status/1791498187313963308

- Screenshot copy https://jnnnthnn.com/leike.png

https://x.com/janleike/status/1791498187313963308

Comments URL: https://news.ycombinator.com/item?id=40391412

Points: 107

# Comments: 78

GPT-4o outperforms all local models so I figured using it as a fallback was the right approach :)

Comments URL: https://news.ycombinator.com/item?id=40390719

Points: 1

# Comments: 0