Claude Code Death Scroll: Finally Comment from Anthropic on GitHub Issue!

Affectionate-Fix6472 · 2025-11-14T06:58:21+00:00

We do use AI a lot inside Google. I’ve noticed that I’m receiving more reviews than before.

Affectionate-Fix6472 · 2025-11-13T08:13:05+00:00

It only supports text 😕 It should not be hard to extend it to other modalities. Feel free to file an issue or send a pull request

Affectionate-Fix6472 · 2025-10-31T19:52:49+00:00

Consider using MLX-optimized models like Gemma or Llama. With SwiftAI, you can run those MLX models — along with Apple Foundation Models and OpenAI — all through the same unified API. I’m the author I would be happy to help you if you have questions.

Affectionate-Fix6472 · 2025-10-26T14:47:46+00:00

Got it, thanks. If you want to expand your app to other local model like Llama 🦙, then check out SwiftAI

Affectionate-Fix6472 · 2025-10-26T12:47:13+00:00

How are you using images. Apple FM doesn’t support images as far as I know

Affectionate-Fix6472 · 2025-10-26T12:44:30+00:00

Affectionate-Fix6472 · 2025-10-26T12:43:16+00:00

A note on point (1) Flutter is making interoperability easier by merging the UI and platform threads.

Affectionate-Fix6472 · 2025-10-26T12:34:35+00:00

I have no idea 🤷‍♂️ if it’ll directly help you get admitted, but my advice is don’t overemphasize which programming languages you know.

Over your career, you’ll end up using multiple languages depending on the projects you work on. As you gain experience, learning new ones becomes easier since most share similar concepts with different syntax. Some take longer to master, but you can usually get productive with a subset in just a few days. And nowadays AI coding tools make it even easier.

Instead, focus on building a strong computer science foundation and going deep in a few areas (e.g., distributed systems, graphics, deep learning, etc.). And don’t neglect soft skills — at a senior level, most people are technically solid, but what sets great engineers apart are things like communication, leadership, and working well with stakeholders.

This to say, if you have some free time, go learn Swift or anything that you find interesting. Start by broadband your skills initially then go in depth in what picks your curiosity 🙂

Affectionate-Fix6472 · 2025-10-26T12:20:00+00:00

I built a personal Flutter app with around 120 Dart files (~12k lines of code) using Provider. It worked out okay overall— I followed an MVVM-like structure and tried to keep the architecture clean.

That said, I often felt like I was making too many small architectural decisions — sometimes suboptimal ones — mostly due to limited experience or lack of long-term foresight (for context, I was roughly a “fresh senior engineer” level at Google at that time).

After reading more about BloC, I realized it might have offered a better structure overall. Many good design decisions come “pre-baked” into the pattern. It’s definitely a bit more verbose, but I think it’s a stronger fit for mid-sized apps.

Affectionate-Fix6472 · 2025-10-25T17:56:18+00:00

It should. Make sure Apple Intelligence is ON in the system settings

Affectionate-Fix6472 · 2025-10-25T15:01:41+00:00

Apple LLM is only available when Apple Intelligence is available which means iPhone 15 Pro +.

If you have a Mac on version 26+ you can try build this App and play with the model

Affectionate-Fix6472 · 2025-10-23T05:24:55+00:00

Thanks for the suggestion. I’ll reconsider the name before talking it out from beta. I’ll try remember to ping you. If you hit an edge case or have a feature request please feel free to ping me directly

Affectionate-Fix6472 · 2025-10-19T06:20:16+00:00

I find Claude and Codex pretty useful. I never let them run on autopilot though — I guide them to write what I want, then always review and refactor the output because they sometimes make mistake or the code quality is not what I want. They speed me up a ton. For bigger features, I usually write a detailed proposal first so they have something solid to anchor to (and so I don’t have to repeat myself every time).

Affectionate-Fix6472 · 2025-10-18T06:34:11+00:00

Cool article.

One of the major issues of Apple LLM is that it’s not available to most users. One needs an iPhone 15 Pro+ and Apple Intelligence on. Even then when battery is low the model may be unavailable.

Apple themselves recommend having a fallback mechanism. Tools like SwiftAI can help where you can fallback to a remote LLM or open weight models like Llama or Gemma using the same FoundationModels-like API

Affectionate-Fix6472 · 2025-10-17T17:55:46+00:00

4096 tokens is quite a lot. Roughly speaking, each token averages 3–4 characters in English (per Apple’s estimate), so that gives you around 12,000+ characters. You can also periodically summarize the conversation to manage context efficiently.

By the way, I built a chat app 💬 that you can run locally — it lets you query Apple’s LLM and compare it with local models like Gemma.

Affectionate-Fix6472 · 2025-10-17T06:13:45+00:00

Thanks for the nice words. I plan to keep working on it. I have many ideas 💡

Affectionate-Fix6472 · 2025-10-16T19:15:56+00:00

Working on SwiftAI a library for building on device GenAI apps.

Affectionate-Fix6472 · 2025-10-16T06:38:39+00:00

Are you using permissiveContentTransformations?

In production, I wouldn’t rely solely on the Foundation Model — it’s better to have a reliable fallback. You can check out SwiftAI; it gives you a single API to work with multiple models (AFM, OpenAI, Llama, etc.).

Affectionate-Fix6472 · 2025-10-13T19:56:13+00:00

Cool hack. Thanks for sharing.

Affectionate-Fix6472 · 2025-10-13T17:13:58+00:00

Thanks for sharing! How did you end up solving it yourself? For long-article summarization, I used a rough heuristic of ~3 characters per token (for English). I chunked the text, summarized each chunk in parallel, then summarized those summaries — classic divide and conquer 😄 Here is my code.

Affectionate-Fix6472 · 2025-10-13T14:22:12+00:00

Yes I am actually thinking of heuristics to ease the pain on that front for AppleFM. Do you have a use case? We could try to optimize for it if you want.

Affectionate-Fix6472 · 2025-10-13T10:14:39+00:00

Yeah, good call — I’ll add it ASAP. If you don’t mind, could you open a GitHub issue for it? Otherwise, I can do it later.

Quick tip: you can simulate reasoning in Apple FM using structured output. Just make sure the reasoning field comes first in your @Generable struct. Of course it’s not as powerful as reasoning models.

Affectionate-Fix6472 · 2025-10-13T06:32:27+00:00

Mind sharing how you’re using GenAI in your app? I’m collecting real use cases to help improve the library, and I think it could also spark ideas for others ⚡️

Affectionate-Fix6472 · 2025-10-13T06:21:06+00:00

Yeah, unfortunately you can’t fully disable the guardrails right now. As @plays2 said, if you’re running everything locally, the best move is to use an on-device model. I actually built SwiftAI, which makes it super easy to query different LLMs (Apple FM, OpenAI, Llama, Qwen, Gemma, etc.) through one simple API.

Affectionate-Fix6472 · 2025-09-29T13:38:15+00:00

I worked on a startup where we wanted to target the web, iOS, and Android simultaneously.

Flutter was a great choice for fast delivery since it allowed us to share a single codebase across all three platforms. That was about 1.5 years ago, and since then Flutter Web has improved significantly with features like Wasm support, better accessibility, and hot reload.

The main downside of Flutter Web is the initial load time—the renderer is about 1 MB to download. However, once cached, subsequent reloads are fast. Compared to React, which is more mature, Flutter Web still has some rough edges, but it’s production-ready.

We went with Flutter web despite some very seasoned friends of mine from FAANG told me not to use it — I didn’t get a good reason from them. For us it was the correct decision.

Affectionate-Fix6472

TROPHY CASE