elpakal

Ah, I do not unfortunately, except maybe exploring a partnership with someone based in the US (not sure though).

I feel like it’s more “would you like build an app with me” guy

Thanks! Curious what kind of friction you’ve encountered. In my experience buying phone numbers is not hard, finding vanity phone numbers (especially in certain area codes) is because it requires keeping an eye on their rolling availability.

I’ve set up a few 10DLC campaigns as well, it’s a little finicky and takes time but something I can do pretty predictably.

Typical use case can be someone's running an existing campaign (ads, billboard, referrals) and we add a dedicated texting number as the 24/7/multilingual layer on top. No new spend, just coverage after hours or in Spanish etc. Can also serve as the primary feature of a new campaign, admittedly a novel approach but I see there being potential to provide a new channel to reach users where they already are (sms) in extremely saturated markets.

I work mainly with law firms, there are some potential examples on my website if you're curious: https://fractional-engineer.com/sms-intake.

Happy to chat more.

I’m working on building AI-backed sms phone numbers for lead generation campaigns needing 24/7 or multilingual support. Less friction than downloading apps or interfacing with chat bots, and just as powerful.

Raised multilingual here (as in father spoke one, mother spoke another, living abroad and US back and forth). I don't know about the stronger social ties but I have found that thinking in a different language helps me get to sleep easier. There are times when I'm spinning around in webs in English (work, life etc) at night, and when I switch over to Spanish thoughts I fall asleep easier.

Maybe just stuff like that is enough to make a difference.

I work in AI, both building at a large company and consulting on the side. My manager (of two months) uses claude to reply to everyone in Teams and emails, usually filled with nonsensical slop. I believe in its potential when applied correctly but also am realizing that it's unlocking an entirely new kind of fraudster.

At a kill s@@s hackathon at work, I was able to build something that

uses a node image installs claude code runs a /review-like command puts inline comments to PR deletes old comments when rerunning

OCR seems cool, but overkill, and I'm definitely not using Code Rabbit after their CEO was on here acting snobbish a while back.

Point being AI code review in Git** itself isn't hard to do and can add a lot of value quickly.

even worse on mobile

Now can LinkedIn please label posts

Confirmed by Andy Jassy just now https://www.linkedin.com/posts/andy-jassy-8b1615_very-intere...

Apple's Foundation models seem great on paper until you see the 4k context window. (though I know we are still early in this chapter).

dotIPA, an iOS app build size inspector that runs locally on your macOS [$4.99]

Track app size growth over time, inspect contents, spot duplication and size bloat and more.

https://apps.apple.com/us/app/dotipa/id6742254881

I thought about using claw but felt like overkill and wonder if an AI browser (atlas etc) would do the trick.

Really cool idea. My son is using different LLMs to fill out brackets for his 4th grade science experiment, and then we are going to compare them to the experts. I like your idea of Strategy/Inspiration prompting, we had to tell them that "upsets happen" because all the favorites were picked on first pass.

Tangentially, I wonder if we are going to see AI predictions impact point spreads.

thanks

Sorry, I scrolled through some of the rest of the comments on this thread and can’t stay tuned.

This is a known limitation with small LLMs (0.6B-1.2B) doing tool calling.

To me this is this nut to crack, wrt tool calling and locally running inference. This seems like a really cool project and I'm going to dive around a little later but if it's hallucinating for something as basic as this makes me think it's more of POC stage right now (to echo other sentiment here).

file-based state that persists between agent invocations

Can you expand on this with a practical example?

An iOS app size analysis tool you can run on your Mac and track build size changes over time https://apps.apple.com/us/app/dotipa/id6742254881

An iOS build size analysis app that runs locally on your Mac: https://apps.apple.com/us/app/dotipa/id6742254881

Does fastlane still hang for a little before every command? I used to optimize build pipelines for a large company's iOS teams and it always seemed to stall for a little before doing the work. We eventually moved to Xcode Cloud (mainly to avoid code signing) and ran xcodebuild directly.

why would it need local network access though, I wonder?

this just calls Codex CLI with OS sandboxing

The git and terminal views are a big plus for me. I usually have those open and active in addition to my codex CLI sessions.

Excited to try skills, too.

But they created GenMoji?!

A locally running (macOS) iOS build size analysis tool. Been tinkering with Apple Intelligence, trying to implement an on-device size optimization engineer for my users. The small context window for Apple Intelligence has been tricky to get right.

[promo] https://apps.apple.com/us/app/dotipa/id6742254881

I maintain an app size inspection tool that runs locally on your macOS and added the file inspector (Sunburst chart) for Gmail if anyone is interested in exploring its contents.

As others have pointed out, the main executable is huge (~300MB) and there are a lot of localization files, but not too much traditional asset duplication.

You can click into different slices of the app and see what it's made of if interested: https://dotipa.app/?app=Gmail#examples

If you're interested in iOS app size analysis, I build and maintain this https://apps.apple.com/us/app/dotipa/id6742254881 ($4.99). Happy to share download codes, HMU at info [at] dotipa.app

An iOS app size analysis tool you can run on your Mac https://apps.apple.com/us/app/dotipa/id6742254881

Not just about the products imho. I do some consulting for law firms who typically use the MSFT stack, and I was excited about the private ChatGPT services in Azure, because from my (admittedly limited) sample of law firms, nobody likes using Copilot and LLMs need to be private/secure. The amount of outdated and poor quality documentation for Azure services is amazing given how nascent these services are.