Hi HN!
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.
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!
by RockstarSprain ·
Not sure how to put it better but the more I read about AI the less motivation I have to either keep up with the tech advances or to try doing new things... I wonder how others keep or even foster the kind of motivation necessary to try new things and actually stick to doing them long enough? I would appreciate input on this in the most general sense possible.
Hello Hackerians. Please check out another CD (change directory) utility: cd-deluxe. Why? Using command line is great and powerful but the humble default cd command is somewhat weak. And it is one of the most used commands. Here is another attempt at improving it!
Examples: Use "cd --" to go back two directories, "cd ---" to go back 3 directories, etc. Or go in the opposite direction ie "cd +4" to go to the fourth directory visited from the start (or any number). Use "cd ," (comma) to go to the most commonly visited directory (comma meaing "common"). Also see "cd ,,", "cd ,3", etc. List directories visited either in reverse, forward or most common orderings. Plus more - see github. Goal was to be lightweight and fast. Works from the directory stack instead any file based storage. Integrates with bash/zsh/fish/powershell/cmd.exe. With downloads for Linux/maxOS/Windows or build the C++ from source via CMake. Please have a look and let me know of any thoughts. Thanks!
by yuntian ·
We built ProgramAsWeights (PAW) — https://programasweights.com
You describe a function in English — like "classify if this message is urgent" — and PAW compiles it into a tiny neural program (22 MB) that runs locally like a normal Python function. No API keys, no internet after compilation, deterministic output.
It's for tasks that are easy to describe but hard to code with rules: urgency triage, JSON repair, log filtering, tool routing for agents.
pip install programasweights
import programasweights as paw
f = paw.compile_and_load("Classify if this is urgent or not.")
f("Need your signature by EOD") # "urgent"
On our evaluation, this 0.6B interpreter with PAW reaches 73% accuracy. Prompting the same 0.6B directly gets 10%. Even prompting Qwen3 32B only gets 69%.
Also runs in the browser (GPT-2 124M, WebAssembly): https://programasweights.com/browser
You can also use it in your AI agents by copying the prompt here: https://programasweights.com/agents
Source: https://github.com/programasweights
Try it out: https://programasweights.com
by abhay_ramesh ·
For some reason, embedding a Jupyter notebook in a documentation site still means doing one of these: screenshot every cell, run nbconvert and clean up the HTML, copy-paste the code into fenced blocks (losing the output), or iframe in nbviewer. Every time you update the notebook, you redo the whole dance.
notebook-mdx lets you just link the `.ipynb` file and it renders inline in your MDX. No export step, no cleanup, no re-pasting. Update the notebook, rebuild the docs, done.
:::notebook{file="./analysis.ipynb"}
:::
Example output:
- Example 1: https://notebook-mdx.vercel.app/docs/examples/notebook-demo
- Example 2: https://notebook-mdx.vercel.app/docs/examples/directive-exam...
by mercurialsolo ·