simonpure

Official announcement

https://blog.google/innovation-and-ai/models-and-research/ge...

It's available in Antigravity as well -

  Gemini 3.6 Flash (High)
  Gemini 3.6 Flash (Medium)
  Gemini 3.6 Flash (Low)
  Gemini 3.5 Flash (Medium)
  Gemini 3.5 Flash (High)
  Gemini 3.5 Flash (Low)
  Gemini 3.1 Pro (Low)
  Gemini 3.1 Pro (High)
  Claude Sonnet 4.6 (Thinking)
  Claude Opus 4.6 (Thinking)
  GPT-OSS 120B (Medium)

I always wonder why not more companies are using more creative approaches like Google's Dutch auction to set their IPO price.

It seems direct listings gained some popularity but overall most companies seem to rely on the traditional underwriter model.

According to [0] -

22 companies went public on major exchanges using IPO auctions in the U.S. between 1999-2008, but there have been none since then, as of May 2025. Starting in 2018 when Spotify went public, there have been at least 20 companies that have gone public using a direct listing. With both IPO auctions and direct listings, underwriters do not have discretion to allocate shares to their preferred clients.

[0] https://en.wikipedia.org/wiki/OpenIPO

There's a truly decentralized alternative to MLS:

Key Agreement for Decentralized Secure Group Messaging with Strong Security Guarantees [0]

[0] https://eprint.iacr.org/2020/1281

The readme was recently updated.

In regard to AI usage, my fuzzing workflow was automated by AI with a strict harness. I used GPT-5.5-3-Codex-Spark for ALL the fuzzing, as barely any "thought" is necessary when provided with an efficient harness. Contrary to the growing narrative that I'm just some random child burning tokens, I DO actually have a degree in the subject and have published multiple papers on fuzzing methodology. I spent years researching and developing new tools and ideas for how to fuzz. You do NOT need a SOTA model to help you identify these issues, I promise!

Hug of death

` /api/hn -> 504 An error occurred with your deployment FUNCTION_INVOCATION_TIMEOUT cle1::c8vgv-1782399959042-aeba3cae05ff `

And the video version -

https://youtu.be/K1dBf40waNk

Thanks! I've noticed a big jump when they switched to Gemini 3.1 Pro and it really became useful. I like that I can use it from my phone too. It took a bit of trial and error but I came up with a good ralph loop between GitHub Actions and Google Jules using the Jules API. So basically I have Jules extend its TODO.md with the next set of tasks and open a PR then run a GitHub Action with a few checks, auto-merge, and then call back into Jules to kick off the next cycle if there are still open tasks. It then mostly just runs and occasionally gets hang up on some questions that I then answer on my phone mostly just telling it to make a judgement call and keep the build green. You can check out the prompt, action, and past PRs for examples ex. Jules prompt is here: https://github.com/alpeware/datachannel-clj/blob/main/prompt...

I've been working on a pure Clojure implementation of WebRTC Data Channels (SCTP over DTLS over UDP). The library provides a minimal, dependency-free (except for Clojure itself) way to establish peer-to-peer data channels on the JVM.

I've always wanted this and have used it to experiment with Gemini's cloud agent Google Jules.

https://github.com/alpeware/datachannel-clj

I was wondering the same and learned the model doesn't know about itself during training [0]

[0] https://developers.googleblog.com/closing-the-knowledge-gap-...

I've been impressed by Google Jules since the Gemini 3.1 Pro update. Sometimes it's been working on a task for 4h. I've now put it in a ralph loop using a Github Action to call itself and auto merge PRs after the linter, formatter and tests pass. It does still occasionally want my approval, but most of the time I just say Sounds great!

It's currently burning through the TESTING.md backlog: https://github.com/alpeware/datachannel-clj

There's DolphinGemma; no microchips needed -

https://blog.google/technology/ai/dolphingemma/

There's now also Gemini CLI GitHub Actions for a similar async experience -

https://github.com/google-github-actions/run-gemini-cli

He also published animated video versions:

45min https://youtu.be/xguam0TKMw8

5min https://youtu.be/BB2r_eOjsPw

Source: https://x.com/jeremyphoward/status/1944322841866125597?t=3Oa...

Not my project but also tinkering with something similar.

From the comments, it sounds like they'll open source something soon -

https://old.reddit.com/r/ChatGPTCoding/comments/1jibmtc/i_ma...

I was curious as well.

Not OP but via their website linked in their profile -

https://youtu.be/Tl3pGTYEd2I

One of the original authors also published a follow up with some additional details and analysis that may be of interest (still reading through it myself) [0]

[0] https://eprint.iacr.org/2024/696

PubSubHubbub aka WebSub [0] is an extension of RSS feeds to solve the push/pull issue by introducing hubs.

[0] https://en.m.wikipedia.org/wiki/WebSub

I started reading the book but haven't finished it yet. It's also been a while since I've been surfing. I enjoyed the video and it's a good reminder to both finish reading the book and go surfing.

What were your main takeaways of the book and how has it influenced your startup?

This proposal depends on a central server and there is an alternative decentralized proposal - https://eprint.iacr.org/2020/1281

I just finished reading The Master Switch by Tim Wu. It includes the history of broadcasting including why it took so long for FM radio to succeed.

According to him, Sarnoff and Armstrong were friends at some point and RCA financed the development of FM radio initially although they just wanted a more efficient AM network.

As other comments have pointed out, this behavior is enabled by `requestIdleCallback`.

MDN has a good example and looks like this is not supported by Safari -

https://developer.mozilla.org/en-US/docs/Web/API/Background_...

The 1% rule seems to hold up pretty well across any online community [0]

[0] https://en.m.wikipedia.org/wiki/1%25_rule

In Internet culture, the 1% rule is a general rule of thumb pertaining to participation in an internet community, stating that only 1% of the users of a website add content, while the other 99% of the participants only lurk.

The BIP buffer.

It's a ring buffer compatible with APIs that don't specifically support it.

It's a great fit for any network I/O and I believe Android uses it under the hood.

https://www.codeproject.com/Articles/3479/The-Bip-Buffer-The...

There's also this Tech Talk Linus gave in 2007 -

https://youtu.be/4XpnKHJAok8

If you're interested in this topic, I highly suggest some of the talks and papers about the LMAX Disruptor [0] and Martin Thompson's latest project Aeron [1]. It targets the JVM, but the lessons are generally applicable since I don't think Concord/Aria are open source.

[0] https://lmax-exchange.github.io/disruptor/ [1] https://github.com/real-logic/aeron

I'd also add cgrandes ClojureDart to the list.

I would generalize your observation as a logical consequence of Greenspun's tenth rule and conclude that we will eventually get a hosted lisp for any sufficiently relevant programing language.

There's a wonderful podcast about array languages -

https://www.arraycast.com/

Lots of great stories about software engineering besides talking about the different dialects of array languages.

Yes, it's an effort to standardize and future proof.

Cloudflare's post [0] has some more background information.

[0] https://blog.cloudflare.com/hybrid-public-key-encryption/